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Feasibility assessment of introducing distributed energy resources in urban areas of China
Applied Thermal Engineering 30 (2010) 2584e2593
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Feasibility assessment of introducing distributed energy resources in urban areas of China Hongbo Ren a, *, Weisheng Zhou b, Ken’ichi Nakagami b, Weijun Gao c, Qiong Wu c a
Ritsumeikan Global Innovation Research Organization, Ritsumeikan University, 603-8577 Kyoto, Japan College of Policy Sciences, Ritsumeikan University, 603-8577 Kyoto, Japan c Faculty of Environmental Engineering, The University of Kitakyushu, 808-0135 Kitakyushu, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 10 February 2010 Accepted 12 July 2010 Available online 15 July 2010
In this study, based on the consideration of achieving a low-carbon city, a distributed energy system is promoted by integrating combined heat and power (CHP) plant, biomass energy and photovoltaic technology, for the urban areas in China. An analytical model has been developed for estimating an economically efficient installation and operation pattern for the distributed energy system. As an illustrative example, a numerical study is conducted of feasible distributed energy system for a model area in Shanghai, while considering five scenarios with different technology combinations. According to the simulation results, although enjoying reasonable environmental merits, it is hard to diffuse the distributed generation technologies, especially some renewable ones, in the model area from the economic point of view. Currently, the most feasible technology is the natural gas CHP system, which has a cost reduction ratio of only 0.7%. In addition, the sensitivity analyses illustrate that the introduction of electricity buy-back and the reduction of biogas price can promote the adoption of some renewable technologies to some extent. Ó 2010 Elsevier Ltd. All rights reserved.
Keywords: Feasibility assessment Distributed energy resources Analytical model Urban area China
1. Introduction Due to long-term economic development, energy consumption in China has been increasing for decades. The growth has obviously speeded up in the new century, from 1386 million tons of standard of coal equivalent (Mtce) in 2000 to 2850 Mtce in 2008 [1]. This rising demand has turned China from a net energy exporter to a net energy importer. On the other hand, Chinese CO2 emissions in 2008 was 6.9 billion metric tons of carbon, which accounted for about 22% of global CO2 emissions, overtaking the United States and becoming the dominant country in the global warming debate. In addition, as the largest developing country in the world, the Chinese government took its responsibility positively and announced to reduce the intensity of CO2 emissions per unit of GDP in 2020 by 40e45 percent compared with the level of 2005. In order to achieve such a dramatic goal and realize a sustainable lowcarbon society, various innovative measures have been and will be executed in China. In natural, China’s energy issues are mainly rooted in its ongoing industrialization, modernization and urbanization [2]. According to the calculation made by Dhakal [3], the * Corresponding author. Tel.: þ81 075 466 3348; fax: þ81 075 465 8245. E-mail address: [email protected] (H. Ren). 1359-4311/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.applthermaleng.2010.07.009
urban contribution to China’s total commercial energy uses was about 84% in the year 2006. Correspondingly, the urban area is always recognized as the most important location for energy conservation. In the past few years, along with the rapid urbanization, the energy conservation in the civilian sector, which reflects the improvement of living standard, plays an important role in the sustainable development of the city. Especially, in the Yangtze River Delta area, which has relatively large economic scale and population size, as well as enough attention to the environmental protection, more and more attention is paid to the reformation of urban energy system. Furthermore, the recent sudden rise of oil price also encourages the introduction of energy conservation and advanced energy systems. The distributed energy resource (DER), including combined heat and power (CHP), photovoltaic (PV), wind turbine and biomass energy, etc., is one of the most dominant options and is expected to be widely introduced. About the adoption of DER system in China, Fu et al. [4] introduced the performance tests of several combined cooling, heating and power (CCHP) systems in combination with thermally-activated (TA) technologies. Hao et al. [5] analyzed the sustainable characteristics of building CHP technology and studied its prospects in China. Okada et al. [6] examined the energetic and environmental
H. Ren et al. / Applied Thermal Engineering 30 (2010) 2584e2593
Nomenclature Afac Celec Cfuel Cinv Com Ctotal d h i j m Pelec Pequ
annuity factor of the capital cost of distributed generators, % cost for grid electricity purchase, Yen cost for fuel consumption, Yen annualized investment cost, Yen operation and management cost, Yen total annual cost, Yen day in a month hour in a day index of DER technologies index of fuel types month in a year electricity tariff rate, Yen/kWh capital cost of the distributed generators, Yen/kW
effects with the adoption of CHP system in Guangzhou, China. Aki and Murata [7] analyzed the technology, economy and policy related issues for introducing natural gas CHP system in the urban areas of China. Kosugi et al. [8] examined the method of improving the economic performance of CHP system in China by making use of the Clean Development Mechanism (CDM) and Energy service company (ESCO) frameworks. Xuan et al. [9] assessed the introduction feasibility of CHP system for the skyscraper complex in China. Liu et al. [10] analyzed the performance of a combined CHP and liquid-desiccant system in a demonstration building located in Beijing, China. It could be found that all of the above studies focused on the natural gas CHP system. Other DER technologies, for example, PV and biomass which are considered to be feasible options for future energy supply in the urban area, are never taken into consideration. In addition, the influence of some key economic and policy factors on the introduction of DER system is uncertain. In a previous study [11], from the viewpoints of design and evaluation of the DER system, by integrating the technical and financial information, as well as energy demands, a customer aided optimization model has been developed for the introduction of economically optimal DER systems in Japan. Using the developed model, the optimal adoption and operation strategies of CHP, PV and biomass energy systems for residential buildings in Japan have been examined [12e14]. However, with different local conditions (e.g. climate, energy demands, etc.) and market mechanisms (e.g. tariff structures, etc.), a design and evaluation tool for the introduction of DER systems in China is necessary. The First section of this paper introduces the background of Chinese energy consumption and corresponding local and global environmental issues. The Second section reviews the current status of DER adoption in China, especially in the urban areas. The Third section presents a framework of the urban DER system along
Pfuel Pomf Pomv Qegen Qepur Qfpur Qload Qrec Rcap u
2585
fuel price, Yen/kWh fixed operation and maintenance cost, Yen/kW variable operation and maintenance cost, Yen/kWh on-site power generation, kW amount of electricity purchase from the utility, kW amount of fuel consumption, kW customer load, kW amount of recovered heat, kW rated capacity of the distributed generators, kW end uses, including electricity, cooling, heating and hot water
Greek symbols h efficiency of direct fuel combustion, % g efficiency of recovered heat utilization, %
with an analytical model, which can aid the decision making while introducing DER system in the urban areas of China. In the Fourth section, the foundational information of the studied case is introduced. Some major findings of the case study are presented in Section five. Finally, Section six draws a conclusion for the study. 2. Current status of DER adoption in China By the end of 2004, distributed generation took up about 15.1% in Chinese total power generation, which implied significant potential before reaching the market penetration in leading countries such as Denmark, the Netherlands and Finland [15,16]. In China, the predominant forms of DER are coal fired steam CHP systems to provide heat to municipal district heating systems and industrial sites, small-scale hydro electric power, as well as distributed generation for backup power whenever the normal source of electricity fails. In the following, the current status of DER adoption in China is assessed by grouping them into thermal (CHP) and renewable technologies. Especially, the DER systems suitable for the urban areas are focused. 2.1. Combined heat and power technologies In 2004, the total CHP capacity in China reached 56 GW and 30 GW of which was gas fired [17]. It should be recognized that CHP system is mainly based on fossil fuels but can also be based on biofuels. Therefore, CHP technologies can be also renewable. Currently, fossil fuel fired CHP system is the dominant DER technology in the urban areas of China. Table 1 shows the installed CHP systems in Shanghai, the largest city in China. It can be found that CHP systems are mainly introduced in the public buildings (e.g. hospital, airport, etc.). From a technical viewpoint, gas turbine combined with a waste heat boiler is the most popular selection. In
Table 1 Currently installed CHP systems in Shanghai. Item
Site
Capacity (kW)
Technologies
1 2 3 4
Pudong International Airport Huangpu Central Hospital Minhang Central Hospital University of Shanghai for Science and Technology Shuya Liangzi Ministry of Health Jinhu Electronic Accessories Co., Ltd. Zizhu Science-based Industrial Park Shanghai Global Financial Hub Shanghai Jinqiao Sports Center
4000 1130 400 60
Gas turbine, Waste heat boiler Gas turbine, Waste heat boiler Gas engine, Waste heat boiler Micro turbine, Absorption Chiller, Waste heat boiler Diesel engine, Waste heat boiler Gas turbine Micro turbine, Absorption Chiller Gas turbine, Waste heat boiler Gas engine, Waste heat boiler
5 6 7 8 9
300 2000 60 1000 315
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addition, the small-scale micro turbine is usually adopted accompanying with the absorption chiller and waste heat boiler, to form a CCHP system. Although several systems have been installed as shown in the table, according to a previous investigation [18], some of these plants have been out of operation due to the weak economic performance. By analyzing the local conditions as well as investigating the design and operation processes, the barriers against the introduction of CHP system in Chinese urban areas can be concluded as follows: 1. relatively low electricity tariff rate compared with the fuel prices (e.g. natural gas); 2. insufficient promotion policies; 3. high initial cost; 4. lack of a decision support system for rational plan and management. 2.2. Renewable energy technologies By the year 2007, China’s total renewable energy use reached 194 Mtce, accounting for 7.3% of total primary energy consumption [1]. Among the various types of renewable resources, hydropower and wind power play the main role [19,20]. However, most of those are large plants which would not usually be considered as distributed generation. As another important type of renewable resources, solar energy, which is abundant in China, is expected to play more and more important role. However, the main form of solar energy use in China is the supply of hot water to urban and rural residents, which cannot be considered as distributed generation [21]. Fig. 1 illustrates annual and cumulative installation capacity of PV system in China since 1990. It can be found that the PV application has been developed at a relatively steady but low speed, which is about 17% annually. By the year 2008, the total PV capacity in China was about 125 MW, which was far below some pioneering countries, such as Spain, Germany, and Japan. Among all the applications, about 43% was for remote areas power supply, 40% for communication and industrial applications. Distributed building integrated PV (BIPV) system, which takes up the dominant share in the PV market of developed countries, is rarely employed. Currently, it is mainly adopted in some demonstration buildings [22,23]. Biomass is another key renewable energy source expected to play an important role in Chinese energy supply. In 2005, it contributed about 11% of the primary energy supply. However, most of which were traditional biomass for cooking and space heating in rural households, and was not taken into consideration by the renewable energy statistics. As a modern measure of biomass application, the capacity of biomass power generation was about 2000 MW in 2005. Most of those were fired by agricultural and forestry wastes [24]. However, the increasing biomass resources in the urban area are paid little attention.
