- Email: [email protected]
Thermal management of the waste energy of a stand-alone hybrid PV-wind-battery power system in Hong Kong
Energy Conversion and Management xxx (xxxx) xxxx
Contents lists available at ScienceDirect
Energy Conversion and Management journal homepage: www.elsevier.com/locate/enconman
Thermal management of the waste energy of a stand-alone hybrid PV-windbattery power system in Hong Kong ⁎
J. Yana,b, Lin Lua, , Tao Mac, Yuekuan Zhoua, C.Y. Zhaob a
Renewable Energy Research Group, Department of Building Services Engineering, The Hong Kong Polytechnic University, Hong Kong, China Institute of Engineering Thermophysics, Shanghai Jiao Tong University, Shanghai, China c School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Solar-wind-battery system Dump load Thermal energy Heat Energy losses
This paper firstly investigated the thermal management of wasted energy from a stand-alone hybrid solar-windbattery power system. The total dump load or waste power can be up to 50% of total system power yield, and therefore waste energy management is urgent with high necessity. A new phase change material (PCM: Ba (OH)2·8H2O) with high storage capacity is introduced for the thermal management of hybrid power system. Different renewable energy configurations with different battery storage capacities are simulated and investigated. For different scenarios, the ratio of the captured thermal energy from waste energy to total solar/ wind power output ranges from 24.45% to 72.48% regarding all system losses. The cases without battery bank are featured by high thermal energy amount/ percentage (waste energy) and high power supply failure. Typical results show that, the total yearly renewable power output is 173,877 kWh with only 51.99% directly for demand load, and 57,672 kWh with 33.17% can be effectively stored in the thermal storage tank as heat, which can supply about 136 people’ heat demand per year. Compared with the water tank, the PCM thermal storage tank can save much space and land because of its high energy density. Appropriate thermal management of standalone hybrid solar-wind-battery power systems is necessary and feasible.
1. Introduction The major source of electricity is generated by burning fossil fuels. To reduce greenhouse gas emissions from burning fossil fuels, renewable and sustainable energy is an option. Renewable energy technologies, such as thermal solar energy, solar photovoltaic (PV), wind energy, bioenergy, hydropower, etc., are widely used to produce electricity all over the world. Renewables has the fast in the electricity sector by about 2.6% per year from 2012 to 2040. About 23.7% global electricity (1849 GW) is generated by sustainable energy in 2015 [1]. Since the wind power and solar energy have the inherent intermittency and fluctuation, the system can be combined with other energy methods to form a hybrid system to deal with the intermittent nature [2,3]. Usually, the energy storage methods, such as battery [4] and pumped storage [5], are necessary for their independent application processes and reliable power supply. When the wind, solar, or hybrid wind-solar energy system used as a stand-alone system, the dump load (to absorb excess power when the storage unit is fully charged [6]) is a significant problem, due to timing mismatch between power demand and generation. In real applications,
⁎
typical dumping loads are usually resistive loads such as air heaters or water heater components; increasing the battery capacity can effectively reduce the dumped power [7]. According to the studies of Lu and Ma et al. [8–10], more than 50%, 48.6% (as shown in Fig. 1) and 30% of the total energy output were transferred to a dump load as spilled energy, respectively. Other studies also presented similar results [11–14]. Therefore, the dump load or waste energy management is urgent with high necessity. It is important to find an appropriate method which can easily and economically store the waste energy. Battery energy is the most utilized method in solar PV system because the common use of solar PV is to provide electricity. Regarding the combined operation strategies, Angenendt et al. [15] found that battery size strongly influenced the economics of PV-battery storage systems with power-to-heat coupling. Ma et al. [16] established a standalone PV system (19.8 kWp) on an isolated island in Hong Kong. The roundtrip efficiency of the battery bank during a year was 74.3%, and the state of charge (SOC) was above 50% for the most time of the year. PCMs used in the PV units are also studied in recent years, especially for the cooling of the PV panel [17–19]. The electrical power of PV was improved around 13.6% by using PCM with 30 °C melting point
Corresponding author. E-mail address: [email protected] (L. Lu).
https://doi.org/10.1016/j.enconman.2019.112261 Received 30 August 2019; Received in revised form 5 November 2019; Accepted 6 November 2019 0196-8904/ © 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: J. Yan, et al., Energy Conversion and Management, https://doi.org/10.1016/j.enconman.2019.112261
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
Nomenclature
Subscripts
Symbols
batt B C CT
cp Cbatt DOD e E E(t) fR GT GS h H Href HWT L n N P PRP t T v v (t) VB
specific heat at constant pressure, kJ/kg·°C nominal capacity of one battery allowed depth of discharge, % efficiency, % energy, kWh energy at a time (t), kWh loss factor or derating factor of PV module, % hourly global solar radiation, kW/m2 standard incident radiation, 1000 W/m2 enthalpy, kJ/kg total thermal energy stored in the PCM tank, kWh reference height, m hub height, m total latent heat of the material, kJ/kg total number number electrical power, kW rated power output of PV module, kW time temperature, °C wind speed, m/s wind speed at H at a time (t), m/s rated voltage of the battery, V
day dload eh F gen inv liquidus load peak PV ref R solidus WT
Abbreviations ACH CAES DOD PV PCM SA SOC STC T-CCES
Greek β ΔH η σ
battery battery and inverter cut-in demand for energy during the days only energize by battery bank days only energize by storage bank daily load demand electrical heating cut-off system generators inverter liquidus load demand peak load solar photovoltaic/PV module reference rated solidus/eutectic wind turbines
liquid fraction latent heat in the PCM tank efficiency, % the self-discharge rate
air change rate per hour compressed air energy storage depth of discharge solar photovoltaic phase change material stand-alone state of charge standard test conditions thermal-compressed supercritical carbon dioxide energy storage
Superscripts γ
friction coefficient
Fig. 1. Summary of the energy flow during the simulated year [9].
compressed air energy storage (CAES) method [22], thermal-compressed supercritical carbon dioxide energy storage (T-CCES) system [23], fuel cell vehicle [24], and CAES & pumped hydroelectric storage system [25]. In addition, thermal energy storage is an important method. A new method of direct thermal energy storage was used by Okazaki et al. [26] in a wind power utilizing study. An optimization of capacities and distribution of electric heater and thermal storage for reduction of wind power curtailment was studied by Gou et al. [27]. The economic benefit in this case was improved about 44.65% after the optimization. However, the main energy storage material in above
according to the study of Su et al. [20]. PCMs are also introduced into the PV systems recently, especially when there are heating load requirements in the system. In addition, a PV-thermal collector system with ejector refrigeration cycle and PCM storage was investigated by Ghorbani et al. [21]. Increasing the battery capacity can effectively reduce the dumped power [7], but the cost of lithium-ion battery storage is very high. Therefore, the new feasibility methods which can use the dump load by low cost are necessary to be investigated. There are many storage methods in previous studies of wind turbine power system, such as 2
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
storage methods are expensive and complicated. Generally, there are many storage methods in solar PV system, wind turbine power system, solar thermal system, and hybrid renewable energy system. However, the researches on PCMs storage in PV-wind hybrid power systems are limited. As mentioned above, in a stand-alone hybrid photovoltaic-wind-battery power system, there is a large amount of dump load. Increasing the battery capacity can effectively reduce the dump load, but the cost is very high. At the same time, heating load may also be expected. Therefore, the application of heat storage in a PV-wind hybrid system becomes a promising method. The materials used in the thermal energy storage method usually are water and PCMs. Considering the low energy density of water, the PCMs can be a better choice. Among the PCMs, paraffin wax is often used, but the high cost and the risk of burning restrict its application. Therefore, this paper aims to analyze the feasibility of a thermal storage application for a stand-alone hybrid solar-wind-battery system in Hong Kong, and to propose a new PCM (Ba(OH)2·8H2O) for the thermal management of hybrid power system.
studies is water, and the sensible heat of water is much lower than the latent heat of other phase change materials. Heat storage is the most common method in solar thermal application, and water is the mainly utilized material [28–30]. In the study of Antoniadis and Martinopoulos [31], a new seasonal solar heat storage (water) method could cover about 67% of the heating load requirement. There are three main heat storage technologies, including sensible heat storage, latent heat storage, and chemical heat storage. The hot water storage is a typical sensible heat storage, but the small energy density of water restricts its application. Though the chemical heat storage has a large storage density, it is still in the experimental stage [32]. The latent heat storage (PCMs) is one of the most promising methods due to its advantages, such as great energy density, small temperature difference in the process of phase change and so on [33,34]. The large energy density can reduce the storage volume by over 50% [35]. Therefore, many researchers used the PCM method in their studies, especially in recent years [36–38]. Stearic acid and palmitic acid were used as different heat storage PCMs to provide the hot water in a solar thermal system [39]. A novel heat storage system using PCM was studied by numerical method for direct steam solar power plants by Kargar et al. [40]. In general, the PCM is a promising material in thermal solar system [41–44], and the paraffin wax is the most popular materials among PCMs. Standalone hybrid renewable energy systems are commonly used in remote and island areas to provide reliable power supply. There are many storage methods in the above three renewable systems, but battery storage is still the most utilized method in hybrid power systems because of the reliable electric requirement [2,45]. In addition, the pumped storage and fuel cell methods are other alternatives to further produce the electricity. Sultan et al. [5] studied a mathematical model of a proposed hybrid system, including solar PV, wind energy, and a pumped storage power station. The application of pumped hydro energy storage was also studied in a PV-wind system by Ma et al. [10,46]. In their study, about 38% of total output (456.6 kWh/day) was transferred to the pump unit for lifting water to upper reservoir, but there were only 56.6 kWh which could be reused again. Ishaq et al. [47] studied a solar-wind hybrid system with a hydrogen production linked with a hydrogen compression system, and Sichilalu et al. [48] studied a grid-tied PV–wind-fuel cell hybrid power supply system. Zhang et al. [49] and Madaci et al. [13] also investigated the application of fuel cell in a stand-alone hybrid solar and wind energy system. All the above
2. System component modelling 2.1. System description The hybrid solar-wind-battery system with thermal energy storage is presented in Fig. 2, which consists of a solar PV system, a wind power system, a storage bank (electric batteries and PCM thermal storage tank), load, an inverter, and a controller. The dump load, due to timing mismatch between power demand and generation, will be converted to heat, which will be thereafter stored in a PCM thermal storage tank via electric heater. The thermal energy in the seasonal heat storage tank can be used to cover the year-round heating demand of residents. An isolated land is considered as the application area of this system, which can be called a stand-alone (SA) system. The operation strategy of this kind system is shown in Fig. 3. The electric demand of buildings will be covered by solar PV and wind turbines. The battery bank will be discharged when the load exceeds the renewable energy. By contrast, whenever the renewable energy is higher than the electric demand and the SOC of battery is above 95%, the surplus renewable energy will be converted into thermal energy, which will be stored in the PCM thermal storage tank. A typical hourly mean load profile, throughout the whole year, is
Fig. 2. The energy flow diagram of proposed hybrid (PV-wind) system with battery and thermal storage. 3
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
Fig. 3. Operating strategy of the hybrid solar-wind energy system with thermal and battery storages.
