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Analysis of the integrated performance and redundant energy of CCHP systems under different operation strategies
Energy and Buildings 99 (2015) 231–242
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Energy and Buildings journal homepage: www.elsevier.com/locate/enbuild
Analysis of the integrated performance and redundant energy of CCHP systems under different operation strategies Longxi Li, Hailin Mu ∗ , Nan Li, Miao Li School of Energy and Power Engineering, Dalian University of Technology, Dalian 116023, China
a r t i c l e
i n f o
Article history: Received 23 December 2014 Received in revised form 10 February 2015 Accepted 19 April 2015 Available online 25 April 2015 Keywords: Operation strategies CCHP systems Integrated performance Redundant energy
a b s t r a c t Operation strategy is one of the critical factors that can affect the energy saving, economic, and environmental performance of a combined cooling, heating, and power (CCHP) system. This study models a CCHP system to investigate its annual total cost reduction, primary energy saving, and carbon dioxide emission reduction with respect to a reference system under five different operation strategies as follows: following the electric load (FEL), following the thermal load, following a hybrid electric–thermal load, following the seasonal operation strategy, and following the electric–thermal load of buildings (FLB). All the different operation strategies were optimized considering the part-load conditions for office and residential buildings in Dalian, China. The results indicate that the FLB and FEL yielded better performance than the other strategies. Furthermore, the redundant electricity and heat generated by CCHP systems were analyzed. The CCHP system operating under the strategies that produce less redundant electricity or heat may not yield better performance. However, the CCHP system operating under the strategies that produce huge redundant energy may achieve good integrated performance. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Combined cooling, heating, and power (CCHP) system is recognized as tri-generation that generates power, heating, and cooling to meet building demand. By placing the power generation unit (PGU) near the site or onsite, a CCHP system can utilize the waste heat expelled by PGU to generate thermal load. Moreover, a CCHP system is highly safe and flexible to be on or off grid [1,2]. A good CCHP system should save primary energy, be energy efficient, economic, and reduce pollution. In general, the above criteria, which are nondimensional analysis, have been used directly or indirectly to evaluate the performance of CCHP systems [3–15]. The performance of a CCHP system is determined according to its design. In the design phase of a CCHP system, operation strategy, which is one of the critical factors, should be taken into account. Different operation strategies could affect the sizes of equipment, and performances and configurations of CCHP systems. In other words, operation strategy governs the overall performance of a CCHP system. Typically, a CCHP system operates in one of the two modes: following the electric load (FEL) and following the thermal load (FTL) [16]. The two modes are also described as electric
∗ Corresponding author. Tel.: +86 411 84708095. E-mail address: [email protected] (H. Mu). http://dx.doi.org/10.1016/j.enbuild.2015.04.030 0378-7788/© 2015 Elsevier B.V. All rights reserved.
demand management (EDM) and thermal demand management (TDM). Numerous researchers have studied the FEL and FTL strategies to evaluate the performance of CCHP systems [4,9,17–22]. When the FEL is executed, the CCHP system will operate to meet the electricity demand of building first, and the additional thermal demand that the heat recovery system cannot afford is satisfied by an auxiliary boiler. On the other hand, if the CCHP system operates under FTL, the system will fulfil the thermal demand of building, and insufficient electricity will be supplied by local grid. Because of different loads of buildings and evaluation criteria, the FEL or FTL strategy yielded better performance than FTL or FEL, and the reference system [4,16]. Nevertheless, some researchers consider that the two basic operation strategies could not yield superior integrated performance at times. Therefore, other strategies based on the FEL and FTL strategies have been developed, such as minimum distance strategy [3] and compromised electric–thermal load strategy [5]. Moreover, two other strategies are known: one is following the seasonal operation strategy (FSS), and the other is following a hybrid electric–thermal load (FHL). The FSS strategy comprises two parts: FEL and FTL [8], defined by a novel parameter called LR, representing the ratio of monthly electric load to thermal load. If LR > 1, i.e., the monthly electric load is higher than the thermal load, the CCHP system will operate under FEL; otherwise, the system will operate following the thermal load.
