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A novel operation strategy for CCHP systems based on minimum distance
Applied Energy 128 (2014) 325–335
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Applied Energy journal homepage: www.elsevier.com/locate/apenergy
A novel operation strategy for CCHP systems based on minimum distance C.Y. Zheng, J.Y. Wu ⇑, X.Q. Zhai Institute of Refrigeration and Cryogenics, Shanghai Jiao Tong University, Shanghai 200240, China
h i g h l i g h t s
g r a p h i c a l a b s t r a c t
A novel operation strategy based on
minimum distance which is flexible and adaptable was proposed. An integrated evaluation criterion reflecting the matching performance was presented. The strategy and criterion was used to optimize the design of the CCHP system.
a r t i c l e
i n f o
Article history: Received 7 October 2013 Received in revised form 23 April 2014 Accepted 26 April 2014 Available online 20 May 2014 Keywords: CCHP systems Minimum distance operation strategy Matching performance Evaluation criterion
a b s t r a c t A novel operation strategy based on minimum distance was proposed. Also, an integrated evaluation criterion which can reflect the matching performance between the CCHP (combined cooling, heating and power) system and the building was presented. A hospital in Shanghai was used to evaluate the CCHP system with the proposed strategy using the proposed evaluation criterion. The proposed operation strategy was compared with FEL (following the electric load), FTL (following the thermal load) and FHL (following hybrid electric-thermal load) strategies. The results show that the matching performance evaluation criterion is reasonable and integrated. The system with a better matching performance would be fully used and maintain high efficiency. Compared with FEL, FTL and FHL strategies, the proposed operation strategy is flexible and adaptable, which can lead to a better matching performance for a CCHP system. In the case study, the optimized power generation unit capacity and weightings of the optimized operation strategy are 900 kW and w1,above equals to 0.4, w1,below equals to 0.1, respectively. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Combined cooling, heating, and power (CCHP) as distributed energy supply systems are more and more popular all over the ⇑ Corresponding author. Tel./fax: +86 21 34206776. E-mail address: [email protected] (J.Y. Wu). http://dx.doi.org/10.1016/j.apenergy.2014.04.084 0306-2619/Ó 2014 Elsevier Ltd. All rights reserved.
world because of their potential to reduce cost, primary energy, and emissions [1–4]. The selection of the operation strategy in CCHP systems must be accomplished by considering both weather conditions and building demands. Because the thermal and power demands of buildings vary with the level of activity and climatic conditions, it is always hard for a power generation unit (PGU) to cover both electrical and thermal demands at the same time. As
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Nomenclature ATCSR CCHP CC CHP CO2E CO2ERR COP FEL FHL FTL ICE LHV MD MP OC PESR PGU SP Symbols a, b, c, d D E Eo to Ed F f P Q Qw to Td S T W w
g
annual total cost saving ratio combined cooling, heating and power capital cost combined heating and power CO2 emission CO2 emission reduction ratio coefficient of performance following the electric load following hybrid electric-thermal load following the thermal load internal combustion engine low heat value of natural gas (kW h/m3) minimum distance matching performance operation cost primary energy saving ratio power generation unit separate production
coefficients of polynomial equations distance electricity (kW h) the ratio between excess electricity to electricity demand fuel (kW h) part load factor price (U/kW h) thermal energy (kW h) the ratio between waste heat to thermal demand the integrated performance thermal weighting of evaluation criteria weighting of distance efficiency level
a result, an improper operation strategy would lead to either the waste of electricity or the wasted of heat, which definitely decreases the performance of system. For a CCHP system, ideally, all of the building loads are satisfied by the cogeneration equipment while the cogeneration part maintain a high efficiency and no excess energy is produced. At this time, the best matching performance between the CCHP system and the building is achieved. However, in actual fact, the auxiliary equipments are always needed and the excess energy is unavoidable. For this reason, how to design the CCHP system and determine the operation strategy to achieve a better match performance is an important problem that should be solved. The selection of the operation strategy and the evaluation criterion for evaluating the match performance is the key to solve this problem. Two of the most common operation strategies are (1) to follow the electric load (FEL) while using the recovered heat to help offset the heating or cooling demand and (2) to follow the thermal load (FTL) using the electric generation to help offset electric demand [5]. When a CCHP system operates under FEL strategy, the least waste electricity would be produced. Similarly, when a CCHP system operates under FTL strategy, the least waste heat would be produced. It is to say that these strategies cannot minimize the waste electricity and waste heat at the same time. The influence of building load on the performance of a CCHP system has been investigated by several authors. Mago et al. [6] analyzed the per-
l
CO2 emission conversion factor (g/kW h)
Subscripts negative + positive ac absorption chiller above above the energy supply curve B boiler below below the energy supply curve c cooling cogen the cogeneration part of the system e electricity Ec electric chiller eq equipment ev the evaluated system ex exhaust f fuel grid electricity grid h heating in electricity put into the system max maximum value normal normalization on on-peak off off-peak on-site on site out electricity put out from the system whole the whole system pgu power generation unit r recovery rated the rated capacity rc recovery heat for space cooling rh recovery heat for supply heating SP separate system sum sum
formance of CCHP and CHP systems into an office building in four climate zones in USA. Wang et al. [7] employed multi-criteria to compare the performance of a CCHP system for a hotel building in five different climate zones in China. Both of them reported that different strategies were applicable to different kinds of building load. Besides, the choice of an operation strategy was usually governed by the loading of the prime mover as well as a few extraneous circumstances including the ability to sell back electricity to the grid or store it on site for later use via some battery system [8]. Also, the price of fuel vs. that of purchased from a traditional source affected the management of a plant [9]. Cardona et al. [10] pointed that the FEL was used in the desire to avoid the waste any of thermal energy rejected from the prime mover. On the other hand, FTL strategy was most commonly used where excess electricity produced could sold back to the grid. In actual, the load characteristics for different types of building in different climate zones are different. Also, the policy and the price parameters of different countries and regions are different. Consequently, either FEL or FTL strategy cannot completely deal with these complex situations. An adaptable operation strategy is necessary. An evaluation criterion plays an important role in the selection of an operation strategy. The cost saving, energy saving and environmental performance are usually involved in the evaluation criteria of a CCHP system. As these criteria often conflict with each other [11,12] for a CCHP system, the multi-criteria evaluation methods have been taken into account. Masood Ebrahimi et al.
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[13] used two multi-criteria decision-making algorithms of fuzzy logic and grey incidence approach to choose the best prime mover for a micro-CCHP system. They reported that the decision made by these approaches agree with each other. Hongbo Ren et al. [14] employed two multi-criteria evaluation methods to select the energy supply system. It presented that different evaluation methods may give different results. There was no rule to indicate one method is better than another. Wang et al. [15] presented a fuzzy multi-criteria decision-making model for trigeneration systems. It reported that the integrated evaluation in this approach was needed to improve in some aspects. Wang et al. [16] used the improved grey incidence approach to evaluate the distributed trigeneration systems. They presented that this method was simple and practical, which could provide a reliable evaluation method for the distributed trigeneration systems. As an energy supply system, the most important task of a CCHP system is to satisfy the demands of a building, at the same time, maintaining high efficiency. The more energy from CCHP system is used to satisfy the building load, the better performance of the whole system would be achieved in the certain region. But in this process, the efficiency of the CCHP system often decreases because of the increase of the excess energy produced by the CCHP system. On the other hand, the less excess energy is produced by the CCHP system, the higher efficiency of the CCHP system would be achieved. However, most of the evaluation criteria only focus on the performance of the whole system. The efficiency of the cogeneration part is ignored. Consequently, the matching performance between a CCHP system and the building loads should consider these two aspects. The objective of this investigation is to propose a novel operation strategy based on minimum distance and evaluate the performance of a CCHP system operating under this strategy. The results are compared with a CCHP system operating FEL, FTL and FHL (follow hybrid electric-thermal load) [8]. The energy flows model of CCHP system is developed. Besides, an evaluation criterion which reflects the matching performance between the CCHP system and the building is presented. Moreover, the novel operation strategy is described. Lastly, the design method and performance of CCHP system are analyzed in a case study.
where Egrid,in is the electricity from grid, Egrid,out is the electricity sold back to grid and Eec is the electricity demand of the electric chiller. The electricity used by chiller is calculated as:
2. Analysis methodology
Eec ¼
2.1. Energy flows of a CCHP system
where Qec is the cooling produced by the electric chiller, and COPec is the electric chiller’s coefficient of performance. The thermal energy balance in winter and summer is different. In winter, there is no cooling demand. But there are both heat and cooling demand in summer.
