An optimization method applied to active solar energy systems for buildings in cold plateau areas – The case of Lhasa

An optimization method applied to active solar energy systems for buildings in cold plateau areas – The case of Lhasa

Applied Energy xxx (2016) xxx–xxx Contents lists available at ScienceDirect Applied Energy journal homepage: www.elsevier.com/locate/apenergy An op...

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Applied Energy xxx (2016) xxx–xxx

Contents lists available at ScienceDirect

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

An optimization method applied to active solar energy systems for buildings in cold plateau areas – The case of Lhasa q Pengfei Si a, Ya Feng a,⇑, Yuexia Lv b,⇑, Xiangyang Rong a, Yungang Pan c, Xichen Liu a, Jinyue Yan d,e a

China Southwest Architecture Design and Research Institute Corp., Ltd., Chengdu, China School of Mechanical & Automotive Engineering, Qilu University of Technology, Jinan, China c China Architecture Design Group, Beijing, China d School of Business, Society and Energy, Mälardalen University, Västerås, Sweden e School of Chemical Science and Engineering, Royal Institute of Technology, Stockholm, Sweden b

h i g h l i g h t s  Develop an optimization model for integrated solar energy systems.  Apply the model to a typical office building located in Lhasa.  PV systems are superior to solar thermal systems in cold plateau areas.  Financial subsidies influence the system more than commercial electricity prices.  Conduct LCA to compare performances of an optimal system and a conventional one.

a r t i c l e

i n f o

Article history: Received 15 March 2016 Received in revised form 25 October 2016 Accepted 14 November 2016 Available online xxxx Keywords: Integrated solar thermal and photovoltaic systems Solar energy Optimization model System performance Life cycle assessment

a b s t r a c t Solar energy for building applications may significantly reduce the conventional energy consumption and the related carbon dioxide emissions. The comprehensive utilization of integrated solar thermal and photovoltaic systems is undoubtedly a subject of interest. In the present paper, an optimization model was proposed for integrated solar energy systems, aiming to figure out the optimal utilization and economical efficiency of solar energy resources for buildings in cold plateau areas. A case study in Lhasa city was further carried out in order to evaluate the energy and economic performance of the developed model. The results indicated that solar photovoltaic systems are preferred than solar thermal systems for typical office buildings in cold plateau areas with rich solar energy resources. In addition, a sensitivity analysis was performed to investigate the influences of financial subsidies and commercial electricity prices on the system economical performance. Furthermore, life cycle assessment was conducted to compare and analyze the performances of an optimization system and a conventional system. Ó 2016 Elsevier Ltd. All rights reserved.

1. Introduction With the remarkable growth of the plateau architectural areas, shortage of traditional building energy supply and fragility of ecological environment are becoming the prominent factors to restrict the development of the plateau areas. As an effective, renewable, safe and eco-friendly energy resource, efficient utilization of solar energy has undoubtedly been regarded as an encouraging solution to global energy shortage, as well as an effective way to achieve

q The short version of the paper was presented at CUE2015 on Nov. 15–17, Fuzhou, China. This paper is a substantial extension of the short version. ⇑ Corresponding authors. E-mail addresses: [email protected] (Y. Feng), [email protected] (Y. Lv).

sustainable development for human beings. Qinghai-Tibet Plateau, Inner Mongolia Plateau and other plateau areas with abundant solar energy resources show high potentials to develop solar energy systems for buildings on a large scale. In addition, solar thermal and photovoltaic technologies have been widely applied in plateau buildings due to the rapid development of solar energy technologies and the gradual cost reduction of solar energy utilization equipment [1]. Therefore, integrating high-efficient solar energy systems with low energy consumption buildings is of great significance in energy and cost saving for plateau areas, which has drawn more and more attentions in recent years. Active solar thermal application technologies have recently become a research emphasis in the field of building solar utilization with the rapid development of active solar energy products

http://dx.doi.org/10.1016/j.apenergy.2016.11.066 0306-2619/Ó 2016 Elsevier Ltd. All rights reserved.

Please cite this article in press as: Si P et al. An optimization method applied to active solar energy systems for buildings in cold plateau areas – The case of Lhasa. Appl Energy (2016), http://dx.doi.org/10.1016/j.apenergy.2016.11.066