selected, as shown in Fig. 4. The area of the building is about 668 m2. The number of floors is 3, and the height is 3 m for each floor. The window to wall ratio is 20%. The occupant density and the infiltration rate are 13 m2/person and 0.288 air change rate per hour (ACH) [50]. Internal heat gains are 10 and 15 W/m2 from the equipment and the lighting system. A hydronic air handling unit is designed with the supply air temperature between 17 and 21 °C. In addition, a hydronic space cooling system is designed to cover the space cooling demand with a supply chilled water temperature at 15 °C. The rated capacities of chillers for the air handling cooling and the space cooling are 293 kW and 506 kW [51], with nominal COPs at 2.8 and 2.6, respectively [52]. The daily mean load is estimated at 250 kWh/day in this paper.
respect to reference height [2].
v (t)/ vref (t ) = (HWT / Href )r
Usually the value of γ is taken as 1/7. Wind turbines arrangement effect (wake effect) in this study is assumed to be zero [2]. 2.4. Battery bank The lead-acid battery is usually used in energy systems because of the low capital cost, high depth of discharge (DOD), and reliability. The detailed information of the battery used in this study is shown in Table 3. The following equations are used to calculate the battery bank state of charge (SOC) at a time (t) [14]: Discharging process:
2.2. Solar PV module
Ebatt (t ) = Ebatt (t − 1)·(1 − σ ) − [(Eload (t )/einv ) − Egen (t )]
The rated power of polycrystalline PV module used in this research is 270 Wp. The essential information of PV module is shown in Table 1 [9,53]. At low mean temperature topography [54], the power of PV generator (kWh) can be obtained according to the following equation:
PPV (t ) = PRP ·fR ·(GT (t )/ GS )
Ebatt (t ) = Ebatt (t − 1)·(1 − σ ) + [Egen (t ) − (Eload (t )/ einv )]·ebatt
(1)
2.3. Wind turbine The power output curve has an important influence on a power output of a wind energy system. In addition, the local wind speed distribution, and the hub height of the wind tower are another two important parameters to affect the performance of each wind power generator. An appropriate power output model is a basic element in the simulation. The power output of a wind turbine can be calculated by [2]:
(νc ≤ ν ≤ νR ) ⎧ PR·(ν − νc )/(νR − νc ) PR (νR < ν ≤ νF ) ⎨ (ν < νc and ν > νF ) ⎩0
(4)
Charging process:
A derating factor (fR) of 80% is used in this paper [53].
PW (ν ) =
(3)
(2)
Basic description of wind turbine used in this paper is shown in Table 2. Different wind power generators have various hub heights, and the following equation is a simple model to calculate wind speed with
Fig. 4. Hourly mean load demand. 4
(5)
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
Table 1 PV module details.
Table 4 Ba(OH)2·8H2O details.
Manufacturer
Suntech solar panel
Mean specific heat capacity
1.817 kJ/(kg·°C)
Model Maximum operating current Maximum operating voltage Maximum power at STC Dimensions No. of cells Slop (degree) Lifetime Power tolerance
Polycrystalline 8.69 A 31.1 V 270 W 1650*992*35 mm 60 (6*10) 22.3° 25 years 0/+5W
Mean Density Latent heat Tsolidus Tliquidus
1.9 g/cm3 331.7 kJ/kg 76 °C 80 °C
where
h = href + Table 2 Wind turbine details. Sunning wind power Ltd.
Rated power Rated voltage (AC) Hub height Rated wind speed (m/s) Cunt-out wind speed (m/s) Cut-in wind speed (m/s) Survival wind speed (m/s) Life time
5.2 kW 48 V/300 V 15 11 None – Continuous Operation 2.5 70 25 years
T
ref
cp dT
⎧0 B = (T − Tsolidus )/ Tliquidus − Tsolidus if ⎨ ⎩1
(11)
if T < Tsolidus Tsolidus ≤ T ≤ Tliquidus if
T > Tliquidus
(12)
Afterwards, the calculation equation of latent heat amount can be obtained according to the following equation:
ΔH = βL
(13)
The latent heat content can vary between zero (for a solid) and L (for a liquid). The Ba(OH)2·8H2O is used as the PCM in this paper, and the property of the PCM is shown in Table 4 [33]. The energy balance equation of thermal storage tank can be calculated as:
Table 3 Technical details of battery and converter. component
Converter
∫T
The liquid fraction, β, can be defined as:
Manufacturer
Battery
(10)
H = h + ΔH
Manufacturer Nominal voltage Nominal capacity Maximum depth of discharge Roundtrip efficiency Life time
Zuhai seawill technology Co., Ltd. 2V 1000 Ah 80% 88% 20 years
Rated power Inverter efficiency (DC-AC) Rectifier efficiency (AC-DC) Life time
26 kW 90% 85% 20 years
H = (PPV + PWT − Eload − Ebatt )·ηeh
99% is employed for ηeh in this study. Heat insulation is assumed for this thermal storage tank. 3. Results and discussion According to our previous work [9], the installation capacities of solar PV and wind turbines are 145 kWp and 10.4 kW, as presented as Case 1 in this study. Different installation capacities of PV and wind turbines under a similar total capacity are also studied in this paper. A greater wind power case is presented as Case 2 with PV and wind turbine capacities of 103.4 kWp and 52 kW, respectively. Solar PV modules with 155.3 kWp are presented as Case 3, and Wind turbines with 156 kW are presented as Case 4. The thermal management of waste energy is studied at different battery storage capacities. There are six different scenarios for the battery storage capacity: Case n-0 without battery (0-day battery storage); Case n-1 with 1-day’s battery storage; Case n-2 with 2-days’ battery storage; Case n-3 with 3days’ battery storage; Case n-4 with 4-days’ battery storage; Case n-5 with 5-days’ battery storage. n can be 1, 2, 3 and 4, corresponding to Case 1, Case 2, Case 3 and Case 4. The simulation results of different cases are shown in Table 5. Case n-3 has a proper configuration and relative stable results. Therefore, the Case n-3 will be analyzed as a typical sample in the following discussion.
Energy generated Egen by PV and wind at a time (t) can be calculated as [14]:
Egen (t ) = NPV ·EPV (t ) + NWT ·EWT (t )
(6)
To design a storage bank meeting the required autonomous days, the following sizing approach is used:
CAh = ECT /(eB ·DOD ·VB ) = nday ·Edload/(eB ·DOD ·VB )
(7)
nbatt = CAh/ Cbatt
(8)
2.5. Power converter Converters are required when a system contains different DC and AC facilities. Wind power, load and dump energy have AC features while PV modules and storage bank are with DC features. The size of the converter depends on the peak load (Ppeak) demand of the system. The power rating (Pinv) of converter can be calculated as [14]:
Pinv = Ppeak / einv
(14)
3.1. Simulation results of renewable energy, battery and thermal energy storage
(9)
The detailed specification of converter is shown in Table 3.
The daily mean power generated by solar PV and wind turbines in different months are shown in Fig. 5. Most power is produced by PV in Case 1, Case 2 and Case 3, especially in the summer. The maximum total power and PV power are produced in July, and the minimum total power and PV power are in December. Generally, the wind power output is high in April, May and September.
2.6. PCM thermal storage tank The enthalpy of the phase change materials, H, is calculated as the sum of the sensible enthalpy, h, and the latent heat, ΔH [55–57]: 5
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
Table 5 Comparison of different cases. Total renewable output PV
WIND
Case 1 165,560 kWh 95.22%
Case 1 8317 kWh 4.78%
Case 2 118,081 kWh 73.95%
Case 3 177,275 kWh 100%
/
Case 2 41,586 kWh 26.05%
/
Case 4 124,758 kWh 100%
Case
days of battery storage
Thermal energy
Losses of electricity to heat
Converter losses
Battery bank losses
Useful energy
Failure days
Case 1–0
0
Case 1–2
2
Case 1–3
3
Case 1–4
4
Case 1–5
5
17,388 kWh 10% 16,598 kWh 9.55% 16,578 kWh 9.53% 16,565 kWh 9.53% 16,563 kWh 9.53% 16,566 kWh 9.53%
33,385 kWh 19.20% 86,443 kWh 49.71% 89,464 kWh 51.45% 90,396 kWh 51.99% 90,633 kWh 52.12% 90,760 kWh 52.20%
218
1
1232 kwh 0.71% 628 kWh 0.36% 593 kWh 0.34% 583 kWh 0.33% 580 kWh 0.33% 578 kWh 0.33%
/
Case 1–1
121,872 kWh 70.09% 62,151 kWh 35.74% 58,723 kWh 33.77% 57,672 kWh 33.17% 57,405 kWh 33.01% 57,256 kWh 32.93%
Case 2–0
0
Case 2–2
2
Case 2–3
3
Case 2–4
4
Case 2–5
5
15,967 kWh 10% 15,293 kWh 9.58% 15,253 kWh 9.55% 15,242 kWh 9.55% 15,237 kWh 9.54% 15,236 kWh 9.54%
42,531 kWh 26.64% 86,944 kWh 54.45% 89,701 kWh 56.18% 90,585 kWh 56.73% 91,047 kWh 57.02% 91,157 kWh 57.09%
192.6
1
1012 kWh 0.63% 507 kWh 0.32% 476 kWh 0.30% 466 kWh 0.29% 461 kWh 0.29% 459 kWh 0.29%
/
Case 2–1
100,157 kWh 62.73% 50,193 kWh 31.44% 47,090 kWh 29.49% 46,093 kWh 28.87% 45,580 kWh 28.55% 45,447 kWh 28.46%
Case 3–0
0
Case 3–2
2
Case 3–3
3
Case 3–4
4
Case 3–5
5
17,728 kWh 10% 16,905 kWh 9.54% 16,873 kWh 9.52% 16,872 kWh 9.52% 16,870 kWh 9.52% 16,869 kWh 9.52%
29,768 kWh 16.79% 85,308 kWh 48.12% 89,119 kWh 50.27% 90,057 kWh 50.80% 90,293 kWh 50.93% 90,503 kWh 51.05%
222
1
1299 kWh 0.73% 666 kWh 0.38% 623 kWh 0.35% 612 kWh 0.35% 609 kWh 0.34% 607 kWh 0.34%
/
Case 3–1
128,481 kWh 72.48% 65,963 kWh 37.21% 61,645 kWh 34.77% 60,576 kWh 34.17% 60,309 kWh 34.02% 60,071 kWh 33.89%
Case 4–0
0
Case 4–1
1
Case 4–2
2
Case 4–3
3
Case 4–4
4
Case 4–5
5
72,229 kWh 57.90% 44,916 kWh 36.00% 38,441 kWh 30.81% 34,624 kWh 27.75% 31,969 kWh 25.62% 30,504 kWh 24.45%
730 kWh 0.58% 454 kWh 0.36% 388 kWh 0.31% 350 kWh 0.28% 323 kWh 0.26% 308 kWh 0.25%
12,476 kWh 10% 12,108 kWh 9.71% 12,024 kWh 9.64% 11,973 kWh 9.60% 11,940 kWh 9.57% 11,922 kWh 9.56%
8057 kWh 4.63% 8519 kWh 4.90% 8660 kWh 4.98% 8696 kWh 5.00% 8716 kWh 5.01%
6729 kWh 4.21% 7147 kWh 4.48% 7281 kWh 4.56% 7342 kWh 4.60% 7368 kWh 4.61%
8433 kWh 4.76% 9014 kWh 5.09% 9158 kWh 5.17% 9194 kWh 5.19% 9227 kWh 5.20% / 3678 kWh 2.95% 4551 kWh 3.65% 5065 kWh 4.06% 5422 kWh 4.35% 5619 kWh 4.50%
39,324 kWh 31.52% 63,601 kWh 50.98% 69,354 kWh 55.59% 72746 kWh 58.31% 75,104 kWh 60.20% 76,404 kWh 61.24%
25.9 6 1.9 0.5 0
22 7.2 3 1 0.4
30.1 7.7 2.4 1.4 0.5 218 115 85.6 70.4 60.2 54
circles and the black line of the hollow triangles represent the PV output and WT output. Usually, solar power is produced during the daytime. It is used to cover the demand load first, and the surplus is used to charge the battery bank and PCM thermal storage tank, as indicated by the blue line of the hollow circles in Fig. 6. The black dash line illustrates the battery SOC and stands for the amount of power stored in the battery bank. The battery bank is intermittently charged or discharged during this week. If the SOC is larger than 95%, the surplus energy is then fed into the PCM thermal storage tank, represented by the green line. During this week, the renewable power exceeds the load during daytime, and the battery bank will release energy at night in Case 1–3 and Case 3–3. The wind and solar resources can meet the demand load during the whole days of 1st to 3th April in Case 2–3. In general, the energy profiles of Case 1–3, Case 2–3, and Case 3–3 are similar, and thermal energy is largely stored during the first five days. However, Case 4–3 is different. The wind power can meet the demand load from 1st to 4th April, and heat is largely obtained during the period. Then,