A schematic of the redundant CCHP system is shown in Fig. 1. According to Fig. 1, it can be observed that this CCHP system can be divided into two parts: (1) cogeneration part which comprises
a power generation unit (PGU) and an absorption chiller; (2) auxiliary part which consists of the grid, an electric chiller and an auxiliary boiler. The energy flows of the CCHP system are presented and analyzed as follows: For a CCHP system, the fuel is supplied to the PGU to produce the electricity for the building. Then the waste heat from the PGU is recovered to provide heating or cooling when needed. The shortage of electricity can be compensated by the grid when the electricity produced by the PGU is not enough. In winter, when the recovered heat is less than the heat demand, the shortage of heat is supplemented by an auxiliary boiler. In summer, the recovered heat is used to produce cooling by an absorption chiller; if it is not enough to satisfy the cooling demand, the shortage of cooling is supplemented by an electric chiller. When the recovered heat is more than the thermal demand, the excess heat is wasted. If the electricity produced by PGU is more than the electricity demand, the excess electricity is sold back to the grid. The energy demands of a building include: (1) electrical energy demand, E; (2) cooling demand for space cooling, Qc; (3) heating demand for space heating and/or domestic hot water, Qh. The generated electricity from the PGU can be estimated as:
Epgu ¼ F pgu gpgu;e
ð1Þ
where Fpgu is fuel consumption of the PGU and gpgu,e is the PGU generation efficiency. gpgu,e is calculated as [18]: 3 2 gpgu;e ¼ a1 fpgu þ b1 fpgu þ c1 fpgu þ d1
ð2Þ
where fpgu is part load factor of the PGU, a1, b1, c1, d1 are the coefficient of the non-linear function, which are shown in Table 1. The electrical energy balance is expressed as:
Egrid;in ¼ E þ Eec Epgu
Epgu 6 E þ Eec
Egrid;out ¼ Epgu E Eec
Epgu > E þ Eec
Q ec COPec
Fig. 1. Energy flows of the redundant CCHP system.
ð3Þ
ð4Þ
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Table 1 Coefficients of polynomial equations. bi
ci
di
Q ec ¼ 0
1 2 3
0.1283 0.7098 0.6181
0.6592 1.5206 0.8669
0.7945 1.1191 0.4724
0.003 0.835 –
The heat recovered from the PGU to satisfy the heat demand is calculated as:
ð5Þ
where Qac is the cooling produced by the absorption to satisfy the cooling demand, Qrc is the heat from the PGU supplied to the absorption chiller, and COPac is the absorption chiller’s COP. The COPac can be estimated as [17]:
COPac ¼
0
fac < 0:2
a3 fac2 þ b3 fac þ c3
fac P 0:2
ð6Þ
where fac is the part load factor of absorption chiller and the coefficients a3, b3, c3 are shown in Table 1. The heat from the PGU supplied to the absorption chiller is calculated as:
Q rc ¼ Q r
Q r COP ac 6 Q c
Q rc ¼ Q c =COPac
Q r COPac > Q c
ð7Þ
where Qr is all the heat recovered from the PGU, which can be estimated as:
Q r ¼ F pgu gpgu;r
ð8Þ
where gpgu,r is the PGU heat recovery efficiency, which is calculated as [18]: 3 2 gpgu;r ¼ a2 fpgu þ b2 fpgu þ c2 fpgu þ d2
fpgu ¼
Epgu PGUrated
ð10Þ
where PGUrated is the rated capacity of PGU. The cooling produced by the electric chiller is estimated as:
Q ec ¼ Q c Q r =COPac
Q r COPac 6 Q c
Q ec ¼ 0
Q r COPac > Q c
ð11Þ
The heat recovered from the PGU to satisfy the heat demand is calculated as:
Q rh ¼ Q r Q rc
0 6 Q r Q rc 6 Q h
Q rh ¼ Q h
Q r Q rc > Q h
ð12Þ
The supplement fuel consumption to the boiler can be estimated as:
Fb ¼
Qb
Q rh ¼ Q r Q rh ¼ Q h
Qr 6 Qh Qr > Qh
ð17Þ
The supplement heat from the boiler can be calculated as:
Qb ¼ Qh Qr
Qr 6 Qh
Qb ¼ 0
Qr > Qh
In this paper, the energy saving or economical saving of the excess electricity is not considered when evaluating the MP between the CCHP system and the building. To carry out this analysis, an existing conventional separate production (SP) system shown in Fig. 2, as a reference system, is compared with the evaluated CCHP system. Three criteria are employed to evaluate the performances of the cogeneration part and the whole CCHP system. They are: (1) Primary energy saving ratio (PESR), which is defined as the ratio of the saving energy of the evaluated system to the energy consumption of SP system; (2) CO2 emission reduction ratio (CO2ERR), which is defined as the ratio of the reducing CO2 emission of the evaluated system to the CO2 emission of SP system; and (3) annual total cost saving ratio (ATCSR), which is defined as the ratio of the reducing annual total cost of the evaluated system to the annual total cost of SP system. 2.2.1. Cogeneration part evaluation The PESR of the cogeneration part can be calculated as:
PESRcogen ¼
F SP:cogen F cogen 100% F SP;cogen
F SP;cogen ¼
Epgu Egrid;out
ge ggrid
þ
Q ac Q þ rh COPec ge ggrid gb
F cogen ¼ F pgu
Qb ¼ 0
0 6 Q r Q rc 6 Q h
Q b ¼ Q h Q rh
Q r Q rc > Q h
The CO2ERR of the cogeneration part can be calculated as:
CO2 ERRcogen ¼
CO2 ESP;cogen CO2 Ecogen 100% CO2 ESP;cogen
ð22Þ
where the CO2ESP,cogen and CO2Ecogen can be calculated as:
CO2 ESP;cogen ¼ lf
Q þ le Epgu Egrid;out þ ac gb COP ec
Q rh
CO2 Ecogen ¼ lf F pgu
ð23Þ ð24Þ
ð14Þ
2.1.2. Thermal energy flows in winter In winter, none of the cooling is produced by electric and absorption chillers, then:
ð20Þ ð21Þ
where gb is the efficiency of boiler, Qb is the supplement heat from the boiler. Qb can be calculated as:
ð19Þ
where the FSP,cogen and Fcogen can be calculated as:
ð13Þ
gb
ð18Þ
2.2. Evaluation criteria
ð9Þ
where a2, b2, c2, d2 are the coefficient of the non-linear function, which are shown in Table 1. The part load factor is calculated as:
ð16Þ
ai
Q ac ¼ Q rc COPac
ð15Þ
i
2.1.1. Thermal energy flows in summer In summer, the cooling demand should be satisfied preferentially and the cooling produced by the absorption chiller is calculated as:
Q ac ¼ 0
Fig. 2. Energy flows of the SP system.
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The ATCSR of the cogeneration part can be calculated following Eq. (25):
ATCSP;cogen ATCcogen 100% ATCSP;cogen
ATCSRcogen ¼
ð25Þ
where the ATCSRSP,cogen and ATCSRcogen can be calculated as:
ATCSP;cogen ¼ R
n1 X ðNk Pk;eq Þ k¼1
365 X 24 X Q ik;ac Q ik;rh pik;e;in þ Eik;pgu Eik;grid;out þ pik;f 1 þ COPec gb i¼1 k¼1 ð26Þ ATCcogen ¼ R
n2 365 X 24 X X ðNk Pk;eq Þ þ ðF ik;pgu Pik;f 2 Þ
ð27Þ
i¼1 k¼1
k¼1
Fig. 3. Loading regime chart.
where R is the capital recovery factor [7], N is the installed power of equipment, Peq is the initial capital cost of each king of equipment, n1 is the number of equipments for the SP system, n2 is the number of equipments for the CCHP system, Pik,f2 is the price of natural gas for CCHP system, Pik,e,in is the price of electricity bought from the grid, and Pik,f1 is the price of natural gas for the boiler. The integrated performance of the cogeneration part can be expressed as:
Scogen ¼ W 1 PESRcogen þ W 2 CO2 ERRcogen þ W 3 ATCSRcogen
ð28Þ
where W1, W2 and W3 are the respective weights of PESR, CO2ERR and ATCSR respectively, which satisfy 0 6 W1, W2 ,W3 6 1 and W1 + W2 + W3 = 1. They are all set to be 1/3 in this study. 2.2.2. The whole CCHP evaluation The PESR of the whole CCHP system can be calculated following Eq. (29):
PESRwhole ¼
F SP:whole F whole 100% F SP;whole
ð29Þ Fig. 4. CCHP system minimum distance operation strategy.
where the FSP,whole and Fwhole can be calculated as:
F SP;whole ¼
E
ge ggrid
þ
Qc Q þ h COPec ge ggrid gb
F whole ¼ F pgu þ F b þ
Egrid;in
ge ggrid
ð30Þ
ð31Þ
The CO2ERR of the whole CCHP system can be calculated as:
CO2 ERRwhole ¼
CO2 ESP;whole CO2 Ewhole 100% CO2 ESP;whole
ð32Þ
where the CO2ESP,whole and CO2Ewhole can be calculated as:
CO2 ESP;whole ¼ lf
Qc þ le E þ gb COPec
Qh
CO2 Ewhole ¼ lf ðF pgu þ F b Þ þ le Egrid;in
ð33Þ ð34Þ
The ATCSR of the whole CCHP system can be calculated as:
ATCSRwhole ¼
ATCSP;whole ATCwhole 100% ATCSP;whole
ð35Þ
Fig. 5. Electric, cooling and heating load duration curves.
where the ATCSRSP,whole and ATCSRwhole can be calculated as:
ATCSP;whole
n1 X ¼R ðNk P k;eq Þ
ATCwhole ¼ R
k¼1
k¼1
365 X 24 X Q ik;c Q ik;h pik;e;in þ Eik þ pik;f 1 þ COPec gb i¼1 k¼1
n2 365 X 24 X X ðNk Pk;eq Þ þ ðEik;grid;in Pik;e;in þ F ik;b Pik;f 1
þ F ik;pgu Pik;f 2 Þ ð36Þ
i¼1 k¼1
ð37Þ
The integrated performance of the cogeneration part can be expressed as:
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Table 2 Main parameters employed for evaluation and analysis. Variable COP of electric chiller Boiler efficiency [20] Grid generation efficiency [20] Grid transmission efficiency [20] CO2 conversion factor of electricity from grid [20] CO2 conversion factor of natural gas [20] Low heat value of natural gas Favorable price of natural gasa Normal price of natural gasa Price of electricity on-peaka Price of electricity off-peaka a
Symbol Unit
Value
COPe
4.0 80.0 35.0 92.2 923 220 9.86 2.43 3.99 1.032 0.474
gb ge ggrid le lf LHV Pf1 Pf2 Pe,on Pe,off
– % % % g/kW h g/kW h kW h/m3 U/m3 U/m3 U/kW h U/kW h
These parameters are the energy price based on the policy of Shanghai [21,22].