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[2–5]. Maurer et al. [6] presented four new and simple models for the building-integrated solar thermal systems, which are more accurate than neglecting the coupling to the buildings and less complicated than detailed physical models. Lamnatou et al. [7] evaluated their patented building-integrated solar thermal collector, and revealed that configuration with collectors in parallel connection may considerably improve the environmental profile of the configuration with collectors in series. Mateus et al. [8] carried out an energy and economic analysis of an integrated solar absorption cooling and heating system for building applications by the TRNSYS software tool, considering different building types (residential, office and hotel) and climates (Berlin, Lisbon and Rome). On the other hand, photovoltaic (PV) modules which have the peculiar characteristic of being integrated with buildings becomes one of the best options to utilize solar energy by capturing and converting it into electricity directly [9,10]. Hwang et al. [11] analyzed the maximum electric energy production according to the inclination and direction of photovoltaic installations. Vats et al. [12] carried out comparative studies between a building integrated semitransparent photovoltaic thermal system and a building integrated opaque photovoltaic thermal system, which are respectively integrated to the facade and roof of a room with and without air duct for ventilation for the cold climatic conditions of Srinagar, India. Peng et al. [13] systematically discussed issues concerning building-integrated photovoltaic (BIPV) in architectural design in China, and further proposed a novel structural design scheme for BIPV, with the characteristics of easy maintenance and replacement of photovoltaic cell modules, prefabricated in factories and mounted on site. Zomer et al. [14] compared BIPV and buildingapplied photovoltaics (BAPV) approaches by using typical figures of merit to assess the technology and layout of PV modules to be installed on the building envelope of two Brazilian Airports, and then reached a compromise of pleasant integration and small energy losses. A number of developed life cycle impact assessment (LCIA) methodologies, such as the RECIPE methodology [15], the Eco-Indicator 99 (EI99) methodology [16,17] and the Eco-Scarcity methodology [18], have been applied to conduct life cycle assessment (LCA) of PV systems. In addition, the use of concentration technologies is beneficial on reducing the environmental burdens. Therefore, two widely used methodologies EI99 and EPS 2000 are used to perform the life cycle impact assessment and environmental impact evaluation, respectively, and the results showed that significant benefits are gained using the Building Integration Concentrated Photovoltaics (BICPV) schemes [19]. Several studies have also been devoted to study the combined heating and power system (CHP), which not only produces solar electric energy but also delivers thermal energy as the byproduct [20,21]. Michael et al. [22] combined the electrical and thermal components in a single unit area and proposed a reference guide for flat plate solar photovoltaic-thermal systems, to overcome the disadvantages of the low energy of the solar PV module, the low exergy of the solar flat plate thermal collector and limited usable shadow-free space on building roof-tops. Sanaye et al. [23] presented the energy, exergy and economic optimization of a combined cooling, heating and power (CCHP) solar generation system equipped with conventional photovoltaic, concentrated photovoltaic/thermal (CPVT), and evacuated tube (ET) collectors, to achieve the highest values of relative net annual benefit (RNAB) and exergy efficiency as two objectives. According to above discussions, a variety of researches have investigated the independent solar thermal technologies, independent photovoltaic technologies and combined photovoltaic thermal systems applied in the buildings. However, few studies focused on the comprehensive photovoltaic thermal utilization systems used in most plateau areas because of the complexity of integrated solar thermoelectricity coupling systems and the short-

age of corresponding design methodologies, significantly hindering the promotion of the integrated photovoltaic and thermal systems. Therefore, in this paper, an optimization model coupled with solar thermal and photovoltaic systems is proposed. Based on the developed model, a case study for a typical office building located at Lhasa is illustrated to reasonably configure the solar thermal and photovoltaic systems. This study aims to achieve the optimization utilization and economical efficiency of solar energy resources for buildings in cold plateau areas. 2. Methodology 2.1. Study area Tibetan plateau is characterized by all year-round sunshine, dry climate and long heating supply period. The solar radiation over the Tibetan plateau is greater than that over other sites in China, which ranks second on earth, following the Sahara Desert [24]. According to the 5-year observation data received by a set of pyranometer instruments set up in Gaize, on the Tibetan Plateau, the average daily radiation was 21 MJ m2 day1 with maximum daily values of 27 MJ m2 day1 occurring in June and minimum values of 14 MJ m2 day1 in December, which is much higher than those measured in other regions at similar latitudes [25]. 2.2. Physical model Based on the climate and energy supply features in plateau cold areas, an active solar energy comprehensive utilization system applicable is proposed. In winter, the system utilizes the solar thermal as the main heating source, while utilizes the power-driven air source heat pumps as an auxiliary thermal source; meanwhile, the system utilizes a photovoltaic power generation system which could deliver the generated power to the grid, relieving the power supply shortage. In summer, ventilation rather than chiller can meet indoor cooling requirements due to relatively low temperature around 16.4 °C in the hottest month of June. The entire system is highly effective and environmentally friendly, and beneficial to protect the fragile ecological environment. The schematic drawing

Fig. 1. System physical model.