According to Fig. 5, the power generated by solar PV is much larger than the power generated by wind turbines under a same capacity of PV and wind turbines, except for April. The daily mean renewable power is usually greater than the load in different months, except for the Case 4. The superfluous electric energy is changed to thermal energy and stored as heat in this study. The load exceeds the renewable power during June, July and August under Case 4. Therefore, the only wind case will have more failure days, as demonstrated in Table 5. The results of a typical example of Case n-3 during a week are shown in Fig. 6. It shows that the power generated by PV and wind turbine is much larger than the load and the excess energy will be stored in the battery bank. The battery bank will release energy when the load exceeds the sustainable energy, and the further extra electrical energy will be changed into heat and then stored as thermal energy in the PCM thermal storage tank if the battery SOC is above 95%. If there is no PCM thermal storage tank, this part energy (the further extra electricity) will be used as the waste energy and dump load. The black line displays the load profile for this study. The red lines of the solid 6
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
simulated year and the comparison of different forms of energy. As shown in Fig. 7, the total renewable output is 173,877 kWh, including PV power of 165,560 kWh and wind turbine of 8317 kWh. Most of the power (51.99%) is used to supply the load (useful energy), and 33.17% of the energy is stored in the PCM thermal storage tank as heat. This thermal energy can be used to supply the daily heat demand of residents. As shown in Fig. 8, the rest part of the renewable output is converted into different energy losses, including converter losses, battery bank losses and losses of electricity to heat. The loss during the electricity changed into heat is 0.33%, which is the minimum losses. The largest loss is the converter loss at 9.53%, because the renewable output is DC power and DC/AC converter is needed. If the heat thermal management is not provided, a total system energy loss of 48.01%. Therefore, thermal management is very important for stand-alone solar/wind energy systems. 3.3. The effects of different cases and battery bank capacity on thermal energy
Fig. 5. Hourly mean load and power generated by PV and wind in different months.
Figs. 9 and 10 summarize the thermal energy conditions under different renewable energy configurations with different battery storage capacities. In general, Case 3 (only PV) has the greatest waste heat, but there is still half day’s power failure Case 3–5. Case 1–5 provides reliable power supply without failure. If there is no battery bank (0-day battery storage), a greatest thermal energy amount and will be resulted together with also the largest power failure days. Therefore, it is not an appropriate configuration considering the demand of electric load. Basically, Case 4 (only wind turbine) has the worst performance, and Case 4–1 has a bigger thermal energy percentage than Case 1–1 and Case 2–1. In addition, the heat amount is very similar when the battery storage capacity is above 2 days under the Case 1, Case 2 and Case 3. However, as shown in Fig. 9, the thermal energy amount of Case 4 is obviously decreasing with the increase of battery bank capacity. In addition, different conditions for the battery storage capacity are simulated, and the results are illustrated in Table 5. For Case n-0, if
the wind energy is insufficient, and the battery bank discharges and supplies the additional energy with dropping SOC. Due to the limit of the maximum allowable charging rate (95%) and state of the battery during the calculation step, the excessive energy is not totally stored in the batter bank when the SOC has not arrived a 100% level for sometimes. With abundant wind and solar energy and high SOC, a lot of thermal energy is obtained and stored in the PCM tank.
3.2. The analysis of thermal energy among the different energy forms In this part, Case 1–3 is analyzed as a typical case. The results of other cases are shown in Table 5. The results from Case n-1 to Case n-5 have the similar trend, except that Case n-0 has a greater thermal energy. Figs. 7 and 8 display the energy flow of Case 1–3 during the
Fig. 6. Hourly sample simulation results for a week (1st to 7th April).(a) Case 1–3; (b) Case 2–3; (c) Case 3–3; (d) Case 4–3. 7
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
Fig. 7. Summary of the energy flow during the simulated year. (Case 1–3).
there is no battery bank, the power supply failure days and heat will be very large. The useful electrical energy of Case 3–0 has the least amount of about 29,768 kWh with useful rate of 16.79% only, so most power is wasted or converted into thermal energy. Case 3–0 has the largest amount of thermal energy, about 128,481 kWh during the whole year. The power failure days will be reduced with the increase of battery bank capacity. There will be no failure days with a 5-days’ battery storage for Case 1–5. Thermal energy storage is declined with the increase of battery bank capacity. It shows that the difference of rate of thermal energy is less than 1% after the battery bank capacity is above 2 days, except Case 4. The heat stored into the thermal tank is relatively stable when the battery bank capacity is above 2 days. In addition, Case 4 (only wind turbine) has the least amount of thermal energy and the worst power supply failure. 3.4. PCM thermal storage tank Fig. 11 shows the results of accumulative heat of cases with 3 day’s battery storage capacity during the simulated year. The slope of the line represents the accumulated amount of thermal energy. For instance, the slope of the line is gentle on the 150th day with less thermal energy produced. The total thermal energy of Case 1–3, Case 2–3, Case 3–3, and Case 4–3, which can be stored in the PCM thermal storage tank, is about 57,672 kWh, 46,028 kWh, 60,576 kWh, and 34,217 kWh,
Fig. 9. Comparison of total heat storage under different cases (Different renewable energy configurations with different battery storage capacities).
respectively, during the simulated year. The figures are very promising. It is assumed that 40 L hot water is needed for one person. The daily mean temperature of the hot water needs to raise 25 °C (For instance,
Fig. 8. Comparison of different forms of energy. (Case 1–3). 8
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
Hong Kong, and proposed a new PCM technology for the thermal storage. The main conclusions are drawn as below: 1. For a stand-alone hybrid solar-wind-battery power system, the dump load or waste power can reach up to 50%. Therefore, waste energy management or thermal management is urgent with high necessity. 2. A new PCM (Ba(OH)2·8H2O) for the thermal management of hybrid power system is newly introduced which has high storage capacity. 3. Different renewable energy configurations with different battery storage capacities are simulated and investigated. For different scenarios, the ratio of the captured thermal energy from waste energy to total solar/wind power output can range from 24.45% to 72.48% regarding all system losses, such as wiring and inverter losses, battery charging/discharging losses, thermal storage loss, etc. The cases without battery bank are featured by high thermal energy amount/ percentage (waste energy) and high power supply failure. Furthermore, the energy systems with only wind turbines perform the worst. 4. In a typical Case 1–3, the total yearly renewable power output is 173,877 kWh with only 51.99% directly for demand load and 33.17% being effectively stored in the thermal storage tank as heat. 5. The new PCM technology for the thermal storage is feasible. The total stored thermal energy of Case 1–3, Case 2–3, Case 3–3 and Case 4–3 in the PCM thermal storage tank is about 57,672 kWh, 46,028 kWh, 60,576 kWh, and 34,217 kWh, respectively, during the simulated year. The simulation results show that the total thermal energy storage of Case 1–3 can supply about 136 people’ heat demand per year. Compared with the water tank, the PCM thermal storage tank can save much space and land because of its high energy density.
Fig. 10. Comparison of thermal energy percentage under different cases (Different renewable energy configurations with different battery storage capacities).
To conclude, appropriate thermal management of stand-alone hybrid solar-wind-battery power systems is necessary and feasible. It can fully utilize the waste energy or dump load to provide a large amount of heating load. Declaration of Competing Interest Fig. 11. Accumulative thermal energy during the simulated year. (Case n-3).
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
from 25 °C to 50 °C). Then, the daily thermal load is calculated to be about 1.16 kWh, and the yearly thermal load is 423.4 kWh per person. Therefore, the total thermal energy storage of Case 1–3 can supply about 136 people’ heat demand per year. The number of the people is 108 for Case 2–3, 143 for Case 3–3 and 80 for Case 4–3, respectively. According to the description of PCM (Ba(OH)2·8H2O) property in Section 2.6, 1-ton materials of this PCM can store about 112.3 kWh thermal energy from 50 °C to 90 °C. Considering the hot water temperature and heat transfer temperature difference, the initial temperature 50 °C is selected in the calculation. Considering the application of the seasonal heat storage, it needs about 514 tons PCM materials for the total thermal energy in Case 1–3, and it will be about 270 m3. If we use the water tank to store this heat, 1-ton water can store about 46.4 kWh thermal energy from 50 °C to 90 °C. It needs about 1243 tons water for the total thermal energy in Case 1–3, and it will be about 1243 m3. The volume of water tank is about 4.6 times larger than that of the PCM tank. The cost of land can sharply reduce with PCM tank. The PCM tank volume of Case 2–3, Case 3–3, and Case 4–3 will be about 216 m3, 284 m3, and 160 m3, respectively. The corresponding volume of water tank is about 994 m3, 1306 m3, and 736 m3, respectively.