Swhole ¼ W 1 PESRwhole þ W 2 CO2 ERRwhole þ W 3 ATCSRwhole
ð38Þ
where W1, W2 and W3 are the respective weights of PESR, CO2ERR and ATCSR respectively, which satisfy 0 6 W1, W2 ,W3 6 1 and W1 + W2 + W3 = 1. They are all set to be 1/3 in this study. 2.2.3. The matching performance The best matching performance between the CCHP system and the building is achieved when all of the building loads are satisfied by the cogeneration equipment while the cogeneration part maintain a high efficiency and no excess energy is produced. But this ideal situation cannot be achieved in the near future. Therefore, the matching performance can be divided into two aspects: (1) the efficiency and availability of the cogeneration equipment to satisfy the building load; (2) the contribution of the cogeneration equipment to satisfy the building load. According to the definition of Scogen, the Scogen can reflect the efficiency of the cogeneration equipment to satisfy the building load. With less excess energy, the higher efficiency of the cogeneration equipment, the higher
Fig. 6. The sum of the performances of the whole CCHP systems and the cogeneration part with PGU capacity of 1000 kW for all operation strategies.
Scogen would be. On the other hand, according to the definition of Swhole, the Swhole can reflect the contribution of the cogeneration equipment to satisfy the building load. When the performance of cogeneration equipment is better than that of the SP system, the more energy from the cogeneration equipment is used to satisfy the building load, the higher Swhole would be. As a consequence, the MP between the CCHP system and the building can be defined as:
MP ¼ e1 Swhole;normal þ e2 Scogen;normal
MP 2 ½0; 1
ð39Þ
where Sev,normal is the normalized value of Sev; e1 and e2 are the weights of Swhole,normal and Scogen,normal, respectively, which satisfy 0 6 e1, e2 6 1 and e1 + e2 = 1. They are set to be 0.5 in this study. The Min–max normalization method [19] is used in this analysis.
Table 3 Unit price of the facilities in the CCHP system [7]. Facility
PGU
Heating coil
Boiler
Absorption chiller
Electric chiller
Unit price, U/kW
6800
200
300
1200
970
Table 4 The MP of the CCHP system for different w1,above and w1,below. (PGUrated = 1000 kW). w1,above
a b c d e f g h
w1,below
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
0.62e 0.62 0.62 0.62 0.33 0.26 0.25 0.25 0.25 0.25 0.25
0.62 0.62 0.62 0.62 0.33 0.26 0.25 0.25 0.25 0.25 0.25
0.62 0.62 0.62 0.62 0.33 0.26 0.25 0.25 0.25 0.25 0.25
0.62 0.62 0.62 0.62 0.33 0.26 0.25 0.25 0.25 0.25 0.25
0.88a 0.88b,f 0.88c 0.88d 0.58 0.50 0.49 0.49 0.49 0.49 0.49
0.78 0.78 0.78 0.78 0.47 0.39 0.38 0.38 0.38 0.38 0.38
0.73 0.73 0.73 0.73 0.41 0.33 0.33 0.32 0.32 0.32 0.32
0.73 0.73 0.73 0.73 0.40 0.32 0.31 0.31 0.31 0.31 0.31
0.71 0.71 0.71 0.71 0.37 0.29 0.28 0.28 0.28 0.28 0.28
0.71 0.71 0.71 0.71 0.37 0.29 0.28 0.28 0.28 0.28 0.28
0.71g 0.71 0.71 0.71 0.37 0.29 0.28 0.28 0.28 0.28 0.28h
The The The The The The The The
number of significant number of significant number of significant number of significant MP of FEL strategy; MP of MD strategy; MP of FHL strategy; MP of FTL strategy.
digits digits digits digits
is is is is
eight: eight: eight: eight:
0.88055255. 0.88055268. 0.88055266. 0.88054769.
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2.3. Minimum distance (MD) operation strategy One of the challenges in CCHP system applications is the matching of thermal load and electrical load. For a CCHP system operating FEL and FTL, the least attractive times of operation occur when large amounts of excess heat and electricity are produced respectively. When a system operates following a hybrid electric-thermal load (FHL) [8], none of excess energy is produced. But the cogeneration part may not be made fully use to satisfy the demands of the building at this time. Here, an optimized operation strategy based on the minimum distance (MD) is developed in order to make the CCHP system fully use with less excess energy. The load point L (E, T) are determined by the electric demand E and the thermal energy demand T. The thermal energy thermal is calculated as:
T ¼ Qh þ
Qc COPac
331
above the curve l, the excess heat decreases but the electricity from the grid increases when w1,above changes from 0 to 1. However, for the load point below the curve l, the excess electricity increases but the supplement heat decreases when w1,below
(a)
ð40Þ
The models of FEL, FTL and FHL strategies have been stated by Mago et al. [8]. The model of MD strategy is stated in this paper as follow. According to Eqs. (1) and (8), the electricity generated by the PGU can be expressed as a function of the heat recovered and PGU efficiency:
Epgu ¼
gpgu;e Q gpgu;r r
ð41Þ
From Eqs. (1), (8), and (41), it is seen that the power generated is a nonlinear function of the recovered heat. In Fig. 3, the curve l represents a perfect match between thermal load and electrical load, which is found using Eq. (41). Because of the fluctuation of building loads, it is seldom for this operational line to be achieved. For that reason, the operation of the system should be following this line. In Fig. 3, point A and point B are typical cases of CCHP operation. The characteristics of the system operating FEL and FTL have already been described in [8]. According to Fig. 3, it is found that there are four kinds of distance from a certain load point to the energy supply curve l. DT+ and DT represent the supplement heat from the boiler and the excess heat respectively. Similarly, DE+ and DE represent the supplement electricity from the gird and the excess electricity respectively. Then the integrated distance can be expressed as:
Dsum ¼ w1 ðDTþ þ DT Þ þ w2 ðDEþ þ DE Þ
(b)
ð42Þ
where w1 and w2 are the respective weights of thermal and electric distance, which satisfy 0 6 w1, w2 6 1 and w1 + w2 = 1. Combining Fig. 4, the description of MD strategy can be described as follow: for a load point L (EL, TL), an operation point O (EO, TO) which minimizes Dsum can be found on the curve l, and then the point O is considered to be the operation point for this load point when the CCHP system operates under MD strategy. It should be highlighted here that when there are two operation points can minimizes the distance for a load point, the one with a higher part load factor would be selected. Fig. 4 shows the operation points of the CCHP system operating under MD with different weightings for point Labove, Lbelow. For point Labove, when w1,above = 0 and w2,above = 1, the system operates at point O0 and it runs FEL; when w1,above = 1 and w2,above = 0, the system operates at point O00 and it runs FTL. On the other hand, for point Lbelow, when w1,below = 0 and w2,below = 1, the system operates at point O00 and it runs FEL; when w1,below = 1 and w2,below = 0, the system operates at point O0 and it runs FTL. Then, the system operates at the points on curve l between point O0 and point O00 for the other weightings. It is said that the operation strategy can be changed by changing the weightings. It is important to notice that the effects of the same operation strategy for the load point above and below the curve l are different. For the load point
(c)
Fig. 7. Variations in Swhole (a), Scogen (b) and MP (c) for various w1,above (w1,below = 0) and PGU capacities.
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(a)
(b)
(d)
(c)
Fig. 8. Fraction of overall annual electric and thermal demand met by CCHP system, the ratio of waste heat to thermal demand and the annual generating efficiency for various w1,above (w1,below = 0) and PGU capacities.
changes from 0 to 1. It is said that w1,above and w1,below are two decision variables to optimize the operation strategy. Once the PGU capacity is determined, the distribution of the load points relative to the curve l is determined too. In other words, w1,above and w1,below are independent to optimize the operation strategy for a PGU capacity.
Based upon the energy load profiles, a CCHP system with optimized PGU capacity and operation strategy was developed by using the MD strategy and MP evaluation criterion. Besides, the performance of this CCHP system for the optimized operation strategy was comprised with that for FEL, FTL and FHL. 3.2. The performance of MD vs. that of FEL and FTL
3. Case study 3.1. Energy load profiles and input values This section presents the results obtained by using the models described in Section 2. A hospital in Shanghai, with a covered area of 70,488 m2, is as a case to be evaluated and analyzed. The peaks of the electric, cooling and heating loads of the building are 3910.5 kW, 2879.6 kW and 2529.7 kW, respectively. The cooling hours for summer are 2664 h, the heating hours for winter are 2688 h and the transition seasons are totally 3408 h. The hot water for the hospital to bath or cook is supplied in the whole year. The duration curve for the electric, cooling and heating loads are shown in Fig. 5. The main parameters employed for the evaluation and analysis are listed in Table 2. The installation costs are summarized in Table 3.
