Hybrid pumped hydro and battery storage for renewable energy based power supply system

Applied Energy 257 (2020) 114026

Contents lists available at ScienceDirect

Applied Energy journal homepage: www.elsevier.com/locate/apenergy

Hybrid pumped hydro and battery storage for renewable energy based power supply system

T

Muhammad Shahzad Javeda,1, Dan Zhongb,1, Tao Maa, , Aotian Songc, Salman Ahmeda ⁎

a

School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China Zhuhai Da Hengqin Science and Technology Development Co. Ltd, Zhuhai, China c Shenzhen Pavo-Tech Development Co. Ltd, Shenzhen, China b

HIGHLIGHTS

GRAPHICAL ABSTRACT

hybrid pumped and battery storage • A(HPBS) is proposed for off-grid re-

Modelling

Performance evaluation

newable energy systems.

novel operating strategy of HPBS • Abased renewable energy system is de-

• • •

veloped. The operation range of reversible pump-turbine machine is defined for each storage functionality. Three factors SOP, SUF and EUR are put forwarded for HPBS evaluation. The proposed study could support the hybrid storage deployment for remote areas.

53.0 kWp

Upper reservoir

PV array

Dump Load WT Pump/turbine

PV array

Evaluation indices Storage overall performance • Storage usage factor • Energy utilization ratio

AC bus

DC bus

175.2 kWh

•

Dump load

202.0 kWh 26.7 192.0 kWh kWh

32.4 kWh

Bat tery bank

32.4 kWh

Hybrid charge cont roller

255.6 kWh Load

12.7 kWh

181.8 kWh

131.9 kWh

15.0 kW

88.0 kWh

31.0 kW

36.0 kWh

255.6 kWh

Wind turbine

Pump & Motor

LR

58.0 kWh

670 m3 UR

8758 m3

660 m3 Turbine & Generator

31.0 kW

Battery Bank

Motor/ Generator

Water Electricity

ARTICLE INFO

ABSTRACT

Keywords: Hybrid pumped and battery storage Renewable energy Energy balance analysis Storage overall performance Energy utilization ratio

It is very challenging for single energy storage to make an off-grid renewable energy (RE) system that is fully capable and reliable, unless there are an oversized generator and storage capacities which eventually lead to high dump load, due to high variability and intermittency of RE resources. In this study, a hybrid pumped and battery storage (HPBS) system is proposed to make the off-grid RE system more reliable and sustainable. Firstly sizing of RE generators and energy storages is accomplished, then a novel operating strategy of the HPBS based RE system is developed, considering the operating range of reversible pump-turbine machine, to extract maximum stored energy by operating HPBS at optimum efficiency. In the proposed model, the battery is only used in order to meet very low energy shortfalls considering the net power deficiency and state of charge, while pumped hydro storage works as the main storage for high energy demand. To make sure the functionality of each energy storage, HPBS operating strategy is developed based on the operating range, both in discharging/charging, of reversible pump-turbine machine which is defined after several simulation cases. Some indicators including storage overall performance (SOP), energy utilization ratio (EUR) and storage usage factor (SUF) are taken into account for HPBS performance analysis. It is observed, that by employing the hydro turbine with operation in range from 20% to 100%, a high SUF for pumped storage can be attained while the SOP of battery is high due to

Corresponding author. E-mail address: [email protected] (T. Ma). 1 These authors contributed eqaully to this work. ⁎

https://doi.org/10.1016/j.apenergy.2019.114026 Received 27 May 2019; Received in revised form 9 October 2019; Accepted 14 October 2019 0306-2619/ © 2019 Elsevier Ltd. All rights reserved.

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

a small regular energy flow from it. After one-year simulation, the overall SOP and SUF of HPBS is calculated as 66.4% and 7.3% respectively, while EUR of the whole system is 16.5%. Finally, the energy balance of the proposed system is analyzed to reveal the detailed operational performance of HPBS.

Nomenclature

Pnet Pt b

d wall thickness of upper reservoir EPV - nominal nominal available PV energy (kWh) EWT - nominal nominal available WT energy (kWh) EUR energy utilization ratio PPV power produced by solar arrays (kW) PWT power produced by all wind turbines (kW) pc p surplus power sent to PHS pump from charge controller (kW) pg c generated power sent to charge controller from PHS (kW) Pload load demand (kW) Prated rated power of reversible pump-turbine machine (kW) Pb p power sent to pump/motor from battery bank (kW) Pbatt battery bank power (kW) Pexcess additional surplus power when pump is running at rated speed (kW)

p

Pg c Pb c Ps l RES SOCbatt SOCres SOP SUF Varray pump gen

PT

net surplus power sent to pump/motor (kW) power sent to battery bank when turbine is running at rated speed (kW) generated PHS power sent to controller (kW) battery bank power sent to controller (kW) total hybrid storage power sent to meet load (kW) renewable energy system state of charge of battery bank state of charge of upper reservoir storage overall performance storage usage factor battery array voltage total PHS charging efficiency total PHS discharging efficiency efficiency of reversible pump-turbine machine/PHS

performance of RES considering different energy storages like, PHS, battery, hydrogen based units and inferred that fuel cells are most economical energy storage in hydrogen based energy storage. Zheng et al. [17] comprehensively reviewed the hydrogen based energy storage units and declared that integration of hybrid approaches is promising. An optimization tool for the design of fuel cells integrated RES is developed by Sorrentino et al. [18] in terms of economical and technical feasibility. A comprehensive review about EES options for increased intermittent RE penetration, especially for an off-grid RES, is given in Refs. [19,20]. In authors’ previous studies, PHS is first proposed for standalone applications [21] and compared battery storage [22], the mathematical model and sizing method was developed [23,24], and has been widely used in follow-up studies in literature, such as Ref. [25] proposed the PHS in conjunction with off-grid hydrokinetic system by using same PHS mathematical model and performed techno-economic feasibility by comparing it with battery storage option. Capacity sizing of PHS based RE system is performed considering the demand side response in operational planning and whole system life cycle cost is minimized in Ref. [26]. The idea of integrating PV-PHS system with small hydroelectric system to ensure continuous and reliable power supply throughout the year, considering same PHS model, is accomplished in Ref. [27]. Similarly, numerous case studies in literature consisted of the authors’ proposed PHS model with different ideas. To overcome the disharmony between RE generation and load demand, the integration of PHS and battery has been proposed in literature but barely explored. For example, feasibility study of different energy storages for a remote island in Hong Kong is discussed in Ref. [2] and suggested that solar/wind/PHS/battery system is most economical and viable option for proposed island. Realistic PHS storage model considering the water level, flow rate and losses was proposed in Ref. [28] and validated through experiments, claiming that estimated error of stored water reduced significantly from 13.17% to 0.74%. Risk assessment predictive method for PHS based wind farm is proposed and compared with other alternative methods in Ref. [29]. Cost optimal RES for six different islands across the globe using PHS and battery energy storages with the aim of increased penetration of RE is presented in Ref. [30] and the study claims that increased penetration of RE caused a reduction of cost of energy (COE) for the islands. RES with PHS-battery hybrid storage for remote area to solve water and energy

1. Introduction With the awareness of fossil fuel energy and the increasing deployment of renewable energy (RE), the electrical power production has significantly changed, eventually intensifying the reliability and sustainability challenges for off-grid power supply [1]. RE intermittency and non-uniformity between generation-supply limits the RE integration at large scale, especially when the energy system is autonomous and RE is the primary energy source [2,3]. To overcome these challenges viable solutions have been made which include demand management through load shifting, electrical energy storage (EES), national grids interconnection etc. Among all these possible approaches, EES has been proposed as the most promising solution [4,5]. Although EES is a developed technology, it still has many unexplored areas for research [2]. The main function of EES in renewable energy systems (RES) is to ensure power generation when RE sources are unable to meet the load demand and make sure of RE generation when demand is low i.e. time-shifting and load leveling. Having an economical and viable energy storage is still a great challenge, especially for an off-grid RES. Usually, autonomous RES employs rechargeable batteries to overcome the disharmony between generation and supply [6,7]. Due to their short time period needed for construction of energy bank and flexible installation location, rechargeable batteries have been widely used for off-grid RES studies [8]. Among all rechargeable batteries, lead-acid and lithium-ion batteries are always considered as a premium choice for micro grids due to fast and steady response time, small selfdischarge rate (less than0.3%), low capital cost and a good cycle efficiency (63–90%) [9,10]. On other hand, pumped hydro storage (PHS) integrated RES has gained much popularity due to low maintenance cost, long life, high energy density, and environment friendly. Some globally installed PHS are comprehensively analyzed and presented in Ref. [11]. However, PHS low power density and risk of energy spill to balance inferior energy shortages necessitates the hybridization of PHS by employing complimentary characteristic energy storage and hence enhance the energy storage range of services for RES. Hybrid energy storage technologies are broadly studied in literature for instance: battery/pumped hydro [2], battery/supercapacitor [12], battery/fuel cell [13], battery/flywheel [14] and battery/flywheel/capacitors [15]. Awan et al. [16] analyzed the techno-economic 2