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Nomenclature ATC ATCR CCHP CDE CDER EDM FEL FHL FLB FSS FTL GA LR NLR PES PGU TDM Symbols a, b, c C COP Crf E F f G Ir J n Q x y ˛, ˇ, ˇ1
annual total cost annual total cost reduction combined cooling, heating and power carbon dioxide emission carbon dioxide emission reduction electric demand management following the electric load following a hybrid electric–thermal load following the electric–thermal load of buildings following seasonal operation strategy following the thermal load genetic algorithm ratio of monthly electric load to thermal load ratio of hourly electric load to thermal load primary energy saving power generation unit thermal demand management coefficients of polynomial equation cost (¥/kW h) coefficient of performance capital recovery factor electricity (kW h) fuel consumption (kW h) ratio of electricity load to the maximum electricity output installed capacity of equipment (kW) interest rate integrated saving ratio service life of equipment thermal energy (kW h) ratio of electric chiller cooling to total cooling load switch node of NLR constant coefficients efficiency emission factor (g/kW h) ratio of the redundant energy of each strategy to the total redundant electricity and heat
Subscripts ab absorption chiller c cooling demand of buildings maximum electricity output cap e electricity ec electric chiller grid electricity grid heating demand of buildings h he heating exchanger type of equipment i max maximum output ng natural gas pgu power generation unit heat recovery system rec user use by buildings w redundant energy ε case operation strategy ϕ Superscript cc capital cost CCHP combined cooling, heating and power reference energy system RE
The result indicates that the FSS strategy has an advantage over FEL and FTL in the perspective of energy saving. In all the strategies reported in Ref. [8], FSS and FEL exhibited the best integrated performance. In Refs. [7,23], an optimized operation strategy, FHL, was applied. The PGU efficiency was assumed to be a constant and the linear relationship between the electricity produced by PGU and the heat recovered by the CCHP system was established. Therefore, the constant was used to determine whether the CCHP system operated following the electric load or thermal load. If a CCHP system operated following this strategy, the energy waste could be avoided under ideal conditions that the efficiency of PGU is constant. The CCHP system yielded the best performance in general offices under the FHL strategy than the FEL and FTL strategies. From the above literatures, it is evident that CCHP systems yielded the greatest savings, which are mainly dependent on operation strategy, loads of buildings, and nominal PGU capacity. In this study, the operation strategy “following the electric–thermal load of buildings” (FLB), which is based on the FSS strategy [8], has been applied to investigate the performance of the CCHP system. This study aims to analyze energy saving, and economic and environmental performance of the CCHP system under five different operation strategies in office and residential buildings. Moreover, redundant energy, i.e., excess electricity and heat produced by the CCHP system, has also been investigated. Section 2 describes the system configuration and analytical model. Three cases and simulation parameters used in the mathematical model are presented in Section 3. Moreover, the results optimized by genetic algorithm (GA) are analyzed in Section 4. Finally, the conclusion is summarized in Section 5. 2. Analysis methodology 2.1. System description To compare with the CCHP system, a typical reference system is shown in Fig. 1. The electricity, heating, and cooling demands in the reference system are provided by the local utility grid, gas boiler, and electric cooling system, respectively. The schematic of the modeled CCHP system is shown in Fig. 2. Electricity is provided by the gas-fired PGU and local utility grid. The waste heat discharged from PGU is recovered by the heat recovery system, which supplies thermal energy to an absorption chiller and a heating exchanger. The cooling demand of buildings is satisfied by the absorption chiller and electric chiller. Space heating and domestic hot water demand is provided by the heating exchanger. When the heat recovery system cannot afford the thermal demand, an auxiliary boiler is used to provide the additional heat. The construction of the CCHP system is applicable to the following five operation strategies. 2.2. Analytical model In this section, the models for the CCHP system under five operation strategies are explained. The basic constraints about energy consumption balance and PGU efficiency curve fitting are described. Moreover, five distinctive operation strategies and evaluation criteria are described and defined. 2.2.1. Basic constraints When a CCHP system operates following the five operation strategies, the electrical or thermal energy balance needs to be satisfied. The electrical energy balance can be described as follows: Euser + Eec = Epgu + Egrid
(1)
L. Li et al. / Energy and Buildings 99 (2015) 231–242
Fig. 1. Schematic of the proposed reference system.
Fig. 2. Schematic of the modeled CCHP system.