Please cite this article in press as: Si P et al. An optimization method applied to active solar energy systems for buildings in cold plateau areas – The case of Lhasa. Appl Energy (2016), http://dx.doi.org/10.1016/j.apenergy.2016.11.066

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of the proposed physical model is shown in Fig. 1. A solar heat collector and an air source heat pump auxiliary thermal source provide heat source for the heating system of buildings in winter, while a photovoltaic system supplies power for the electrical appliances in the buildings, an air source heat pump and a delivery water pump. The extra electricity can be delivered to the grid during the off-peak hours, whereas the insufficient parts can also be bought from the grid during the peak hours. In the proposed model, there is a strong coupling relationship between the solar thermal and photovoltaic, as shown in Fig. 2. The solar collector size may affect the heat load of the auxiliary heat source, which further affects the power balance relation of photovoltaic systems and installation area of the solar photovoltaic cells. On the other hand, the change of photovoltaic area may inversely affect heat collection capacity and thermal storage characteristics of solar thermal systems. The interaction between solar thermal and photovoltaic is reflected not only during the solar thermal/photovoltaic conversion process and thermal storage/electric power storage process, but also reflected during the annual energy consumption of the buildings. Moreover, it has an important influence on the economic performance of the integrated utilization systems. The coupling relationship among building energy consumption, energy generation and energy storage, coupled with the dynamic changes of meteorological parameters, ultimately forms a complicated multi-variable dynamic coupling process. Correspondingly, it is critical to determine the optimal matching relationship between solar thermal and photovoltaic in the aforementioned active solar energy utilization systems.

utilization perspective. Under the premise of meeting thermal and power demands in buildings, less annual calculation cost corresponds to better solar energy comprehensive utilization systems considering from the economical efficiency perspective. 2.3.1. Constraints 2.3.1.1. System hourly electricity balance relation.

Q fd ðh; Ad;w Þ  Q q ðhÞ  Q g ðh; Ar;w Þ ¼ Q s ðh; Ad;w ; Ar;w Þ

where Q fd ðh; Ad;w Þ is the hourly power generation capacity of the photovoltaic equipment, kW h; Q q ðhÞ is the hourly power consumption of other equipment excluding the heating equipment, kW h; positive Q s ðh; Ad;w ; Ar;w Þ represents the hourly on-grid power, while negative value represents the hourly power consumption from urban grid, kW h; Q g ðh; Ar;w Þ is the hourly power consumption of a heating system, kW h; Ad;w is the coverage roof area of the photovoltaic generation equipment, m2; Ar;w is the coverage roof area of the solar thermal equipment, m2. 2.3.1.2. At time h, the system hourly heat balance relation. Direct heating capacity of a collector is expressed by:

(

Q j:g ðhÞ ¼

Q j ðhÞ; Q f ðhÞ > Q j ðhÞ Q f ðhÞ; Q f ðhÞ 6 Q j ðhÞ

ð2Þ

Heat balance equation of the residual heat in a water tank can be expressed by:

(

Q y ðhÞ ¼ 2.3. Optimized mathematical model Solar powered building integration technology is mostly applicable for the solar energy installed on the building roofs. Thus the optimization method in this study is based on the assumption that the solar energy equipment is installed on the roofs. Regarding the buildings as an opening system, in which the annual power and thermal demands are constant, the commercial energy switching between the systems and the environment can only occur in grid integration points. Under the premise of meeting the thermal and power demands in buildings, less commercial power (difference value between municipal grid power consumption and generated on-grid energy) corresponds to better solar energy comprehensive utilization systems considering from the energy

ð1Þ

_

Q y ðh  1Þ þ Q ðhÞ  Q gq ðhÞ; Q y ðh  1Þ P Q gq ðhÞ 0; Q y ðh  1Þ < Q gq ðhÞ

ð3Þ

Insufficient heat after direct heat supplied by a solar collector can be expressed by:

(

Q gq ðhÞ ¼

Q j ðhÞ  Q f ðhÞ; Q f ðhÞ  Q j ðhÞ < 0 Q f ðhÞ  Q j ðhÞ P 0

0;

ð4Þ

The water tank instant heat storage capacity can be expressed by: _

Q ðhÞ ¼

(

Q j ðhÞ  Q f ðhÞ; Q j ðhÞ  Q f ðhÞ > 0 0;

Q j ðhÞ  Q f ðhÞ 6 0

ð5Þ

Building load

Power load

Heating load Thermal storage

Power grid Photovoltaic

Solar thermal

Heat pump

Fig. 2. Coupling relationship between the solar thermal and photovoltaic.

Please cite this article in press as: Si P et al. An optimization method applied to active solar energy systems for buildings in cold plateau areas – The case of Lhasa. Appl Energy (2016), http://dx.doi.org/10.1016/j.apenergy.2016.11.066

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Heating capacity of the auxiliary heat source can be expressed by: _

(

Q fz ðhÞ ¼

Q gq ðhÞ  Q y ðh  1Þ; Q y ðhÞ ¼ 0 Q y ðhÞ–0

0;

Z

h

Q j ðhÞ ¼ h1

3600gþh  Ar;w = cos b  IðhÞ 1000

ð6Þ

2.3.2. Objective function Considering from the energy saving point of view, the objective function is:

ð7Þ

S ¼ min½Q n;h ðAd;w ; Ar;w Þ

where Qj(h) is the solar energy absorbed by a collector, kJ; the solar surface tilt angle b is the angle between the plane of the tilted surface and the horizontal, °; I(h) is the sun radiation intensity on a tilted face at time h, W/m2; Qf (h) is the required heat for heating at time h, kJ; gþ h is positive value in the collector efficiency. 2.3.1.3. Annual on-grid energy, kW h.