Acknowledgments This work is supported by the National Natural Science Foundation of China (Grant No: 51706130), and the Hong Kong Scholars Program (Grant No: XJ2018015). References [1] Goel S, Sharma R. Performance evaluation of stand alone, grid connected and hybrid renewable energy systems for rural application: a comparative review. Renew Sustain Energy Rev 2017;78:1378–89. [2] Yang H, Lu L, Zhou W. A novel optimization sizing model for hybrid solar-wind power generation system. Sol Energy 2007;81:76–84. [3] Yang HX, Lu L, Burnett J. Weather data and probability analysis of hybrid photovoltaic–wind power generation systems in Hong Kong. Renew Energy 2003;28:1813–24. [4] Plytaria MT, Bellos E, Tzivanidis C, Antonopoulos KA. Financial and energetic evaluation of solar-assisted heat pump underfloor heating systems with phase change materials. Appl Therm Eng 2019;149:548–64. [5] Sultan HM, Zaki Diab AA, Kuznetsov Oleg N, Zubkova Irina S. Design and evaluation of PV-wind hybrid system with hydroelectric pumped storage on the National Power System of Egypt. Global Energy Interconnection 2018;1:301–11. [6] Alnasir Z, Kazerani M. An analytical literature review of stand-alone wind energy conversion systems from generator viewpoint. Renew Sustain Energy Rev 2013;28:597–615. [7] Li H, Campana PE, Tan Y, Yan J. Feasibility study about using a stand-alone wind power driven heat pump for space heating. Appl Energy 2018;228:1486–98.
4. Conclusions This paper firstly investigated the thermal management of the waste energy of a stand-alone hybrid solar-wind-battery power system in 9
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
thermochemical heat storage. Appl Energy 2016;175:277–84. [33] Wang Q, Wang J, Chen Y, Zhao CY. Experimental investigation of barium hydroxide octahydrate as latent heat storage materials. Sol Energy 2019;177:99–107. [34] Zhou Y, Zheng S, Zhang G. Study on the energy performance enhancement of a new PCMs integrated hybrid system with the active cooling and hybrid ventilations. Energy 2019;179:111–28. [35] Teamah HM, Lightstone MF, Cotton JS. Potential of cascaded phase change materials in enhancing the performance of solar domestic hot water systems. Sol Energy 2018;159:519–30. [36] Abu-Arabi M, Al-harahsheh M, Mousa H, Alzghoul Z. Theoretical investigation of solar desalination with solar still having phase change material and connected to a solar collector. Desalination 2018;448:60–8. [37] Raj AK, Srinivas M, Jayaraj S. A cost-effective method to improve the performance of solar air heaters using discrete macro-encapsulated PCM capsules for drying applications. Appl Therm Eng 2019;146:910–20. [38] Bilardo M, Fraisse G, Pailha M, Fabrizio E. Modelling and performance analysis of a new concept of integral collector storage (ICS) with phase change material. Sol Energy 2019;183:425–40. [39] Prakash J, Roan D, Tauqir W, Nazir H, Ali M, Kannan A. Off-grid solar thermal water heating system using phase-change materials: design, integration and real environment investigation. Appl Energy 2019;240:73–83. [40] Kargar MR, Baniasadi E, Mosharaf-Dehkordi M. Numerical analysis of a new thermal energy storage system using phase change materials for direct steam parabolic trough solar power plants. Sol Energy 2018;170:594–605. [41] Zhao J, Yuan Y, Haghighat F, Lu J, Feng G. Investigation of energy performance and operational schemes of a Tibet-focused PCM-integrated solar heating system employing a dynamic energy simulation model. Energy 2019;172:141–54. [42] Hirmiz R, Lightstone MF, Cotton JS. Performance enhancement of solar absorption cooling systems using thermal energy storage with phase change materials. Appl Energy 2018;223:11–29. [43] Wang Y, Yang X, Xiong T, Li W, Shah KW. Performance evaluation approach for solar heat storage systems using phase change material. Energy Build 2017;155:115–27. [44] Wang Z, Sun S, Lin X, Liu C, Tong N, Sui Q, et al. A remote integrated energy system based on cogeneration of a concentrating solar power plant and buildings with phase change materials. Energy Convers Manage 2019;187:472–85. [45] Huang Q, Shi Y, Wang Y, Lu L, Cui Y. Multi-turbine wind-solar hybrid system. Renew Energy 2015;76:401–7. [46] Ma T, Yang H, Lu L. Feasibility study and economic analysis of pumped hydro storage and battery storage for a renewable energy powered island. Energy Convers Manage 2014;79:387–97. [47] Ishaq H, Dincer I, Naterer GF. Development and assessment of a solar, wind and hydrogen hybrid trigeneration system. Int J Hydrogen Energy 2018;43:23148–60. [48] Sichilalu S, Tazvinga H, Xia X. Optimal control of a fuel cell/wind/PV/grid hybrid system with thermal heat pump load. Sol Energy 2016;135:59–69. [49] Zhang W, Maleki A, Rosen MA, Liu J. Sizing a stand-alone solar-wind-hydrogen energy system using weather forecasting and a hybrid search optimization algorithm. Energy Convers Manage 2019;180:609–21. [50] Performance-based building energy code 2007. https://www.emsd.gov.hk/ filemanager/en/content_725/PBBEC_Guidelines_2007.pdf. [51] Air-Cooled Liquid Chillers with Integrated Hydronic Module, 30RB 162-802 Nominal cooling capacity 162-774 kW. https://climamarket.bg/wp-content/ uploads/Tech-Spec-Carrier-30RB-162-802.pdf; 2012. [52] Zhou Y, Cao S. Energy flexibility investigation of advanced grid-responsive energy control strategies with the static battery and electric vehicles: a case study of a highrise office building in Hong Kong. Energy Convers Manage 2019;199:111888. [53] Ma T, Javed MS. Integrated sizing of hybrid PV-wind-battery system for remote island considering the saturation of each renewable energy resource. Energy Convers Manage 2019;182:178–90. [54] Singh S, Singh M, Kaushik SC. Feasibility study of an islanded microgrid in rural area consisting of PV, wind, biomass and battery energy storage system. Energy Convers Manage 2016;128:178–90. [55] Arampatzis G, Assimacopoulos D. Numerical modeling of convection-diffusion phase change problems. Comput Mech 1998;21:409–15. [56] Sciacovelli A, Colella F, Verda V. Melting of PCM in a thermal energy storage unit: numerical investigation and effect of nanoparticle enhancement. Int J Energy Res 2013;37:1610–23. [57] Lu W, Liu Z, Flor J-F, Wu Y, Yang M. Investigation on designed fins-enhanced phase change materials system for thermal management of a novel building integrated concentrating PV. Appl Energy 2018;225:696–709.
[8] Lu L. Investigation on characteristics and application of hybrid solar-wind power generation systems. The Hong Kong Polytechnic University; 2004. [9] Ma T, Yang H, Lu L. A feasibility study of a stand-alone hybrid solar–wind–battery system for a remote island. Appl Energy 2014;121:149–58. [10] Ma T, Yang H, Lu L, Peng J. Technical feasibility study on a standalone hybrid solarwind system with pumped hydro storage for a remote island in Hong Kong. Renew Energy 2014;69:7–15. [11] Kalantar M, Mousavi G. SM. Dynamic behavior of a stand-alone hybrid power generation system of wind turbine, microturbine, solar array and battery storage. Appl Energy 2010;87:3051–64. [12] Astolfi M, Mazzola S, Silva P, Macchi E. A synergic integration of desalination and solar energy systems in stand-alone microgrids. Desalination 2017;419:169–80. [13] Madaci B, Chenni R, Kurt E, Hemsas KE. Design and control of a stand-alone hybrid power system. Int J Hydrogen Energy 2016;41:12485–96. [14] Javed MS, Song A, Ma T. Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm. Energy 2019;176:704–17. [15] Angenendt G, Zurmühlen S, Rücker F, Axelsen H, Sauer DU. Optimization and operation of integrated homes with photovoltaic battery energy storage systems and power-to-heat coupling. Energy Convers Manage: X 2019;1:100005. [16] Ma T, Yang H, Lu L. Performance evaluation of a stand-alone photovoltaic system on an isolated island in Hong Kong. Appl Energy 2013;112:663–72. [17] Ma T, Zhao J, Li Z. Mathematical modelling and sensitivity analysis of solar photovoltaic panel integrated with phase change material. Appl Energy 2018;228:1147–58. [18] Tabet Aoul K, Hassan A, Shah AH, Riaz H. Energy performance comparison of concentrated photovoltaic – phase change material thermal (CPV-PCM/T) system with flat plate collector (FPC). Sol Energy 2018;176:453–64. [19] Zhou Y, Zheng S, Zhang G. Artificial neural network based multivariable optimization of a hybrid system integrated with phase change materials, active cooling and hybrid ventilations. Energy Convers Manage 2019;197:111859. [20] Su D, Jia Y, Lin Y, Fang G. Maximizing the energy output of a photovoltaic–thermal solar collector incorporating phase change materials. Energy Build 2017;153:382–91. [21] Ghorbani B, Mehrpooya M, Sharifzadeh MMM. Introducing a hybrid photovoltaicthermal collector, ejector refrigeration cycle and phase change material storage energy system (Energy, exergy and economic analysis). Int J Refrig 2019;103:61–76. [22] Jin H, Liu P, Li Z. Dynamic modeling and design of a hybrid compressed air energy storage and wind turbine system for wind power fluctuation reduction. Comput Chem Eng 2019;122:59–65. [23] Chaychizadeh F, Dehghandorost H, Aliabadi A, Taklifi A. Stochastic dynamic simulation of a novel hybrid thermal-compressed carbon dioxide energy storage system (T-CCES) integrated with a wind farm. Energy Convers Manage 2018;166:500–11. [24] Hemmati R. Technical and economic analysis of home energy management system incorporating small-scale wind turbine and battery energy storage system. J Clean Prod 2017;159:106–18. [25] Caralis G, Christakopoulos T, Karellas S, Gao Z. Analysis of energy storage systems to exploit wind energy curtailment in Crete. Renew Sustain Energy Rev 2019;103:122–39. [26] Okazaki T, Shirai Y, Nakamura T. Concept study of wind power utilizing direct thermal energy conversion and thermal energy storage. Renew Energy 2015;83:332–8. [27] Gou X, Chen Q, Hu K, Ma H, Chen L, Wang X-H, et al. Optimal planning of capacities and distribution of electric heater and heat storage for reduction of wind power curtailment in power systems. Energy 2018;160:763–73. [28] Launay S, Kadoch B, Le Métayer O, Parrado C. Analysis strategy for multi-criteria optimization: application to inter-seasonal solar heat storage for residential building needs. Energy 2019;171:419–34. [29] Artur C, Neves D, Cuamba BC, Leão AJ. Comparison of two dynamic approaches to modelling solar thermal systems for domestic hot water. Sustain Energy Technol Assess 2018;30:292–303. [30] Hohne PA, Kusakana K, Numbi BP. Optimal energy management and economic analysis of a grid-connected hybrid solar water heating system: a case of Bloemfontein, South Africa. Sustain Energy Technol Assess 2019;31:273–91. [31] Antoniadis CN, Martinopoulos G. Optimization of a building integrated solar thermal system with seasonal storage using TRNSYS. Renew Energy 2019;137:56–66. [32] Yan J, Zhao CY. Experimental study of CaO/Ca(OH)2 in a fixed-bed reactor for
10
Contents lists available at ScienceDirect
Energy Conversion and Management journal homepage: www.elsevier.com/locate/enconman
Thermal management of the waste energy of a stand-alone hybrid PV-windbattery power system in Hong Kong ⁎
J. Yana,b, Lin Lua, , Tao Mac, Yuekuan Zhoua, C.Y. Zhaob a
Renewable Energy Research Group, Department of Building Services Engineering, The Hong Kong Polytechnic University, Hong Kong, China Institute of Engineering Thermophysics, Shanghai Jiao Tong University, Shanghai, China c School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Solar-wind-battery system Dump load Thermal energy Heat Energy losses
This paper firstly investigated the thermal management of wasted energy from a stand-alone hybrid solar-windbattery power system. The total dump load or waste power can be up to 50% of total system power yield, and therefore waste energy management is urgent with high necessity. A new phase change material (PCM: Ba (OH)2·8H2O) with high storage capacity is introduced for the thermal management of hybrid power system. Different renewable energy configurations with different battery storage capacities are simulated and investigated. For different scenarios, the ratio of the captured thermal energy from waste energy to total solar/ wind power output ranges from 24.45% to 72.48% regarding all system losses. The cases without battery bank are featured by high thermal energy amount/ percentage (waste energy) and high power supply failure. Typical results show that, the total yearly renewable power output is 173,877 kWh with only 51.99% directly for demand load, and 57,672 kWh with 33.17% can be effectively stored in the thermal storage tank as heat, which can supply about 136 people’ heat demand per year. Compared with the water tank, the PCM thermal storage tank can save much space and land because of its high energy density. Appropriate thermal management of standalone hybrid solar-wind-battery power systems is necessary and feasible.