150 Annual installation
3. Methodology 3.1. Modeling of urban distributed energy system In the urban area, based on the natural gas CHP plants, a DER system can be realized by integrating PV cells and biomass power generations, as well as other subsidiary equipments. Based on the concept of local production for local consumption of biomass resources, while considering the local characteristics in the urban area, the urban biomass is usually considered to be collected and gasified into biogas, which can be used as the fuel for a CHP plant. Fig. 2 shows the image of the proposed DER system for urban areas in China. The DER generations cover all or part of the local electricity requirements, the deficiency is served by the utility grid. Furthermore, according to the current electric power standard, electricity buy-back is not permitted even if on-site generation is over the electricity load. As to the thermal load, the recovered heat from CHP plants is used for heating and hot water requirements. The deficiency is supplied by the natural gas fired backup boiler. In addition, the absorption chiller is employed to serve the cooling load. It should be indicated that solar thermal is not considered here, although it has been widely applied in Chinese urban area. This is because the focus of this study is to examine the feasibility of introducing distributed energy resources, which are recognized as the supply side activities. However, as one of the most important energy conservation measures, solar thermal is always recognized as a demand side activity and does not belong to the scope of DER.
3.2. Description of the analytical model Based on the super structure illustrated above, a mathematical model is developed for estimating an economically efficient installation and operation pattern for the distributed energy system in Chinese urban areas. Although environmental issues are paid more and more attention, economics are still the most important key while introducing DER systems. Therefore, the model minimizes total system cost of meeting predefined energy demands including electricity, cooling, space heating and water heating within a geographical area over a given planning horizon. It includes alternative supply infrastructures for multiple energy carriers: electricity, natural gas, biomass and solar energy. The competition between different energy types is implicitly handled by the algorithm. Fig. 3 shows the flow chart of the analytical model. The input data for the model inputs include: hourly electric and heating demand profiles for a full year; equipment costs and specifications; and economic and policy information. Based on the inputted local features, the analytical model is executed while considering the balance between supply and demand of energy resources, equipment availability, as well as supply share and costs. The results obtained from this process are the optimal combination of on-site
Cumulative installation Primary energy
PV capacity (MW)
Utility Grid 100
Distributed Generation
Biogas
CHP Recovered heat
Natural gas
50
Electricity
System connecting
Electricity
Thermal exchanger
CHP
Hot water Boiler
PV
Thermal exchanger
Heating 0 1990
1992
1994
1996
1998
2000
2002
2004
2006
Fig. 1. Annual and cumulative capacity of PV installation in China.
2008
Absorption chiller Fig. 2. Super structure of the DER system in the urban area.
Cooling
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described in Eq. (6). It illustrates that energy demand of a consumer at a period can be satisfied with on-site generation, via direct purchase or a combination of both.
Qload ðm; d; h; uÞ ¼ Qegen ðm; d; h; uÞ þ Qepur ðm; d; h; uÞ X hj;u $Qfpur ðj; m; d; h; uÞ þ j
þ
X
gi;u $Qrec ði; m; d; h; uÞ
cm; d; h; u
i
(6) Fig. 3. Flow chart of the analytical model for DER introduction.
generation and heat recovery, an elementary operating schedule of how the equipments should be used, and summary result for each scenario, such as total electricity bill, CO2 emissions, power generation and purchase in each hour, etc.
Another key performance constraint is that the power generated in any instant may not exceed the rated capacity of the generator, as shown in Eq. (7).
X
Qegen ði; m; d; h; uÞ Rcap ðiÞ
ci; m; d; h
(7)
u
4. Illustrative example 3.3. Objective function and main constraints While promoting the introduction of distributed energy system, the relatively high cost is one of the main barriers. Therefore, the objective function is set from the economic viewpoint by minimizing total annual system cost, as shown in Eq. (1). In this study, the following costs are taken into account: the investment cost for the distributed generators, the operation and management (O&M) cost, the cost for electricity purchase, and the cost for fuel purchase.
Min Ctotal ¼ Cinv þ Com þ Celec þ Cfuel
(1)
The annual capital cost is described in Eq. (2). It indicates the annual amount equivalent to present investment and is calculated over the estimated lifetime of the corresponding equipments.
Cinv ¼
X
Rcap ðiÞ$Pequ ðiÞ$Afac ðiÞ
(2)
i
The O&M cost is composed of fixed and variable ones, as illustrated in Eq. (3). The fixed O&M cost is calculated with the installed system capacity multiplied by a unit cost coefficient, and the variable one is considered as a function of the cumulative power generation during the calculation period.
Com ¼
X i
Rcap ðiÞ$Pomf ðiÞ þ
X
XXXX i
m
d
In this study, in order to analyze the optimal adoption of DER system in urban areas of China, a model area in Shanghai is selected for case study. It is the economic, political and cultural center of the city, with a total area of 30 km2 and a population of about 100,000. The civilian facilities are mainly composed of residence, office, hospital, hotel and commercial buildings. Among which, residence has the largest floor area, followed by the commercial and office buildings. 4.1. Energy demands Local energy demands are of vital importance to the economic, energetic and environmental performances, in other words, the potential of DER adoption. In this study, the collection of energy data including electricity, cooling, heating and hot water loads is also necessary. Currently, the building energy intensity data is not yet well developed in China. Therefore, in this study, based on the energy consumption intensity data for various buildings in Japan [25,26], by using a temperature correlation coefficient, the energy demands in the model area are presumed. Detailed calculation methods are presented in Appendix. Figs. 4 and 5 illustrate the monthly and hourly load requirements for various load types, respectively. According to the figures, the following conclusions can be deduced.
h
Qegen ði; m; d; h; uÞ$Pomv ðiÞ
1. The electricity load shows little variation throughout the whole year, and has a mean value over 90 million kW. The peak demand occurs in July, which is about 116 million kW.
(3)
u
The cost for electricity purchase is described by Eq. (4). It is calculated with cumulative amount of electricity purchase multiplied by the utility tariff rate. A flat tariff rate is assumed based on the current situation in China.
X X X X
Qepur ðm; d; h; uÞ$Pelec
m
d
h
(4)
u
The cost for fuel consumption is calculated with cumulative fuel consumption multiplied by the fuel price, as shown in Eq. (5).
Cfuel ¼
i X X X X Xh Qfpur ðj; m; d; h; uÞ$Pfuel ðjÞ j
m
d
h
(5)
Electricity Cooling load Load ( Million kW )
Celec ¼
160 Heating load Hot water
120
80
40
u
The main constraints to be included are the balance between supply and demand of energy resources, as well as the performance limitation of each kind of equipment, as shown in follows. The energy balance constrains that the outflow must equal the sum of the inflows multiplied by their individual efficiencies, as
0 1
2
3
4
5
6 7 Month
8
9
10
Fig. 4. Monthly cumulative energy loads in the model area.
11
12
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1.0
Spring
Summer
Autumn
Winter
2
Irradiation (kW/m )
0.8
0.6
0.4
0.2
0.0 1
Fig. 5. Hourly mean energy loads in the model area (summer and winter).
2. Comparing with the electricity load, monthly cooling load illustrates remarkable fluctuation throughout the whole year. During the midsummer period, the cooling load exceeds the electricity load, and peaks at 150 million kW. 3. The maximum heating load happens in January, which is about 122 million kW. Because of the hot weather in the local area, the heating load is not necessary in summer. 4. The requirement of hot water is smooth around the whole year. Generally, the consumption in summer is relatively smaller than in other seasons. 5. The cooling and heating loads make up the majority of thermal requirements, hot water load is relatively small. Furthermore, the fluctuation of cooling and heating loads seems to be more obvious than that of the electricity load. 6. The peak periods of thermal and electricity loads always happen at different hours. In summer, the peak hours for thermal and electricity loads are 16:00 and 15:00 respectively; in winter, the hours are 9:00 and 17:00, respectively.