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where Euser is the electricity consumed by users, Eec is the electricity consumed by electric chiller, Epgu is the electricity generated by PGU, and Egrid is the electricity provided by the utility grid. The fuel consumption by PGU, Fpgu , can be calculated using the following equation: Fpgu =
Epgu pgu
(2)
where pgu is the efficiency of PGU. As a part-load operation, the PGU efficiency, which varies according to the PGU load, can be expressed as follows [6]: pgu = a + bf + cf 2 f =
(4)
where a, b, and c are constant coefficients as reported in Ref. [6], f is the ratio of PGU load to the maximum electricity output of PGU, and Ecap is the maximum electricity output of PGU. For the PGU with an internal combustion engine, Cho et al. established a common linear relationship between the fuel consumption and electricity generated by PGU [24], and examined a variety of PGUs [25]. It is widely used to study the CCHP systems [14,21,25–27] and estimated as follows: Fpgu = ˛ × Epgu + ˇ
(5)
Also, it can be replaced by Fpgu = ˛ × f + ˇ1 Ecap
Qc − x × Qc Q = + h ab he
⎩
(8)
Qec = Eec × COPec
(9)
where Qrec is the recovered waste heat from PGU, Qboiler is the heat generated from the auxiliary boiler, Qc is the cooling demand, Qh is the heating demand, x is the ratio of electric cooling to the total cooling load [12], ab and he are the efficiencies of absorption chiller and heating exchanger, Qec is the cooling load produced by the electric chiller, and COPec is the coefficient of the performance of electric chiller. In this study, the heating demand includes the space heating load and domestic hot water load, which are assumed to share the same efficiency of the boiler and heating exchanger. The recovered heat can be estimated as follows:
Qrec = Fpgu − Epgu × rec
(10)
where rec is the efficiency of the heat recovery system. Based on Eq. (6), there is a linear relationship between Qrec and Epgu , which can be expressed as follows:
Qrec = ˛ × Epgu − Epgu + ˇ1 × Ecap × rec
(11)
2.2.2. Operational strategies Five operational strategies are discussed, such as following the electric load, following the thermal load, following a hybrid electric–thermal load, following the seasonal operation strategy, and following the electric–thermal load of buildings.
0 ≤ f < 25%
Euser + Eec ,
25% ≤ f ≤ 100%
Ecap ,
100% < f
⎫ ⎬
(12)
⎭
where the threshold, 25%, is assumed to be the on–off coefficient [6,28]. If PGU cannot satisfy the electricity demand, electricity from the utility grid is supplied to the buildings. Therefore,
Egrid =
Euser + Eec − Epgu ,
Euser + Eec > Epgu
0,
otherwise
(13)
Under the FEL strategy, the thermal load is satisfied using a heat recovery system and an auxiliary gas boiler in the CCHP system. The gas consumption of the boiler, Fboiler , can be calculated using the following equation:
Qboiler =
⎧ ⎨ (Qc − x × Qc ) + ⎩
ab
Qh − Qrec , he
0,
⎫
Qh (Qc − x × Qc ) + > Qrec ⎬ ab he
⎭
otherwise
(14)
Fboiler =
(7)
Qec x= Qc
Epgu =
⎧ ⎨ 0,
(6)
where ˛, ˇ,and ˇ1 are constant coefficients. ˛ and ˇ1 can be estimated using Eqs. (2)–(6). The linear relationship between fuel consumption and electricity output from PGU is presented in Section 3.2 (Fig. 6). The thermal balance of the CCHP system can be expressed as follows:
2.2.2.1. Following the electric load For the FEL strategy, the CCHP system operates using Eq. (1) to meet the electricity demand. Because of the low efficiency of PGU, the CCHP system could not achieve a satisfactory integrated performance. Therefore, the CCHP system operates in a cutoff scenario in this study. The on–off status is shown as follows:
(3)
Epgu Ecap
Qrec + Qboiler
Two basic operation strategies, FEL and FTL, have been frequently studied by researchers. Moreover, two strategies, FHL and FSS, have been developed based on FEL and FTL. FLB is a novel operation strategy presented in this study.
Qboiler b
(15)
where b is the efficiency of the boiler. Importantly, redundant heat, which is the excess heat generated by the CCHP system under the FEL strategy and discharged into atmosphere, can be expressed as follows: Qw = Qrec −
Q (Qc − x × Qc ) − h ab he
(16)
where Qw is the redundant heat generated by the CCHP system. Therefore, the total energy consumption under the FEL strategy, CCHP , can be estimated using the following equation: FFEL CCHP FFEL = Fpgu + Fboiler +
Egrid
(17)
e grid
where e is the electricity generation efficiency of the grid and grid is the transmission efficiency of the utility grid. 2.2.2.2. Following the thermal load For the FTL strategy, the CCHP system should operate using Eq. (7) to satisfy the thermal load. Similarly to the FEL strategy, a low PGU efficiency could reduce the overall performance of a CCHP system. Therefore, the part-load operation of the CCHP system under the FTL strategy was considered and differed significantly from the earlier studies, whose efficiency of PGU was constant when the CCHP system operated under the FTL strategy. Based on the satisfaction of the thermal demand, the electricity generated by PGU, Ereq , can be calculated using Eq. (11) as follows:
Ereq =
(Qc − x × Qc )/ab rec + Qh /he rec − ˇ1 × Ecap ˛−1
(18)
L. Li et al. / Energy and Buildings 99 (2015) 231–242
235
Fig. 3. Optimization procedure of the CCHP system.