1. Introduction The major source of electricity is generated by burning fossil fuels. To reduce greenhouse gas emissions from burning fossil fuels, renewable and sustainable energy is an option. Renewable energy technologies, such as thermal solar energy, solar photovoltaic (PV), wind energy, bioenergy, hydropower, etc., are widely used to produce electricity all over the world. Renewables has the fast in the electricity sector by about 2.6% per year from 2012 to 2040. About 23.7% global electricity (1849 GW) is generated by sustainable energy in 2015 [1]. Since the wind power and solar energy have the inherent intermittency and fluctuation, the system can be combined with other energy methods to form a hybrid system to deal with the intermittent nature [2,3]. Usually, the energy storage methods, such as battery [4] and pumped storage [5], are necessary for their independent application processes and reliable power supply. When the wind, solar, or hybrid wind-solar energy system used as a stand-alone system, the dump load (to absorb excess power when the storage unit is fully charged [6]) is a significant problem, due to timing mismatch between power demand and generation. In real applications,
⁎
typical dumping loads are usually resistive loads such as air heaters or water heater components; increasing the battery capacity can effectively reduce the dumped power [7]. According to the studies of Lu and Ma et al. [8–10], more than 50%, 48.6% (as shown in Fig. 1) and 30% of the total energy output were transferred to a dump load as spilled energy, respectively. Other studies also presented similar results [11–14]. Therefore, the dump load or waste energy management is urgent with high necessity. It is important to find an appropriate method which can easily and economically store the waste energy. Battery energy is the most utilized method in solar PV system because the common use of solar PV is to provide electricity. Regarding the combined operation strategies, Angenendt et al. [15] found that battery size strongly influenced the economics of PV-battery storage systems with power-to-heat coupling. Ma et al. [16] established a standalone PV system (19.8 kWp) on an isolated island in Hong Kong. The roundtrip efficiency of the battery bank during a year was 74.3%, and the state of charge (SOC) was above 50% for the most time of the year. PCMs used in the PV units are also studied in recent years, especially for the cooling of the PV panel [17–19]. The electrical power of PV was improved around 13.6% by using PCM with 30 °C melting point
Corresponding author. E-mail address: [email protected] (L. Lu).
https://doi.org/10.1016/j.enconman.2019.112261 Received 30 August 2019; Received in revised form 5 November 2019; Accepted 6 November 2019 0196-8904/ © 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: J. Yan, et al., Energy Conversion and Management, https://doi.org/10.1016/j.enconman.2019.112261
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
Nomenclature
Subscripts
Symbols
batt B C CT
cp Cbatt DOD e E E(t) fR GT GS h H Href HWT L n N P PRP t T v v (t) VB
specific heat at constant pressure, kJ/kg·°C nominal capacity of one battery allowed depth of discharge, % efficiency, % energy, kWh energy at a time (t), kWh loss factor or derating factor of PV module, % hourly global solar radiation, kW/m2 standard incident radiation, 1000 W/m2 enthalpy, kJ/kg total thermal energy stored in the PCM tank, kWh reference height, m hub height, m total latent heat of the material, kJ/kg total number number electrical power, kW rated power output of PV module, kW time temperature, °C wind speed, m/s wind speed at H at a time (t), m/s rated voltage of the battery, V
day dload eh F gen inv liquidus load peak PV ref R solidus WT
Abbreviations ACH CAES DOD PV PCM SA SOC STC T-CCES
Greek β ΔH η σ
battery battery and inverter cut-in demand for energy during the days only energize by battery bank days only energize by storage bank daily load demand electrical heating cut-off system generators inverter liquidus load demand peak load solar photovoltaic/PV module reference rated solidus/eutectic wind turbines
liquid fraction latent heat in the PCM tank efficiency, % the self-discharge rate
air change rate per hour compressed air energy storage depth of discharge solar photovoltaic phase change material stand-alone state of charge standard test conditions thermal-compressed supercritical carbon dioxide energy storage
Superscripts γ
friction coefficient
Fig. 1. Summary of the energy flow during the simulated year [9].
compressed air energy storage (CAES) method [22], thermal-compressed supercritical carbon dioxide energy storage (T-CCES) system [23], fuel cell vehicle [24], and CAES & pumped hydroelectric storage system [25]. In addition, thermal energy storage is an important method. A new method of direct thermal energy storage was used by Okazaki et al. [26] in a wind power utilizing study. An optimization of capacities and distribution of electric heater and thermal storage for reduction of wind power curtailment was studied by Gou et al. [27]. The economic benefit in this case was improved about 44.65% after the optimization. However, the main energy storage material in above
according to the study of Su et al. [20]. PCMs are also introduced into the PV systems recently, especially when there are heating load requirements in the system. In addition, a PV-thermal collector system with ejector refrigeration cycle and PCM storage was investigated by Ghorbani et al. [21]. Increasing the battery capacity can effectively reduce the dumped power [7], but the cost of lithium-ion battery storage is very high. Therefore, the new feasibility methods which can use the dump load by low cost are necessary to be investigated. There are many storage methods in previous studies of wind turbine power system, such as 2
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
storage methods are expensive and complicated. Generally, there are many storage methods in solar PV system, wind turbine power system, solar thermal system, and hybrid renewable energy system. However, the researches on PCMs storage in PV-wind hybrid power systems are limited. As mentioned above, in a stand-alone hybrid photovoltaic-wind-battery power system, there is a large amount of dump load. Increasing the battery capacity can effectively reduce the dump load, but the cost is very high. At the same time, heating load may also be expected. Therefore, the application of heat storage in a PV-wind hybrid system becomes a promising method. The materials used in the thermal energy storage method usually are water and PCMs. Considering the low energy density of water, the PCMs can be a better choice. Among the PCMs, paraffin wax is often used, but the high cost and the risk of burning restrict its application. Therefore, this paper aims to analyze the feasibility of a thermal storage application for a stand-alone hybrid solar-wind-battery system in Hong Kong, and to propose a new PCM (Ba(OH)2·8H2O) for the thermal management of hybrid power system.
studies is water, and the sensible heat of water is much lower than the latent heat of other phase change materials. Heat storage is the most common method in solar thermal application, and water is the mainly utilized material [28–30]. In the study of Antoniadis and Martinopoulos [31], a new seasonal solar heat storage (water) method could cover about 67% of the heating load requirement. There are three main heat storage technologies, including sensible heat storage, latent heat storage, and chemical heat storage. The hot water storage is a typical sensible heat storage, but the small energy density of water restricts its application. Though the chemical heat storage has a large storage density, it is still in the experimental stage [32]. The latent heat storage (PCMs) is one of the most promising methods due to its advantages, such as great energy density, small temperature difference in the process of phase change and so on [33,34]. The large energy density can reduce the storage volume by over 50% [35]. Therefore, many researchers used the PCM method in their studies, especially in recent years [36–38]. Stearic acid and palmitic acid were used as different heat storage PCMs to provide the hot water in a solar thermal system [39]. A novel heat storage system using PCM was studied by numerical method for direct steam solar power plants by Kargar et al. [40]. In general, the PCM is a promising material in thermal solar system [41–44], and the paraffin wax is the most popular materials among PCMs. Standalone hybrid renewable energy systems are commonly used in remote and island areas to provide reliable power supply. There are many storage methods in the above three renewable systems, but battery storage is still the most utilized method in hybrid power systems because of the reliable electric requirement [2,45]. In addition, the pumped storage and fuel cell methods are other alternatives to further produce the electricity. Sultan et al. [5] studied a mathematical model of a proposed hybrid system, including solar PV, wind energy, and a pumped storage power station. The application of pumped hydro energy storage was also studied in a PV-wind system by Ma et al. [10,46]. In their study, about 38% of total output (456.6 kWh/day) was transferred to the pump unit for lifting water to upper reservoir, but there were only 56.6 kWh which could be reused again. Ishaq et al. [47] studied a solar-wind hybrid system with a hydrogen production linked with a hydrogen compression system, and Sichilalu et al. [48] studied a grid-tied PV–wind-fuel cell hybrid power supply system. Zhang et al. [49] and Madaci et al. [13] also investigated the application of fuel cell in a stand-alone hybrid solar and wind energy system. All the above
2. System component modelling 2.1. System description The hybrid solar-wind-battery system with thermal energy storage is presented in Fig. 2, which consists of a solar PV system, a wind power system, a storage bank (electric batteries and PCM thermal storage tank), load, an inverter, and a controller. The dump load, due to timing mismatch between power demand and generation, will be converted to heat, which will be thereafter stored in a PCM thermal storage tank via electric heater. The thermal energy in the seasonal heat storage tank can be used to cover the year-round heating demand of residents. An isolated land is considered as the application area of this system, which can be called a stand-alone (SA) system. The operation strategy of this kind system is shown in Fig. 3. The electric demand of buildings will be covered by solar PV and wind turbines. The battery bank will be discharged when the load exceeds the renewable energy. By contrast, whenever the renewable energy is higher than the electric demand and the SOC of battery is above 95%, the surplus renewable energy will be converted into thermal energy, which will be stored in the PCM thermal storage tank. A typical hourly mean load profile, throughout the whole year, is
Fig. 2. The energy flow diagram of proposed hybrid (PV-wind) system with battery and thermal storage. 3
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
Fig. 3. Operating strategy of the hybrid solar-wind energy system with thermal and battery storages.