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

shortage simultaneously is proposed and discussed in Ref. [31], while dynamic modelling and supervisory controller for the integration of wind/diesel generator/battery/PHS is proposed in Ref. [32]. Therefore, it is meaningful to explore the significance of hybrid pumped and battery storage (HPBS) for remote areas. After looking into the literature, it is evident that very few studies explore the domain of HPBS due to the non-availability of any software and operational algorithm that can develop and simulate the HPBS model. Thus, an effective operating and management strategy is still indispensable to address the hybrid storage issues with daily RE generation and load demand schedule. Compared with the existing research of energy storage for RE built environment, the advantages and highlights of our study are mentioned as follows:

description, components sizing and modelling method is presented in Section 2. Section 3 discusses the system’s operating strategy and energy balance model, while system evaluation indicators are introduced in Section 4. Section 5 presents the results and brief discussion. Finally, concluding remarks are given in Section 6. 2. System description, components sizing and modelling 2.1. System description The system components and energy flow of RES with HPBS system are shown in Fig. 1. The main components of the system are photovoltaic (PV) modules, wind turbine, hybrid charge controller, PHS with reversible adjustable pump-turbine machine, lead-acid batteries, load, inverter, dump load/water desalination plant. The red lines represent the electricity flow while water flow is shown with blue. The hybrid charge controller regulates the whole system, including the AC/DC load fluctuations and RE intermittency with the help of HPBS. Solar and wind are the only energy generation sources while the hybrid storage will be employed on the basis of amount of net power (surplus or deficit) to balance the generation-demand and mitigate the intermittency of RE sources. The operating principle of the HPBS base RES is of vital importance and divided into charging and discharging scenarios i.e. when the net power is positive for any time period, it means there will be a charging process for that time period and vice versa. The operating strategy will be briefly discussed in following sections. The benefit of proposed operating strategy is that PHS will come in operation only when absolute power deficiency is higher, thus it will work as peak power shaving. As the power density and response time of battery bank is higher than PHS (as presented in Table 1), it is obvious that battery bank can easily and rapidly deal with the inferior power shortages and hence can avoid the low-efficiency output of pump/turbine at partial loads. Another major benefit of the proposed operating strategy is that it will reduce the start/stop numbers of reversible pumpturbine machine and will increase the operating life, which is the major

1. Most studies focus on single energy storage for RES i.e. wither PHS or battery only, however, this paper presents the operation model of hybrid storage. 2. Existing studies do not consider the operating range of energy storages for the operating strategy of RES, which is important for hybrid storage usage to make sure about the functionality of each storage, however, this paper defines the operating range of each energy storage. 3. Operating range of reversible pump-turbine machine is defined precisely after several simulations of different cases having various ranges, to extract the maximum stored energy. 4. Factors like the storage overall performance (SOP) and storage usage factor (SUF) have been considered in this study to assess the HPBS performance specifically while existing studies considered these factors to analyze the whole system performance. Whole system performance is evaluated in terms of energy utilization ratio (EUR). 5. Considering the 100% reliability constraint, the abilities of HPBS to adjust the energy deficits/surplus have been assessed and compared which is also one of innovations. The rest of the paper is structured as follows. A brief system

Upper reservoir PV array Inverter

Dump Load/water cleaning

Pumping Hybrid charge controller

AC load Pump/turbine

Wind turbine

Motor/Generator

Lower reservoir/ Natural sea

Battery Bank

Fig. 1. The energy flow diagram of typical hybrid storage based standalone RES. 3

Generation

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

Table 1 Technical characteristics of PHS and batteries [11,35].

H0 =

Parameter

unit

PHS

Lead-acid

Lithium-ion

Energy density Power density Power rating Self-discharge Discharge efficiency Cycling times Response time Storage duration Maturity Lifetime

W h/L W/L MW % %

0.5–2 0.5–1.5 100–50,000 very small 87

50–90 10–400 0–40 0.1–0.3 85

200–400 1500–10,000 0–100 0.1–0.3 85

cycles – –

10,000–30,000 minutes/not rapid long-term

– Years

mature 40–60

500–1800 milliseconds minutes-days (short term) mature 5–15

1000–20,000 milliseconds minutes-days (short term) demonstration 5–15

(cos

s

a] × N

s

+

)

sin . sin

180

)

(2)

248 + dn 365

(3) (4)

= cos 1 ( tan . tan )

N=

2 cos 1 ( tan . tan ) 15

(5)

Based on the above provided Eqs. (1)–(5), the average and maximum possible monthly daily sunshine hours for the proposed island are calculated and shown in Table 2. Here it is important to note that the average mid-day of each month is taken as reference [36], while second last column shows the monthly daily average solar radiation obtained from metrological laboratory and last column illustrates the monthly average extraterrestrial radiation on the proposed island.

2.2.1. Solar energy potential assessment Solar radiation profile can also be expressed in the form of sunshine hours when specific site data is not available especially for remote/offgrid areas, and average incident radiations can be estimated by using empirical relationships [36,37]. The data for nearby metrological station in Shanghai Jiao Tong University is used to calculate the monthly average daily number of bright sunshine hours of the proposed island. The number of bright sunshine hours can be calculated as [37]:

2.2.2. Wind energy potential assessment It is widely known that wind energy is more variable and intermittent in nature compared to solar energy. In order to obtain the maximum benefit from the wind, it is very important to comprehensively analyze the variation and energy flux for the available wind speed data. Wind speed data is collected by small metrological station in Shanghai Jiao Tong University using anemometer, and assessed using Weibull parameters i.e. scale parameter (c ) and shape factor (k ), yearly average wind power density and monthly wind potential are computed to analyze the wind resource. The Weibull probability density function (PDF) in terms of wind speed can be described as [38]:

(1)

b

. cos . sin

s

360dn 365

where s is the sunset (hour) angle in degree; is the latitude of proposed location (31. 4° ); is the declination angle in degree; dn is the accumulated number of days starting 1st January as one; Hsc is the solar constant with value 1367 W/m2. Moreover, the provided empirical calculation can only be performed when the absolute value of latitude | | is not more than 66. 5° [37]. Finally maximum possible number of daylight hours can be accumulated as:

2.2. Resource evaluation

[H / H0

(1 + 0.033 cos

= 23.45 sin 360

component of PHS capital cost. Deriaz pump turbine [33] is assumed in this study which has adjustable blades and angle of blades can be altered with respect to change in head height to keep optimum efficiency. A desalination plant can be employed with PHS to supply fresh water for remote community which can be operated with additional surplus electricity of the RES [34].

n=

24 Hsc

where n is the daily monthly average bright sunshine hours; H is the monthly average incident radiation on horizontal surface (kWh/m2/ day); H0 is the monthly average extraterrestrial (clear sky) radiation on horizontal surface of proposed location (kWh/m2/day); N is the monthly average maximum possible daily hours of bright sunshine; a and b are the climatic empirical regression coefficients having an average value of 0.3 and 0.34 for proposed location, according to the practice of handbook [37]. The value of H0 for any location can be computed using the following equations [36]:

f (v ) =

k v . c c

k 1

v c

exp

k

(k > 0, c > 0, v > 0)

(6)

v

F (v ) =

f (v ) dv

(7)

0

k=

c=

1.086

v¯

(1

k

10)

(8)

v¯ (1 + 1/ k )

(9)