Table 1 Three simulation cases with two types of building combinations. Floor area of buildings (m2 )
Cases
Office Case 1 Case 2 Case 3
60,000 0 30,000
Residence 0 60,000 30,000
The operational constraints under the FTL strategy can be described as follows: Epgu =
⎧ ⎨ 0, ⎩
0 ≤ f < 25%
Ereq ,
25% ≤ f ≤ 100%
Ecap ,
100% < f
⎫ ⎬ ⎭
to provide additional heat. Therefore, the expressions of Qboiler and Fboiler are the same as Eqs. (14) and (15). The electricity from utility grid can be expressed as Eq. (13). Redundant electricity, Ew , which is the surplus electricity produced by PGU under the FTL strategy can be estimated as follows: Ew = Epgu − Euser − Eec
CCHP , can be Furthermore, the total energy consumption, FFTL expressed as follows:
CCHP FFTL = Fpgu + Fboiler +
(19)
where f is defined as the ratio of Ereq to Ecap under the FTL strategy. If the heat recovery system cannot satisfy the thermal demand of buildings when Epgu = 0 or Epgu = Ecap , an auxiliary boiler is used
(20)
Egrid e grid
(21)
2.2.2.3. Following a hybrid electric–thermal load The CCHP system operated under FEL and FTL strategies produced a large amount of redundant heat or electricity. Mago et al. [23] achieved a better performance using the FHL strategy than FEL
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Fig. 4. Heating, cooling, and electricity demands of office buildings.
Fig. 5. Heating, cooling, and electricity demands of residential buildings.
and FTL. They found a relationship between electricity generated by PGU and recovered heat, which can be expressed as follows: Epgu =
pgu
rec 1 − pgu
Qrec
(22)
The pgu has been assumed as a constant value to determine whether the CCHP system operates under FEL or FTL. However, under the part-load scenario, pgu cannot be deduced without the electricity output and nominal capacity of PGU. Therefore, in this study, FHL was modified by switching between FEL and FTL based on the principle of no redundant electricity and heat, and can be calculated by Eqs. (16) and (20). No superfluous
electricity or heat is produced by PGU. The procedure of a new FHL strategy can be represented as follows:
text conditions FHL = FTL Ew
Ew ≤ 0,
FTL
Ew > 0,
FEL
(23)
Eq. (23) also can be expressed as follows:
text conditions FHL = FEL Qw
Qw ≤ 0,
FEL
Qw > 0,
FTL
(24)
This indicates that the CCHP system operates following the thermal load or following the electric load first and then switches to the
L. Li et al. / Energy and Buildings 99 (2015) 231–242
Fig. 6. Linear relationship between Fpgu /Ecap and f
Table 2 Coefficients and goodness of fit. Function Fpgu Ecap
Coefficients
= ˛ × f + ˇ1
˛ = 2.578 ˇ1 = 0.7027
Epgu /Ecap .
Table 3 Input values for CCHP system and reference system simulation. SSE
0.007384
R-square
0.9987
Adjusted R-square
RMSE
0.9986
0.02297
Item
Parameter
Symbol
CCHP system [6]
Coefficient of performance of absorption chiller Efficiency coefficients of PGU
COPab
other strategy if redundant electricity or heat is produced, as Ew > 0 or Qw > 0. Therefore, Ew and Qw are always less than or equal to 0 under the FHL strategy. 2.2.2.4. Following the seasonal operation strategy In the seasonal operation strategy, a parameter named the load ratio LR is defined [8] as follows: LR =
237
monthly electric load monthly thermal load
Reference energy system [6]
(25)
If LR < 1, the CCHP system operates under the FTL strategy during the month. In contrast, the system operates under the FEL strategy. Under the FSS strategy, the CCHP system reported in Ref. [8] achieved a better primary energy saving performance than FEL and FTL; however, there is no economic and environmental merit.
Unit price of equipment [11] (¥/kW)a Emission factor [11,27] (g/kW h) a
Efficiency of boiler Efficiency of heating exchanger Efficiency of heat recovery system Live time of equipment, year Coefficient of performance of electric chiller Efficiency of boiler Efficiency of heating exchanger Generation efficiency Transmission efficiency of electric grid Absorption chiller Electric chiller Boiler Power generation unit Electricity emission factor Natural gas emission factor
1 ¥ = 0.16 $ (US dollar).