Q s;w ðAd;w ; Ar;w Þ ¼

h¼8765 X 

Q s ðh; Ad;w ; Ar;w Þ; Q s ðh; Ad;w ; Ar;w Þ > 0



Q s ðh; Ad;w ; Ar;w Þ < 0

0;

h¼0

ð8Þ 2.3.1.4. Annual urban grid electricity consumption, kW h.

Q s;x ðAd;w ; Ar;w Þ ¼

h¼8765 X 

jQ s ðh; Ad;w ; Ar;w Þj; Q s ðh; Ad;w ; Ar;w Þ < 0



Q s ðh; Ad;w ; Ar;w Þ > 0

0;

h¼0

which is the collector service life (15 years) in the present study; P is the operation cost; hg is the capital recovery coefficient.

¼ min½Q s;x ðAd;w ; Ar;w Þ  Q s;w ðAd;w ; Ar;w Þ

ð14Þ

Considering from the economical point of view, the objective function is:

S ¼ min½ZðAd;w ; Ar;w Þ   n ið1 þ iÞ KðA ; A Þ þ PðA ; A Þ ¼ min r;w r;w d;w d;w n ð1 þ iÞ  1

ð15Þ

2.3.3. Solution method MATLAB is used to solve the equations by using the solution flow shown in Fig. 3. A computational logic diagram can be divided into three modules: initial input, optimization calculation and results output. Hourly load data calculated by DesignBuilder software, building meteorological parameters, equipment performance parameters and other data are input to the optimization

ð9Þ 2.3.1.5. Annual energy consumption (calculated by electricity consumption), kW h.

Q n;h ðAd;w ; Ar;w Þ ¼ Q s;x ðAd;w ; Ar;w Þ  Q s;w ðAd;w ; Ar;w Þ

ð10Þ

2.3.1.6. Roof area limited constraint, m2.

Ad;w þ Ar;w 6 Aw

ð11Þ 2

where Aw is the total roof area, m . 2.3.1.7. Annual operation cost, Yuan.

PðAd;w ; Ar;w Þ ¼ P w ðAd;w ; Ar;w Þ h¼8765 X  Q fd ðh; Ad;w Þ þ h¼0

  Q s ðh; Ad;w ; Ar;w Þ; Q s ðh; Ad;w ; Ar;w Þ > 0   ps 0  Q s ðh; Ad;w ; Ar;w Þ  ðpd þ ps Þ; Q s ðh; Ad;w ; Ar;w Þ > 0 þ 0; Q s ðh; Ad;w ; Ar;w Þ 6 0   jQ s ðh; Ad;w ; Ar;w Þj  pc ; Q s ðh; Ad;w ; Ar;w Þ < 0 ð12Þ  0; Q s ðh; Ad;w ; Ar;w Þ P 0 where Pw ðAd;w ; Ar;w Þ is the annual maintenance cost, Yuan; pc is the commercial electricity price, Yuan/kW h; ps is the subsidy price for photovoltaic power generation, Yuan/kW h; pd is the desulfurization benchmark electricity price, Yuan/kW h. 2.3.1.8. Calculated annual cost, Yuan. Dynamic analysis method is used to carry out the technical economical analysis. The calculated annual cost can be obtained by:

ZðAd;w ; Ar;w Þ ¼ hg KðAd;w ; Ar;w Þ þ PðAd;w ; Ar;w Þ n

¼

ið1 þ iÞ KðAd;w ; Ar;w Þ þ PðAd;w ; Ar;w Þ n ð1 þ iÞ  1

ð13Þ

where K is the initial investment, Yuan; i is the interest rate/yield rate, %, which is 8% in the present study; n is the production period,

Fig. 3. Calculation solution flow chart.

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The developed simulation model is applied to a typical office building located in Lhasa city which lies in the center of Tibetan Plateau as the capital of the Tibet Autonomous Region, China. The main meteorological parameters in Lhasa are shown in Fig. 4. The annual average temperature is 8.1 °C and the outdoor average temperature is 7.5 °C. The coldest month is January, with a monthly average temperature of approximately 1.6 °C, while the hottest month is June, with a monthly average temperature of approximately of 16.4 °C. Lhasa is a city of severe shortage in fossil energy, as well as the city with the highest power consumption ratio in China urban energy consumption. Moreover, local power in Lhasa is mainly supplied from hydro power plants. As shown in Fig. 5, winter has the highest peak of power consumption and dry season for hydraulic power facilities, resulting in insufficient power supply. Therefore, it is not advisable to meet the heating demands in winter using traditional fossil energy and electric heating facilities. With an elevation of 3650 m, Lhasa is also known as the city of sunlight mainly due to high solar radiation and extensive sunshine hours. In accordance with the measurement of annual solar radiation in China, the largest solar direct radiation and the longest sunshine duration are found in Qinghai-Tibet plateau [26,27], in which the annually accumulated solar radiation in Lhasa is up to 7200 MJ/ m2, ranking first in cities of China. Therefore, solar energy has been considered as a promising option to upgrade heating systems in Lhasa, which could reduce the demands in fossil fuel and eliminate carbon dioxide emission accordingly. Except for solar energy, the use of air source heat pumps is regarded as another encouraging way for heating due to acceptable outdoor temperature and dry climate in winter. Fig. 6 shows frosting characteristics of air source heat pumps in Lhasa. As shown in Fig. 6, only 2% working conditions of the air source heat pumps are in the frosting zone for a whole year. It is not necessary to eliminate and melt the frost at most time, reducing the frosting energy