In order to compare MD operation strategy with FEL, FTL and FHL strategies, three aspects are taken into account: (1) the performance of the whole CCHP system; (2) the performance of the cogeneration part of the CCHP system; (3) the amount of excess heat and electricity. The PGU capacity is 1000 kW in this section. Table 4 shows that the MP of the CCHP system for different w1,above and w1,below. It can be observed that the best MP (0.88) is achieved when w1,above equals to 0.4 and w1,below equals to 0.1. Therefore, the MD strategy for 1000 kW PGU capacity is determined to be that w1,above equals to 0.4 and w1,below equals to 0.1. As shown in Table 4, when both w1,above and w1,below are equal to 0 (FEL strategy), the MP is 0.62; when both are equal to 1 (FTL strategy), the MP is 0.28; when w1,above equals to 1 and w1,below equals to 0 (FHL strategy), the MP is 0.71. The sum of the performances of the whole CCHP systems and the cogeneration part for
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(a)
(b)
Fig. 10. The ratio of excess electricity to electricity demand of the building for various w1,below (w1,above = 0) and PGU capacities.
(c) Fig. 11. Weightings w1,above and w1,below of the CCHP systems with the best MP for each PGU capacity.
3.3. Design of CCHP system based on MD and MP
Fig. 9. Variations in Swhole (a), Scogen (b) and MP (c) for various w1,below (w1,above = 0) and PGU capacities.
all operation strategies are shown in Fig. 6. It can be seen that MD presents the highest ATCSR and CO2ERR. Although the PESR of MD is lower than that of FHL, MD has the best performance in the integrated criterion S.
Fig. 7 shows the variations in Swhole, Scogen and MP of the CCHP systems for various w1,above and PGU capacities while w1,below equals to 0. From Fig. 7(a), it can be observed that the Swhole increases firstly, reaches the maximum value, then decreases with the increase of w1,above for all the PGU capacities. It is deduced that neither FEL nor FTL operation strategy can lead the best performance of the whole system for the load points above the energy supply curve in this case, but the operation strategy between them. The electric demand is relatively more than that of thermal in this case. As a consequence, the fraction of overall annual electric demand met by cogeneration part of FEL is much larger than that of FTL, as shown in Fig. 8(a). However, the difference of the fraction of thermal demand met by cogeneration part between FEL and FTL is small, as shown in Fig. 8(b). For these reasons, FEL strategy leads a better performance of the whole system than that of FTL, as shown in Fig. 7(a). From Fig. 7(b), it is shown that the Scogen increases with some fluctuation with the increase of w1,above when the PGU capacity is less than 1300 kW. At this time, the performance of cogeneration
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Fig. 12. Variations in Swhole and Scogen of the CCHP systems with the best MP for each PGU capacity and the MP of them.
part for the system operating FTL is better than that operating FEL. However, when the PGU capacity is greater than 1300 kW, a reverse tendency is observed. The reason is that the ratio of waste heat to thermal demand of the building of FTL is much smaller than that of FEL, as shown in Fig. 8(c). The waste heat begins to decrease when w1,above excesses 0.3. The excess energy and generating efficiency are the key factors when evaluating the performance of the cogeneration part. From Fig. 8(d), it can be found that the generating efficiency of the PGU reaches maximum value when w1,above is equal to 0.4. For this reason, the performances of the whole system and the cogeneration part are sharply improved when w1,above is equal to 0.4, as shown in Fig. 7(a) and (b). The annual generating efficiency decreases sharply, when the PGU capacity is greater than 1300 kW, as shown in Fig. 8(d). It leads a worse Scogen of FTL, comparing to FEL, as shown in Fig. 7(b). The results deduced from Fig. 7(a) and (b) prove that the variations of Swhole and Scogen with weighting and PGU capacity are different. There is not an identical function between them. It is said that MP defined based on these two evaluation criteria is meaningful to evaluate the matching performance between CCHP system and the building. From Fig. 7(c), it is deduced that the MP of CCHP system for various PGU capacities are different. Moreover, it fluctuates with the weighting and has the maximum value. It can be observed that the best MP is achieved when w1,above is equal to 0.4 for all of these PGU capacities. The regions which are circled by ellipse in Figs. 7 and 8 reveal the reasons. The most important reason is that the annual generating efficiency reaches maximum value when w1,above is equal to 0.4. What’s more, from Figs. 7 and 8, it can be verified that the system, which cogeneration part satisfies as many demands of the building as possible with high efficiency and availability, would get a better MP. In other word, MP can reflect the matching performance between the CCHP system and the building in a good way. Fig. 9 shows the variations in Swhole, Scogen and MP of the CCHP systems for various w1,below and PGU capacities while w1,above equals to 0. From Fig. 9, it can be found that Swhole, Scogen and MP almost decrease with the increase of w1,below for all the PGU capacities. They decrease sharply when w1,below between 0.3 and 0.5. The reason is that the ratio of excess electricity to electricity demand of the building increases sharply in this region, as shown in Fig. 10. Comparing Fig. 7(c) with Fig. 9(c), it can be observed that the w1,above and w1,below which make the best MP are different.
As a consequence, in order to determine the PGU capacity and the corresponding operation strategy with the best MP, the following two steps should be taken: (1) find the weighting values w1,above and w1,below which makes the CCHP system has the best MP for each PGU capacity; (2) find the PGU capacity which has the best MP among the cases found in the first step. Fig. 11 shows the weightings of the CCHP systems with the best MP for each PGU capacity. It can be found that most of the systems with the maximum MP for different PGU capacities are not FEL or FTL, but the strategies between them. Fig. 12 shows the performances of the cases found in the first step. It can be observed that Swhole gradually increases, reaches the maximum value when the PGU capacity is 1300 kW , and then decreases with the increase of the capacity of the PGU. Meanwhile, the Scogen reaches the maximum value when PGU capacity is 200 kW, and then decreases with the increase of the capacity of PGU. As for MP, it goes up with the increase of PGU capacity. Then, it decreases when the PGU is beyond 900 kW. According to Figs. 11 and 12, it can be conclude that when the capacity of PGU is 900 kW and w1,above equals to 0.4, w1,below equals to 0.1, the CCHP system has the best MP in this case. 4. Conclusions This paper proposed a novel operation strategy for CCHP systems based on minimum distance. Besides, an integrated evaluation criterion was developed, which could be used to evaluate the matching performance between a CCHP system and a building. Then the CCHP system of a hospital in Shanghai was designed based on the MD operation strategy and MP evaluation criterion. Moreover, the CCHP system with MD operation strategy was compared with that under three operating modes including FEL, FTL and FHL. The results and analysis lead to the following conclusions: (1) All of FEL, FTL and FHL strategies cannot lead to the best matching performance between a CCHP system and a building for most situations. However, MD strategy can make a CCHP system operate between FEL and FTL mode by changing the weightings above and below the energy supply curve. MD strategy is a flexible and adaptable operation strategy, which can lead to the best matching performance of a CCHP system and a building.
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(2) The MP is an integrated evaluation criterion for considering the performance of both the whole system and the cogeneration part. It can reflect the matching performance between the CCHP system and the building in a good way. (3) The MD strategy and MP evaluation criterion can be used to determine the optimized PGU capacity and operation strategy for the CCHP system. In this case study, the optimized PGU capacity and weightings of the optimized operation strategy are 900 kW and w1,above equals to 0.4, w1,below equals to 0.1, respectively. MD presents the highest ATCSR and CO2ERR. Although the PESR of MD is lower than that of FHL, MD has the best performance in the integrated criterion S.
Acknowledgements This work was supported by National Natural Science Foundation of China under the contract No. 51076099 and Shanghai Commission of Science and Technology under the contract No. 12 dz1200101. References [1] Wu DW, Wang RZ. Combined cooling, heating and power: a review. Prog Energ Combust 2006;32(5):459–95. [2] Chicco G, Mancarella P. Distributed multi-generation: a comprehensive view. Renew Sust Energ Rev 2009;13(3):535–51. [3] Medrano M, Brouwer J, McDonell V, Mauzey J, Samuelsen S. Integration of distributed generation systems into generic types of commercial buildings in California. Energ Build 2008;40(4):537–48. [4] Lai SM, Hui CW. Integration of trigeneration system and thermal storage under demand uncertainties. Appl Energ 2010;87(9):2868–80. [5] Mago PJ, Luck R. Evaluation of a base-load combined heating and power system with thermal storage for different small building application. Int J Energ Res 2013;37(2):179–88.