Table 2 Monthly daily and maximum possible average hours of bright sunshine available at the involved island. Month

jth day of month

dn

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Average

J 31 + j 59 + j 90 + j 120 + j 151 + j 181 + j 212 + j 243 + j 273 + j 304 + j 334 + j

15 45 74 105 135 166 196 227 258 288 319 349

(°) −21.2 −13.6 −2.8 9.4 18.8 23.3 21.5 13.8 2.2 −9.6 −19.2 –23.3

s

(°)

76.4 81.5 88.3 95.7 102.0 105.0 104.0 98.5 91.3 84.1 77.9 74.9

N (hour)

n (hour)

n

10.2 10.9 11.8 12.8 13.6 14.0 13.8 13.1 12.2 11.2 10.4 10.0

2.9 3.7 5.1 7.0 7.1 8.0 8.8 8.0 7.7 6.3 6.2 4.4 6.3

0.3 0.3 0.4 0.5 0.5 0.6 0.6 0.6 0.6 0.5 0.5 0.4

4

N

H (kWh/m2/day)

H0 (kWh/m2/day)

2.3 2.9 3.9 4.9 5.3 5.5 5.8 5.3 4.6 3.7 2.9 2.4 4.1

5.7 7.0 8.7 10.2 11.1 11.1 11.3 10.5 8.9 7.5 5.8 5.3 8.6

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

Eload is the average daily load demand; CF is the load capacity factor for each involved generation source which is assumed as 0.5 for both solar and wind turbine sizing; PT is the efficiency of reversible pump-turbine machine; TPS is the average daily peak sunshine hours; e is the PV array losses and overall loss factor due to array shading, AC&DC wire losses, higher temperature losses and production tolerance. The value of loss factor (e ) for this study is taken as 20% [39,40]. The energy output model for solar PV arrays employed for this paper is same as used in study [6]. The detail specifications of PV module are revealed in Table 5.

Table 3 Monthly Weibull parameters and mean wind speed. Month

Mean speed (m/s)

Surface power density (W/m2)

Shape parameter (K)

Scale parameter (c)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

6.2 6.2 5.8 5.4 5.0 5.3 5.3 5.2 5.8 5.7 6.0 5.9

280.8 274.2 226.7 183.1 147.5 174.4 173.6 167.6 225.9 221.3 248.9 239.0

2.0 2.0 1.9 1.9 2.0 1.9 2.0 2.0 2.0 1.9 2.0 2.0

7.0 6.9 6.5 6.0 5.6 5.9 5.9 5.9 6.5 6.4 6.5 6.6

2.3.2. Wind turbine (WT) A wind turbine of 5 kW rated capacity is employed in this study [3]. The detail specifications of employed WT are presented in Table 5. The WT capacity sizing is made on basis of available theoretical wind power density at the proposed island and can be described as:

where represents the gamma function; v¯ is the average wind speed; is the variance of wind speed; F (v ) is the cumulative distribution function and v is the wind speed. The monthly Weibull parameters, mean wind speed and surface power density are presented in Table 3. It can be seen that summer has lower wind potential compared to the winter. The overall monthly Weibull parameters indicate a good potential for wind energy with an average surface power density of 213.1 W/m2 and theoretical potential of annual wind power of 1,866.8 kWh/m2.

NWT = PT

flosses = 1

h

+

(1

Eload × CF × Eth × AWT × flosses

fdowntime )(1

farray )(1

(15)

fsoiling )(1

fother )

(16)

2.3.3. Pumped hydro storage (PHS) In this study, PHS is potential key energy storage which accommodates all major surplus energy from RE generators and shortage of energy due to the demand side variations. From literature, it is observed that volume of upper reservoir (UR) and net difference between UR and lower reservoir (LR) are the most significant variables for the PHS design [24]. Other design parameters may involve size of pump-turbine machine, penstock size and lower reservoir volume. Generally 3–5 days of autonomy for energy storage is considered for standalone RES in literature [41,42]. The net head (difference between UR and LR) of PHS depends on site characteristics and pump-turbine machine design. Most studies employed the net head in range between 40 and 100 m [24,29]. In this study, 3 days of autonomy and 40-meter net head is used for PHS sizing and detailed sizing procedure of PHS is shown in Fig. 4. The detail specification of reversible machine and PHS are illustrated in Table 6.

(10)

d

BI

where flosses is overall loss factor which includes downtime losses, array losses, soiling losses and other losses factors as 6%, 2%, 4%, 4% respectively; Eth is the theoretical wind power potential at proposed island (kWh/m2) and AWT is swept area (m2) of WT. The energy output model for WT employed in this is same as used in study [21].

2.2.3. Load profile modelling The load is a very important part of energy generation system and has a noticeable effect on the system configuration. The proposed island has currently no permanent inhabitants, so initially load is designed for small community with daily average demand of 255.6 kWh, illustrated in Fig. 2. To make the load more realistic and practical, it is synthesized by adding some daily and hourly randomness by using the following equation:

=1+

×

where d and h are the daily and hourly perturbation factors. In literature 2% to 20% randomness for baseload has been used while in this study 5% daily and hourly randomness is employed [6,7]. As load profile also depends on seasonal variations, monthly load coefficients are also applied. The scaled load of a complete year is displayed in Fig. 3, while the average daily and monthly load with seasonal load coefficients, hourly and daily perturbation, is shown in Table 4. 2.3. System components sizing and modelling

(a) Upper reservoir sizing

2.3.1. PV array The capacity and design of solar array largely depend on the load demand and the output of power from PV array. In this study capacity sizing of solar array is made on the basis of number of peak solar hours (as analyzed in Section 2.2.1) and can be described as:

The water storage capacity of UR can be evaluated by using following equation [21]:

PT

n mod BI

=

PT

=

ule

=

batt

Eload × CF × BI × TPS × (1 e)

(12)

×

(13)

pump

+ 2

gen

15

(11)

CPV Csin gle inv

18

Load (kW)

Cpv =

21

12 9 6 3

(14)

0

where BI is efficiency of battery and inverter; Csin gle is the rated capacity of single PV module (265 W); CPV is the total capacity of PV array for proposed study; n mod ule is the total number of PV modules;

0

4

8

12 Hour

16

20

Fig. 2. Hourly load demand of a typical day. 5

24

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

35

Load (kW)

30 25 20 15 10 5 0

Jan

Apr

Mar

Feb

Jun

May

Jul

Sep

Aug

Dec

Nov

Oct

Fig. 3. One year scaled load profile. Table 4 Scaled average daily and monthly load demand. Month

No. of days

Load coefficient

Jan 31 0.7 Feb 28 0.7 Mar 31 0.9 Apr 30 0.9 May 31 1.1 Jun 30 1.2 Jul 31 1.3 Aug 31 1.4 Sep 30 1.1 Oct 31 1.0 Nov 30 1.0 Dec 31 0.7 Total yearly load

Select design parameters

Avg. load (kWh/ day)

Monthly Load (without randomness)

Monthly Load (with randomness)

178.9 178.9 230.0 230.0 281.1 306.7 332.2 357.8 281.1 255.6 255.6 178.9

5545.9 5009.3 7130.5 6900.5 8715.0 9200.7 10299.6 11091.9 8433.9 7922.8 7667.2 5545.9 93463.4

5726.5 5189.8 7311.1 7081.1 8895.6 9381.2 10480.2 11272.5 8614.5 8103.4 7847.8 5726.5 95630.2

V

.