3.1. Basic procedures for practical engineering applications The project building parameters (such as physical features, shape coefficient, window-wall ratio and building envelope thermal parameters), local meteorological parameters, equipment work schedules and other information are collected before conducting optimal matching calculation. Commercial load simulation software DesignBuilder is adopted to calculate the thermal load and power load of the buildings. Meanwhile, the solar energy equipment parameters, local energy prices, energy policies and other constraints are determined. Load calculation results and constraints are input into optimization model, and step length is set for optimization calculation. The optimal matching scheme obtained through simulation calculation is used to evaluate the system performances, and a sensitivity analysis is carried out to analyze the effects of different variables on the system optimization scheme, to confirm the final project construction scheme. 3.2. Building parameters Traditional architectures in Lhasa are multi-story buildings with 3–4 floors. To satisfy the sunlight and solar passive heating requirements, the building spacing is relatively larger, as shown in Fig. 7. Offices, guest rooms, drawing rooms, living rooms and other primary rooms are oriented towards the south, while secondary rooms such as store rooms and toilets are oriented towards the north. Majority of the public buildings only have south oriented rooms with large windows, and generally the north orientation is the corridor. The paper selected an office building of Department of Construction in Tibet Autonomous Region as the research objective. The building is a three-floor office building, with a height of 3 m, building area of about 2946 m2 and utilizable roof area of about 800 m2. Three-dimensional model for the office building is shown in Fig. 8. The thermal parameters of the building envelope structure are arranged in line with provisions in GB50189-2015. 3.3. Load simulation The studied building has no stable hot water load requirements. By considering the relatively smaller length and relatively lower outdoor ambient temperature in summer, there are no cooling 20

Global Horizontal irradiation ( MJ/m2)

900

Global Horizontal irradiation Average outdoor temperature

800

18 16

700

14

600

12 10

500

8 400

6

300

4 2

200

0 100

-2

)

3. Case study

consumption and being beneficial for effective operation of air source heat pumps. Thus, air source heat pumps are selected as the auxiliary heating equipment in the case study.

Average outdoor temperature (

calculation module, to calculate the hourly energy collection of the equipment. The power and heat balance relationship mentioned in 2.3.1.1 and 2.3.1.2 (Eqs. (1)–(7)) are used to conduct hourly dynamic calculation; Eqs. (8)–(10) are used to calculate annual energy consumption; Eqs. (12) and (13) are used for calculation of economical performance; Eqs. (14) and (15) are the objective functions and enumeration calculation is continuously conducted (Eq. (11) is the enumeration constraint), to finally obtain the optimal configuration and the targeted value.

-4

0 Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Dec

Months Fig. 4. Main meteorological parameters in Lhasa.

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Fig. 5. Comparison between power supply and power consumption in Lhasa.

100

100 90

Easy to frost area

90 80

Outdoor air relative humidity (%)

80 70

No frost area

70

60

60

50

50

40

40

30

30

20

20

10

10

0

0

-10 -15.0 -12.5 -10.0 -7.5 -5.0 -2.5

0.0

2.5

5.0

-10 7.5 10.0 12.5 15.0 17.5 20.0

Outdoor air dry bulb temperature ( ) Fig. 6. Frosting characteristics of air source heat pumps in Lhasa.

Fig. 7. Typical buildings in Lhasa.

demands. Therefore, only the building power load and heating load are taken into account for the simulation calculation. 3.3.1. Power load As to the power load for indoor lighting and relevant electrical appliances, hour variation coefficient is set according

to the building operation rules, distinguishing the workdays and rest days. Considering the fact that the power consumption of heating systems varies during the optimization process of the integrated systems, the building power load predication given excludes the power load for the heating systems.