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[6] Mago PJ, Fumo N, Charmra LM. Performance analysis of CCHP and CHP systems operating following the thermal and electric load. Int J Energ Res 2009;33(9):852–64. [7] Wang JJ, Zhang CF, Jing YY. Multi-criteria analysis of combined cooling, heating and power systems in different climate zones in China. Appl Energ 2010;87(4):1247–59. [8] Mago PJ, Chamra LM, Ramsay J. Micro-combined cooling, heating and power systems hybrid electric-thermal load following operation. Appl Therm Eng 2010;30:800–6. [9] Cardona E, Piacentino A. Matching economical, energetic, and environmental benefits: an analysis for hybrid CCHP-heat pump systems. Energy 2006;31(4):490–515. [10] Cardona E, Piacentino A. A methodology for sizing a trigeneration plant in Mediterranean areas. Appl Therm Eng 2003;23(13):1665–80. [11] Wu JY, Wang JL, Li S. Multi-objective optimal operation strategy study of micro-CCHP system. Energy 2012;48:472–83. [12] Mago PJ, Chamra LM. Analysis and optimization of CCHP systems based on energy, economical, and environmental considerations. Energ Build 2009;41:1099–106. [13] Evrahimi M, Keshavarz A. Prime mover selection for a residential micro-CCHP by using two multi-criteria decision-making methods. Energ Build 2012;55:322–31. [14] Ren HB, Gao WJ, Zhou WS. Multi-criteria evaluation for the optimal adoption of distributed residential energy systems in Japan. Energ Policy 2009;37(12):5484–93. [15] Wang JJ, Jing YY, Zhang CF, Shi GH, Zhang XT. A fuzzy multi-criteria decisionmaking model for trigeneration system. Energ Policy 2008;36(10):3823–32. [16] Wang JJ, Jing YY, Zhang CF, Zhang XT, Shi GH. Integrated evaluation of distributed triple-generation systems using improved grey incidence approach. Energy 2008;33:1427–37. [17] Broad Group [Internet]. China. [cited 21.04.14]. [18] TRNSYS. TRNSYS 17 transient system simulation TYPE902. [19] Visalakshi NK, Thangavel K. Impact of normalization in distributed K-means clustering. Int J Soft Comput 2009;4(4):168–72. [20] Wang JJ, Jing YY, Zhang CF, Zhai ZJ. Performance comparison of combined cooling heating and power system in different operation modes. Appl Energ 2011;88(12):4621–31. [21] Shanghai Municipal Development & Reform Commission. China. [cited 21.04.14]. [22] Shanghai municipal gas management office. China. [cited 21.04.14]
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Applied Energy journal homepage: www.elsevier.com/locate/apenergy
A novel operation strategy for CCHP systems based on minimum distance C.Y. Zheng, J.Y. Wu ⇑, X.Q. Zhai Institute of Refrigeration and Cryogenics, Shanghai Jiao Tong University, Shanghai 200240, China
h i g h l i g h t s
g r a p h i c a l a b s t r a c t
A novel operation strategy based on
minimum distance which is flexible and adaptable was proposed. An integrated evaluation criterion reflecting the matching performance was presented. The strategy and criterion was used to optimize the design of the CCHP system.
a r t i c l e
i n f o
Article history: Received 7 October 2013 Received in revised form 23 April 2014 Accepted 26 April 2014 Available online 20 May 2014 Keywords: CCHP systems Minimum distance operation strategy Matching performance Evaluation criterion
a b s t r a c t A novel operation strategy based on minimum distance was proposed. Also, an integrated evaluation criterion which can reflect the matching performance between the CCHP (combined cooling, heating and power) system and the building was presented. A hospital in Shanghai was used to evaluate the CCHP system with the proposed strategy using the proposed evaluation criterion. The proposed operation strategy was compared with FEL (following the electric load), FTL (following the thermal load) and FHL (following hybrid electric-thermal load) strategies. The results show that the matching performance evaluation criterion is reasonable and integrated. The system with a better matching performance would be fully used and maintain high efficiency. Compared with FEL, FTL and FHL strategies, the proposed operation strategy is flexible and adaptable, which can lead to a better matching performance for a CCHP system. In the case study, the optimized power generation unit capacity and weightings of the optimized operation strategy are 900 kW and w1,above equals to 0.4, w1,below equals to 0.1, respectively. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Combined cooling, heating, and power (CCHP) as distributed energy supply systems are more and more popular all over the ⇑ Corresponding author. Tel./fax: +86 21 34206776. E-mail address: [email protected] (J.Y. Wu). http://dx.doi.org/10.1016/j.apenergy.2014.04.084 0306-2619/Ó 2014 Elsevier Ltd. All rights reserved.
world because of their potential to reduce cost, primary energy, and emissions [1–4]. The selection of the operation strategy in CCHP systems must be accomplished by considering both weather conditions and building demands. Because the thermal and power demands of buildings vary with the level of activity and climatic conditions, it is always hard for a power generation unit (PGU) to cover both electrical and thermal demands at the same time. As
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Nomenclature ATCSR CCHP CC CHP CO2E CO2ERR COP FEL FHL FTL ICE LHV MD MP OC PESR PGU SP Symbols a, b, c, d D E Eo to Ed F f P Q Qw to Td S T W w
g
annual total cost saving ratio combined cooling, heating and power capital cost combined heating and power CO2 emission CO2 emission reduction ratio coefficient of performance following the electric load following hybrid electric-thermal load following the thermal load internal combustion engine low heat value of natural gas (kW h/m3) minimum distance matching performance operation cost primary energy saving ratio power generation unit separate production
coefficients of polynomial equations distance electricity (kW h) the ratio between excess electricity to electricity demand fuel (kW h) part load factor price (U/kW h) thermal energy (kW h) the ratio between waste heat to thermal demand the integrated performance thermal weighting of evaluation criteria weighting of distance efficiency level
a result, an improper operation strategy would lead to either the waste of electricity or the wasted of heat, which definitely decreases the performance of system. For a CCHP system, ideally, all of the building loads are satisfied by the cogeneration equipment while the cogeneration part maintain a high efficiency and no excess energy is produced. At this time, the best matching performance between the CCHP system and the building is achieved. However, in actual fact, the auxiliary equipments are always needed and the excess energy is unavoidable. For this reason, how to design the CCHP system and determine the operation strategy to achieve a better match performance is an important problem that should be solved. The selection of the operation strategy and the evaluation criterion for evaluating the match performance is the key to solve this problem. Two of the most common operation strategies are (1) to follow the electric load (FEL) while using the recovered heat to help offset the heating or cooling demand and (2) to follow the thermal load (FTL) using the electric generation to help offset electric demand [5]. When a CCHP system operates under FEL strategy, the least waste electricity would be produced. Similarly, when a CCHP system operates under FTL strategy, the least waste heat would be produced. It is to say that these strategies cannot minimize the waste electricity and waste heat at the same time. The influence of building load on the performance of a CCHP system has been investigated by several authors. Mago et al. [6] analyzed the per-
l
CO2 emission conversion factor (g/kW h)
Subscripts negative + positive ac absorption chiller above above the energy supply curve B boiler below below the energy supply curve c cooling cogen the cogeneration part of the system e electricity Ec electric chiller eq equipment ev the evaluated system ex exhaust f fuel grid electricity grid h heating in electricity put into the system max maximum value normal normalization on on-peak off off-peak on-site on site out electricity put out from the system whole the whole system pgu power generation unit r recovery rated the rated capacity rc recovery heat for space cooling rh recovery heat for supply heating SP separate system sum sum
formance of CCHP and CHP systems into an office building in four climate zones in USA. Wang et al. [7] employed multi-criteria to compare the performance of a CCHP system for a hotel building in five different climate zones in China. Both of them reported that different strategies were applicable to different kinds of building load. Besides, the choice of an operation strategy was usually governed by the loading of the prime mover as well as a few extraneous circumstances including the ability to sell back electricity to the grid or store it on site for later use via some battery system [8]. Also, the price of fuel vs. that of purchased from a traditional source affected the management of a plant [9]. Cardona et al. [10] pointed that the FEL was used in the desire to avoid the waste any of thermal energy rejected from the prime mover. On the other hand, FTL strategy was most commonly used where excess electricity produced could sold back to the grid. In actual, the load characteristics for different types of building in different climate zones are different. Also, the policy and the price parameters of different countries and regions are different. Consequently, either FEL or FTL strategy cannot completely deal with these complex situations. An adaptable operation strategy is necessary. An evaluation criterion plays an important role in the selection of an operation strategy. The cost saving, energy saving and environmental performance are usually involved in the evaluation criteria of a CCHP system. As these criteria often conflict with each other [11,12] for a CCHP system, the multi-criteria evaluation methods have been taken into account. Masood Ebrahimi et al.
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[13] used two multi-criteria decision-making algorithms of fuzzy logic and grey incidence approach to choose the best prime mover for a micro-CCHP system. They reported that the decision made by these approaches agree with each other. Hongbo Ren et al. [14] employed two multi-criteria evaluation methods to select the energy supply system. It presented that different evaluation methods may give different results. There was no rule to indicate one method is better than another. Wang et al. [15] presented a fuzzy multi-criteria decision-making model for trigeneration systems. It reported that the integrated evaluation in this approach was needed to improve in some aspects. Wang et al. [16] used the improved grey incidence approach to evaluate the distributed trigeneration systems. They presented that this method was simple and practical, which could provide a reliable evaluation method for the distributed trigeneration systems. As an energy supply system, the most important task of a CCHP system is to satisfy the demands of a building, at the same time, maintaining high efficiency. The more energy from CCHP system is used to satisfy the building load, the better performance of the whole system would be achieved in the certain region. But in this process, the efficiency of the CCHP system often decreases because of the increase of the excess energy produced by the CCHP system. On the other hand, the less excess energy is produced by the CCHP system, the higher efficiency of the CCHP system would be achieved. However, most of the evaluation criteria only focus on the performance of the whole system. The efficiency of the cogeneration part is ignored. Consequently, the matching performance between a CCHP system and the building loads should consider these two aspects. The objective of this investigation is to propose a novel operation strategy based on minimum distance and evaluate the performance of a CCHP system operating under this strategy. The results are compared with a CCHP system operating FEL, FTL and FHL (follow hybrid electric-thermal load) [8]. The energy flows model of CCHP system is developed. Besides, an evaluation criterion which reflects the matching performance between the CCHP system and the building is presented. Moreover, the novel operation strategy is described. Lastly, the design method and performance of CCHP system are analyzed in a case study.
where Egrid,in is the electricity from grid, Egrid,out is the electricity sold back to grid and Eec is the electricity demand of the electric chiller. The electricity used by chiller is calculated as:
2. Analysis methodology
Eec ¼
2.1. Energy flows of a CCHP system
where Qec is the cooling produced by the electric chiller, and COPec is the electric chiller’s coefficient of performance. The thermal energy balance in winter and summer is different. In winter, there is no cooling demand. But there are both heat and cooling demand in summer.