Watt %

g hmean

16.9 1640 × 992 × 35 31 8.5 5000 5200 3 25 12 60 4

% mm V A Watt Watt m/s m/s m/s m/s m

Ah

4

1

3

d 3 V 4

2

× g × hmean

3

Select reversible machine using parameters

qmax , p peak , head mean

nbatt 24

(b)

water used during generating mode. The SOC of PHS can be calculated same as battery bank by using the following equation:

SOC (t ) =

QUR (t ) QUR (max)

QUR (min)

QUR (t )

(19)

QUR (max)

(20)

where QUR (min) and QUR (max) are the upper and lower limits of water storage in UR. Usually, the lower limit of UR is set as zero [24] but in this study minimum limit is kept as 5% [43] to preserve for emergency use, keeping the reversible machine efficiency high as water bed has sand, rocks or other contaminations which can produce a significant effect on reversible machine life. Usually the size of UR and LR is recommended same, but remote islands have supplementary benefit of

t

qg (t ) dt

narrays

Fig. 4. Energy storage sizing flow diagram (a) PHS (b) Battery pack.

where nday is the number of continuous days that UR can provide electricity without any input when it is full; gen is the generating efficiency of PHS; is water density (1000 kg/m3); g is the acceleration due to gravity (9.81 m/s2); hmean mean height difference between UR and LR and V is the volume of UR (m3). The water stored in UR at any time QUR (t ) can be calculated by using the following equation:

t 1

ctot Ah csin gle

Array sizing

(17)

qp (t ) dt

E 24 load DOD VB

Total number of batteries

Calculate concrete volume

(a)

t 1

nhr

nbatt Vcon

inv

Capacity sizing

ctot

Select the reservoir shape i.e. cylindrical, spherical

106

)+

batt

TR

BI

265 80

1)(1

gen

nday Eload 3.6*106 gen

Rated power Derating factor ( fPV ) Efficiency PV module dimensions Maximum operating voltage Maximum operating current Rated power Maximum power Cut-in wind speed Cut-off wind speed Rated wind speed Survival wind speed Rotor diameter

QUR (t ) = QUR (t

.g .hmean .

BI

Calculate U.R volume

PV module

t

Calculate

p peak

qmax

Unit

×

Select design parameters

ndays , array voltage, DOD

Calculate maximum flow rate

Value

gen

P

generating

Parameter

nday × Eload × 3.6 ×

. m . pipe TR . GR . pipe

pumping

Component

V=

cAh , voltage

Calculate the charging and discharging efficiencies

Table 5 PV and wind turbine key specifications.

Wind turbine (WT)

Select battery model

ndays , head mea

(18)

where is the self-discharge/losses incurred in PHS due to leakage and evaporation, these losses are ignored in this study for simplification; qp is the quantity of water added due to the pumping and qg is 6

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

dispose-off problems after the useful life of batteries compared to the PHS and frequent replacements during entire RES lifetime, the days of autonomy considered in this study for battery bank sizing is 10 hrs. The other major reason for smaller amount of days of autonomy is that in this proposed study most of the time battery bank will serve to accommodate small power deficiency/surplus. The battery bank sizing procedure is illustrated in Fig. 4. The battery bank capacity in amperehours (Ah) can be evaluated by using following equations:

Table 6 PHS and battery key specifications. Component

Parameter

Value

Unit

PHS

Rated power of reversible machine (Prated ) UR capacity Pumping co-efficient (cp )

31.0 766.8 7.6

kW kWh m3/kWh

Turbine co-efficient (ct ) Maximum flow rate (Qmax ) Mean head (hmean ) Efficiency of pump-turbine reversible machine ( PT ) Type Nominal capacity (Csin gle )

Battery

Nominal voltage Maximum depth of discharge (DOD) Roundtrip efficiency Lifetime throughput Total battery bank capacity

0.088 243.7 40.0 81.5

kWh/m3 m3/h m %

Ctot

Lead-acid 1000 Ah 2.0 70.0 86.0 3326 192.0

Nbatt =

V % % kW kWh

pump

=

p (t )

gh p

×

m

×

= cp × pc

pipe

p (t )

(21) (22)

(c) Discharging/generating mode The reversible machine will run as turbine/generating mode when there will be power deficit equal to/more than 20% of reversible machine rated power. The reason of selecting 20% unit for generating mode is discussed with detail in the result and discussion section. The rated power of reversible machine is selected based on the peak power demand throughout the year which is 31 kW. The power produced by generator at time (t) can be expressed as:

gen

c

(t ) =

=

TR

gen

×

gh. qt (t ) = ct × qt (t ) GR

×

pipe

(25)

Ctot Ah Cbatt

(26)

The principal objective of the operating strategy is to configure the utility of HPBS for off-grid energy system by increasing the reliability, storage usage factor, storage overall performance and overall system energy utilization ratio. The proposed operating strategy is based on the net power scheduling to describe whether RE generator has surplus power after meeting the load demand or unable to meet the consumption. After the net power scheduling, which will be based on available generation power, SOC level of each energy storage and amount of surplus/deficit power, it will be decided which energy storage device will come in active mode for that time period. Similarly, each time hybrid charge controller will decide whether power will be charged/discharged from PHS/battery. The system operating strategy consists of two stages. Stage one performs modelling of input data, hourly incident solar radiance, wind speed, and load demand. At stage two, after resources evaluation and load models, load balance will be checked at time (t) based on the energy produced from RE generators and load demand at that time. If surplus power is available, the HPBS will be derived for charging operation and if load balance shows the power deficiency, HPBS discharging will start. For charging mode different conditions are set depending on the availability of amount of surplus power. All conditions will be checked, and PHS/battery will be activated accordingly. After each time (t) period, final values of storage and generation will be recorded. The operating strategy is presented with a flow diagram in Fig. 5, and discussed in detail as below.

where p , m , pipe are the efficiencies of pump, motor and pipe (losses) which are taken as 0.92, 0.95, 0.95 respectively; pc p is the surplus power from the hybrid charge controller to pump (kW); cp is the water pumping coefficient of reversible machine in charging mode (m3/ kWh).

pg

24 × Eload × DOD × VB

3. Operating strategy and energy balance model

When there will be surplus energy after meeting the load demand, the reversible machine will be operated as pump/motor unit and water will be sucked from LR to UR for that time period. The machine will be operated in pumping mode only when available surplus power is equal to/more than 70% of reversible machine rated power [46]. The detail working principle of reversible machine is explained in following section. The water sent from LR to UR at time (t) can be expressed as:

× pc

nhr

where Nbatt is the total number of batteries; Cbatt is the capacity of one battery (Ah); Ctot Ah is the total capacity of a battery bank (Ah); nhr is total hours of autonomy; DOD is allowable depth of discharge and VB is the voltage of single battery. The charging and discharging model of battery bank employed in this paper is same as used in study [47]. The detail specifications of the lead-acid battery employed in this study are given in Table 6.

(b) Charging/Pumping mode

pump

=

BI

using seawater as LR. The construction cost of PHS can be reduced greatly by considering seawater as LR. Feasibility study of seawater as LR has been proposed in literature [44,45].

qp (t ) =

Ah

3.1. Charging mode

(23)

Firstly, the net power at any time Pnet (t ) will be calculated and if found positive, charging conditions will be applied on HPBS. The net power can be calculated by using following expression:

(24)

where TR , GR , pipe are the efficiencies of turbine, generator and pipe (losses) which are taken as 0.89, 0.95, 0.95; gen , pump are the overall pumping and generating mode efficiencies; qt (t ) is volumetric flow rate of water sent to turbine (m3/sec); pg c (t ) is the power from turbine/generator to hybrid charge controller (kW) and ct is the power generating coefficient of reversible machine in discharging mode (kWh/m3).

Pnet (t ) = NPV PPV (t ) + NWT PWT (t )

Pload (t ) (Pnet (t ) > 0)

(27)

In positive net power condition, the amount of positive net power will be checked. According to an engineering practice book [46], the efficiency of pumps can be kept optimum if speed of the pump remains in range of 70% to 100% of rated pump speed. It means when variation in the available head is between 70 and 100% range of rated pump head, pump will operate at maximum efficiency. Due to this fact, charging mode of HPBS is further divided into three scenarios and presented with flow chart in Fig. 6.

2.3.4. Battery storage The deep-cycle lead-acid battery is employed in this study [11,35]. Due to high operating and maintenance cost, high self-discharge rate, 7

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

Stage#01

Available RE resources data

Calculate wind energy potential & Weibull parameters [K,C]

Calculate peak sun hours per day Initial load design PV capacity sizing and arrays modelling

Seasonal load co-efficients computation

PV arrays output power calculation

Daily & hourly randomness computation

Wind turbine sizing & modelling

Wind turbine output power caluculation

Modelling of scaled load

Integrating the generation and load models Stage#02

t=1

1

Dump Load

No

Yes

Check pump mode conditions met ?

Check load met & balance ?

No

Check turbine mode conditions met ?