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lector selected for the studied system is a flat plate collector. A collector’s tilt of 50° with respect to the horizontal plane was selected. The collector could undertake the working pressure of 0.6 MPa. The dimension of the collector is 2000 mm (height)  1000 mm (height)  78 mm (thickness) and the weight is 33.5 kg. The total area of the collector is 2.00 m2 with an aperture area of 1.86 m2. The inlet temperature and outlet temperature of the solar collector are 50 °C and 60 °C, respectively. The efficiency of a flat plate collector can be calculated as:

g ¼ 0:7595  5:7375ðT i  T a Þ=IðhÞ

where g is the collector efficiency; I(h) is the solar radiation received per collector area, W/m2; Ti is the collector fluid inlet temperature, °C; Ta is the ambient temperature, °C. Solar photovoltaic cells manufactured by YINGLI Solar Company were selected as the research object, and its performance parameters are shown in Table 1. The annual attenuation performance of the photovoltaic systems can be basically divided into two stages, which is 610% in the first 0–10 years and 620% in the next 11–25 years, indicating that the module efficiency after 25 years is still 80% of the nominal power. The overall system efficiency of the photovoltaic systems takes 75% in the present study.

Fig. 8. 3D model of load simulation in office building.

3.3.2. Heating load DesignBuilder load simulation software is adopted to carry out heating load simulation calculation for typical office buildings in Lhasa, with the building model shown in Fig. 8. The lighting duration, personnel hour-by-hour in building ratio, hour-by-hour utilization ratio of electrical appliances, air conditioning and heating room temperature, lighting power density, personnel density, equipment power density and timetable are determined in accordance with Chinese National Standard GB50189-2015 and practical engineering situations. The heating period of Lhasa area is from November 15 to March 15 of the next year. According to the simulation calculation, the peak heating load and annual total heating load are 53.67 kW and 59,218 kW h, respectively; the peak power load and annual total power load are 82.0 kW and 205,242 kW h, respectively. The change of heating load and power load in a week is shown in Fig. 9. Intermittent heating mode is applied because the studied office building is only used in the day time. It can be observed from Fig. 9 that, the heating load only occurs in the day time. Local solar energy is extremely abundant during the day time, and the solar energy radiation obtained by windows and other passive devices are strong, resulting in that the accumulated heating load over the whole heating season is far lower than that of the same type of office buildings in that area.

3.4.2. Boundary conditions for economical efficiency In Lhasa, the commercial electricity price is 0.8521 Yuan/kW h; desulfurization benchmark electricity price is 0.38 Yuan/kW h; the yield is 8%; the collector’s service life is 15 years and the photovoltaic cell panel’s service life is 25 years. The commercial electricity price of the auxiliary power supply and subsidy price for the photovoltaic power generation are 0.42 Yuan/kW h and 0.42 Yuan/kW h, respectively. 4. Results and discussions In order to evaluate the energetic and economic performance of the systems presented, dynamic simulations and sensitivity analysis were carried out on the basis of the developed simulation model.

3.4. Solution boundary conditions

4.1. Energy saving based optimization results of active solar energy system

3.4.1. Solar collector performance By taking into account the plateau climatic conditions and flatplate collector with better bearing capacity, the solar thermal col-

Fig. 10 shows the influences of the solar thermal/photoelectric area on annual power consumption of typical office buildings in

100

100

Heating load

90

Load (kW)

ð16Þ

Electrical load

90

80

80

70

70

60

60

50

50

40

40

30

30

20

20

10

10

0

0 0

20

40

60

80

100

120

140

160

Hours of a week Fig. 9. Change of heating and power load in a week.

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Table 1 Solar photovoltaic cell performance parameters.

Heating

Output generation power (Wp) Power tolerance (%) Working voltage at the maximum power point Vm (V) Working current at the maximum power point Im (A) Open circuit voltage Voc (V) Short circuit current Isc (A) Module efficiency (%)

250 0/+5 30.4 8.24 38.4 8.79 15.3

Lhasa. To achieve the minimum annual power consumption, all roof areas of the studied office building should be covered by solar photovoltaic. In other words, from the perspective of maximum energy saving in the building, the roofs preferably adopt the integrated energy supply systems combining the solar photovoltaic and the air source heat pumps. The results shown in Fig. 9 can be attributed to four primary reasons. The first one is the difference in the utilization time span in throughout year. As shown in Fig. 11, the solar photovoltaic systems can be used in the whole year, generating available energy for 12 months; while the solar thermal systems are only utilized in the heating season from November 15 to March 15 of the next year, only generating available energy for 4–5 months. The annual utilization period of the solar photovoltaic systems is 2–3 times higher than that of the solar thermal heating systems. Secondly, the daily utilization periods of the solar photovoltaic systems and the solar thermal systems are different as shown in Fig. 12. The heat collection efficiency of the solar thermal systems is not only affected by radiation intensity, but also relevant with outdoor dry-bulb temperature. Lower outdoor temperature is unfavorable for the solar thermal systems to obtain solar radiation energy. During the period with lower outdoor temperature and lower solar radiation strength, the heat loss caused by heat convection at the collector surface is more than the solar radiation received by the collector surface. Therefore, during the sunrise and sunset period with lower temperature, the collector surface receiving solar radiation could not generate available energy, consequently reducing the effective heat collecting time by more than 2 h in comparison with the solar radiation time, especially in cloudy and snow weather conditions. In comparison, the photo-

Photovoltaic power generation

Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec. Fig. 11. Photovoltaic/solar thermal system utilization time in a year.