selected, as shown in Fig. 4. The area of the building is about 668 m2. The number of floors is 3, and the height is 3 m for each floor. The window to wall ratio is 20%. The occupant density and the infiltration rate are 13 m2/person and 0.288 air change rate per hour (ACH) [50]. Internal heat gains are 10 and 15 W/m2 from the equipment and the lighting system. A hydronic air handling unit is designed with the supply air temperature between 17 and 21 °C. In addition, a hydronic space cooling system is designed to cover the space cooling demand with a supply chilled water temperature at 15 °C. The rated capacities of chillers for the air handling cooling and the space cooling are 293 kW and 506 kW [51], with nominal COPs at 2.8 and 2.6, respectively [52]. The daily mean load is estimated at 250 kWh/day in this paper.
respect to reference height [2].
v (t)/ vref (t ) = (HWT / Href )r
Usually the value of γ is taken as 1/7. Wind turbines arrangement effect (wake effect) in this study is assumed to be zero [2]. 2.4. Battery bank The lead-acid battery is usually used in energy systems because of the low capital cost, high depth of discharge (DOD), and reliability. The detailed information of the battery used in this study is shown in Table 3. The following equations are used to calculate the battery bank state of charge (SOC) at a time (t) [14]: Discharging process:
2.2. Solar PV module
Ebatt (t ) = Ebatt (t − 1)·(1 − σ ) − [(Eload (t )/einv ) − Egen (t )]
The rated power of polycrystalline PV module used in this research is 270 Wp. The essential information of PV module is shown in Table 1 [9,53]. At low mean temperature topography [54], the power of PV generator (kWh) can be obtained according to the following equation:
PPV (t ) = PRP ·fR ·(GT (t )/ GS )
Ebatt (t ) = Ebatt (t − 1)·(1 − σ ) + [Egen (t ) − (Eload (t )/ einv )]·ebatt
(1)
2.3. Wind turbine The power output curve has an important influence on a power output of a wind energy system. In addition, the local wind speed distribution, and the hub height of the wind tower are another two important parameters to affect the performance of each wind power generator. An appropriate power output model is a basic element in the simulation. The power output of a wind turbine can be calculated by [2]:
(νc ≤ ν ≤ νR ) ⎧ PR·(ν − νc )/(νR − νc ) PR (νR < ν ≤ νF ) ⎨ (ν < νc and ν > νF ) ⎩0
(4)
Charging process:
A derating factor (fR) of 80% is used in this paper [53].
PW (ν ) =
(3)
(2)
Basic description of wind turbine used in this paper is shown in Table 2. Different wind power generators have various hub heights, and the following equation is a simple model to calculate wind speed with
Fig. 4. Hourly mean load demand. 4
(5)
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
Table 1 PV module details.
Table 4 Ba(OH)2·8H2O details.
Manufacturer
Suntech solar panel
Mean specific heat capacity
1.817 kJ/(kg·°C)
Model Maximum operating current Maximum operating voltage Maximum power at STC Dimensions No. of cells Slop (degree) Lifetime Power tolerance
Polycrystalline 8.69 A 31.1 V 270 W 1650*992*35 mm 60 (6*10) 22.3° 25 years 0/+5W
Mean Density Latent heat Tsolidus Tliquidus
1.9 g/cm3 331.7 kJ/kg 76 °C 80 °C
where
h = href + Table 2 Wind turbine details. Sunning wind power Ltd.
Rated power Rated voltage (AC) Hub height Rated wind speed (m/s) Cunt-out wind speed (m/s) Cut-in wind speed (m/s) Survival wind speed (m/s) Life time
5.2 kW 48 V/300 V 15 11 None – Continuous Operation 2.5 70 25 years
T
ref
cp dT
⎧0 B = (T − Tsolidus )/ Tliquidus − Tsolidus if ⎨ ⎩1
(11)
if T < Tsolidus Tsolidus ≤ T ≤ Tliquidus if
T > Tliquidus
(12)
Afterwards, the calculation equation of latent heat amount can be obtained according to the following equation:
ΔH = βL
(13)
The latent heat content can vary between zero (for a solid) and L (for a liquid). The Ba(OH)2·8H2O is used as the PCM in this paper, and the property of the PCM is shown in Table 4 [33]. The energy balance equation of thermal storage tank can be calculated as:
Table 3 Technical details of battery and converter. component
Converter
∫T
The liquid fraction, β, can be defined as:
Manufacturer
Battery
(10)
H = h + ΔH
Manufacturer Nominal voltage Nominal capacity Maximum depth of discharge Roundtrip efficiency Life time
Zuhai seawill technology Co., Ltd. 2V 1000 Ah 80% 88% 20 years
Rated power Inverter efficiency (DC-AC) Rectifier efficiency (AC-DC) Life time
26 kW 90% 85% 20 years
H = (PPV + PWT − Eload − Ebatt )·ηeh
99% is employed for ηeh in this study. Heat insulation is assumed for this thermal storage tank. 3. Results and discussion According to our previous work [9], the installation capacities of solar PV and wind turbines are 145 kWp and 10.4 kW, as presented as Case 1 in this study. Different installation capacities of PV and wind turbines under a similar total capacity are also studied in this paper. A greater wind power case is presented as Case 2 with PV and wind turbine capacities of 103.4 kWp and 52 kW, respectively. Solar PV modules with 155.3 kWp are presented as Case 3, and Wind turbines with 156 kW are presented as Case 4. The thermal management of waste energy is studied at different battery storage capacities. There are six different scenarios for the battery storage capacity: Case n-0 without battery (0-day battery storage); Case n-1 with 1-day’s battery storage; Case n-2 with 2-days’ battery storage; Case n-3 with 3days’ battery storage; Case n-4 with 4-days’ battery storage; Case n-5 with 5-days’ battery storage. n can be 1, 2, 3 and 4, corresponding to Case 1, Case 2, Case 3 and Case 4. The simulation results of different cases are shown in Table 5. Case n-3 has a proper configuration and relative stable results. Therefore, the Case n-3 will be analyzed as a typical sample in the following discussion.
Energy generated Egen by PV and wind at a time (t) can be calculated as [14]:
Egen (t ) = NPV ·EPV (t ) + NWT ·EWT (t )
(6)
To design a storage bank meeting the required autonomous days, the following sizing approach is used:
CAh = ECT /(eB ·DOD ·VB ) = nday ·Edload/(eB ·DOD ·VB )
(7)
nbatt = CAh/ Cbatt
(8)
2.5. Power converter Converters are required when a system contains different DC and AC facilities. Wind power, load and dump energy have AC features while PV modules and storage bank are with DC features. The size of the converter depends on the peak load (Ppeak) demand of the system. The power rating (Pinv) of converter can be calculated as [14]:
Pinv = Ppeak / einv
(14)
3.1. Simulation results of renewable energy, battery and thermal energy storage
(9)
The detailed specification of converter is shown in Table 3.
The daily mean power generated by solar PV and wind turbines in different months are shown in Fig. 5. Most power is produced by PV in Case 1, Case 2 and Case 3, especially in the summer. The maximum total power and PV power are produced in July, and the minimum total power and PV power are in December. Generally, the wind power output is high in April, May and September.
2.6. PCM thermal storage tank The enthalpy of the phase change materials, H, is calculated as the sum of the sensible enthalpy, h, and the latent heat, ΔH [55–57]: 5
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
Table 5 Comparison of different cases. Total renewable output PV
WIND
Case 1 165,560 kWh 95.22%
Case 1 8317 kWh 4.78%
Case 2 118,081 kWh 73.95%
Case 3 177,275 kWh 100%
/
Case 2 41,586 kWh 26.05%
/
Case 4 124,758 kWh 100%
Case
days of battery storage
Thermal energy
Losses of electricity to heat
Converter losses
Battery bank losses
Useful energy
Failure days
Case 1–0
0
Case 1–2
2
Case 1–3
3
Case 1–4
4
Case 1–5
5
17,388 kWh 10% 16,598 kWh 9.55% 16,578 kWh 9.53% 16,565 kWh 9.53% 16,563 kWh 9.53% 16,566 kWh 9.53%
33,385 kWh 19.20% 86,443 kWh 49.71% 89,464 kWh 51.45% 90,396 kWh 51.99% 90,633 kWh 52.12% 90,760 kWh 52.20%
218
1
1232 kwh 0.71% 628 kWh 0.36% 593 kWh 0.34% 583 kWh 0.33% 580 kWh 0.33% 578 kWh 0.33%
/
Case 1–1
121,872 kWh 70.09% 62,151 kWh 35.74% 58,723 kWh 33.77% 57,672 kWh 33.17% 57,405 kWh 33.01% 57,256 kWh 32.93%
Case 2–0
0
Case 2–2
2
Case 2–3
3
Case 2–4
4
Case 2–5
5
15,967 kWh 10% 15,293 kWh 9.58% 15,253 kWh 9.55% 15,242 kWh 9.55% 15,237 kWh 9.54% 15,236 kWh 9.54%
42,531 kWh 26.64% 86,944 kWh 54.45% 89,701 kWh 56.18% 90,585 kWh 56.73% 91,047 kWh 57.02% 91,157 kWh 57.09%
192.6
1
1012 kWh 0.63% 507 kWh 0.32% 476 kWh 0.30% 466 kWh 0.29% 461 kWh 0.29% 459 kWh 0.29%
/
Case 2–1
100,157 kWh 62.73% 50,193 kWh 31.44% 47,090 kWh 29.49% 46,093 kWh 28.87% 45,580 kWh 28.55% 45,447 kWh 28.46%
Case 3–0
0
Case 3–2
2
Case 3–3
3
Case 3–4
4
Case 3–5
5
17,728 kWh 10% 16,905 kWh 9.54% 16,873 kWh 9.52% 16,872 kWh 9.52% 16,870 kWh 9.52% 16,869 kWh 9.52%
29,768 kWh 16.79% 85,308 kWh 48.12% 89,119 kWh 50.27% 90,057 kWh 50.80% 90,293 kWh 50.93% 90,503 kWh 51.05%
222
1
1299 kWh 0.73% 666 kWh 0.38% 623 kWh 0.35% 612 kWh 0.35% 609 kWh 0.34% 607 kWh 0.34%
/
Case 3–1
128,481 kWh 72.48% 65,963 kWh 37.21% 61,645 kWh 34.77% 60,576 kWh 34.17% 60,309 kWh 34.02% 60,071 kWh 33.89%
Case 4–0
0
Case 4–1
1
Case 4–2
2
Case 4–3
3
Case 4–4
4
Case 4–5
5
72,229 kWh 57.90% 44,916 kWh 36.00% 38,441 kWh 30.81% 34,624 kWh 27.75% 31,969 kWh 25.62% 30,504 kWh 24.45%
730 kWh 0.58% 454 kWh 0.36% 388 kWh 0.31% 350 kWh 0.28% 323 kWh 0.26% 308 kWh 0.25%
12,476 kWh 10% 12,108 kWh 9.71% 12,024 kWh 9.64% 11,973 kWh 9.60% 11,940 kWh 9.57% 11,922 kWh 9.56%
8057 kWh 4.63% 8519 kWh 4.90% 8660 kWh 4.98% 8696 kWh 5.00% 8716 kWh 5.01%
6729 kWh 4.21% 7147 kWh 4.48% 7281 kWh 4.56% 7342 kWh 4.60% 7368 kWh 4.61%
8433 kWh 4.76% 9014 kWh 5.09% 9158 kWh 5.17% 9194 kWh 5.19% 9227 kWh 5.20% / 3678 kWh 2.95% 4551 kWh 3.65% 5065 kWh 4.06% 5422 kWh 4.35% 5619 kWh 4.50%
39,324 kWh 31.52% 63,601 kWh 50.98% 69,354 kWh 55.59% 72746 kWh 58.31% 75,104 kWh 60.20% 76,404 kWh 61.24%
25.9 6 1.9 0.5 0
22 7.2 3 1 0.4
30.1 7.7 2.4 1.4 0.5 218 115 85.6 70.4 60.2 54
circles and the black line of the hollow triangles represent the PV output and WT output. Usually, solar power is produced during the daytime. It is used to cover the demand load first, and the surplus is used to charge the battery bank and PCM thermal storage tank, as indicated by the blue line of the hollow circles in Fig. 6. The black dash line illustrates the battery SOC and stands for the amount of power stored in the battery bank. The battery bank is intermittently charged or discharged during this week. If the SOC is larger than 95%, the surplus energy is then fed into the PCM thermal storage tank, represented by the green line. During this week, the renewable power exceeds the load during daytime, and the battery bank will release energy at night in Case 1–3 and Case 3–3. The wind and solar resources can meet the demand load during the whole days of 1st to 3th April in Case 2–3. In general, the energy profiles of Case 1–3, Case 2–3, and Case 3–3 are similar, and thermal energy is largely stored during the first five days. However, Case 4–3 is different. The wind power can meet the demand load from 1st to 4th April, and heat is largely obtained during the period. Then,