Yes

No

Unmet Load

Yes

Turn on pump/ battery bank charge accordingly

Turn on turbine/ battery bank discharge accordingly

Store the final values of storage, generation and load models

t = t+1

1

No

t ≥ t(max) Yes

Calculate SOP, EUR & SUF Fig. 5. Operating strategy of RES with PHS-battery storage.

3.1.1. Scenario #01 (0.7Prated Pnet Prated) In this case, priority will be given to the PHS charging and the pump will run with optimum efficiency. If battery bank SOC is less than 100% and PHS is fully charged, then the additional surplus power will be sent to the battery bank. When SOC of both energy storages is 100% than surplus power will be considered as a dump. The operations shown within the dotted box are secondary means these operations will be performed when priority-based operation cannot run or SOC of respective storage is 100%.

achieve high efficiency of HPBS. By operating pump below than 70%, more power will be lost due to the low pump efficiency. It is better to give priority to the battery bank charging in this condition and PHS charging will be kept as secondary operation when SOC of battery bank is 100%. One sub condition, to complement both storages each other, is added for PHS charging considering battery bank SOC 90\% [31]. If SOC of battery is more than 90% and SOC of PHS is below than 90%, pump will run at rated speed for that time period and additional power will be extracted from battery bank to charge the PHS. In this case, it is important to note that the battery only provides additional power to keep pump running above 70% rated power while the main driver power for pump running will remain surplus RE power and can be

3.1.2. Scenario #02 (Pnet < 0.7Prated) In this scenario priority will be given to the battery bank charging to 8

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

0.7 Prated

3

SOCres

SOCmax

SOCres

SOCmax

SOCbatt

SOCmax

SOCbatt

SOCmax

c p Pnet

Excess energy dumped

Q t

c p Pnet

SOCres

SOCmax

SOCbatt

SOCmax

SOCmax

SOCres

SOCmax

SOCbatt SOCres

Excess energy dumped

SOCbatt

0.9 SOCmax

c p Pnet

p

SOCres

Q t

SOCmax

SOCres

SOCmax

SOCbatt

SOCmax

SOCbatt

SOCmax

Excess energy dumped

SOCres

SOCmax

SOCbatt

SOCmax

0.9 SOCmax

c p Pnet

Energy dumped

Batt. bank charging

Batt. bank discharging

Prated 3

SOCres

Q t

Q t

c p Prated

2

c p Prated

4

0.9 SOCmax

0.9 SOCmax

Pnet 1

Energy dumped

SOCmax

Batt. bank charging Q t

SOCmax

3

SOCres

Batt. bank charging

SOCmax

SOCbatt

0.7 Prated

2

SOCbatt

SOCres

Excess energy dumped

Batt. bank charging

1

4

Batt. bank charging

Pnet

Q t

Prated

2

1

Q t

Pnet

4

SOCres

SOCmax

SOCbatt

SOCmax

Batt. bank charging

c p Prated

SOCres

SOCmax

SOCbatt

SOCmax

Energy dumped

Excess energy dumped

Batt. bank charging

Fig. 6. PHS-battery charging mode conditions.

expressed as:

Pb

p (t )

charging of PHS and battery bank can be expressed as:

= Prated (t )

Pbatt (t ) = Pbatt (t

Pnet (t ) 1)

Pb

p (t )

(28)

Pexcess (t ) = Pnet (t )

(29)

Pbatt (t ) = Pbatt (t

(30)

Prated

(31)

1) + Pexcess (t )

3.2. Discharging mode

3.1.3. Scenario #03 (Pnet > Prated) This scenario is similar to scenario #01, except that in this case, both energy storages can be in charging mode as available net surplus power is more than rated power of pump. Although RE generator is precisely sized, variability in RE generators output and high variation of available RE sources can often lead to this scenario. Also energy utilization ratio of the whole system can be enhanced by reducing the amount of rejected RE due to the capacity issues of single energy storage and hence signifies the hybrid storage benefit. If one or both energy storages SOC is 100%, excess power will be dumped. Simultaneous

When calculated net power Pnet (t ) for any time period (t ) is negative, discharging mode conditions will be applied.

Pnet (t ) = NPV PPV (t ) + NWT PWT (t )

Pload (t ) (Pnet (t ) < 0)

(32)

To overcome the produced power deficiency, the same strategy as charging mode is applied. In discharging mode 20% unit is set similar to the 70% for charging mode to decide which energy storage will be discharged for that time period. To enhance the storage usage factor of PHS and storage overall performance of the hybrid energy storage, 20% 9

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

Pnet

0.3Prat 3

1 2 SOCres

SOCmin

Pnet

Q t

SOCres

SOCmin

SOCbatt

SOCmin

Batt. bank discharging

SOCmin

SOCbatt

SOCmin

Energy not supplied

cT

Pnet 1

SOCbatt

SOCres

0.3Prat 3

2

SOCmin

Batt. bank discharging

4

SOCbatt

SOCmin

SOCbatt

SOCmin

SOCres

0.9 SOCmax

SOCres

0.9 SOCmax

Q t

Prat

cT

Q t

Pnet

SOCres

SOCmin

SOCbatt

SOCmin

Energy not supplied

cT

Batt. bank charging Fig. 7. PHS-battery discharging mode conditions.

unit is set which is discussed with detail in results section. Two scenarios are made accordingly with respect to the amount of net power deficit. The flow chart of PHS-battery discharging mode conditions is shown in Fig. 7.

NPV PPV .

3.2.1. Scenario #01 (|Pnet| 0.2Prated ) In this case, when absolute power deficiency is equal to/more than 20% of turbine rated power, priority will be given to PHS discharging for that time period. If SOC of PHS is equal or less than minimum SOC than battery bank will become active to cover power deficiency. If the overall SOC of hybrid storage is less than minimum SOC, than power shortage will be considered as fail in power supply.

NPV PPV .

= PRE

b (t )

= Prated (t )

Pbatt (t ) = Pbatt (t

|Pnet (t )| 1) + Pt

b (t )

l (t )

+ NWT PWT. p WT

+ Pc

p (t )

+ Pc

b (t )

+ Pc

d (t )

(35)

Discharging mode energy balance model:

= PRE

inv . fPV l (t )

+ NWT PWT. p WT + |ENS|

+ Pg

c (t )

+ Pb

c (t )

(36)

where inv is the inverter efficiency which is the ratio of AC output to DC input power; p WT is the probability of WT power output; PRE l is the power directly send to the load from RE generation unit; Pc p is the surplus power sent for water pumping from LR to UR by controller; Pc b is the additional surplus power used for battery bank charging sent by charge controller; Pc d is excess power when SOC of HPBS is 100%; ENS is energy not served due to high load demand or non-availability of RE; Pg c is power sent from PHS turbine/generator to controller; Pb c power sent to controller by battery bank discharging. The load consumption is primarily covered by RE energy generation and HPBS. The energy balance model for load consumption is modelled as:

3.2.2. Scenario #02 (|Pnet | < 0.2Prated) Priority is given to the battery bank discharging in this case as net power shortage is less than 20% of the reversible machine rated power. Here one additional sub condition is added similar to the charging mode. When net power deficiency is less than 20%, also SOC of battery is at lower bound, and SOC of PHS is more than 90% then turbine will run at rated speed and additional power will be used to charge battery bank for that time period. If SOC of PHS is less than 90% then turbine will run just to meet the power deficit until battery bank charged. The power sent to battery from hydro turbine can be expressed as:

Pt

inv . fPV

Pload (t ) = PRE

l (t )

+ Ps

l (t )

where PRE l is load directly covered by RE generation and Ps load covered by HPBS discharging.