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voltaic systems are still capable of generating available power during sunrise and sunset period with lower temperature. The third reason lies in the difference between the energy storage systems and the energy utilization systems. The urban power grid with infinite energy storage capacity can be used as an ideal energy storage system of the solar photovoltaic systems, indicating that the power generated by the photovoltaic systems can be wholly utilized excluding the system internal loss. In contrast, for the solar thermal heating systems, during the initial heating stage and the terminal heating stage with low heating load requirements, the water temperature in the accumulated hot water tank is higher than the design value because the required heat storage capacity is higher than the water tank storage capacity due to the limitation of water tank volume, as shown in Fig. 13. On one hand, the increase in return water temperature and collector convection heat exchange amount leads to reduction in heat collection efficiency of the collector and reduction in heat storage of the systems. On the other hand, the heat loss in the water tank is increased, further reducing the energy efficiency of the whole system.

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Hour Fig. 10. Influence of solar thermal/photovoltaic area on annual power consumption of typical office buildings in Lhasa.

Fig. 13. Water temperature dynamic curve of solar thermal heating system.

Please cite this article in press as: Si P et al. An optimization method applied to active solar energy systems for buildings in cold plateau areas – The case of Lhasa. Appl Energy (2016), http://dx.doi.org/10.1016/j.apenergy.2016.11.066

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Meanwhile, due to the limitation of energy utilization termination of the heating systems, the solar radiation energy received during heating terminal period could not be completely utilized, thus the existence of partial waste energy further reduces the systems’ energy saving. In other words, the photovoltaic systems may make use of the dispatching capacity of urban grid to apply the surplus on-grid power for other electrical loads. In contrast, the hot water generated by heating system can only be utilized in the same building. Therefore, the heat energy generated during heating terminal period could not be exhausted by the building nor be dispatched to other places. Thus, there is partial waste energy which could not be completely utilized. The fourth reason lies in the energy grade difference. Even though the photoelectric conversion efficiency of solar photovoltaic systems is around 15%, much lower than the heating collecting efficiency 35–40% of solar thermal heating systems, the electric energy generated by the solar photovoltaic systems is of high energy grade compared to the hot water around 55 °C generated by the solar thermal systems. Air source heat pumps driven by 1 kW h electrical energy could generate 2–3 kW h hot water around 55 °C, indicating the energy saving potentials of the photovoltaic systems. 4.2. Economical efficiency based optimization results of active solar energy system The influences of the solar thermal/photoelectric area on annual calculation costs of typical office buildings in Lhasa are shown in Fig. 14, taking into account the government photovoltaic allowance and taxes. It can be obviously observed that, based on the solar energy comprehensive utilization proposal, all roof areas are covered by solar photovoltaic to achieve the minimum annual calculation costs in office buildings. In other words, considering from the building economical perspective, the building roofs should preferably adopt the solar photovoltaic systems. The research results of Ghafoor et al. [28] also showed that, steadily decreasing prices have made photovoltaic systems more favorable, even without consideration of public subsidies. Except for the reasons as previously described in Section 4.1 and Ref. [28], the economical efficiency of the solar photovoltaic systems is superior to that of the solar thermal systems because of the better financial allowance policy of the photovoltaic systems compared with the latter. Furthermore, the service life of the pho-

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tovoltaic systems is generally 25 years, 10 years more than the service life of the solar thermal systems. Even though the unit area cost of the solar photovoltaic power generation systems is higher than that of the solar thermal heating systems, the initial investment difference between above two types is reduced taking the service life into account, thus improving the economical efficiency of the solar photovoltaic power generation systems. 4.3. Building energy performance evaluation Fig. 15 shows the annual performance evaluation results of an optimization system. The proportion of on-grid energy in generating capacity of the photovoltaic systems changes within 16%–29%, which is relatively lower in heating season and higher in non heating season; the average proportion of annual on-grid energy accounts for 23.0% of the photovoltaic systems’ generating capacity. It can be attributed to that, the photovoltaic systems’ generating capacity during heating season is lower than that during non heating season; in addition, the electricity demands of the whole building during heating season is higher than that during non heating season because of the electricity consumption by the heating systems. It can also be observed from Fig. 15 that, the self-use energy proportion of the photovoltaic systems accounts for 42%–76% of total electricity consumption in the studied building, in which the self-use proportion of the photovoltaic systems during non heating season is higher than that during heating season, and 59.2% annual electricity consumption in the building is supplied by the photovoltaic generation system. It indicates that, the annual electricity consumption of an active solar building is decreased by about 60% in comparison with buildings adopting ordinary electricity and air source heat pumps. The annual power consumption of the whole building is 70.7 kW h/m2. Annual on-grid energy of the photovoltaic generation systems accounts for about 45% of annual urban power consumption of the building. Considering one year as an evaluation period, annual overall electricity consumption of the building (15.8 kW h/m2) is 55% of actual urban power grid consumption after deducting the on-grid energy (28.9 kW h/m2), that is, the annual energy saving rate of the active solar building is about 78% taking into account the contribution of the active solar building on urban power grid. 4.4. Sensitivity analysis A sensitivity analysis was carried out in order to analyze the effects of the variability in financial subsidies and commercial electricity price on energy efficiency and economic feasibility of the system under investigation. 4.4.1. Influence of financial subsidies on the system economical efficiency Fig. 16 shows the calculated annual cost of a system adopting photovoltaic technology integrated with air source heat pumps with and without financial subsidies, respectively. The calculated annual cost of the system increases in case of no financial subsidies. For example, the calculated annual cost is increased by 49% when 800 m2 photovoltaic cell panel is used, increasing from original 115,140 Yuan to 171,524 Yuan, which indicates that the financial subsidies has a significant influence on the system economical efficiency.