4.2. Local energy reserves The biomass resources in the urban area are mainly composed of the park pruning branch, municipal solid waste, and the sewage sludge. Table 2 shows the utilizable energy of each resource. As the most important determinative factor of PV generation, Fig. 6 shows the mean hourly irradiation data in various seasons. Total annual irradiation is about 1300 kWh/m2 [31]. 4.3. Market information According to the investigation from local utility companies, the tariff database can be developed. Currently, the electricity tariff rate is about 7.8 Yen/kWh, and the natural gas price is about 30 Yen/m3 [32,33]. The biogas price may illustrate large fluctuation according to various biomass resources, collection difficulty, and gasification methods. In Japan, in order to promote the utilization of biomass energy, some large gas companies have issued the ‘Biogas purchase contact’, which sets the biogas price at the same level of the natural gas price [34]. However, in China, a special tariff rate for biogas has not yet been determined. In this study, accounting for future Table 2 Utilizable energy from various biomass resources [27e30]. Item
Generation intensity Utilizable Thermal Energy rate (%) unit (MJ/kg) (PJ)
Park pruning branch 1.7 t/ha Municipal solid waste 1.1 kg/person/day Sewage sludge 0.8 kg/person/day
71% 30% 70%
19.8 17.1 12.7
7.3 224.7 259.6
3
5
7
9
11 13 15 Hour in a day
17
19
21
23
Fig. 6. Hourly mean irradiation data in different seasons.
uncertainties in policy and cost conditions, a relatively high price of 35 Yen/m3 is assumed. 4.4. Technical information According to previous research and investigation from the manufactures, the technical and cost information of DER technologies is determined. It includes capital cost, maintenance costs (fixed and variable), lifetime, fuel type and efficiencies (electricity and heat), etc. Table 3 shows the characteristics of various technologies examined in this study. 4.5. Scenario setting The main targets of this study may be summarized as the following two aspects: firstly, to understand the economically optimal distributed energy system while minimizing total annual costs; secondly, to examine to what extent the local natural resources can contribute to the CO2 emissions and corresponding economic performances. Based on these considerations, the following five scenarios are assumed for analysis. Scenario 1 Conventional system. It is the base scenario which indicates the conventional energy supply system. The electricity load is served by utility grid and thermal (both heating and cooling) loads by natural gas boiler combined with an absorption chiller. Scenario 2 Optimal system. The system combination is optimized by using the analytical model. All distributed generators can be introduced freely without specific appointment. Scenario 3 PV system. The local solar energy is assumed to be fully utilized by installing BIPV systems on all building roofs. In other words, the Table 3 Technical and cost information of various DER technologies [35e39]. Item
PV
CGS
Life time (Year) Investment (104 Yen/kW) Subsidies (104 Yen/kW) Maintenance cost Fixed (104 Yen/kW) Variable (104 Yen/kW)
20 60 28 0.23 0
15 30 e 0.26 1
15 70 e 1.82 1.18
Fuel type Efficiency
Solar 14 e
Natural gas 28 48
Biogas 32 52
Electricity (%) Heat (%)
H. Ren et al. / Applied Thermal Engineering 30 (2010) 2584e2593
capacity of PV system is set a constant value, while the sizes of other technologies are determined according to the calculation of the analytical model.
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Scenario 5 Renewable system. The local renewable resources (solar and biomass energies) are assumed to be fully utilized by introducing both PV and biomass CHP systems. In this scenario, only the capacity of natural gas CHP plant is optimized by the analytical model.
following, taking electricity supply as an example, the optimal running schedules of various scenarios are analyzed. As shown in Fig. 7, generally, for all scenarios, DER equipments only supply a relatively small share of total electricity demands. For example, in scenario 2, the natural gas CHP plant operates at rated capacity from 8:00 to 24:00 in summer; and from 6:00 to 24:00 in winter. This is because of relatively low thermal load in the night (see Fig. 5). Even the CHP plant is operated at partial load, the recovered heat can serve all the thermal demands. It means that the optimal operation is heat following operation in nature. In scenario 3 (PV system), besides the natural gas CHP plant, the PV cells serve a little part of the electricity load in the day time. As to scenario 4 (Biomass system), the biomass CHP plant is adopted and operated at rated capacity throughout the whole year. For scenario 5 (Renewable system), the operation of CHP plants is similar to scenario 4, and the performance of PV cells is similar to scenario 3.
5. Results and discussions
5.3. Electricity load composition and fossil fuel consumption
5.1. Optimal adoption results
Annual electricity consumption in the model area is about 1.3 billion kWh. Fig. 8 shows the share of electricity supply for various scenarios. According to the figure, 81 MW PV cells supply about 8.1% of total electricity load. On the other hand, even if the local biomass resources are fully utilized, it takes up only 10.8% of the total demand. For the optimal system, the power from DER technologies serves about 14.7% of the electrical requirements, the deficiency is supplied by the utility grid. The renewable system has the largest power supply share from DER technologies, which is about 24.2%. Fig. 9 illustrates the fossil fuel consumption for various scenarios. As is expected that the renewable system (scenario 5) has the least fossil fuel consumption, which is about 19.2% less than the conventional system. The reduction ratios of scenario 2, scenario 3 and scenario 4 are 5.3%, 11.1% and 13.4%, respectively.
Scenario 4 Biomass system. In this scenario, based on a pre-assumed biomass CHP plant, the capacities of PV and natural gas CHP systems are selected by executing the analytical model. The biomass resources as illustrated in Table 2, are assumed to be exhausted.
Table 4 shows the simulation results of various scenarios by executing the analytical model. The total introduction capacities of scenarios 2e5 are 25.0 MW, 106.0 MW, 24.1 MW and 105.1 MW, respectively. In the optimal system (scenario 2), only 25 MW natural gas CHP plants are introduced; as to the PV system (scenario 3), 81 MW PV cells are added. The biomass system (scenario 4) has the smallest capacity, which is composed of a 8.5 MW natural gas CHP plant and a 15.6 MW biomass CHP plant. As to the renewable system (scenario 5), although all assumed technologies are introduced, the total capacity is smaller than the PV system. From the viewpoint of annual energy cost due to fuel and power consumptions, compared with the conventional system (scenario 1), the introduction of DER system (scenarios 2e5) leads to more or less reduction. However, because of the relatively high investment cost of the DER equipments, scenario 5 which introduces all DER technologies has the largest total annual cost. The optimal system (scenario 2) is recognized as the economically optimal alternative with the least total cost. Generally, from the economic point of view, it is reasonable that natural gas CHP plant is the dominant DER technology in China. However, in order to realize a wide penetration, the increase of customer merits through the reduction of investment and running costs is necessary. The renewable technologies, such as PV, biomass, etc., seem to be very hard to be diffused without radical policies.
5.4. Cost-effectiveness of CO2 emissions reduction The reduction of CO2 emissions is one of the most important incentives to the adoption of DER systems. In this study, considering the carbon neutral characteristic, CO2 emissions of biomass CHP system is recognized to be zero. Fig. 10 shows annual CO2 emissions and corresponding reduction cost (compared with the conventional system) for various scenarios. As to the total emissions, for all scenarios, the dominant emission source is grid power, followed by natural gas for non-DER use. In addition, compared with the conventional system, the reduction ratios of scenarios 2e5 are 8.6%, 15.5%, 14.1% and 20.9%, respectively. As is expected, the CO2 emissions of the renewable system is the lowest among all assumed scenarios. On the other hand, looking into the reduction cost of CO2 emissions, it can be found except the optimal system (scenario 2),
5.2. Optimal supply characteristics Besides the equipment combination, the operation strategies also have great effects on the economics of the DER system. In the
Table 4 Optimal adoption results and corresponding economic performances of various scenarios. System combinationa
Scenario
Scenario Scenario Scenario Scenario Scenario a
1 2 3 4 5
e a:25.0 MW a:25.0MW b:81.0 MW a:8.5 MW c:15.6 MW a:8.5 MWb:81.0 MW c:15.6 MW
a: Natural gas CHP; b: PV; c: Biomass CHP.
Annual cost (108 Yen) Annual capital
O&M
Grid electricity
Natural gas Power
Heat
0.0 0.4 2.0 0.6 2.2
0.0 0.3 0.4 0.5 0.7
9.8 8.3 7.5 8.3 7.4
0.0 1.6 1.6 0.5 0.5
5.5 4.6 4.6 4.5 4.5
Biogas
Total cost
0.0 0.0 0.0 1.5 1.5
15.3 15.2 16.1 15.9 16.8
Reduction rate of total cost (%)
e 0.7 5.2 3.9 9.8
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Fig. 7. Hourly electricity supply characteristics (summer and winter).
all other systems introducing DER technologies (scenarios 3e5) have relatively large reduction cost, which is higher than 3 Yen/kgCO2. The renewable system has the largest reduction cost, which is about 5 Yen/kg-CO2. Therefore, it can be deduced that the high environmental merits are at the cost of weak economic performance. From the viewpoint of cost efficiency, scenario 2 can be recognized as the best selection. 5.5. Sensitivity analysis
environmental performance but marginal economic benefit, in Chinese urban areas. However, the economics are considered to play a main role in the decision making of DER adoption. Therefore, in this section, aiming at improving the economic performance of the DER system, sensitivity analyses of some key influence factors are executed. In addition, considering the uncertainty of local energy demands due to the approximate calculation illustrated in Appendix section, a sensitivity analysis on energy demands is also included. In the following, by taking annual cost reduction ratio as an exogenous variable, the effects of electricity buy-back price and biogas price, as
According to the above analysis, currently, the introduction of DER system especially some renewable technologies result in good
Fig. 8. Annual electricity load shares for various scenarios.
Fig. 9. Annual fossil fuel consumptions for various scenarios.
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Reduction ratio of total annual cost (%)
6 Scenario 2
Scenario 3
Scenario 4
Scenario 5
3 0 -3 -6 -9 -12 -15 10
18
26 34 3 Biogas price (Yen/m )
42
50
Fig. 10. Annual CO2 emissions and corresponding reduction costs for various scenarios. Fig. 12. Economic influence of biogas price.
well as the variation of energy demands on the economic adoption of DER system are analyzed.
system from on-site use to selling back to the grid, due to the increased buy-back price.