2.2.2.5. Following the electric–thermal load of buildings In this paper, the LR in Eq. (25) is redefined as follows: NLR =
hourly electric load hourly thermal load
(26)
According to Eq. (25), the switch node, 1, is changed to an optimized value, y. If NLR < y, the CCHP system operates following the thermal load during that hour. Otherwise, the system operates following the electric load. 2.3. Evaluation criteria The performance of a CCHP system compared to the reference system under different operation strategies can be evaluated in terms of annual total cost reduction (ATCR), primary energy saving (PES), and carbon dioxide emission reduction (CDER). The ATCR, PES, and CDER can be expressed as the following equations: ATCR =
ATCRE − ATCCCHP ATCRE
(27)
Table 4 Parameters of genetic algorithm. Parameter
Value
Number of individuals Maximum generation Precision of variables Generation gap Crossover probability Mutation probability
60 100 20 0.9 0.7 0.01
Search field PGU capacity (kW) x y
0–2000 0–1 0–100
Value 0.7
a b c b he rec
0.1 0.4 −0.2 0.8 0.8 0.8
n COPec
20 3
b he e grid Cicc
grid ng
0.8 0.8 0.35 0.92 1200 970 300 6800 1200 220
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L. Li et al. / Energy and Buildings 99 (2015) 231–242
Fig. 7. Time of use tariff for office buildings.
Fig. 8. Graduated power tariff for residential buildings.
PES =
F RE − F CCHP F RE
CDER =
(28)
CDERE − CDECCHP
(29)
CDERE
where ATC is the annual total cost, F is the total energy consumption, and CDE is the carbon dioxide emission. ATC, F, and CDE are specified in the following equations. ATC = Crf ×
i
Cicc × Gi +
charge of natural gas and grid electricity, respectively. Crf is the capital recovery factor, which can be computed as follows:
hour
×Cng + Egrid,hour × Ce,hour
Fboiler + Fpgu
(30)
where i is the type of equipment, Cicc is the capital cost of equipcap ment, Gi is the nominal capacity, and Cng and Ce,hour are the hourly
Crf = Ir ×
1+
1
(31)
(1 + Ir )n − 1
where Ir is the interest rate, n is the service life of equipment. It is assumed that all types of equipment have the same value of Ir and n. FCCHP was calculated using Eqs. (17) and (21), and FRE is the total energy consumption of the reference system, which can be expressed as follows: F RE =
Euser + EpRE + Qc /COPec e grid
+
Qh /he b
CDE = (Fpgu + Fboiler ) × ng + Egrid × grid
(32) (33)
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Fig. 9. Performance of CCHP systems in office buildings.
239
Fig. 11. Performance of CCHP systems in complex buildings.
Genetic algorithm was applied to solve the optimal problems. The procedure of optimization by GA is shown in Fig. 3. 3. Case study 3.1. Energy load profiles
Fig. 10. Performance of CCHP systems in residential buildings.
where ng and grid are the emission factors of natural gas and grid electricity, respectively. 2.4. Solution method
In Dalian, many mixed areas comprising office and residential buildings exist within neighboring districts. The occupancy rate of residential buildings is relatively low during the working time, whereas that of the office buildings is opposite. Therefore, an obvious difference exists between the load demand of office and residential buildings. Moreover, the demand load characteristics of buildings could affect the performance of different operation strategies in the CCHP system. For comparing more different buildings loads, two types of buildings and three cases have been assumed as shown in Table 1. Hypothetical office and residential buildings were simulated in Dalian, which is located at a latitude of 39.03◦ N and a longitude of 121.46◦ W. Both the thermal and electricity demands of the above buildings fluctuated hourly in the entire year. The heating, cooling, and electricity demands of the hypothetical buildings are the same as that reported in Ref. [15]. The demands of the buildings with a floor area of 60,000 m2 are shown in Figs. 4 and 5. 3.2. Simulation parameters
The weight method was applied in this paper to analyze multiple objective issues. The integrated performance of the CCHP system can be estimated as follows: Jmax = ı1 × ATCR + ı2 × PES + ı3 × CDER
(34)
where ı1 , ı2 , and ı3 are the weights of ATCR, PES, and CDER, respectively. In this paper, the three weights are all considered to be equal to 1/3 [3,11].
For reasonable results, the nonlinear efficiency of PGU has been studied considering the part-load scenario. A common linear relationship exists between the fuel consumption and electricity generated by PGU [25]. The curve fitting of the functional relationship is shown in Fig. 6. The black points were computed using Eqs. (2) and (3), and the blue line was fitted using Eq. (6). The coefficients and goodness of fit were applied to the following calculation, as shown in Table 2.