A schematic of the redundant CCHP system is shown in Fig. 1. According to Fig. 1, it can be observed that this CCHP system can be divided into two parts: (1) cogeneration part which comprises
a power generation unit (PGU) and an absorption chiller; (2) auxiliary part which consists of the grid, an electric chiller and an auxiliary boiler. The energy flows of the CCHP system are presented and analyzed as follows: For a CCHP system, the fuel is supplied to the PGU to produce the electricity for the building. Then the waste heat from the PGU is recovered to provide heating or cooling when needed. The shortage of electricity can be compensated by the grid when the electricity produced by the PGU is not enough. In winter, when the recovered heat is less than the heat demand, the shortage of heat is supplemented by an auxiliary boiler. In summer, the recovered heat is used to produce cooling by an absorption chiller; if it is not enough to satisfy the cooling demand, the shortage of cooling is supplemented by an electric chiller. When the recovered heat is more than the thermal demand, the excess heat is wasted. If the electricity produced by PGU is more than the electricity demand, the excess electricity is sold back to the grid. The energy demands of a building include: (1) electrical energy demand, E; (2) cooling demand for space cooling, Qc; (3) heating demand for space heating and/or domestic hot water, Qh. The generated electricity from the PGU can be estimated as:
Epgu ¼ F pgu gpgu;e
ð1Þ
where Fpgu is fuel consumption of the PGU and gpgu,e is the PGU generation efficiency. gpgu,e is calculated as [18]: 3 2 gpgu;e ¼ a1 fpgu þ b1 fpgu þ c1 fpgu þ d1
ð2Þ
where fpgu is part load factor of the PGU, a1, b1, c1, d1 are the coefficient of the non-linear function, which are shown in Table 1. The electrical energy balance is expressed as:
Egrid;in ¼ E þ Eec Epgu
Epgu 6 E þ Eec
Egrid;out ¼ Epgu E Eec
Epgu > E þ Eec
Q ec COPec
Fig. 1. Energy flows of the redundant CCHP system.
ð3Þ
ð4Þ
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Table 1 Coefficients of polynomial equations. bi
ci
di
Q ec ¼ 0
1 2 3
0.1283 0.7098 0.6181
0.6592 1.5206 0.8669
0.7945 1.1191 0.4724
0.003 0.835 –
The heat recovered from the PGU to satisfy the heat demand is calculated as:
ð5Þ
where Qac is the cooling produced by the absorption to satisfy the cooling demand, Qrc is the heat from the PGU supplied to the absorption chiller, and COPac is the absorption chiller’s COP. The COPac can be estimated as [17]:
COPac ¼
0
fac < 0:2
a3 fac2 þ b3 fac þ c3
fac P 0:2
ð6Þ
where fac is the part load factor of absorption chiller and the coefficients a3, b3, c3 are shown in Table 1. The heat from the PGU supplied to the absorption chiller is calculated as:
Q rc ¼ Q r
Q r COP ac 6 Q c
Q rc ¼ Q c =COPac
Q r COPac > Q c
ð7Þ
where Qr is all the heat recovered from the PGU, which can be estimated as:
Q r ¼ F pgu gpgu;r
ð8Þ
where gpgu,r is the PGU heat recovery efficiency, which is calculated as [18]: 3 2 gpgu;r ¼ a2 fpgu þ b2 fpgu þ c2 fpgu þ d2
fpgu ¼
Epgu PGUrated
ð10Þ
where PGUrated is the rated capacity of PGU. The cooling produced by the electric chiller is estimated as:
Q ec ¼ Q c Q r =COPac
Q r COPac 6 Q c
Q ec ¼ 0
Q r COPac > Q c
ð11Þ
The heat recovered from the PGU to satisfy the heat demand is calculated as:
Q rh ¼ Q r Q rc
0 6 Q r Q rc 6 Q h
Q rh ¼ Q h
Q r Q rc > Q h
ð12Þ
The supplement fuel consumption to the boiler can be estimated as:
Fb ¼
Qb
Q rh ¼ Q r Q rh ¼ Q h
Qr 6 Qh Qr > Qh
ð17Þ
The supplement heat from the boiler can be calculated as:
Qb ¼ Qh Qr
Qr 6 Qh
Qb ¼ 0
Qr > Qh
In this paper, the energy saving or economical saving of the excess electricity is not considered when evaluating the MP between the CCHP system and the building. To carry out this analysis, an existing conventional separate production (SP) system shown in Fig. 2, as a reference system, is compared with the evaluated CCHP system. Three criteria are employed to evaluate the performances of the cogeneration part and the whole CCHP system. They are: (1) Primary energy saving ratio (PESR), which is defined as the ratio of the saving energy of the evaluated system to the energy consumption of SP system; (2) CO2 emission reduction ratio (CO2ERR), which is defined as the ratio of the reducing CO2 emission of the evaluated system to the CO2 emission of SP system; and (3) annual total cost saving ratio (ATCSR), which is defined as the ratio of the reducing annual total cost of the evaluated system to the annual total cost of SP system. 2.2.1. Cogeneration part evaluation The PESR of the cogeneration part can be calculated as:
PESRcogen ¼
F SP:cogen F cogen 100% F SP;cogen
F SP;cogen ¼
Epgu Egrid;out
ge ggrid
þ
Q ac Q þ rh COPec ge ggrid gb
F cogen ¼ F pgu
Qb ¼ 0
0 6 Q r Q rc 6 Q h
Q b ¼ Q h Q rh
Q r Q rc > Q h
The CO2ERR of the cogeneration part can be calculated as:
CO2 ERRcogen ¼
CO2 ESP;cogen CO2 Ecogen 100% CO2 ESP;cogen
ð22Þ
where the CO2ESP,cogen and CO2Ecogen can be calculated as:
CO2 ESP;cogen ¼ lf
Q þ le Epgu Egrid;out þ ac gb COP ec
Q rh
CO2 Ecogen ¼ lf F pgu
ð23Þ ð24Þ
ð14Þ
2.1.2. Thermal energy flows in winter In winter, none of the cooling is produced by electric and absorption chillers, then:
ð20Þ ð21Þ
where gb is the efficiency of boiler, Qb is the supplement heat from the boiler. Qb can be calculated as:
ð19Þ
where the FSP,cogen and Fcogen can be calculated as:
ð13Þ
gb
ð18Þ
2.2. Evaluation criteria
ð9Þ
where a2, b2, c2, d2 are the coefficient of the non-linear function, which are shown in Table 1. The part load factor is calculated as:
ð16Þ
ai
Q ac ¼ Q rc COPac
ð15Þ
i
2.1.1. Thermal energy flows in summer In summer, the cooling demand should be satisfied preferentially and the cooling produced by the absorption chiller is calculated as:
Q ac ¼ 0
Fig. 2. Energy flows of the SP system.
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The ATCSR of the cogeneration part can be calculated following Eq. (25):
ATCSP;cogen ATCcogen 100% ATCSP;cogen
ATCSRcogen ¼
ð25Þ
where the ATCSRSP,cogen and ATCSRcogen can be calculated as:
ATCSP;cogen ¼ R
n1 X ðNk Pk;eq Þ k¼1
365 X 24 X Q ik;ac Q ik;rh pik;e;in þ Eik;pgu Eik;grid;out þ pik;f 1 þ COPec gb i¼1 k¼1 ð26Þ ATCcogen ¼ R
n2 365 X 24 X X ðNk Pk;eq Þ þ ðF ik;pgu Pik;f 2 Þ
ð27Þ
i¼1 k¼1
k¼1
Fig. 3. Loading regime chart.
where R is the capital recovery factor [7], N is the installed power of equipment, Peq is the initial capital cost of each king of equipment, n1 is the number of equipments for the SP system, n2 is the number of equipments for the CCHP system, Pik,f2 is the price of natural gas for CCHP system, Pik,e,in is the price of electricity bought from the grid, and Pik,f1 is the price of natural gas for the boiler. The integrated performance of the cogeneration part can be expressed as:
Scogen ¼ W 1 PESRcogen þ W 2 CO2 ERRcogen þ W 3 ATCSRcogen
ð28Þ
where W1, W2 and W3 are the respective weights of PESR, CO2ERR and ATCSR respectively, which satisfy 0 6 W1, W2 ,W3 6 1 and W1 + W2 + W3 = 1. They are all set to be 1/3 in this study. 2.2.2. The whole CCHP evaluation The PESR of the whole CCHP system can be calculated following Eq. (29):
PESRwhole ¼
F SP:whole F whole 100% F SP;whole
ð29Þ Fig. 4. CCHP system minimum distance operation strategy.