5.5.1. Sensitivity of electricity buy-back price As one of the promotion policies to stimulate DER penetration, electricity buy-back has been introduced in a lot of countries. In Japan, the buy-back price for electricity out of PV system is about 24 Yen/kWh (the level of electricity tariff rate), which may be doubled in the new future. On the other hand, although electricity buy-back from DER system is not permitted in China according to current electric power standard, as the continuing global warming, it is considered to be a necessary policy to promote the introduction of renewable energies (e.g. PV, biomass energy, etc.). In the following, while assuming the feasibility of selling electricity out of PV system back into the grid, the influence of the buy-back price on the economic performance of DER system is assessed. According to the results shown in Fig. 11, the rise of buy-back price leads to more or less increase of annual cost reduction ratio for all scenarios. As to scenarios 2 and 4, in which PV capacity is not specified, the variation of buy-back price has no influence on annual cost unless it is increased above 16 Yen/kWh (the level of power generation cost of PV system). As the buy-back price exceeds this critical point, the PV system illustrates its economic benefits and is introduced gradually. On the other hand, in scenarios 3 and 5, a specific PV capacity (determined according the roof area of local buildings) is assumed, when the buy-back price increases above 8 Yen/kWh (the level of electricity tariff rate in the local area), the cost reduction ratios start to increase in a linear way. This is because of the transformation of electricity out of PV
5.5.2. Sensitivity of biogas price Fig. 12 shows the influence of biogas price on the economics of DER systems. According to the discussion illustrated in Section 4, the biogas price is assumed to be 35 Yen/m3 in this study. In the future, on the one hand, as the development of gasification technology and the introduction of inverse onerous contract, the biogas price is expected to be reduced gradually; on the other hand, along with the rising price in the global energy market, the biogas may also illustrate a rising tendency. Therefore, in the following, the sensitive analysis is executed for both increased and reduced biogas prices. From Fig. 12, the decrease of biogas price results in increased cost reduction ratios for scenarios 4 and 5. However, as to scenarios 2 and 3, unless the biogas price is reduced below 18 Yen/m3, annual energy cost stands at the same value as the change of biogas price. This is because when biogas price is relatively high, the biomass CHP system is not introduced from the economic viewpoint. In other words, the critical price of biogas to illustrate economic merit is 18 Yen/m3. 5.5.3. Sensitivity of local energy demands As is discussed above, due to the absence of detailed building information, an energy intensity method has been employed to calculate the local energy demands. It may result in more or less uncertainty although it has even been proved to have considerable precision [41]. In the following, local energy demands are endued
6 Scenario 2
Scenario 3
Scenario 4
Scenario 5
Reduction ratio of total annual cost (%)
Reduction ratio of total annual cost (%)
6 3 0 -3 -6 -9 -12 -15
Scenario 2
4
8 12 Electricity buy-back price (Yen/kWh)
16
Fig. 11. Economic influence of electricity buy-back price.
20
Scenario 4
Scenario 5
0
-6
-12
-18
-24 0
Scenario 3
-50
-30
-10
10
30
Increment ratio of energy demands (%) Fig. 13. Economic influence of the variation of energy demands.
50
2592
H. Ren et al. / Applied Thermal Engineering 30 (2010) 2584e2593
a variation between 50% and 150% of current value, and the influence on the reduction ratio of total annual cost is shown in Fig. 13. From this figure, it is interesting to notice that the economics of scenario 1 (optimal system) illustrates no obvious relationship with the variation of energy demands. In other words, total annual cost of scenario 1 becomes larger linearly with the local energy demands. Looking into the optimal results of parameter analysis, it is because the variation of energy demands results in the change of natural gas CHP capacity with the same scale. Correspondingly, all the components in Eq. (1) and finally the total annual cost show a linear variation. Furthermore, as to scenarios 3e5 which introduce definite capacity of renewable energy resources, the reduction ratios of total annual cost rise as the increase of local energy demands. Especially, as the energy demands are reduced to half of current value, the economic performance of scenario 5 (renewable system) is fairly unsatisfying, which has an increased total annual cost by about 22%. However, it should be indicated that actual energy demands in the local area may be lower than the calculation value. This is due to: on the one hand, electricity consumption intensity in Shanghai may be smaller than that of Tokyo because of lower life level; on the other hand, Tokyo may also have larger heat consumption intensity because of the difference in life styles. Therefore, introducing distributed renewable resources in Chinese urban area may result in much worse economic performance, which validates the importance of adopting some policies (e.g. electricity buy-back) which have been analyzed above.
5. The variation of energy demands has no influence on the economic performance of the optimal system which introduces natural gas CHP plants only. On the other hand, introducing distributed renewable energy resources may lead to worse economic performance due to possible lower energy demands. In the following study, an integrated energy system optimization model should be developed to support the decision making for the sustainable use of energy in the local area while covering both the energy supply and demand sides, and provide feasible generation settlements between utility grid, distributed generations, as well as optimal diffusion of energy efficiency measures (e.g. solar heater, etc.). In addition, in order to cope with the uncertainties of some techno-economic parameters which may illustrate great fluctuation from a long-term viewpoint, a long-term energy system optimization model is also necessary to be formed so as to provide beneficial recommendations for the establishment of long-term energy and environmental policies.
Acknowledgements This research has been supported by Global Environment Research Fund by the Ministry of the Environment Japan (E-0804), as well as Kansai Research Foundation for Technology Promotion and Yazaki Memorial Foundation for Science and Technology. Acknowledgement is also due to two anonymous reviewers who provided us with helpful comments.
6. Conclusions and perspectives In this study, in order to realize a low-carbon city, the DER system is proposed for the urban areas in China. By investigating necessary technical and financial information, as well as local energy demands, an analytical model is developed to determine the optimal system combination and operation pattern of the DER system. Using the model, taking a model area in Shanghai as a case study, the optimal DER systems are analyzed for five scenarios. According to the simulation results, the following conclusions can be deduced. 1. Currently, although the introduction of DER system in Chinese urban area leads to reasonable environmental merit, the economic benefit is marginal. Because of the high capital cost, the feasible technologies are some mature ones, such as natural gas CHP plant with a relatively low cost reduction ratio of about 0.7%. 2. Because of the limit resource reservation in the urban area, even if total renewable resources are fully utilized, the on-site power generation only takes up 24% of the total requirements. 3. The introduction of all assumed DER technologies results in reduced CO2 emissions. However, from the cost-effective viewpoint, natural gas CHP system is currently the best selection. The CO2 emissions reduction costs of the renewable energies (e.g. PV, biomass) are always at a relatively high level which is above 3 Yen/kg-CO2. 4. In order to improve the economic performance of the DER system, according to the results of sensitivity analyses, the introduction of electricity buy-back and the reduction of biogas price can promote the adoption of DER system positively. As the buy-back price is above 16 Yen/kWh, the PV system illustrates its economic merit and is introduced gradually. In addition, the biogas CHP system is introduced and shows good economic performance as the biogas price is below 18 Yen/m3.
Appendix This appendix presents the load correction method which is applied in this study to calculate the energy demands in a Chinese urban area. In Japan, Tokyo is the focus of building energy intensity study, for example, in the Ojima’s hourly energy unit [25] and yearly energy consumption from the Japan Cogeneration Research Cenetre [40]. Actually, Tokyo and Shanghai share similar latitudes, sunshine hours and outside temperatures (see Table A1). Therefore, energy intensity data in Shanghai can be deduced by adjusting the corresponding data in Tokyo while accounting for the differences in heating degree days (HDD) and cooling degree days (CDD) between the two cities [41]. Based on these differences, the energy intensity in Shanghai is estimated by using a temperature correlation coefficient, as shown in Fig. A1.
Energy intensity of Tokyo
Local conditions in Tokyo
Local conditions in Shanghai
Degree day correction Energy intensity of Shanghai
Area of different types of buildings in the model area
Energy demands of the model area in Shanghai Fig. A1. Flow chart of the calculation method for local energy demands.
H. Ren et al. / Applied Thermal Engineering 30 (2010) 2584e2593
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Table A1. Comparison of local conditions in Shanghai and Tokyo. Area
Latitude ( )
Annual sunshine time (hours)
Mean outside temperature ( C)
HDD (days)
CDD (days)
Shanghai Tokyo Shanghai/Tokyo
31.2 35.4 0.9
1821.0 1996.0 0.9
17.4 17.0 1.0
1691.0 1405.0 1.2
164.0 210.0 0.8
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[18] J. Xuan. Study on the introduction feasibility of CHP system in commercial building in Shanghai, Master thesis, Japan. The University of Kitakyushu; 2007. [19] Energy Information Administration, Energy Information Administration international statistics database, Washington, DC; 2009. [20] WWEA, World wind energy report 2008. World Wind Energy Association, 2009. [21] Z. Luo, China Solar Water Heater Market Report 2008, Solar Thermal Utilization Committee in China. Association of Rural Energy Industry, Beijing, 2008. [22] National Development and Reform Commission, Chinese renewable energy industry development report; 2007. [23] Tsinghua University. Present situation and prediction on photovoltaic in China. In: Proceeding of China renewable energy development strategy workshop; 2005. [24] X. Zhang, R. Wang, H. Molin, M. Eric. A study of the role played by renewable energies in China’s sustainable energy supply, Energy. doi:10.1016/ j.energy.2009.05.030. [25] Ojima lab, Consumption Unit for Electricity, Heating, Cooling and Hot Water. WasedaUniversity, 1995. [26] Nishita, The Investigation on Energy Consumption in Kyushu. Kyushu Sangyo University, 1997. [27] New Energy and Industrial Technology Development Organization (NEDO), Biomass energy introduction support database available at: http://app2.infoc. nedo.go.jp/biomass-db/. [28] About the Municipal solid waste available at: http://www.excite.co.jp/News/ china/20090321/Searchina_20090321001.html. [29] S. Adachi. Research on the composting of sewage sludge in waste water treatment system, Ph.D. thesis. Okayama University; 2006. [30] Shanghai Statistics Bureau, Statistical Yearbook of Shanghai 2008. Shanghai Statistics Press, Shanghai, 2008. [31] Shanghai Weather Bureau available at: http://www.soweather.com/pubweb/. [32] Shanghai Electric Power Co., Ltd available at: http://www.shanghaipower. com/. [33] Shanghai Gas Co., Ltd available at: http://www.shgas.com.cn/main.asp#. [34] Osaka Gas Co., Ltd available at: http://www.osakagas.co.jp/company/press/pr_ 2008/080328.html. [35] Sharp Corporation available at: http://www.sharp.co.jp/. [36] The subsidies policy for PV introduction in China available at: http://www. gov.cn/zwgk/2009-03/26/content_1269258.htm. [37] Y. Ruan, Q. Liu, W. Zhou, R. Firestone, W. Gao, T. Watanabe, Optimal option of distributed generation technologies for various commercial buildings, Applied Energy 86 (9) (2009) 1641e1653. [38] Yanmar Co., Ltd available at: http://www.yanmar.co.jp/. [39] New Energy and Industrial Technology Development Organization (NEDO) available at: http://www.nedo.go.jp/nedata/index.html. [40] T. Kashiwagi, Natural Gas Cogeneration Plan/Design Manual 2002. Japan Industrial Publishing Co., Ltd, 2002. [41] X. Wei, Research on network of district heating and cooling system, Ph.D. thesis, Tokyo: Waseda University, 2003.