(33)

(37) l

is

4. System evaluation indicators

(34)

4.1. Storage overall performance (SOP) Storage overall performance (SOP) is proposed in this study to evaluate the energy storage of off-grid RE systems, especially for hybrid storage. The SOP is defined as the quotient of actual energy provided by the energy storage to cover the energy deficiency and total theoretical energy provided to the storage during a specific time period, which is one year for this study. It involves all type of losses/efficiencies of

3.3. Energy balance model The energy balance model of all involved components i.e. generation components, HPBS and load consumption at a time (t) can be expressed as: Energy balance model during charging: 10

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

hybrid storage i.e. charging & discharging efficiency of hybrid storage, piping & transmission losses (from RE generators to storage and storage to load) and inverter losses. The SOP is a dimensionless parameter and has no relation with load met/not met or RE generation variability. SOP can be expressed as:

SOP =

0

Fig. 8 shows the average daily PHS/battery charging and discharging power for each month. It can be seen that PHS effectively has high power circulation compared to the battery throughout the year except Dec and Jan which is due to the low energy demand in that time period as discussed in Section 2.2.3. On the contrary battery bank has monthly average energy transfer of no more than 30 kWh except Aug because of the peak load demand. It can be concluded that battery just covers the small power deficits while high power shortage, especially in summer, due to the high cooling load, is covered by PHS demonstrating the significance of HPBS for off-grid. One reason of more battery discharging/charging in Aug result from PHS’s low SOC, therefore more battery power is used to charge PHS to maintain minimum SOC of PHS and to cover high peaks during next time step. It can be seen that dump load (black dotted line) is high in winter as compared to summer. Particularly, a zero dump load can be seen in Aug when there is a peak load demand. Moreover, the high monthly charging power of PHS compared to the discharging power is due to the losses incurred and PHS overflow (dump load) when SOC of PHS was 100%, while battery has almost same monthly average charging and discharging power. The total energy sent to the PHS and battery for charging in a year is 32,198.5 kWh, 11,810kWh respectively while total energy discharged from PHS and battery is 21,179 kWh, 9,621.5 kWh.

Eserved t 0

Ein

(38)

The higher the value of SOP, the better the energy system exploiting the potential of energy storage. 4.2. Energy utilization ratio (EUR) It is the ratio of nominal energy available and actual energy utilized by the RES to meet the load demand. The whole system performance can be evaluated in relation to available energy generation sources and can be expressed as:

EUR =

EPV

load

+ EWT

load

+ Estorage

EPV - nominal + EWT - nominal

EPV - nominal =

Gi dt . APV

EWT - nominal = Eth × AWT

load

(39) (40) (41)

5.2. Comparative energy output analysis of PHS and battery bank

where EPV load , EWT load , Estorage load are the actual energy amounts contributed to meet load demand by PV,WT and energy storage; Gi is the incident solar radiation (kWh/m2); APV , AWT is the total area of PV and wind turbine.

The daily status and output of each energy storage are displayed in Fig. 9 and Fig. 10. It can be seen from Fig. 9 that UR has very low water volume for the months of Aug and Jan, while during other months regular charging and discharging can be seen except Mar and Apr when most of the time UR is full. It is also evident from figures that during the months when the UR has low water volume, battery bank power also reduces, which thus proves that battery works as supplementary when UR has minimum charge status. Except for the months of Jan, Aug and Nov during other months’ battery bank have very small changes in energy status which illustrate that small power deficiencies are accommodated by battery bank. It can also be verified from Fig. 10, that the battery bank has frequent output no more than 7 kWh, except in Aug when battery bank has to complement the UR low charge status. It can also be seen that the daily energy output of PHS is in the range of 10-30kWh. During Feb, there is a very low power output from PHS, due to the very low load demand. A zero value for the power output can be seen during last two weeks. However, battery has a frequent low discharge throughout the year which is due to the very low frequent energy shortfalls.

4.3. Storage usage factor (SUF) Storage usage factor (SUF) is employed to investigate that how much RES makes potential use of HPBS. SUF is used to comprehensively analyze the performance of energy storage system not only in the regard to how effectively complement the excess energy and load deficiency to enhance the energy usage, but also the energy storages technical behavior [48]. SUF can be expressed as: t

SUF =

0 t 0

Estorage Eactual

load

output

(42)

where Estorage load is the energy sent to load by energy storage (HPBS); Eactual output is the actual energy output of storage if it works normally considering all losses and efficiencies of components.

120

5. Results and discussion

PHS (kWh)

The proposed mathematical models described above are used to design a HPBS based RES for a remote island named as “Jiuduansha”, located near Shanghai (31°4’ N, 121° 45’ E). The necessary input data, i.e. solar radiation, wind speed and load, is discussed in detail in Section 2. The MATLAB R2018b version is used to simulate and evaluate the results while no energy deficit is allowed during simulation. The system components capacity sizing is carefully performed, which are: PV array (200 units, 53 kWp), WT (3 units, 15.6 kW), battery storage (96 units, 192 kWh), UR (8758 m3, 766.8kWh). Please note that the proposed system components capacity may not be optimal from a techno-operational or economic perspective but it can meet the supply requirements reliably, the current study focuses only the technical feasibility of the HPBS for the off-grid RES. Multi-objective optimization on components capacity considering HPBS will be carried out in future work.

Charging power Discharging power Dump load

120

90

90

60

60

30

30

0 Jan Feb Mar Apr May Jun

Jul

Battery bank (kWh)

t

5.1. Charging and discharging power of HPBS

0 Aug Sep Oct Nov Dec

Month Fig. 8. Monthly average charging, discharging power and dump load. 11

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

UR volume [1e3 m^3]

8 6 4 2 0

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Nov

Oct

Sep

Dec

Battery bank status [kWh]

200 150 100 50 0

Jan

Mar

Feb

Apr

Jun

May

Jul

Aug

Oct

Sep

Nov

Dec

Fig. 9. PHS-battery energy storage status.

PHS output [kWh]

30 20 10 0

Jan

Feb

Mar

Jun

May

Apr

Aug

Jul

Sep

Oct

Nov

Dec

Battery output [kWh]

30 20 10 0

Jan

Feb

Mar

Apr

May

Jun

Aug

Jul

Sep

Oct

Nov

Dec

Total storage output [kWh]

30 20 10 0

Jan

Feb

Mar

May

Apr

Jun

Aug

Jul

Oct

Sep

Fig. 10. Daily PHS-battery energy output.

53.0 kWp PV array

AC bus

DC bus

175.2 kWh

Dump load

202.0 kWh 192.0 kWh Battery bank

32.4 kWh

Hybrid charge controller

26.7 kWh

12.7 kWh

181.8 kWh

131.9 kWh

88.0 kWh

15.0 kW

Water Electricity

Wind turbine

31.0 kW Pump & Motor 670.0 m3

36.0 kWh LR

UR

8758 m3

32.4 kWh 255.6 kWh Load

255.6 kWh

58.0 kWh

660.0 m3 Turbine & Generator

31.0 kW Fig. 11. Whole system energy flow and water flow.

12

Nov

Dec

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

5.3. Hybrid system energy flow and water flow

100

Fig. 11 illustrates the daily average electricity flow between the different system components and water flow between PHS components. It can be seen 58% of the total (306 kWh average daily) produced energy is directly consumed to meet load demand while 37% energy is sent to the HPBS, 29% sent to PHS and 8% directed towards battery bank, and 4.1% is considered as dump energy. The average daily water circulation between UR and LR is shown with blue lines, as 670 m3 water sent by the pump to UR and 660 m3 consumed by the turbine to generate electricity. The difference, 10 m3 per day (average), between water pumping and returning back to the LR is due to the losses considered i.e. water pipe losses, charging/discharging losses. The daily average solar and wind outputs account for 56% and 44% respectively. Very high energy input and output for PHS can be seen compared to battery bank which will increase the SUF of PHS which is discussed in the following section.

SOP-PHS SOP-Batt SUF-PHS SUF-Batt

80 70 60 50 40 30 20 10

0 Jan Feb Mar Apr May Jun

Jul

Aug Sep Oct Nov Dec

Month Fig. 12. Monthly SOP and SUF of PHS-battery.

100

Monthly storage overall performance (SOP) and storage usage factor (SUF) of each energy storage is displayed in Fig. 12 and overall system energy utilization ratio (EUR) is exposed in Fig. 13. It is worthwhile to note that battery bank has a high SOP while PHS has a high SUF throughout the year, due to the fact that battery has very low frequent charge and discharge throughout the year compared to PHS, as some times PHS remains non-operational due to very low energy demand (discussed in Section 5.2). The SOP of PHS is significantly low in Feb and Dec while battery SOP increased during these months due to the low energy deficits. The high SOP of both storages during summer can be seen with a peak in Aug. SUF of PHS peaks at Jul almost 40%, while battery bank SUF is less than 5% throughout the year. Continuous increase in SOP and SUF of HPBS during summer can be seen (Fig. 13), followed by a substantial decrease in Sep occurs, which again rises during Oct-Nov and finally there is a drop again in Dec. Monthly overall SOP of HPBS has the highest value in Aug at 89% while the lowest is Feb (35%). Furthermore, SUF of HPBS throughout the year is less than 10% (Aug) means that same storage capacity can utilized for higher loads by increasing the capacity of energy generators but storage autonomy will be compromised. Monthly overall system EUR (blue line) shows that system performs best in Nov and worst in Feb due to the fact that Feb has low energy demand while Nov has very low RE and

SOP SUF EUR

90 80 70 60 50 40 30 20 10 0

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec --

Month Fig. 13. SOP and SUF of HPBS and whole system EUR.