where the FSP,whole and Fwhole can be calculated as:
F SP;whole ¼
E
ge ggrid
þ
Qc Q þ h COPec ge ggrid gb
F whole ¼ F pgu þ F b þ
Egrid;in
ge ggrid
ð30Þ
ð31Þ
The CO2ERR of the whole CCHP system can be calculated as:
CO2 ERRwhole ¼
CO2 ESP;whole CO2 Ewhole 100% CO2 ESP;whole
ð32Þ
where the CO2ESP,whole and CO2Ewhole can be calculated as:
CO2 ESP;whole ¼ lf
Qc þ le E þ gb COPec
Qh
CO2 Ewhole ¼ lf ðF pgu þ F b Þ þ le Egrid;in
ð33Þ ð34Þ
The ATCSR of the whole CCHP system can be calculated as:
ATCSRwhole ¼
ATCSP;whole ATCwhole 100% ATCSP;whole
ð35Þ
Fig. 5. Electric, cooling and heating load duration curves.
where the ATCSRSP,whole and ATCSRwhole can be calculated as:
ATCSP;whole
n1 X ¼R ðNk P k;eq Þ
ATCwhole ¼ R
k¼1
k¼1
365 X 24 X Q ik;c Q ik;h pik;e;in þ Eik þ pik;f 1 þ COPec gb i¼1 k¼1
n2 365 X 24 X X ðNk Pk;eq Þ þ ðEik;grid;in Pik;e;in þ F ik;b Pik;f 1
þ F ik;pgu Pik;f 2 Þ ð36Þ
i¼1 k¼1
ð37Þ
The integrated performance of the cogeneration part can be expressed as:
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Table 2 Main parameters employed for evaluation and analysis. Variable COP of electric chiller Boiler efficiency [20] Grid generation efficiency [20] Grid transmission efficiency [20] CO2 conversion factor of electricity from grid [20] CO2 conversion factor of natural gas [20] Low heat value of natural gas Favorable price of natural gasa Normal price of natural gasa Price of electricity on-peaka Price of electricity off-peaka a
Symbol Unit
Value
COPe
4.0 80.0 35.0 92.2 923 220 9.86 2.43 3.99 1.032 0.474
gb ge ggrid le lf LHV Pf1 Pf2 Pe,on Pe,off
– % % % g/kW h g/kW h kW h/m3 U/m3 U/m3 U/kW h U/kW h
These parameters are the energy price based on the policy of Shanghai [21,22].
Swhole ¼ W 1 PESRwhole þ W 2 CO2 ERRwhole þ W 3 ATCSRwhole
ð38Þ
where W1, W2 and W3 are the respective weights of PESR, CO2ERR and ATCSR respectively, which satisfy 0 6 W1, W2 ,W3 6 1 and W1 + W2 + W3 = 1. They are all set to be 1/3 in this study. 2.2.3. The matching performance The best matching performance between the CCHP system and the building is achieved when all of the building loads are satisfied by the cogeneration equipment while the cogeneration part maintain a high efficiency and no excess energy is produced. But this ideal situation cannot be achieved in the near future. Therefore, the matching performance can be divided into two aspects: (1) the efficiency and availability of the cogeneration equipment to satisfy the building load; (2) the contribution of the cogeneration equipment to satisfy the building load. According to the definition of Scogen, the Scogen can reflect the efficiency of the cogeneration equipment to satisfy the building load. With less excess energy, the higher efficiency of the cogeneration equipment, the higher
Fig. 6. The sum of the performances of the whole CCHP systems and the cogeneration part with PGU capacity of 1000 kW for all operation strategies.
Scogen would be. On the other hand, according to the definition of Swhole, the Swhole can reflect the contribution of the cogeneration equipment to satisfy the building load. When the performance of cogeneration equipment is better than that of the SP system, the more energy from the cogeneration equipment is used to satisfy the building load, the higher Swhole would be. As a consequence, the MP between the CCHP system and the building can be defined as:
MP ¼ e1 Swhole;normal þ e2 Scogen;normal
MP 2 ½0; 1
ð39Þ
where Sev,normal is the normalized value of Sev; e1 and e2 are the weights of Swhole,normal and Scogen,normal, respectively, which satisfy 0 6 e1, e2 6 1 and e1 + e2 = 1. They are set to be 0.5 in this study. The Min–max normalization method [19] is used in this analysis.
Table 3 Unit price of the facilities in the CCHP system [7]. Facility
PGU
Heating coil
Boiler
Absorption chiller
Electric chiller
Unit price, U/kW
6800
200
300
1200
970
Table 4 The MP of the CCHP system for different w1,above and w1,below. (PGUrated = 1000 kW). w1,above
a b c d e f g h
w1,below
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
0.62e 0.62 0.62 0.62 0.33 0.26 0.25 0.25 0.25 0.25 0.25
0.62 0.62 0.62 0.62 0.33 0.26 0.25 0.25 0.25 0.25 0.25
0.62 0.62 0.62 0.62 0.33 0.26 0.25 0.25 0.25 0.25 0.25
0.62 0.62 0.62 0.62 0.33 0.26 0.25 0.25 0.25 0.25 0.25
0.88a 0.88b,f 0.88c 0.88d 0.58 0.50 0.49 0.49 0.49 0.49 0.49
0.78 0.78 0.78 0.78 0.47 0.39 0.38 0.38 0.38 0.38 0.38
0.73 0.73 0.73 0.73 0.41 0.33 0.33 0.32 0.32 0.32 0.32
0.73 0.73 0.73 0.73 0.40 0.32 0.31 0.31 0.31 0.31 0.31
0.71 0.71 0.71 0.71 0.37 0.29 0.28 0.28 0.28 0.28 0.28
0.71 0.71 0.71 0.71 0.37 0.29 0.28 0.28 0.28 0.28 0.28
0.71g 0.71 0.71 0.71 0.37 0.29 0.28 0.28 0.28 0.28 0.28h
The The The The The The The The
number of significant number of significant number of significant number of significant MP of FEL strategy; MP of MD strategy; MP of FHL strategy; MP of FTL strategy.
digits digits digits digits
is is is is
eight: eight: eight: eight:
0.88055255. 0.88055268. 0.88055266. 0.88054769.
C.Y. Zheng et al. / Applied Energy 128 (2014) 325–335
2.3. Minimum distance (MD) operation strategy One of the challenges in CCHP system applications is the matching of thermal load and electrical load. For a CCHP system operating FEL and FTL, the least attractive times of operation occur when large amounts of excess heat and electricity are produced respectively. When a system operates following a hybrid electric-thermal load (FHL) [8], none of excess energy is produced. But the cogeneration part may not be made fully use to satisfy the demands of the building at this time. Here, an optimized operation strategy based on the minimum distance (MD) is developed in order to make the CCHP system fully use with less excess energy. The load point L (E, T) are determined by the electric demand E and the thermal energy demand T. The thermal energy thermal is calculated as:
T ¼ Qh þ
Qc COPac
331
above the curve l, the excess heat decreases but the electricity from the grid increases when w1,above changes from 0 to 1. However, for the load point below the curve l, the excess electricity increases but the supplement heat decreases when w1,below
(a)
ð40Þ
The models of FEL, FTL and FHL strategies have been stated by Mago et al. [8]. The model of MD strategy is stated in this paper as follow. According to Eqs. (1) and (8), the electricity generated by the PGU can be expressed as a function of the heat recovered and PGU efficiency:
Epgu ¼
gpgu;e Q gpgu;r r
ð41Þ
From Eqs. (1), (8), and (41), it is seen that the power generated is a nonlinear function of the recovered heat. In Fig. 3, the curve l represents a perfect match between thermal load and electrical load, which is found using Eq. (41). Because of the fluctuation of building loads, it is seldom for this operational line to be achieved. For that reason, the operation of the system should be following this line. In Fig. 3, point A and point B are typical cases of CCHP operation. The characteristics of the system operating FEL and FTL have already been described in [8]. According to Fig. 3, it is found that there are four kinds of distance from a certain load point to the energy supply curve l. DT+ and DT represent the supplement heat from the boiler and the excess heat respectively. Similarly, DE+ and DE represent the supplement electricity from the gird and the excess electricity respectively. Then the integrated distance can be expressed as:
Dsum ¼ w1 ðDTþ þ DT Þ þ w2 ðDEþ þ DE Þ
(b)
ð42Þ
where w1 and w2 are the respective weights of thermal and electric distance, which satisfy 0 6 w1, w2 6 1 and w1 + w2 = 1. Combining Fig. 4, the description of MD strategy can be described as follow: for a load point L (EL, TL), an operation point O (EO, TO) which minimizes Dsum can be found on the curve l, and then the point O is considered to be the operation point for this load point when the CCHP system operates under MD strategy. It should be highlighted here that when there are two operation points can minimizes the distance for a load point, the one with a higher part load factor would be selected. Fig. 4 shows the operation points of the CCHP system operating under MD with different weightings for point Labove, Lbelow. For point Labove, when w1,above = 0 and w2,above = 1, the system operates at point O0 and it runs FEL; when w1,above = 1 and w2,above = 0, the system operates at point O00 and it runs FTL. On the other hand, for point Lbelow, when w1,below = 0 and w2,below = 1, the system operates at point O00 and it runs FEL; when w1,below = 1 and w2,below = 0, the system operates at point O0 and it runs FTL. Then, the system operates at the points on curve l between point O0 and point O00 for the other weightings. It is said that the operation strategy can be changed by changing the weightings. It is important to notice that the effects of the same operation strategy for the load point above and below the curve l are different. For the load point
(c)
Fig. 7. Variations in Swhole (a), Scogen (b) and MP (c) for various w1,above (w1,below = 0) and PGU capacities.