Table 5 Ratios of the redundant energy of different strategies to the total redundant electricity and heat in each case. Cases
Case 1 (ε = 1) Case 2 (ε = 2) Case 3 (ε = 3)
Ratios of the redundant energy, ε,ϕ FEL (ϕ = 1) (%)
FTL (ϕ = 2) (%)
FHL (ϕ = 3)
FSS (ϕ = 4) (%)
FLB (ϕ = 5) (%)
Summation (%)
32.35 29.55 27.80
2.56 13.08 11.14
0 0 0
32.58 28.05 33.23
32.51 29.32 27.83
100 100 100
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The simulation parameters applied in this study are shown in Table 3. Among them, the efficiency coefficient of PGU and the efficiency of other equipment in CCHP and reference system are derived from Ref. [6], the unit price of equipment is reported in Ref. [11] and emission factor is reported in Refs. [11,27]. The tariff of natural gas is 0.22 ¥/kW h for all the users. Moreover, the office and residential buildings adopt the time of use tariff and graduated power tariff in Dalian, respectively. The tariff structures are shown in Figs. 7 and 8. The parameters of genetic algorithm are listed in Table 4. 4. Results 4.1. Performance of different operation strategies To study different operation strategies, three criteria comprising the annual total cost reduction, primary energy saving ratio, and carbon dioxide emission reduction of the CCHP systems were analyzed under three cases, as shown in Figs. 9–11. This shows that FLB and FEL are superior to other operation strategies in all the three cases. In case 1, the integrated saving ratios (‘J’ in Figs. 9–11) of the CCHP systems under FEL, FTL, FHL, FSS, and FLB were 22.92%, 13.47%, 13.72%, 21.15%, and 23.12%, respectively. Fig. 9 shows that the FLB strategy yields the best integrated performance, and FLB and FEL showed relatively better performance in all the three evaluation criteria. The ATCR and CDER of the CCHP systems operating under FLB and FEL are almost double than those under FTL and FHL. This is because the CCHP systems operating under the two strategies consume less grid electricity than the other strategies. Because the tariff and carbon dioxide emission factor of grid electricity are higher than those of natural gas under equivalent conditions, the operational cost and carbon dioxide emission of the CCHP system can be relatively reduced. Irrespective of the operation strategy, the residential buildings have a relatively lower ATCR than case 1 shown in Fig. 10. The main reason is the unbalanced ratio of the electricity demand to the thermal demand of residential buildings. It can result in the electricity from grid accounting for a large proportion in electricity consumption under the five strategies. In case 2, the gap of integrated saving ratios among the five strategies is not large. Under the FLB and FEL
strategies, the integrated performance of the CCHP systems yields the highest saving ratios, equal to 12.04%. The CCHP system under FTL still achieved a poor saving ratio of 9.53%. Obviously, the CCHP system under the FHL strategy has the biggest economic merits in residential buildings based on the current evaluation criteria. In case 3, same as case 1, the best operation strategy is FLB. Fig. 11 shows that the saving ratios of the CCHP systems under FLB and FEL are 23.91% and 23.89%, respectively, providing better performance in terms of energy saving and economic and environmental merits among the five strategies in complex buildings. Clearly, the CCHP system operating under the FTL strategy yields the poorest integrated performance in all the three cases. In general, in the CCHP system under either strategy in either case, the environmental benefit is notable than the reference energy system. It can be concluded that the FLB is the best operation strategy in all the three cases. The switch nodes of NLR in the three cases, y, are 3.97%, 0.25%, and 3.46%, respectively. According to Eq. (23), it can be deduced that if the CCHP system operates under FLB, the FEL strategy accounts for a large part of the entire year operation. Owing to the electricity and thermal load profiles of buildings, the FEL strategy is more suitable than FTL in most of the operating time. Therefore, it is the main cause of minor differences in the integrated saving ratios between FLB and FEL in the present study. 4.2. Redundant energy of CCHP systems under different operation strategies Based on the current policy in China and assumption in the present study, the surplus electricity and heat cannot be transferred back to the grid or other users. Therefore, the redundant energy of the CCHP systems, comprising redundant electricity and heat, was analyzed under the five operation strategies. To study the redundant energy of the CCHP systems, the ratios of the redundant energy of different strategies to the total redundant electricity and heat in each case (the same load characteristics), , can be expressed as the following equation: ε,ϕ =
Ew,ε,ϕ + Qw,ε,ϕ
Ew,ε,ϕ + Qw,ε,ϕ
ϕ
Fig. 12. Ratios of grid electricity consumption to total gas consumption.