Contents lists available at ScienceDirect
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Feasibility assessment of introducing distributed energy resources in urban areas of China Hongbo Ren a, *, Weisheng Zhou b, Ken’ichi Nakagami b, Weijun Gao c, Qiong Wu c a
Ritsumeikan Global Innovation Research Organization, Ritsumeikan University, 603-8577 Kyoto, Japan College of Policy Sciences, Ritsumeikan University, 603-8577 Kyoto, Japan c Faculty of Environmental Engineering, The University of Kitakyushu, 808-0135 Kitakyushu, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 10 February 2010 Accepted 12 July 2010 Available online 15 July 2010
In this study, based on the consideration of achieving a low-carbon city, a distributed energy system is promoted by integrating combined heat and power (CHP) plant, biomass energy and photovoltaic technology, for the urban areas in China. An analytical model has been developed for estimating an economically efficient installation and operation pattern for the distributed energy system. As an illustrative example, a numerical study is conducted of feasible distributed energy system for a model area in Shanghai, while considering five scenarios with different technology combinations. According to the simulation results, although enjoying reasonable environmental merits, it is hard to diffuse the distributed generation technologies, especially some renewable ones, in the model area from the economic point of view. Currently, the most feasible technology is the natural gas CHP system, which has a cost reduction ratio of only 0.7%. In addition, the sensitivity analyses illustrate that the introduction of electricity buy-back and the reduction of biogas price can promote the adoption of some renewable technologies to some extent. Ó 2010 Elsevier Ltd. All rights reserved.
Keywords: Feasibility assessment Distributed energy resources Analytical model Urban area China
1. Introduction Due to long-term economic development, energy consumption in China has been increasing for decades. The growth has obviously speeded up in the new century, from 1386 million tons of standard of coal equivalent (Mtce) in 2000 to 2850 Mtce in 2008 [1]. This rising demand has turned China from a net energy exporter to a net energy importer. On the other hand, Chinese CO2 emissions in 2008 was 6.9 billion metric tons of carbon, which accounted for about 22% of global CO2 emissions, overtaking the United States and becoming the dominant country in the global warming debate. In addition, as the largest developing country in the world, the Chinese government took its responsibility positively and announced to reduce the intensity of CO2 emissions per unit of GDP in 2020 by 40e45 percent compared with the level of 2005. In order to achieve such a dramatic goal and realize a sustainable lowcarbon society, various innovative measures have been and will be executed in China. In natural, China’s energy issues are mainly rooted in its ongoing industrialization, modernization and urbanization [2]. According to the calculation made by Dhakal [3], the * Corresponding author. Tel.: þ81 075 466 3348; fax: þ81 075 465 8245. E-mail address: [email protected] (H. Ren). 1359-4311/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.applthermaleng.2010.07.009
urban contribution to China’s total commercial energy uses was about 84% in the year 2006. Correspondingly, the urban area is always recognized as the most important location for energy conservation. In the past few years, along with the rapid urbanization, the energy conservation in the civilian sector, which reflects the improvement of living standard, plays an important role in the sustainable development of the city. Especially, in the Yangtze River Delta area, which has relatively large economic scale and population size, as well as enough attention to the environmental protection, more and more attention is paid to the reformation of urban energy system. Furthermore, the recent sudden rise of oil price also encourages the introduction of energy conservation and advanced energy systems. The distributed energy resource (DER), including combined heat and power (CHP), photovoltaic (PV), wind turbine and biomass energy, etc., is one of the most dominant options and is expected to be widely introduced. About the adoption of DER system in China, Fu et al. [4] introduced the performance tests of several combined cooling, heating and power (CCHP) systems in combination with thermally-activated (TA) technologies. Hao et al. [5] analyzed the sustainable characteristics of building CHP technology and studied its prospects in China. Okada et al. [6] examined the energetic and environmental
H. Ren et al. / Applied Thermal Engineering 30 (2010) 2584e2593
Nomenclature Afac Celec Cfuel Cinv Com Ctotal d h i j m Pelec Pequ
annuity factor of the capital cost of distributed generators, % cost for grid electricity purchase, Yen cost for fuel consumption, Yen annualized investment cost, Yen operation and management cost, Yen total annual cost, Yen day in a month hour in a day index of DER technologies index of fuel types month in a year electricity tariff rate, Yen/kWh capital cost of the distributed generators, Yen/kW
effects with the adoption of CHP system in Guangzhou, China. Aki and Murata [7] analyzed the technology, economy and policy related issues for introducing natural gas CHP system in the urban areas of China. Kosugi et al. [8] examined the method of improving the economic performance of CHP system in China by making use of the Clean Development Mechanism (CDM) and Energy service company (ESCO) frameworks. Xuan et al. [9] assessed the introduction feasibility of CHP system for the skyscraper complex in China. Liu et al. [10] analyzed the performance of a combined CHP and liquid-desiccant system in a demonstration building located in Beijing, China. It could be found that all of the above studies focused on the natural gas CHP system. Other DER technologies, for example, PV and biomass which are considered to be feasible options for future energy supply in the urban area, are never taken into consideration. In addition, the influence of some key economic and policy factors on the introduction of DER system is uncertain. In a previous study [11], from the viewpoints of design and evaluation of the DER system, by integrating the technical and financial information, as well as energy demands, a customer aided optimization model has been developed for the introduction of economically optimal DER systems in Japan. Using the developed model, the optimal adoption and operation strategies of CHP, PV and biomass energy systems for residential buildings in Japan have been examined [12e14]. However, with different local conditions (e.g. climate, energy demands, etc.) and market mechanisms (e.g. tariff structures, etc.), a design and evaluation tool for the introduction of DER systems in China is necessary. The First section of this paper introduces the background of Chinese energy consumption and corresponding local and global environmental issues. The Second section reviews the current status of DER adoption in China, especially in the urban areas. The Third section presents a framework of the urban DER system along
Pfuel Pomf Pomv Qegen Qepur Qfpur Qload Qrec Rcap u
2585
fuel price, Yen/kWh fixed operation and maintenance cost, Yen/kW variable operation and maintenance cost, Yen/kWh on-site power generation, kW amount of electricity purchase from the utility, kW amount of fuel consumption, kW customer load, kW amount of recovered heat, kW rated capacity of the distributed generators, kW end uses, including electricity, cooling, heating and hot water
Greek symbols h efficiency of direct fuel combustion, % g efficiency of recovered heat utilization, %
with an analytical model, which can aid the decision making while introducing DER system in the urban areas of China. In the Fourth section, the foundational information of the studied case is introduced. Some major findings of the case study are presented in Section five. Finally, Section six draws a conclusion for the study. 2. Current status of DER adoption in China By the end of 2004, distributed generation took up about 15.1% in Chinese total power generation, which implied significant potential before reaching the market penetration in leading countries such as Denmark, the Netherlands and Finland [15,16]. In China, the predominant forms of DER are coal fired steam CHP systems to provide heat to municipal district heating systems and industrial sites, small-scale hydro electric power, as well as distributed generation for backup power whenever the normal source of electricity fails. In the following, the current status of DER adoption in China is assessed by grouping them into thermal (CHP) and renewable technologies. Especially, the DER systems suitable for the urban areas are focused. 2.1. Combined heat and power technologies In 2004, the total CHP capacity in China reached 56 GW and 30 GW of which was gas fired [17]. It should be recognized that CHP system is mainly based on fossil fuels but can also be based on biofuels. Therefore, CHP technologies can be also renewable. Currently, fossil fuel fired CHP system is the dominant DER technology in the urban areas of China. Table 1 shows the installed CHP systems in Shanghai, the largest city in China. It can be found that CHP systems are mainly introduced in the public buildings (e.g. hospital, airport, etc.). From a technical viewpoint, gas turbine combined with a waste heat boiler is the most popular selection. In
Table 1 Currently installed CHP systems in Shanghai. Item
Site
Capacity (kW)
Technologies
1 2 3 4
Pudong International Airport Huangpu Central Hospital Minhang Central Hospital University of Shanghai for Science and Technology Shuya Liangzi Ministry of Health Jinhu Electronic Accessories Co., Ltd. Zizhu Science-based Industrial Park Shanghai Global Financial Hub Shanghai Jinqiao Sports Center
4000 1130 400 60
Gas turbine, Waste heat boiler Gas turbine, Waste heat boiler Gas engine, Waste heat boiler Micro turbine, Absorption Chiller, Waste heat boiler Diesel engine, Waste heat boiler Gas turbine Micro turbine, Absorption Chiller Gas turbine, Waste heat boiler Gas engine, Waste heat boiler
5 6 7 8 9
300 2000 60 1000 315
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addition, the small-scale micro turbine is usually adopted accompanying with the absorption chiller and waste heat boiler, to form a CCHP system. Although several systems have been installed as shown in the table, according to a previous investigation [18], some of these plants have been out of operation due to the weak economic performance. By analyzing the local conditions as well as investigating the design and operation processes, the barriers against the introduction of CHP system in Chinese urban areas can be concluded as follows: 1. relatively low electricity tariff rate compared with the fuel prices (e.g. natural gas); 2. insufficient promotion policies; 3. high initial cost; 4. lack of a decision support system for rational plan and management. 2.2. Renewable energy technologies By the year 2007, China’s total renewable energy use reached 194 Mtce, accounting for 7.3% of total primary energy consumption [1]. Among the various types of renewable resources, hydropower and wind power play the main role [19,20]. However, most of those are large plants which would not usually be considered as distributed generation. As another important type of renewable resources, solar energy, which is abundant in China, is expected to play more and more important role. However, the main form of solar energy use in China is the supply of hot water to urban and rural residents, which cannot be considered as distributed generation [21]. Fig. 1 illustrates annual and cumulative installation capacity of PV system in China since 1990. It can be found that the PV application has been developed at a relatively steady but low speed, which is about 17% annually. By the year 2008, the total PV capacity in China was about 125 MW, which was far below some pioneering countries, such as Spain, Germany, and Japan. Among all the applications, about 43% was for remote areas power supply, 40% for communication and industrial applications. Distributed building integrated PV (BIPV) system, which takes up the dominant share in the PV market of developed countries, is rarely employed. Currently, it is mainly adopted in some demonstration buildings [22,23]. Biomass is another key renewable energy source expected to play an important role in Chinese energy supply. In 2005, it contributed about 11% of the primary energy supply. However, most of which were traditional biomass for cooking and space heating in rural households, and was not taken into consideration by the renewable energy statistics. As a modern measure of biomass application, the capacity of biomass power generation was about 2000 MW in 2005. Most of those were fired by agricultural and forestry wastes [24]. However, the increasing biomass resources in the urban area are paid little attention.