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(a)
(b)
(d)
(c)
Fig. 8. Fraction of overall annual electric and thermal demand met by CCHP system, the ratio of waste heat to thermal demand and the annual generating efficiency for various w1,above (w1,below = 0) and PGU capacities.
changes from 0 to 1. It is said that w1,above and w1,below are two decision variables to optimize the operation strategy. Once the PGU capacity is determined, the distribution of the load points relative to the curve l is determined too. In other words, w1,above and w1,below are independent to optimize the operation strategy for a PGU capacity.
Based upon the energy load profiles, a CCHP system with optimized PGU capacity and operation strategy was developed by using the MD strategy and MP evaluation criterion. Besides, the performance of this CCHP system for the optimized operation strategy was comprised with that for FEL, FTL and FHL. 3.2. The performance of MD vs. that of FEL and FTL
3. Case study 3.1. Energy load profiles and input values This section presents the results obtained by using the models described in Section 2. A hospital in Shanghai, with a covered area of 70,488 m2, is as a case to be evaluated and analyzed. The peaks of the electric, cooling and heating loads of the building are 3910.5 kW, 2879.6 kW and 2529.7 kW, respectively. The cooling hours for summer are 2664 h, the heating hours for winter are 2688 h and the transition seasons are totally 3408 h. The hot water for the hospital to bath or cook is supplied in the whole year. The duration curve for the electric, cooling and heating loads are shown in Fig. 5. The main parameters employed for the evaluation and analysis are listed in Table 2. The installation costs are summarized in Table 3.
In order to compare MD operation strategy with FEL, FTL and FHL strategies, three aspects are taken into account: (1) the performance of the whole CCHP system; (2) the performance of the cogeneration part of the CCHP system; (3) the amount of excess heat and electricity. The PGU capacity is 1000 kW in this section. Table 4 shows that the MP of the CCHP system for different w1,above and w1,below. It can be observed that the best MP (0.88) is achieved when w1,above equals to 0.4 and w1,below equals to 0.1. Therefore, the MD strategy for 1000 kW PGU capacity is determined to be that w1,above equals to 0.4 and w1,below equals to 0.1. As shown in Table 4, when both w1,above and w1,below are equal to 0 (FEL strategy), the MP is 0.62; when both are equal to 1 (FTL strategy), the MP is 0.28; when w1,above equals to 1 and w1,below equals to 0 (FHL strategy), the MP is 0.71. The sum of the performances of the whole CCHP systems and the cogeneration part for
C.Y. Zheng et al. / Applied Energy 128 (2014) 325–335
333
(a)
(b)
Fig. 10. The ratio of excess electricity to electricity demand of the building for various w1,below (w1,above = 0) and PGU capacities.
(c) Fig. 11. Weightings w1,above and w1,below of the CCHP systems with the best MP for each PGU capacity.
3.3. Design of CCHP system based on MD and MP
Fig. 9. Variations in Swhole (a), Scogen (b) and MP (c) for various w1,below (w1,above = 0) and PGU capacities.
all operation strategies are shown in Fig. 6. It can be seen that MD presents the highest ATCSR and CO2ERR. Although the PESR of MD is lower than that of FHL, MD has the best performance in the integrated criterion S.
Fig. 7 shows the variations in Swhole, Scogen and MP of the CCHP systems for various w1,above and PGU capacities while w1,below equals to 0. From Fig. 7(a), it can be observed that the Swhole increases firstly, reaches the maximum value, then decreases with the increase of w1,above for all the PGU capacities. It is deduced that neither FEL nor FTL operation strategy can lead the best performance of the whole system for the load points above the energy supply curve in this case, but the operation strategy between them. The electric demand is relatively more than that of thermal in this case. As a consequence, the fraction of overall annual electric demand met by cogeneration part of FEL is much larger than that of FTL, as shown in Fig. 8(a). However, the difference of the fraction of thermal demand met by cogeneration part between FEL and FTL is small, as shown in Fig. 8(b). For these reasons, FEL strategy leads a better performance of the whole system than that of FTL, as shown in Fig. 7(a). From Fig. 7(b), it is shown that the Scogen increases with some fluctuation with the increase of w1,above when the PGU capacity is less than 1300 kW. At this time, the performance of cogeneration
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C.Y. Zheng et al. / Applied Energy 128 (2014) 325–335
Fig. 12. Variations in Swhole and Scogen of the CCHP systems with the best MP for each PGU capacity and the MP of them.
part for the system operating FTL is better than that operating FEL. However, when the PGU capacity is greater than 1300 kW, a reverse tendency is observed. The reason is that the ratio of waste heat to thermal demand of the building of FTL is much smaller than that of FEL, as shown in Fig. 8(c). The waste heat begins to decrease when w1,above excesses 0.3. The excess energy and generating efficiency are the key factors when evaluating the performance of the cogeneration part. From Fig. 8(d), it can be found that the generating efficiency of the PGU reaches maximum value when w1,above is equal to 0.4. For this reason, the performances of the whole system and the cogeneration part are sharply improved when w1,above is equal to 0.4, as shown in Fig. 7(a) and (b). The annual generating efficiency decreases sharply, when the PGU capacity is greater than 1300 kW, as shown in Fig. 8(d). It leads a worse Scogen of FTL, comparing to FEL, as shown in Fig. 7(b). The results deduced from Fig. 7(a) and (b) prove that the variations of Swhole and Scogen with weighting and PGU capacity are different. There is not an identical function between them. It is said that MP defined based on these two evaluation criteria is meaningful to evaluate the matching performance between CCHP system and the building. From Fig. 7(c), it is deduced that the MP of CCHP system for various PGU capacities are different. Moreover, it fluctuates with the weighting and has the maximum value. It can be observed that the best MP is achieved when w1,above is equal to 0.4 for all of these PGU capacities. The regions which are circled by ellipse in Figs. 7 and 8 reveal the reasons. The most important reason is that the annual generating efficiency reaches maximum value when w1,above is equal to 0.4. What’s more, from Figs. 7 and 8, it can be verified that the system, which cogeneration part satisfies as many demands of the building as possible with high efficiency and availability, would get a better MP. In other word, MP can reflect the matching performance between the CCHP system and the building in a good way. Fig. 9 shows the variations in Swhole, Scogen and MP of the CCHP systems for various w1,below and PGU capacities while w1,above equals to 0. From Fig. 9, it can be found that Swhole, Scogen and MP almost decrease with the increase of w1,below for all the PGU capacities. They decrease sharply when w1,below between 0.3 and 0.5. The reason is that the ratio of excess electricity to electricity demand of the building increases sharply in this region, as shown in Fig. 10. Comparing Fig. 7(c) with Fig. 9(c), it can be observed that the w1,above and w1,below which make the best MP are different.
As a consequence, in order to determine the PGU capacity and the corresponding operation strategy with the best MP, the following two steps should be taken: (1) find the weighting values w1,above and w1,below which makes the CCHP system has the best MP for each PGU capacity; (2) find the PGU capacity which has the best MP among the cases found in the first step. Fig. 11 shows the weightings of the CCHP systems with the best MP for each PGU capacity. It can be found that most of the systems with the maximum MP for different PGU capacities are not FEL or FTL, but the strategies between them. Fig. 12 shows the performances of the cases found in the first step. It can be observed that Swhole gradually increases, reaches the maximum value when the PGU capacity is 1300 kW , and then decreases with the increase of the capacity of the PGU. Meanwhile, the Scogen reaches the maximum value when PGU capacity is 200 kW, and then decreases with the increase of the capacity of PGU. As for MP, it goes up with the increase of PGU capacity. Then, it decreases when the PGU is beyond 900 kW. According to Figs. 11 and 12, it can be conclude that when the capacity of PGU is 900 kW and w1,above equals to 0.4, w1,below equals to 0.1, the CCHP system has the best MP in this case. 4. Conclusions This paper proposed a novel operation strategy for CCHP systems based on minimum distance. Besides, an integrated evaluation criterion was developed, which could be used to evaluate the matching performance between a CCHP system and a building. Then the CCHP system of a hospital in Shanghai was designed based on the MD operation strategy and MP evaluation criterion. Moreover, the CCHP system with MD operation strategy was compared with that under three operating modes including FEL, FTL and FHL. The results and analysis lead to the following conclusions: (1) All of FEL, FTL and FHL strategies cannot lead to the best matching performance between a CCHP system and a building for most situations. However, MD strategy can make a CCHP system operate between FEL and FTL mode by changing the weightings above and below the energy supply curve. MD strategy is a flexible and adaptable operation strategy, which can lead to the best matching performance of a CCHP system and a building.
C.Y. Zheng et al. / Applied Energy 128 (2014) 325–335
(2) The MP is an integrated evaluation criterion for considering the performance of both the whole system and the cogeneration part. It can reflect the matching performance between the CCHP system and the building in a good way. (3) The MD strategy and MP evaluation criterion can be used to determine the optimized PGU capacity and operation strategy for the CCHP system. In this case study, the optimized PGU capacity and weightings of the optimized operation strategy are 900 kW and w1,above equals to 0.4, w1,below equals to 0.1, respectively. MD presents the highest ATCSR and CO2ERR. Although the PESR of MD is lower than that of FHL, MD has the best performance in the integrated criterion S.
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