According to Fig. 5, the power generated by solar PV is much larger than the power generated by wind turbines under a same capacity of PV and wind turbines, except for April. The daily mean renewable power is usually greater than the load in different months, except for the Case 4. The superfluous electric energy is changed to thermal energy and stored as heat in this study. The load exceeds the renewable power during June, July and August under Case 4. Therefore, the only wind case will have more failure days, as demonstrated in Table 5. The results of a typical example of Case n-3 during a week are shown in Fig. 6. It shows that the power generated by PV and wind turbine is much larger than the load and the excess energy will be stored in the battery bank. The battery bank will release energy when the load exceeds the sustainable energy, and the further extra electrical energy will be changed into heat and then stored as thermal energy in the PCM thermal storage tank if the battery SOC is above 95%. If there is no PCM thermal storage tank, this part energy (the further extra electricity) will be used as the waste energy and dump load. The black line displays the load profile for this study. The red lines of the solid 6
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
simulated year and the comparison of different forms of energy. As shown in Fig. 7, the total renewable output is 173,877 kWh, including PV power of 165,560 kWh and wind turbine of 8317 kWh. Most of the power (51.99%) is used to supply the load (useful energy), and 33.17% of the energy is stored in the PCM thermal storage tank as heat. This thermal energy can be used to supply the daily heat demand of residents. As shown in Fig. 8, the rest part of the renewable output is converted into different energy losses, including converter losses, battery bank losses and losses of electricity to heat. The loss during the electricity changed into heat is 0.33%, which is the minimum losses. The largest loss is the converter loss at 9.53%, because the renewable output is DC power and DC/AC converter is needed. If the heat thermal management is not provided, a total system energy loss of 48.01%. Therefore, thermal management is very important for stand-alone solar/wind energy systems. 3.3. The effects of different cases and battery bank capacity on thermal energy
Fig. 5. Hourly mean load and power generated by PV and wind in different months.
Figs. 9 and 10 summarize the thermal energy conditions under different renewable energy configurations with different battery storage capacities. In general, Case 3 (only PV) has the greatest waste heat, but there is still half day’s power failure Case 3–5. Case 1–5 provides reliable power supply without failure. If there is no battery bank (0-day battery storage), a greatest thermal energy amount and will be resulted together with also the largest power failure days. Therefore, it is not an appropriate configuration considering the demand of electric load. Basically, Case 4 (only wind turbine) has the worst performance, and Case 4–1 has a bigger thermal energy percentage than Case 1–1 and Case 2–1. In addition, the heat amount is very similar when the battery storage capacity is above 2 days under the Case 1, Case 2 and Case 3. However, as shown in Fig. 9, the thermal energy amount of Case 4 is obviously decreasing with the increase of battery bank capacity. In addition, different conditions for the battery storage capacity are simulated, and the results are illustrated in Table 5. For Case n-0, if
the wind energy is insufficient, and the battery bank discharges and supplies the additional energy with dropping SOC. Due to the limit of the maximum allowable charging rate (95%) and state of the battery during the calculation step, the excessive energy is not totally stored in the batter bank when the SOC has not arrived a 100% level for sometimes. With abundant wind and solar energy and high SOC, a lot of thermal energy is obtained and stored in the PCM tank.
3.2. The analysis of thermal energy among the different energy forms In this part, Case 1–3 is analyzed as a typical case. The results of other cases are shown in Table 5. The results from Case n-1 to Case n-5 have the similar trend, except that Case n-0 has a greater thermal energy. Figs. 7 and 8 display the energy flow of Case 1–3 during the
Fig. 6. Hourly sample simulation results for a week (1st to 7th April).(a) Case 1–3; (b) Case 2–3; (c) Case 3–3; (d) Case 4–3. 7
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
Fig. 7. Summary of the energy flow during the simulated year. (Case 1–3).
there is no battery bank, the power supply failure days and heat will be very large. The useful electrical energy of Case 3–0 has the least amount of about 29,768 kWh with useful rate of 16.79% only, so most power is wasted or converted into thermal energy. Case 3–0 has the largest amount of thermal energy, about 128,481 kWh during the whole year. The power failure days will be reduced with the increase of battery bank capacity. There will be no failure days with a 5-days’ battery storage for Case 1–5. Thermal energy storage is declined with the increase of battery bank capacity. It shows that the difference of rate of thermal energy is less than 1% after the battery bank capacity is above 2 days, except Case 4. The heat stored into the thermal tank is relatively stable when the battery bank capacity is above 2 days. In addition, Case 4 (only wind turbine) has the least amount of thermal energy and the worst power supply failure. 3.4. PCM thermal storage tank Fig. 11 shows the results of accumulative heat of cases with 3 day’s battery storage capacity during the simulated year. The slope of the line represents the accumulated amount of thermal energy. For instance, the slope of the line is gentle on the 150th day with less thermal energy produced. The total thermal energy of Case 1–3, Case 2–3, Case 3–3, and Case 4–3, which can be stored in the PCM thermal storage tank, is about 57,672 kWh, 46,028 kWh, 60,576 kWh, and 34,217 kWh,
Fig. 9. Comparison of total heat storage under different cases (Different renewable energy configurations with different battery storage capacities).
respectively, during the simulated year. The figures are very promising. It is assumed that 40 L hot water is needed for one person. The daily mean temperature of the hot water needs to raise 25 °C (For instance,
Fig. 8. Comparison of different forms of energy. (Case 1–3). 8
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
Hong Kong, and proposed a new PCM technology for the thermal storage. The main conclusions are drawn as below: 1. For a stand-alone hybrid solar-wind-battery power system, the dump load or waste power can reach up to 50%. Therefore, waste energy management or thermal management is urgent with high necessity. 2. A new PCM (Ba(OH)2·8H2O) for the thermal management of hybrid power system is newly introduced which has high storage capacity. 3. Different renewable energy configurations with different battery storage capacities are simulated and investigated. For different scenarios, the ratio of the captured thermal energy from waste energy to total solar/wind power output can range from 24.45% to 72.48% regarding all system losses, such as wiring and inverter losses, battery charging/discharging losses, thermal storage loss, etc. The cases without battery bank are featured by high thermal energy amount/ percentage (waste energy) and high power supply failure. Furthermore, the energy systems with only wind turbines perform the worst. 4. In a typical Case 1–3, the total yearly renewable power output is 173,877 kWh with only 51.99% directly for demand load and 33.17% being effectively stored in the thermal storage tank as heat. 5. The new PCM technology for the thermal storage is feasible. The total stored thermal energy of Case 1–3, Case 2–3, Case 3–3 and Case 4–3 in the PCM thermal storage tank is about 57,672 kWh, 46,028 kWh, 60,576 kWh, and 34,217 kWh, respectively, during the simulated year. The simulation results show that the total thermal energy storage of Case 1–3 can supply about 136 people’ heat demand per year. Compared with the water tank, the PCM thermal storage tank can save much space and land because of its high energy density.
Fig. 10. Comparison of thermal energy percentage under different cases (Different renewable energy configurations with different battery storage capacities).
To conclude, appropriate thermal management of stand-alone hybrid solar-wind-battery power systems is necessary and feasible. It can fully utilize the waste energy or dump load to provide a large amount of heating load. Declaration of Competing Interest Fig. 11. Accumulative thermal energy during the simulated year. (Case n-3).
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
from 25 °C to 50 °C). Then, the daily thermal load is calculated to be about 1.16 kWh, and the yearly thermal load is 423.4 kWh per person. Therefore, the total thermal energy storage of Case 1–3 can supply about 136 people’ heat demand per year. The number of the people is 108 for Case 2–3, 143 for Case 3–3 and 80 for Case 4–3, respectively. According to the description of PCM (Ba(OH)2·8H2O) property in Section 2.6, 1-ton materials of this PCM can store about 112.3 kWh thermal energy from 50 °C to 90 °C. Considering the hot water temperature and heat transfer temperature difference, the initial temperature 50 °C is selected in the calculation. Considering the application of the seasonal heat storage, it needs about 514 tons PCM materials for the total thermal energy in Case 1–3, and it will be about 270 m3. If we use the water tank to store this heat, 1-ton water can store about 46.4 kWh thermal energy from 50 °C to 90 °C. It needs about 1243 tons water for the total thermal energy in Case 1–3, and it will be about 1243 m3. The volume of water tank is about 4.6 times larger than that of the PCM tank. The cost of land can sharply reduce with PCM tank. The PCM tank volume of Case 2–3, Case 3–3, and Case 4–3 will be about 216 m3, 284 m3, and 160 m3, respectively. The corresponding volume of water tank is about 994 m3, 1306 m3, and 736 m3, respectively.