150 Annual installation
3. Methodology 3.1. Modeling of urban distributed energy system In the urban area, based on the natural gas CHP plants, a DER system can be realized by integrating PV cells and biomass power generations, as well as other subsidiary equipments. Based on the concept of local production for local consumption of biomass resources, while considering the local characteristics in the urban area, the urban biomass is usually considered to be collected and gasified into biogas, which can be used as the fuel for a CHP plant. Fig. 2 shows the image of the proposed DER system for urban areas in China. The DER generations cover all or part of the local electricity requirements, the deficiency is served by the utility grid. Furthermore, according to the current electric power standard, electricity buy-back is not permitted even if on-site generation is over the electricity load. As to the thermal load, the recovered heat from CHP plants is used for heating and hot water requirements. The deficiency is supplied by the natural gas fired backup boiler. In addition, the absorption chiller is employed to serve the cooling load. It should be indicated that solar thermal is not considered here, although it has been widely applied in Chinese urban area. This is because the focus of this study is to examine the feasibility of introducing distributed energy resources, which are recognized as the supply side activities. However, as one of the most important energy conservation measures, solar thermal is always recognized as a demand side activity and does not belong to the scope of DER.
3.2. Description of the analytical model Based on the super structure illustrated above, a mathematical model is developed for estimating an economically efficient installation and operation pattern for the distributed energy system in Chinese urban areas. Although environmental issues are paid more and more attention, economics are still the most important key while introducing DER systems. Therefore, the model minimizes total system cost of meeting predefined energy demands including electricity, cooling, space heating and water heating within a geographical area over a given planning horizon. It includes alternative supply infrastructures for multiple energy carriers: electricity, natural gas, biomass and solar energy. The competition between different energy types is implicitly handled by the algorithm. Fig. 3 shows the flow chart of the analytical model. The input data for the model inputs include: hourly electric and heating demand profiles for a full year; equipment costs and specifications; and economic and policy information. Based on the inputted local features, the analytical model is executed while considering the balance between supply and demand of energy resources, equipment availability, as well as supply share and costs. The results obtained from this process are the optimal combination of on-site
Cumulative installation Primary energy
PV capacity (MW)
Utility Grid 100
Distributed Generation
Biogas
CHP Recovered heat
Natural gas
50
Electricity
System connecting
Electricity
Thermal exchanger
CHP
Hot water Boiler
PV
Thermal exchanger
Heating 0 1990
1992
1994
1996
1998
2000
2002
2004
2006
Fig. 1. Annual and cumulative capacity of PV installation in China.
2008
Absorption chiller Fig. 2. Super structure of the DER system in the urban area.
Cooling
H. Ren et al. / Applied Thermal Engineering 30 (2010) 2584e2593
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described in Eq. (6). It illustrates that energy demand of a consumer at a period can be satisfied with on-site generation, via direct purchase or a combination of both.
Qload ðm; d; h; uÞ ¼ Qegen ðm; d; h; uÞ þ Qepur ðm; d; h; uÞ X hj;u $Qfpur ðj; m; d; h; uÞ þ j
þ
X
gi;u $Qrec ði; m; d; h; uÞ
cm; d; h; u
i
(6) Fig. 3. Flow chart of the analytical model for DER introduction.
generation and heat recovery, an elementary operating schedule of how the equipments should be used, and summary result for each scenario, such as total electricity bill, CO2 emissions, power generation and purchase in each hour, etc.
Another key performance constraint is that the power generated in any instant may not exceed the rated capacity of the generator, as shown in Eq. (7).
X
Qegen ði; m; d; h; uÞ Rcap ðiÞ
ci; m; d; h
(7)
u
4. Illustrative example 3.3. Objective function and main constraints While promoting the introduction of distributed energy system, the relatively high cost is one of the main barriers. Therefore, the objective function is set from the economic viewpoint by minimizing total annual system cost, as shown in Eq. (1). In this study, the following costs are taken into account: the investment cost for the distributed generators, the operation and management (O&M) cost, the cost for electricity purchase, and the cost for fuel purchase.
Min Ctotal ¼ Cinv þ Com þ Celec þ Cfuel
(1)
The annual capital cost is described in Eq. (2). It indicates the annual amount equivalent to present investment and is calculated over the estimated lifetime of the corresponding equipments.
Cinv ¼
X
Rcap ðiÞ$Pequ ðiÞ$Afac ðiÞ
(2)
i
The O&M cost is composed of fixed and variable ones, as illustrated in Eq. (3). The fixed O&M cost is calculated with the installed system capacity multiplied by a unit cost coefficient, and the variable one is considered as a function of the cumulative power generation during the calculation period.
Com ¼
X i
Rcap ðiÞ$Pomf ðiÞ þ
X
XXXX i
m
d
In this study, in order to analyze the optimal adoption of DER system in urban areas of China, a model area in Shanghai is selected for case study. It is the economic, political and cultural center of the city, with a total area of 30 km2 and a population of about 100,000. The civilian facilities are mainly composed of residence, office, hospital, hotel and commercial buildings. Among which, residence has the largest floor area, followed by the commercial and office buildings. 4.1. Energy demands Local energy demands are of vital importance to the economic, energetic and environmental performances, in other words, the potential of DER adoption. In this study, the collection of energy data including electricity, cooling, heating and hot water loads is also necessary. Currently, the building energy intensity data is not yet well developed in China. Therefore, in this study, based on the energy consumption intensity data for various buildings in Japan [25,26], by using a temperature correlation coefficient, the energy demands in the model area are presumed. Detailed calculation methods are presented in Appendix. Figs. 4 and 5 illustrate the monthly and hourly load requirements for various load types, respectively. According to the figures, the following conclusions can be deduced.
h
Qegen ði; m; d; h; uÞ$Pomv ðiÞ
1. The electricity load shows little variation throughout the whole year, and has a mean value over 90 million kW. The peak demand occurs in July, which is about 116 million kW.
(3)
u
The cost for electricity purchase is described by Eq. (4). It is calculated with cumulative amount of electricity purchase multiplied by the utility tariff rate. A flat tariff rate is assumed based on the current situation in China.
X X X X
Qepur ðm; d; h; uÞ$Pelec
m
d
h
(4)
u
The cost for fuel consumption is calculated with cumulative fuel consumption multiplied by the fuel price, as shown in Eq. (5).
Cfuel ¼
i X X X X Xh Qfpur ðj; m; d; h; uÞ$Pfuel ðjÞ j
m
d
h
(5)
Electricity Cooling load Load ( Million kW )
Celec ¼
160 Heating load Hot water
120
80
40
u
The main constraints to be included are the balance between supply and demand of energy resources, as well as the performance limitation of each kind of equipment, as shown in follows. The energy balance constrains that the outflow must equal the sum of the inflows multiplied by their individual efficiencies, as
0 1
2
3
4
5
6 7 Month
8
9
10
Fig. 4. Monthly cumulative energy loads in the model area.
11
12
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1.0
Spring
Summer
Autumn
Winter
2
Irradiation (kW/m )
0.8
0.6
0.4
0.2
0.0 1
Fig. 5. Hourly mean energy loads in the model area (summer and winter).