(35)
L. Li et al. / Energy and Buildings 99 (2015) 231–242
where Qw and Ew are calculated using Eqs. (16) and (20), ε indicates the cases, and ϕ indicates the operation strategies. The results are shown in Table 5. The CCHP systems operating under the operation strategies that produce less redundant energy may not yield better performance in all the three cases, as FTL and FHL. However, the CCHP systems under FLB and FEL that achieve good integrated performance generate the huge redundant energy. For example, no redundant energy (Qw = 0, Ew = 0) was obtained when the CCHP system operated under the FHL strategy. However, Figs. 9–11 show that the integrated performance of the FHL strategy is poor. Most agree that little redundant energy will promote the primary energy saving ratio or integrated performance; however, the result turns out to be the opposite. Although the FHL strategy did not provide redundant energy in all the three cases, the integrated performance was not good. It is important to highlight here that if the CCHP system operates under the FHL strategy, to avoid redundant energy production, the system will supplement the rest of electricity and heat through a reference energy system (Fig. 1), which obtains electricity from the utility grid and generates heat from the boiler. In contrast to the other strategies, the gas consumption of PGU was reduced, and the ratio of grid electricity consumption to the total gas consumption increased. The consumption ratios of the CCHP systems under different operation strategies are shown in Fig. 12, exhibiting the reverse trend with the integrated performance shown in Figs. 9–11. The high grid electricity consumption ratio is one reason why the CCHP system yields poor integrated performance. Moreover, the little redundant energy results in a high grid electricity consumption ratio based on the current electricity and thermal demand of buildings. Therefore, the CCHP system operating under the FHL strategy yields poor energy and economic and environmental performance. In brief, the redundant energy cannot be a criterion to evaluate the CCHP system, and no direct connection exists between the integrated performance and redundant energy under the current CCHP system configuration.
5. Conclusions This study analyzed the performance of combined cooling, heating, and power systems based on annual total cost reduction, primary energy saving and carbon dioxide emission reduction, and the redundant electricity and heat under different conditions. Five operation strategies such as following the electric load, following the thermal load, following a hybrid electric–thermal load, following the seasonal operation strategy, and following the electric–thermal load of buildings were evaluated in CCHP systems, which provided the electricity, heating and cooling load to office buildings, residential buildings, and the complex of office and residential buildings. The conclusions can be drawn as follows: The FLB strategy yielded the best integrated performance, and the CCHP systems under the FLB and FEL strategies achieved relatively better performance in all the three cases. However, the FTL strategy yielded the poorest integrated performance in all the three cases. In office buildings, the saving ratios of the integrated performance under FLB and FEL were 23.12% and 22.92%, respectively. In residential buildings, under FLB and FEL strategies, the CCHP systems yielded the highest integrated saving ratios, equal to 12.04%. The CCHP system under the FHL strategy has the biggest economic merits in residential buildings. In complex buildings, the saving ratios of the CCHP systems under FLB and FEL strategies were 23.91% and 23.89%, respectively. The switch nodes of the FLB strategy in the three cases, y, were 3.97%, 0.25%, and 3.46%, respectively. Therefore, if the CCHP system operates under FLB, the FEL strategy accounts for a large part of the
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entire year operation based on the current load profiles of buildings. This is the main reason of the minor differences in the integrated saving ratios between FLB and FEL in the present study. The redundant energy of CCHP systems was analyzed under five different operation strategies. The CCHP systems operating under the operation strategies that produce less redundant energy may not yield better performance in all the three cases, as FTL and FHL. However, the CCHP systems under FLB and FEL that achieve good integrated performance are accompanied with a huge redundant energy. It can be deduced that the redundant energy cannot be a criterion to evaluate CCHP systems under the current CCHP system configuration. Acknowledgement The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China (71273039). References [1] D.W. Wu, R.Z. Wang, Combined cooling, heating and power: a review, Prog. Energy Combust. Sci.V 32 (5–6) (2006) 459–495. [2] M. Jradi, S. Riffat, Tri-generation systems: energy policies, prime movers, cooling technologies, configurations and operation strategies, Renewable Sustainable Energy Rev. 32 (0) (2014) 396–415. [3] C.Y. Zheng, J.Y. Wu, X.Q. Zhai, A novel operation strategy for CCHP systems based on minimum distance, Appl. Energy 128 (0) (2014) 325–335. [4] J.