100

30

90 25

RE to load RE to pump RE to batt. Turbine output Batt. output SOC-batt SOC-UR

20

Power (kW)

Performance indicator (%)

5.4. Hybrid storage performance analysis

15

80 70 60 50 40

10

30 20

5

10 0

2

4

6

8

10

12

14

Time (hour)

16

Fig. 14. Hourly system energy balance (13th Feb). 13

18

20

22

24

0

SOC (%)

Performance indicator (%)

90

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

25

20

Power (kW)

100

RE to load RE to pump RE to batt. Turbine output Batt. output SOC-batt SOC-UR

90 80 70 60

15

50 40

10

SOC (%)

30

30 20

5

10 0

2

4

6

8

10

12

14

16

18

20

22

24

0

Time (hour) Fig. 15. Hourly system energy balance (4th Aug).

Performance indicator (%)

70 60

starts from the morning, seeing the load deficiency, while high energy shortage hours are accommodated by PHS and small load deficiencies are covered by battery bank. In the noon, when solar energy outputs begin to rise, charging of HPBS happens. It is worthwhile to note that the surplus energy on that day is more than the pump rated power, thus the charging of battery and PHS happens at same time. From 5 pm to 10 pm of peak demand hours, turbine runs at full speed to meet load demand. During late night and early morning hours, when there is low energy consumption, the battery discharges frequently. The effective complementary operation between PHS and battery can be seen during low demand and peak demand days, which highlight the benefits of HPBS for off-grid systems.

PHS-0.2p-rated PHS-0.3p-rated Battery-0.2p-rated Battery-0.3p-rated

50 40 30 20 10 0

5.6. Discussion on dispatch strategy of HPBS Energy dispatch strategy for hybrid storage seems to be a major challenge during the planning of RES, especially for off-grid systems, due to the fact that the system can reliably meet load consumption with various dispatching strategies of the hybrid energy storage. In this HPBS, PHS seems to be major source of energy storage but at low net power deficiency hours, when the demand is low or there is a high RE generation, it is inconvenient that the PHS starts discharging under low power and high energy density. Although the battery bank can meet high load demands but its high maintenance and replacement costs, make it unsuitable for off-grid RES. Moreover, hydro turbines have limitations of minimum running speed, which leads to spilling the excess output power of the turbines during low demand hours. In this study, during PHS charging mode, minimum 0.7 is set as threshold of PHS operation due to ensure that pump can be operated in the range of 70% −100% by keeping optimum efficiency, which has been discussed briefly in modelling section. For the hydro turbine operation, it largely depends on the turbine operational range and energy demand. As most of the time designed load in this study remains in the range of 5 kW-15 kW. To enhance the higher SUF of PHS and minimize the dependency on battery bank, different possible parameters are analyzed for turbine mode operation, and the result is shown in Fig. 16. The SUF of PHS and battery bank is analyzed by setting 0.2Prated and 0.3Prated units for the PHS turbine operation. Low SUF of PHS can be seen when the PHS output is controlled by setting parameter 0.3Prated , means turbine will come in operation when power deficiency is equal to or more than 0.3 of the turbine rated power, but battery SUF is very high at this condition throughout the year. On contrary SUF of the PHS increased by setting PHS control strategy at 0.2Prated , means most of the

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec --

Month Fig. 16. SUF of PHS-battery under different hydro turbine operating ranges.

most of the energy demand is met by HPBS. The whole year system SOP, SUF, EUR are 66.4%, 7.3%, and 16.5% respectively. 5.5. Hourly system energy balance To validate the proposed HPBS model, hourly energy balance of two typical days with the lowest and highest demand is presented in Fig. 14 and Fig. 15. As Feb has lowest load demand, energy balance on 13th Feb is displayed (Fig. 14), it can be seen that most of the time demand is directly met by RE generation and in the day time, when generated energy is more than consumption, surplus energy is used to recharge PHS and battery. The battery is charged only at noon at that day due to the excess surplus RE available, while PHS charged frequently from 8am to 7 pm and 9 pm to 12am due to the high wind energy penetration. It can be seen that battery discharging occurs in the morning when there is very low load demand while PHS discharging happens for just one hour in the evening to meet high load demand. Battery SOC remains almost 90% except in the morning times, while PHS state of charge also remains more than 50%. Due to the peak load demand in Aug, the operation performance on 4th Aug is selected, as an example, to examine the PHS and battery operation. It can be seen (Fig. 15) that battery and PHS discharging 14

Applied Energy 257 (2020) 114026

M.S. Javed, et al.

time load deficiency is accommodated by PHS without violating minimum SOC limit. In both scenarios, load demand is successfully met but the battery consumption is very high in 0.3Prated case which will increase the battery maintenance and replacement cost, but in 0.2Prated case the battery bank just cover the very low, usually 5 kW or less, power shortages thus battery has less charging/discharging cycles which will lead to increase battery life and drop the battery operational cost. It can be concluded that for HPBS, turbine operation of PHS is largely dependent on load demand and net power difference which depends on energy generation sources.