2. Comparing with the electricity load, monthly cooling load illustrates remarkable fluctuation throughout the whole year. During the midsummer period, the cooling load exceeds the electricity load, and peaks at 150 million kW. 3. The maximum heating load happens in January, which is about 122 million kW. Because of the hot weather in the local area, the heating load is not necessary in summer. 4. The requirement of hot water is smooth around the whole year. Generally, the consumption in summer is relatively smaller than in other seasons. 5. The cooling and heating loads make up the majority of thermal requirements, hot water load is relatively small. Furthermore, the fluctuation of cooling and heating loads seems to be more obvious than that of the electricity load. 6. The peak periods of thermal and electricity loads always happen at different hours. In summer, the peak hours for thermal and electricity loads are 16:00 and 15:00 respectively; in winter, the hours are 9:00 and 17:00, respectively.
4.2. Local energy reserves The biomass resources in the urban area are mainly composed of the park pruning branch, municipal solid waste, and the sewage sludge. Table 2 shows the utilizable energy of each resource. As the most important determinative factor of PV generation, Fig. 6 shows the mean hourly irradiation data in various seasons. Total annual irradiation is about 1300 kWh/m2 [31]. 4.3. Market information According to the investigation from local utility companies, the tariff database can be developed. Currently, the electricity tariff rate is about 7.8 Yen/kWh, and the natural gas price is about 30 Yen/m3 [32,33]. The biogas price may illustrate large fluctuation according to various biomass resources, collection difficulty, and gasification methods. In Japan, in order to promote the utilization of biomass energy, some large gas companies have issued the ‘Biogas purchase contact’, which sets the biogas price at the same level of the natural gas price [34]. However, in China, a special tariff rate for biogas has not yet been determined. In this study, accounting for future Table 2 Utilizable energy from various biomass resources [27e30]. Item
Generation intensity Utilizable Thermal Energy rate (%) unit (MJ/kg) (PJ)
Park pruning branch 1.7 t/ha Municipal solid waste 1.1 kg/person/day Sewage sludge 0.8 kg/person/day
71% 30% 70%
19.8 17.1 12.7
7.3 224.7 259.6
3
5
7
9
11 13 15 Hour in a day
17
19
21
23
Fig. 6. Hourly mean irradiation data in different seasons.
uncertainties in policy and cost conditions, a relatively high price of 35 Yen/m3 is assumed. 4.4. Technical information According to previous research and investigation from the manufactures, the technical and cost information of DER technologies is determined. It includes capital cost, maintenance costs (fixed and variable), lifetime, fuel type and efficiencies (electricity and heat), etc. Table 3 shows the characteristics of various technologies examined in this study. 4.5. Scenario setting The main targets of this study may be summarized as the following two aspects: firstly, to understand the economically optimal distributed energy system while minimizing total annual costs; secondly, to examine to what extent the local natural resources can contribute to the CO2 emissions and corresponding economic performances. Based on these considerations, the following five scenarios are assumed for analysis. Scenario 1 Conventional system. It is the base scenario which indicates the conventional energy supply system. The electricity load is served by utility grid and thermal (both heating and cooling) loads by natural gas boiler combined with an absorption chiller. Scenario 2 Optimal system. The system combination is optimized by using the analytical model. All distributed generators can be introduced freely without specific appointment. Scenario 3 PV system. The local solar energy is assumed to be fully utilized by installing BIPV systems on all building roofs. In other words, the Table 3 Technical and cost information of various DER technologies [35e39]. Item
PV
CGS
Life time (Year) Investment (104 Yen/kW) Subsidies (104 Yen/kW) Maintenance cost Fixed (104 Yen/kW) Variable (104 Yen/kW)
20 60 28 0.23 0
15 30 e 0.26 1
15 70 e 1.82 1.18
Fuel type Efficiency
Solar 14 e
Natural gas 28 48
Biogas 32 52
Electricity (%) Heat (%)
H. Ren et al. / Applied Thermal Engineering 30 (2010) 2584e2593
capacity of PV system is set a constant value, while the sizes of other technologies are determined according to the calculation of the analytical model.
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Scenario 5 Renewable system. The local renewable resources (solar and biomass energies) are assumed to be fully utilized by introducing both PV and biomass CHP systems. In this scenario, only the capacity of natural gas CHP plant is optimized by the analytical model.
following, taking electricity supply as an example, the optimal running schedules of various scenarios are analyzed. As shown in Fig. 7, generally, for all scenarios, DER equipments only supply a relatively small share of total electricity demands. For example, in scenario 2, the natural gas CHP plant operates at rated capacity from 8:00 to 24:00 in summer; and from 6:00 to 24:00 in winter. This is because of relatively low thermal load in the night (see Fig. 5). Even the CHP plant is operated at partial load, the recovered heat can serve all the thermal demands. It means that the optimal operation is heat following operation in nature. In scenario 3 (PV system), besides the natural gas CHP plant, the PV cells serve a little part of the electricity load in the day time. As to scenario 4 (Biomass system), the biomass CHP plant is adopted and operated at rated capacity throughout the whole year. For scenario 5 (Renewable system), the operation of CHP plants is similar to scenario 4, and the performance of PV cells is similar to scenario 3.
5. Results and discussions
5.3. Electricity load composition and fossil fuel consumption
5.1. Optimal adoption results
Annual electricity consumption in the model area is about 1.3 billion kWh. Fig. 8 shows the share of electricity supply for various scenarios. According to the figure, 81 MW PV cells supply about 8.1% of total electricity load. On the other hand, even if the local biomass resources are fully utilized, it takes up only 10.8% of the total demand. For the optimal system, the power from DER technologies serves about 14.7% of the electrical requirements, the deficiency is supplied by the utility grid. The renewable system has the largest power supply share from DER technologies, which is about 24.2%. Fig. 9 illustrates the fossil fuel consumption for various scenarios. As is expected that the renewable system (scenario 5) has the least fossil fuel consumption, which is about 19.2% less than the conventional system. The reduction ratios of scenario 2, scenario 3 and scenario 4 are 5.3%, 11.1% and 13.4%, respectively.
Scenario 4 Biomass system. In this scenario, based on a pre-assumed biomass CHP plant, the capacities of PV and natural gas CHP systems are selected by executing the analytical model. The biomass resources as illustrated in Table 2, are assumed to be exhausted.
Table 4 shows the simulation results of various scenarios by executing the analytical model. The total introduction capacities of scenarios 2e5 are 25.0 MW, 106.0 MW, 24.1 MW and 105.1 MW, respectively. In the optimal system (scenario 2), only 25 MW natural gas CHP plants are introduced; as to the PV system (scenario 3), 81 MW PV cells are added. The biomass system (scenario 4) has the smallest capacity, which is composed of a 8.5 MW natural gas CHP plant and a 15.6 MW biomass CHP plant. As to the renewable system (scenario 5), although all assumed technologies are introduced, the total capacity is smaller than the PV system. From the viewpoint of annual energy cost due to fuel and power consumptions, compared with the conventional system (scenario 1), the introduction of DER system (scenarios 2e5) leads to more or less reduction. However, because of the relatively high investment cost of the DER equipments, scenario 5 which introduces all DER technologies has the largest total annual cost. The optimal system (scenario 2) is recognized as the economically optimal alternative with the least total cost. Generally, from the economic point of view, it is reasonable that natural gas CHP plant is the dominant DER technology in China. However, in order to realize a wide penetration, the increase of customer merits through the reduction of investment and running costs is necessary. The renewable technologies, such as PV, biomass, etc., seem to be very hard to be diffused without radical policies.
5.4. Cost-effectiveness of CO2 emissions reduction The reduction of CO2 emissions is one of the most important incentives to the adoption of DER systems. In this study, considering the carbon neutral characteristic, CO2 emissions of biomass CHP system is recognized to be zero. Fig. 10 shows annual CO2 emissions and corresponding reduction cost (compared with the conventional system) for various scenarios. As to the total emissions, for all scenarios, the dominant emission source is grid power, followed by natural gas for non-DER use. In addition, compared with the conventional system, the reduction ratios of scenarios 2e5 are 8.6%, 15.5%, 14.1% and 20.9%, respectively. As is expected, the CO2 emissions of the renewable system is the lowest among all assumed scenarios. On the other hand, looking into the reduction cost of CO2 emissions, it can be found except the optimal system (scenario 2),
5.2. Optimal supply characteristics Besides the equipment combination, the operation strategies also have great effects on the economics of the DER system. In the
Table 4 Optimal adoption results and corresponding economic performances of various scenarios. System combinationa
Scenario
Scenario Scenario Scenario Scenario Scenario a
1 2 3 4 5
e a:25.0 MW a:25.0MW b:81.0 MW a:8.5 MW c:15.6 MW a:8.5 MWb:81.0 MW c:15.6 MW
a: Natural gas CHP; b: PV; c: Biomass CHP.
Annual cost (108 Yen) Annual capital
O&M
Grid electricity
Natural gas Power
Heat
0.0 0.4 2.0 0.6 2.2
0.0 0.3 0.4 0.5 0.7
9.8 8.3 7.5 8.3 7.4
0.0 1.6 1.6 0.5 0.5
5.5 4.6 4.6 4.5 4.5
Biogas
Total cost
0.0 0.0 0.0 1.5 1.5
15.3 15.2 16.1 15.9 16.8
Reduction rate of total cost (%)
e 0.7 5.2 3.9 9.8
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Fig. 7. Hourly electricity supply characteristics (summer and winter).
all other systems introducing DER technologies (scenarios 3e5) have relatively large reduction cost, which is higher than 3 Yen/kgCO2. The renewable system has the largest reduction cost, which is about 5 Yen/kg-CO2. Therefore, it can be deduced that the high environmental merits are at the cost of weak economic performance. From the viewpoint of cost efficiency, scenario 2 can be recognized as the best selection. 5.5. Sensitivity analysis
environmental performance but marginal economic benefit, in Chinese urban areas. However, the economics are considered to play a main role in the decision making of DER adoption. Therefore, in this section, aiming at improving the economic performance of the DER system, sensitivity analyses of some key influence factors are executed. In addition, considering the uncertainty of local energy demands due to the approximate calculation illustrated in Appendix section, a sensitivity analysis on energy demands is also included. In the following, by taking annual cost reduction ratio as an exogenous variable, the effects of electricity buy-back price and biogas price, as
According to the above analysis, currently, the introduction of DER system especially some renewable technologies result in good
Fig. 8. Annual electricity load shares for various scenarios.