Acknowledgments This work is supported by the National Natural Science Foundation of China (Grant No: 51706130), and the Hong Kong Scholars Program (Grant No: XJ2018015). References [1] Goel S, Sharma R. Performance evaluation of stand alone, grid connected and hybrid renewable energy systems for rural application: a comparative review. Renew Sustain Energy Rev 2017;78:1378–89. [2] Yang H, Lu L, Zhou W. A novel optimization sizing model for hybrid solar-wind power generation system. Sol Energy 2007;81:76–84. [3] Yang HX, Lu L, Burnett J. Weather data and probability analysis of hybrid photovoltaic–wind power generation systems in Hong Kong. Renew Energy 2003;28:1813–24. [4] Plytaria MT, Bellos E, Tzivanidis C, Antonopoulos KA. Financial and energetic evaluation of solar-assisted heat pump underfloor heating systems with phase change materials. Appl Therm Eng 2019;149:548–64. [5] Sultan HM, Zaki Diab AA, Kuznetsov Oleg N, Zubkova Irina S. Design and evaluation of PV-wind hybrid system with hydroelectric pumped storage on the National Power System of Egypt. Global Energy Interconnection 2018;1:301–11. [6] Alnasir Z, Kazerani M. An analytical literature review of stand-alone wind energy conversion systems from generator viewpoint. Renew Sustain Energy Rev 2013;28:597–615. [7] Li H, Campana PE, Tan Y, Yan J. Feasibility study about using a stand-alone wind power driven heat pump for space heating. Appl Energy 2018;228:1486–98.
4. Conclusions This paper firstly investigated the thermal management of the waste energy of a stand-alone hybrid solar-wind-battery power system in 9
Energy Conversion and Management xxx (xxxx) xxxx
J. Yan, et al.
thermochemical heat storage. Appl Energy 2016;175:277–84. [33] Wang Q, Wang J, Chen Y, Zhao CY. Experimental investigation of barium hydroxide octahydrate as latent heat storage materials. Sol Energy 2019;177:99–107. [34] Zhou Y, Zheng S, Zhang G. Study on the energy performance enhancement of a new PCMs integrated hybrid system with the active cooling and hybrid ventilations. Energy 2019;179:111–28. [35] Teamah HM, Lightstone MF, Cotton JS. Potential of cascaded phase change materials in enhancing the performance of solar domestic hot water systems. Sol Energy 2018;159:519–30. [36] Abu-Arabi M, Al-harahsheh M, Mousa H, Alzghoul Z. Theoretical investigation of solar desalination with solar still having phase change material and connected to a solar collector. Desalination 2018;448:60–8. [37] Raj AK, Srinivas M, Jayaraj S. A cost-effective method to improve the performance of solar air heaters using discrete macro-encapsulated PCM capsules for drying applications. Appl Therm Eng 2019;146:910–20. [38] Bilardo M, Fraisse G, Pailha M, Fabrizio E. Modelling and performance analysis of a new concept of integral collector storage (ICS) with phase change material. Sol Energy 2019;183:425–40. [39] Prakash J, Roan D, Tauqir W, Nazir H, Ali M, Kannan A. Off-grid solar thermal water heating system using phase-change materials: design, integration and real environment investigation. Appl Energy 2019;240:73–83. [40] Kargar MR, Baniasadi E, Mosharaf-Dehkordi M. Numerical analysis of a new thermal energy storage system using phase change materials for direct steam parabolic trough solar power plants. Sol Energy 2018;170:594–605. [41] Zhao J, Yuan Y, Haghighat F, Lu J, Feng G. Investigation of energy performance and operational schemes of a Tibet-focused PCM-integrated solar heating system employing a dynamic energy simulation model. Energy 2019;172:141–54. [42] Hirmiz R, Lightstone MF, Cotton JS. Performance enhancement of solar absorption cooling systems using thermal energy storage with phase change materials. Appl Energy 2018;223:11–29. [43] Wang Y, Yang X, Xiong T, Li W, Shah KW. Performance evaluation approach for solar heat storage systems using phase change material. Energy Build 2017;155:115–27. [44] Wang Z, Sun S, Lin X, Liu C, Tong N, Sui Q, et al. A remote integrated energy system based on cogeneration of a concentrating solar power plant and buildings with phase change materials. Energy Convers Manage 2019;187:472–85. [45] Huang Q, Shi Y, Wang Y, Lu L, Cui Y. Multi-turbine wind-solar hybrid system. Renew Energy 2015;76:401–7. [46] Ma T, Yang H, Lu L. Feasibility study and economic analysis of pumped hydro storage and battery storage for a renewable energy powered island. Energy Convers Manage 2014;79:387–97. [47] Ishaq H, Dincer I, Naterer GF. Development and assessment of a solar, wind and hydrogen hybrid trigeneration system. Int J Hydrogen Energy 2018;43:23148–60. [48] Sichilalu S, Tazvinga H, Xia X. Optimal control of a fuel cell/wind/PV/grid hybrid system with thermal heat pump load. Sol Energy 2016;135:59–69. [49] Zhang W, Maleki A, Rosen MA, Liu J. Sizing a stand-alone solar-wind-hydrogen energy system using weather forecasting and a hybrid search optimization algorithm. Energy Convers Manage 2019;180:609–21. [50] Performance-based building energy code 2007. https://www.emsd.gov.hk/ filemanager/en/content_725/PBBEC_Guidelines_2007.pdf. [51] Air-Cooled Liquid Chillers with Integrated Hydronic Module, 30RB 162-802 Nominal cooling capacity 162-774 kW. https://climamarket.bg/wp-content/ uploads/Tech-Spec-Carrier-30RB-162-802.pdf; 2012. [52] Zhou Y, Cao S. Energy flexibility investigation of advanced grid-responsive energy control strategies with the static battery and electric vehicles: a case study of a highrise office building in Hong Kong. Energy Convers Manage 2019;199:111888. [53] Ma T, Javed MS. Integrated sizing of hybrid PV-wind-battery system for remote island considering the saturation of each renewable energy resource. Energy Convers Manage 2019;182:178–90. [54] Singh S, Singh M, Kaushik SC. Feasibility study of an islanded microgrid in rural area consisting of PV, wind, biomass and battery energy storage system. Energy Convers Manage 2016;128:178–90. [55] Arampatzis G, Assimacopoulos D. Numerical modeling of convection-diffusion phase change problems. Comput Mech 1998;21:409–15. [56] Sciacovelli A, Colella F, Verda V. Melting of PCM in a thermal energy storage unit: numerical investigation and effect of nanoparticle enhancement. Int J Energy Res 2013;37:1610–23. [57] Lu W, Liu Z, Flor J-F, Wu Y, Yang M. Investigation on designed fins-enhanced phase change materials system for thermal management of a novel building integrated concentrating PV. Appl Energy 2018;225:696–709.
[8] Lu L. Investigation on characteristics and application of hybrid solar-wind power generation systems. The Hong Kong Polytechnic University; 2004. [9] Ma T, Yang H, Lu L. A feasibility study of a stand-alone hybrid solar–wind–battery system for a remote island. Appl Energy 2014;121:149–58. [10] Ma T, Yang H, Lu L, Peng J. Technical feasibility study on a standalone hybrid solarwind system with pumped hydro storage for a remote island in Hong Kong. Renew Energy 2014;69:7–15. [11] Kalantar M, Mousavi G. SM. Dynamic behavior of a stand-alone hybrid power generation system of wind turbine, microturbine, solar array and battery storage. Appl Energy 2010;87:3051–64. [12] Astolfi M, Mazzola S, Silva P, Macchi E. A synergic integration of desalination and solar energy systems in stand-alone microgrids. Desalination 2017;419:169–80. [13] Madaci B, Chenni R, Kurt E, Hemsas KE. Design and control of a stand-alone hybrid power system. Int J Hydrogen Energy 2016;41:12485–96. [14] Javed MS, Song A, Ma T. Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm. Energy 2019;176:704–17. [15] Angenendt G, Zurmühlen S, Rücker F, Axelsen H, Sauer DU. Optimization and operation of integrated homes with photovoltaic battery energy storage systems and power-to-heat coupling. Energy Convers Manage: X 2019;1:100005. [16] Ma T, Yang H, Lu L. Performance evaluation of a stand-alone photovoltaic system on an isolated island in Hong Kong. Appl Energy 2013;112:663–72. [17] Ma T, Zhao J, Li Z. Mathematical modelling and sensitivity analysis of solar photovoltaic panel integrated with phase change material. Appl Energy 2018;228:1147–58. [18] Tabet Aoul K, Hassan A, Shah AH, Riaz H. Energy performance comparison of concentrated photovoltaic – phase change material thermal (CPV-PCM/T) system with flat plate collector (FPC). Sol Energy 2018;176:453–64. [19] Zhou Y, Zheng S, Zhang G. Artificial neural network based multivariable optimization of a hybrid system integrated with phase change materials, active cooling and hybrid ventilations. Energy Convers Manage 2019;197:111859. [20] Su D, Jia Y, Lin Y, Fang G. Maximizing the energy output of a photovoltaic–thermal solar collector incorporating phase change materials. Energy Build 2017;153:382–91. [21] Ghorbani B, Mehrpooya M, Sharifzadeh MMM. Introducing a hybrid photovoltaicthermal collector, ejector refrigeration cycle and phase change material storage energy system (Energy, exergy and economic analysis). Int J Refrig 2019;103:61–76. [22] Jin H, Liu P, Li Z. Dynamic modeling and design of a hybrid compressed air energy storage and wind turbine system for wind power fluctuation reduction. Comput Chem Eng 2019;122:59–65. [23] Chaychizadeh F, Dehghandorost H, Aliabadi A, Taklifi A. Stochastic dynamic simulation of a novel hybrid thermal-compressed carbon dioxide energy storage system (T-CCES) integrated with a wind farm. Energy Convers Manage 2018;166:500–11. [24] Hemmati R. Technical and economic analysis of home energy management system incorporating small-scale wind turbine and battery energy storage system. J Clean Prod 2017;159:106–18. [25] Caralis G, Christakopoulos T, Karellas S, Gao Z. Analysis of energy storage systems to exploit wind energy curtailment in Crete. Renew Sustain Energy Rev 2019;103:122–39. [26] Okazaki T, Shirai Y, Nakamura T. Concept study of wind power utilizing direct thermal energy conversion and thermal energy storage. Renew Energy 2015;83:332–8. [27] Gou X, Chen Q, Hu K, Ma H, Chen L, Wang X-H, et al. Optimal planning of capacities and distribution of electric heater and heat storage for reduction of wind power curtailment in power systems. Energy 2018;160:763–73. [28] Launay S, Kadoch B, Le Métayer O, Parrado C. Analysis strategy for multi-criteria optimization: application to inter-seasonal solar heat storage for residential building needs. Energy 2019;171:419–34. [29] Artur C, Neves D, Cuamba BC, Leão AJ. Comparison of two dynamic approaches to modelling solar thermal systems for domestic hot water. Sustain Energy Technol Assess 2018;30:292–303. [30] Hohne PA, Kusakana K, Numbi BP. Optimal energy management and economic analysis of a grid-connected hybrid solar water heating system: a case of Bloemfontein, South Africa. Sustain Energy Technol Assess 2019;31:273–91. [31] Antoniadis CN, Martinopoulos G. Optimization of a building integrated solar thermal system with seasonal storage using TRNSYS. Renew Energy 2019;137:56–66. [32] Yan J, Zhao CY. Experimental study of CaO/Ca(OH)2 in a fixed-bed reactor for
10