[5] Ibrahim H, Ilinca A, Perron J. Energy storage systems - Characteristics and comparisons. Renew Sust Energ Rev 2008;12:1221–50. [6] Ma T, Yang H, Lu L. A feasibility study of a stand-alone hybrid solar–wind–battery system for a remote island. Appl Energ 2014;121:149–58. [7] Javed MS, Ma T. Techno-economic assessment of a hybrid solar-wind-battery system with genetic algorithm. Energy Procedia 2019;158:6384–92. [8] 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. [9] Dufo-López R, Bernal-Agustín JL, Yusta-Loyo JM, Domínguez-Navarro JA, RamírezRosado IJ, Lujano J, et al. Multi-objective optimization minimizing cost and life cycle emissions of stand-alone PV–wind–diesel systems with batteries storage. Appl Energ 2011;88:4033–41. [10] Khare V, Nema S, Baredar P. Solar-wind hybrid renewable energy system: A review. Renew Sust Energ Rev 2016;58:23–33. [11] Chen H, Cong TN, Yang W, Tan C, Li Y, Ding Y. Progress in electrical energy storage system: A critical review. Prog Nat Sci 2009;19:291–312. [12] Ma T, Yang H, Lu L. Development of hybrid battery–supercapacitor energy storage for remote area renewable energy systems. Appl Energ 2015;153:56–62. [13] Li C-H, Zhu X-J, Cao G-Y, Sui S, Hu M-R. Dynamic modeling and sizing optimization of stand-alone photovoltaic power systems using hybrid energy storage technology. Renew Energ 2009;34:815–26. [14] Prodromidis GN, Coutelieris FA. Simulations of economical and technical feasibility of battery and flywheel hybrid energy storage systems in autonomous projects. Renew Energ 2012;39:149–53. [15] Das DC, Roy A, Sinha N. GA based frequency controller for solar thermal–diesel–wind hybrid energy generation/energy storage system. Int J Electr Power Energy Syst 2012;43:262–79. [16] Awan AB, Zubair M, Sidhu GAS, Bhatti AR, Abo-Khalil AG. Performance analysis of various hybrid renewable energy systems using battery, hydrogen, and pumped hydro-based storage units. Int J Energy Res 2018. [17] Zheng Z, Petrone R, Péra MC, Hissel D, Becherif M, Pianese C, et al. A review on non-model based diagnosis methodologies for PEM fuel cell stacks and systems. Int J Hydrogen Energy 2013;38:8914–26. [18] Sorrentino M, Adamo A, Nappi G. Optimal sizing of an rSOC-based renewable microgrid. Energy Procedia 2019;159:237–42. [19] Díaz-González F, Sumper A, Gomis-Bellmunt O, Villafáfila-Robles R. A review of energy storage technologies for wind power applications. Renew Sustain Energy Rev 2012;16:2154–71. [20] Beaudin M, Zareipour H, Schellenberg A, Rosehart W. Chapter 1 - Energy Storage for Mitigating the Variability of Renewable Electricity Sources. In: Du P, Lu N, editors. Energy Storage for Smart Grids. Boston: Academic Press; 2015. p. 1–33. [21] 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 Energ 2014;69:7–15. [22] Ma T, Yang H, Lu L. Study on stand-alone power supply options for an isolated community. Int J Electr Power Energy Syst 2015;65:1–11. [23] Ma T, Yang H, Lu L, Peng J. Optimal design of an autonomous solar–wind-pumped storage power supply system. Appl Energ 2015;160:728–36. [24] Ma T, Yang H, Lu L, Peng J. Pumped storage-based standalone photovoltaic power generation system: Modeling and techno-economic optimization. Appl Energ 2015;137:649–59. [25] Kusakana K. Feasibility analysis of river off-grid hydrokinetic systems with pumped hydro storage in rural applications. Energ Convers Manage 2015;96:352–62. [26] Hu RX, He XY, Jing ZX, Yuan ZX, Wu QH. Capacity configuration optimization for island microgrid with wind/solar/pumped storage considering demand response. IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA) 2015. 2015. p. 1–6. [27] Bhattacharjee S, Nayak PK. PV-pumped energy storage option for convalescing performance of hydroelectric station under declining precipitation trend. Renew Energ 2019;135:288–302. [28] Mousavi N, Kothapalli G, Habibi D, Khiadani M, Das CK. An improved mathematical model for a pumped hydro storage system considering electrical, mechanical, and hydraulic losses. Appl Energ 2019;247:228–36. [29] Yıldıran U, Kayahan İ. Risk-averse stochastic model predictive control-based realtime operation method for a wind energy generation system supported by a pumped hydro storage unit. Appl Energ 2018;226:631–43. [30] Gioutsos DM, Blok K, van Velzen L, Moorman S. Cost-optimal electricity systems with increasing renewable energy penetration for islands across the globe. Appl Energ 2018;226:437–49. [31] Zhao J, Graves K, Wang C, Liao G, Yeh C. A hybrid electric/hydro storage solution for standalone photovoltaic applications in remote areas. 2012 IEEE Power and Energy Society General Meeting. 2012. p. 1–6. [32] Asif MRH, Iqbal T. Dynamic modeling and analysis of a remote hybrid power system with pumped hydro storage. Int J Energy Sci 2013;3:333. [33] Breeze P. Chapter 2 - Pumped Storage Hydropower. In: Breeze P, editor. Power System Energy Storage Technologies. Academic Press; 2018. p. 13–22. [34] Li YQ, Yang MM, Zhao L, Wang FJ. The research of wind-light complementary based on pumped storage power system. Advanced Materials Research. Trans Tech Publ; 2012. p. 1132–6. [35] Luo X, Wang J, Dooner M, Clarke J. Overview of current development in electrical energy storage technologies and the application potential in power system operation. Appl Energ 2015;137:511–36. [36] Bekele G, Tadesse G. Feasibility study of small Hydro/PV/Wind hybrid system for off-grid rural electrification in Ethiopia. Appl Energ 2012;97:5–15. [37] John A, Duffie WAB. Solar engineering of thermal processes. 4th ed. New Jersey: John Wiley & Sons Inc; 2013. p. 36–87.

6. Conclusions This study proposes a hybrid pumped battery storage (HPBS) for the off-grid RES. The mathematical model for each system component is developed and a novel operating strategy based on hybrid storage is introduced. First, the available solar and wind resources for the remote island are evaluated, and then sizing of PV, wind turbine and storage system is presented. Besides, the operating strategy of the HPBS is developed which is rarely explored in existing studies. Operation ranges of each energy storage is of vital importance for hybrid storage proper functionality which are defined in this study after several simulation cases, to extract maximum stored energy keeping HPBS efficiency optimum. Additionally, the power output of each storage and complete system energy flow is simulated with respect to the load demand. Considering the 100% reliability constraint, HPBS performance is evaluated using storage overall performance (SOP) and storage usage factor (SUF) parameters. Detailed energy output analysis revealed that during high power shortage time periods, PHS comes into operation seeing the minimum SOC constraint, while low shortages are covered by the battery bank. The PHS and battery bank remain in operation for 15.5hrs and 12.6hrs per day (average), respectively. The results reveal that by setting hydro turbine operation in the range from 20% to100%, PHS has a high SUF of 30% (yearly average) while battery bank has a high SOP of 95%, due to the frequent low energy shortages. Overall SUF and SOP of HPBS is 7.3% and 66.4%, respectively. The whole system EUR is 16.5%. It is concluded that HPBS can effectively manage energy variations and seems a promising aspect, especially for off-grid RE systems, as PHS and battery storage have complementary characteristics, in addition to supplementing each other during low state of charge periods. Hybrid storage is a popular concept nowadays. After initiating with a strong technical operating strategy of HPBS based on the operating ranges of each energy storage, the next step is to analyze HPBS by performing sensitivity analysis under different conditions i.e. varying load and storage size, varying RE generators saturation and to validate it through experimentation. Acknowledgements The authors would appreciate the financial support provided by the National Natural Science Foundation of China (NSFC) through the Grant 51976124. References [1] Aagreh Y, Al-Ghzawi A. Feasibility of utilizing renewable energy systems for a small hotel in Ajloun city, Jordan. Appl Energ 2013;103:25–31. [2] Ma T, Yang H, Lu L. Feasibility study and economic analysis of pumped hydro storage and battery storage for a renewable energy powered island. Energ Convers Manage 2014;79:387–97. [3] Ma T, Javed MS. Integrated sizing of hybrid PV-wind-battery system for remote island considering the saturation of each renewable energy resource. Energ Convers Manage 2019;182:178–90. [4] Hemmati R, Saboori H. Emergence of hybrid energy storage systems in renewable energy and transport applications – A review. Renew Sustain Energy Rev 2016;65:11–23.

15

Applied Energy 257 (2020) 114026

M.S. Javed, et al. [38] Salimi AA, Karimi A, Noorizadeh Y. Simultaneous operation of wind and pumped storage hydropower plants in a linearized security-constrained unit commitment model for high wind energy penetration. J Storage Mater 2019;22:318–30. [39] Munro K. Designing a stand-alone PV system. Home Power Magaz 2010;136:78. [40] Shabani M, Mahmoudimehr J. Techno-economic role of PV tracking technology in a hybrid PV-hydroelectric standalone power system. Appl Energ 2018;212:84–108. [41] Yang H, Lu L, Burnett J. Weather data and probability analysis of hybrid photovoltaic–wind power generation systems in Hong Kong. Renew Energ 2003;28:1813–24. [42] Kocaman AS, Modi V. Value of pumped hydro storage in a hybrid energy generation and allocation system. Appl Energ 2017;205:1202–15. [43] Rathore A, Patidar N. Reliability assessment using probabilistic modelling of pumped storage hydro plant with PV-Wind based standalone microgrid. Int J Electr Power Energy Syst 2019;106:17–32.

[44] Wu Y, Zhang T, Xu C, Zhang X, Ke Y, Chu H, et al. Location selection of seawater pumped hydro storage station in China based on multi-attribute decision making. Renew Energ 2019;139:410–25. [45] Yao W, Deng C, Li D, Chen M, Peng P, Zhang AH. Optimal sizing of seawater pumped storage plant with variable-speed units considering offshore wind power accommodation. Sustainability 2019;11:1939. [46] Stelzer RS, Walters R. Estimating reversible pump-turbine characteristics. Bureau of Reclamation, Denver, CO (USA). Engineering and Research Center; 1977. [47] Sawle Y, Gupta S, Bohre AK. Socio-techno-economic design of hybrid renewable energy system using optimization techniques. Renew Energ 2018;119:459–72. [48] Muñoz F, Almonacid G, Nofuentes G, Almonacid F. A new method based on charge parameters to analyse the performance of stand-alone photovoltaic systems. Sol Energy Mater Sol Cells 2006;90:1750–63.

16