Fig. 9. Annual fossil fuel consumptions for various scenarios.
H. Ren et al. / Applied Thermal Engineering 30 (2010) 2584e2593
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Reduction ratio of total annual cost (%)
6 Scenario 2
Scenario 3
Scenario 4
Scenario 5
3 0 -3 -6 -9 -12 -15 10
18
26 34 3 Biogas price (Yen/m )
42
50
Fig. 10. Annual CO2 emissions and corresponding reduction costs for various scenarios. Fig. 12. Economic influence of biogas price.
well as the variation of energy demands on the economic adoption of DER system are analyzed.
system from on-site use to selling back to the grid, due to the increased buy-back price.
5.5.1. Sensitivity of electricity buy-back price As one of the promotion policies to stimulate DER penetration, electricity buy-back has been introduced in a lot of countries. In Japan, the buy-back price for electricity out of PV system is about 24 Yen/kWh (the level of electricity tariff rate), which may be doubled in the new future. On the other hand, although electricity buy-back from DER system is not permitted in China according to current electric power standard, as the continuing global warming, it is considered to be a necessary policy to promote the introduction of renewable energies (e.g. PV, biomass energy, etc.). In the following, while assuming the feasibility of selling electricity out of PV system back into the grid, the influence of the buy-back price on the economic performance of DER system is assessed. According to the results shown in Fig. 11, the rise of buy-back price leads to more or less increase of annual cost reduction ratio for all scenarios. As to scenarios 2 and 4, in which PV capacity is not specified, the variation of buy-back price has no influence on annual cost unless it is increased above 16 Yen/kWh (the level of power generation cost of PV system). As the buy-back price exceeds this critical point, the PV system illustrates its economic benefits and is introduced gradually. On the other hand, in scenarios 3 and 5, a specific PV capacity (determined according the roof area of local buildings) is assumed, when the buy-back price increases above 8 Yen/kWh (the level of electricity tariff rate in the local area), the cost reduction ratios start to increase in a linear way. This is because of the transformation of electricity out of PV
5.5.2. Sensitivity of biogas price Fig. 12 shows the influence of biogas price on the economics of DER systems. According to the discussion illustrated in Section 4, the biogas price is assumed to be 35 Yen/m3 in this study. In the future, on the one hand, as the development of gasification technology and the introduction of inverse onerous contract, the biogas price is expected to be reduced gradually; on the other hand, along with the rising price in the global energy market, the biogas may also illustrate a rising tendency. Therefore, in the following, the sensitive analysis is executed for both increased and reduced biogas prices. From Fig. 12, the decrease of biogas price results in increased cost reduction ratios for scenarios 4 and 5. However, as to scenarios 2 and 3, unless the biogas price is reduced below 18 Yen/m3, annual energy cost stands at the same value as the change of biogas price. This is because when biogas price is relatively high, the biomass CHP system is not introduced from the economic viewpoint. In other words, the critical price of biogas to illustrate economic merit is 18 Yen/m3. 5.5.3. Sensitivity of local energy demands As is discussed above, due to the absence of detailed building information, an energy intensity method has been employed to calculate the local energy demands. It may result in more or less uncertainty although it has even been proved to have considerable precision [41]. In the following, local energy demands are endued
6 Scenario 2
Scenario 3
Scenario 4
Scenario 5
Reduction ratio of total annual cost (%)
Reduction ratio of total annual cost (%)
6 3 0 -3 -6 -9 -12 -15
Scenario 2
4
8 12 Electricity buy-back price (Yen/kWh)
16
Fig. 11. Economic influence of electricity buy-back price.
20
Scenario 4
Scenario 5
0
-6
-12
-18
-24 0
Scenario 3
-50
-30
-10
10
30
Increment ratio of energy demands (%) Fig. 13. Economic influence of the variation of energy demands.
50
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a variation between 50% and 150% of current value, and the influence on the reduction ratio of total annual cost is shown in Fig. 13. From this figure, it is interesting to notice that the economics of scenario 1 (optimal system) illustrates no obvious relationship with the variation of energy demands. In other words, total annual cost of scenario 1 becomes larger linearly with the local energy demands. Looking into the optimal results of parameter analysis, it is because the variation of energy demands results in the change of natural gas CHP capacity with the same scale. Correspondingly, all the components in Eq. (1) and finally the total annual cost show a linear variation. Furthermore, as to scenarios 3e5 which introduce definite capacity of renewable energy resources, the reduction ratios of total annual cost rise as the increase of local energy demands. Especially, as the energy demands are reduced to half of current value, the economic performance of scenario 5 (renewable system) is fairly unsatisfying, which has an increased total annual cost by about 22%. However, it should be indicated that actual energy demands in the local area may be lower than the calculation value. This is due to: on the one hand, electricity consumption intensity in Shanghai may be smaller than that of Tokyo because of lower life level; on the other hand, Tokyo may also have larger heat consumption intensity because of the difference in life styles. Therefore, introducing distributed renewable resources in Chinese urban area may result in much worse economic performance, which validates the importance of adopting some policies (e.g. electricity buy-back) which have been analyzed above.
5. The variation of energy demands has no influence on the economic performance of the optimal system which introduces natural gas CHP plants only. On the other hand, introducing distributed renewable energy resources may lead to worse economic performance due to possible lower energy demands. In the following study, an integrated energy system optimization model should be developed to support the decision making for the sustainable use of energy in the local area while covering both the energy supply and demand sides, and provide feasible generation settlements between utility grid, distributed generations, as well as optimal diffusion of energy efficiency measures (e.g. solar heater, etc.). In addition, in order to cope with the uncertainties of some techno-economic parameters which may illustrate great fluctuation from a long-term viewpoint, a long-term energy system optimization model is also necessary to be formed so as to provide beneficial recommendations for the establishment of long-term energy and environmental policies.
Acknowledgements This research has been supported by Global Environment Research Fund by the Ministry of the Environment Japan (E-0804), as well as Kansai Research Foundation for Technology Promotion and Yazaki Memorial Foundation for Science and Technology. Acknowledgement is also due to two anonymous reviewers who provided us with helpful comments.
6. Conclusions and perspectives In this study, in order to realize a low-carbon city, the DER system is proposed for the urban areas in China. By investigating necessary technical and financial information, as well as local energy demands, an analytical model is developed to determine the optimal system combination and operation pattern of the DER system. Using the model, taking a model area in Shanghai as a case study, the optimal DER systems are analyzed for five scenarios. According to the simulation results, the following conclusions can be deduced. 1. Currently, although the introduction of DER system in Chinese urban area leads to reasonable environmental merit, the economic benefit is marginal. Because of the high capital cost, the feasible technologies are some mature ones, such as natural gas CHP plant with a relatively low cost reduction ratio of about 0.7%. 2. Because of the limit resource reservation in the urban area, even if total renewable resources are fully utilized, the on-site power generation only takes up 24% of the total requirements. 3. The introduction of all assumed DER technologies results in reduced CO2 emissions. However, from the cost-effective viewpoint, natural gas CHP system is currently the best selection. The CO2 emissions reduction costs of the renewable energies (e.g. PV, biomass) are always at a relatively high level which is above 3 Yen/kg-CO2. 4. In order to improve the economic performance of the DER system, according to the results of sensitivity analyses, the introduction of electricity buy-back and the reduction of biogas price can promote the adoption of DER system positively. As the buy-back price is above 16 Yen/kWh, the PV system illustrates its economic merit and is introduced gradually. In addition, the biogas CHP system is introduced and shows good economic performance as the biogas price is below 18 Yen/m3.
Appendix This appendix presents the load correction method which is applied in this study to calculate the energy demands in a Chinese urban area. In Japan, Tokyo is the focus of building energy intensity study, for example, in the Ojima’s hourly energy unit [25] and yearly energy consumption from the Japan Cogeneration Research Cenetre [40]. Actually, Tokyo and Shanghai share similar latitudes, sunshine hours and outside temperatures (see Table A1). Therefore, energy intensity data in Shanghai can be deduced by adjusting the corresponding data in Tokyo while accounting for the differences in heating degree days (HDD) and cooling degree days (CDD) between the two cities [41]. Based on these differences, the energy intensity in Shanghai is estimated by using a temperature correlation coefficient, as shown in Fig. A1.
Energy intensity of Tokyo
Local conditions in Tokyo
Local conditions in Shanghai
Degree day correction Energy intensity of Shanghai
Area of different types of buildings in the model area
Energy demands of the model area in Shanghai Fig. A1. Flow chart of the calculation method for local energy demands.
H. Ren et al. / Applied Thermal Engineering 30 (2010) 2584e2593
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Table A1. Comparison of local conditions in Shanghai and Tokyo. Area
Latitude ( )
Annual sunshine time (hours)
Mean outside temperature ( C)
HDD (days)
CDD (days)
Shanghai Tokyo Shanghai/Tokyo
31.2 35.4 0.9
1821.0 1996.0 0.9
17.4 17.0 1.0
1691.0 1405.0 1.2
164.0 210.0 0.8
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