Fig. 14. Influence of solar thermal/photovoltaic area on annual calculation costs of typical office buildings in Lhasa.

4.4.2. Influence of commercial electricity prices on the system economical efficiency Fig. 17 illustrates the influence of commercial electricity prices on the economical efficiency of a solar photovoltaic system. With

Please cite this article in press as: Si P et al. An optimization method applied to active solar energy systems for buildings in cold plateau areas – The case of Lhasa. Appl Energy (2016), http://dx.doi.org/10.1016/j.apenergy.2016.11.066

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the increase in commercial electricity prices, the calculated annual cost of the solar integrated utilization system is linearly increased. For example, the calculated annual cost will be increased by 8506 Yuan for every increase of 0.1 Yuan/kW h in commercial electricity prices. Assuming that the commercial electricity prices increase or decrease within 10%, the calculated annual cost correspondingly changes within ±4%. The results show that the change in commercial electricity prices has less influence on the system economical performance in comparison with the existence of financial subsidies.

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Life cycle assessment is a well established methodology, which is used to assess the energy performances associated with all stages of a system’s life cycle. A complete LCA (including manufacturing, operation and end-of-life) of an optimization system (only photovoltaic on the roof) and a conventional heating system was carried out in the research. Three indices were calculated and analyzed, including Global energy requirement (GER), Global warming potential (GWP) and Energy payback time (EPT). Energy and materials inputs during equipment (heat pumps, PV modules, etc.) manufacture period were calculated with data in Refs. [10,29,30], while the equivalent factor of pollutant emissions to environmental impact potential were calculated with data in Refs. [31,32]. As shown in Fig. 18, for the specific case study, the energy and environmental performances of the optimization system are better than those of the conventional system (impacts 72% lower). This can be attributed to that, the higher impacts caused by the manufacturing and end-of-life of the optimization system are balanced by the energy savings and avoided emissions during the operation step. In comparison with the conventional system, the energy consumption increase during manufacturing and end-of-life steps of the optimization system is about 6% of energy savings and avoided emissions during the operation step. EPT was also calculated in order to estimate the time needed to offset the energy consumption impacts due to the life cycle of the optimization system in substitution with the conventional one. The EPT is about 2.0 years, indicating that the energy saved during the

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useful life of the system overcomes the global energy consumption due to its manufacture and end-of-life of about thirteen times. 5. Conclusions The comprehensive solar utilization systems which integrate solar thermal and photovoltaic technologies have high potentials to reduce the energy consumption and the CO2 emissions for plateau buildings. In this paper, an optimization model is proposed for integrated solar energy systems, aiming to figure out the optimal utilization and economical efficiency of solar energy resources for buildings in cold plateau areas. The results show that, considering the maximum energy saving in the buildings, the building roofs should give priority to adopt the integrated energy supply systems combining the solar photovoltaic and air source heat pumps. While considering from the building economical perspective, the solar photovoltaic systems are more preferable. In comparison with influence caused by financial subsidies, the change in commercial electricity prices has less influence on the system economical performance. Life cycle assessment indicates that, for the specific case study, the energy and environmental performances of the studied optimization system are better than those of the conventional system (impacts 72% lower). The optimal matching between solar thermal and photovoltaic systems may vary in regions with different energy prices and solar resources, which can be analyzed and calculated comprehensively according to the meteorological characteristics, energy resources features and building characteristics. Even though Lhasa located in the cold Tibetan Plateau is selected as the case study in this study, the optimization methods and conclusions proposed are not limited to the studied region and they are also applicable for any cold areas with heating requirements and abundant solar energy resources. Acknowledgement The research was carried out with the financial support of National Natural Science Foundation of China (51578523) and the National High-tech R&D (863) Program (2015AA050402). References [1] Chow TT. A review on photovoltaic/thermal hybrid solar technology. Appl Energy 2010;87:365–79.

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Please cite this article in press as: Si P et al. An optimization method applied to active solar energy systems for buildings in cold plateau areas – The case of Lhasa. Appl Energy (2016), http://dx.doi.org/10.1016/j.apenergy.2016.11.066