-J. Wang, Y.-Y. Jing, C.-F. Zhang, Z. Zhai, Performance comparison of combined cooling heating and power system in different operation modes, Appl. Energy 88 (12) (2011) 4621–4631. [5] G. Han, S. You, T. Ye, P. Sun, H. Zhang, Analysis of combined cooling, heating, and power systems under a compromised electric–thermal load strategy, Energy Build. 84 (0) (2014) 586–594. [6] M. Liu, Y. Shi, F. Fang, A new operation strategy for CCHP systems with hybrid chillers, Appl. Energy 95 (0) (2012) 164–173. [7] P.J. Mago, L.M. Chamra, J. Ramsay, Micro-combined cooling, heating and power systems hybrid electric–thermal load following operation, Appl. Therm. Eng. 30 (8–9) (2010) 800–806. [8] P.J. Mago, A.K. Hueffed, Evaluation of a turbine driven CCHP system for large office buildings under different operating strategies, Energy Build. 42 (10) (2010) 1628–1636. [9] M. Ebrahimi, A. Keshavarz, Sizing the prime mover of a residential microcombined cooling heating and power (CCHP) system by multi-criteria sizing method for different climates, Energy 54 (0) (2013) 291–301. [10] A.A. Knizley, P.J. Mago, A.D. Smith, Evaluation of the performance of combined cooling, heating, and power systems with dual power generation units, Energy Policy 66 (0) (2014) 654–665. [11] J. Wang, Z. Zhai, Y. Jing, C. Zhang, Particle swarm optimization for redundant building cooling heating and power system, Appl. Energy 87 (12) (2010) 3668–3679. [12] J.-J. Wang, Y.-Y. Jing, C.-F. Zhang, Optimization of capacity and operation for CCHP system by genetic algorithm, Appl. Energy 87 (4) (2010) 1325–1335. [13] P.J. Mago, A.D. Smith, Evaluation of the potential emissions reductions from the use of CHP systems in different commercial buildings, Build. Environ. 53 (0) (2012) 74–82. [14] M. Hu, H. Cho, A probability constrained multi-objective optimization model for CCHP system operation decision support, Appl. Energy 116 (0) (2014) 230–242. [15] L. Li, H. Mu, W. Gao, M. Li, Optimization and analysis of CCHP system based on energy loads coupling of residential and office buildings, Appl. Energy 136 (0) (2014) 206–216. [16] P.J. Mago, N. Fumo, L.M. Chamra, Performance analysis of CCHP and CHP systems operating following the thermal and electric load, Int. J. Energy Res. 33 (9) (2009) 852–864. [17] S. Sanaye, N. Khakpaay, Simultaneous use of MRM (maximum rectangle method) and optimization methods in determining nominal capacity of gas engines in CCHP (combined cooling, heating and power) systems, Energy 72 (0) (2014) 145–158. [18] X. Teng, X. Wang, Y. Chen, W. Shi, A simple method to determine the optimal gas turbine capacity and operating strategy in building cooling, heating and power system, Energy Build. 80 (0) (2014) 623–630. [19] W. Jiang-Jiang, Z. Chun-Fa, J. You-Yin, Multi-criteria analysis of combined cooling, heating and power systems in different climate zones in China, Appl. Energy 87 (4) (2010) 1247–1259. [20] Y.-Y. Jing, H. Bai, J.-J. Wang, L. Liu, Life cycle assessment of a solar combined cooling heating and power system in different operation strategies, Appl. Energy 92 (0) (2012) 843–853. [21] A. Smith, R. Luck, P.J. Mago, Analysis of a combined cooling, heating, and power system model under different operating strategies with input and model data uncertainty, Energy Build. 42 (11) (2010) 2231–2240.
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Energy and Buildings journal homepage: www.elsevier.com/locate/enbuild
Analysis of the integrated performance and redundant energy of CCHP systems under different operation strategies Longxi Li, Hailin Mu ∗ , Nan Li, Miao Li School of Energy and Power Engineering, Dalian University of Technology, Dalian 116023, China
a r t i c l e
i n f o
Article history: Received 23 December 2014 Received in revised form 10 February 2015 Accepted 19 April 2015 Available online 25 April 2015 Keywords: Operation strategies CCHP systems Integrated performance Redundant energy
a b s t r a c t Operation strategy is one of the critical factors that can affect the energy saving, economic, and environmental performance of a combined cooling, heating, and power (CCHP) system. This study models a CCHP system to investigate its annual total cost reduction, primary energy saving, and carbon dioxide emission reduction with respect to a reference system under five different operation strategies as follows: following the electric load (FEL), following the thermal load, following a hybrid electric–thermal load, following the seasonal operation strategy, and following the electric–thermal load of buildings (FLB). All the different operation strategies were optimized considering the part-load conditions for office and residential buildings in Dalian, China. The results indicate that the FLB and FEL yielded better performance than the other strategies. Furthermore, the redundant electricity and heat generated by CCHP systems were analyzed. The CCHP system operating under the strategies that produce less redundant electricity or heat may not yield better performance. However, the CCHP system operating under the strategies that produce huge redundant energy may achieve good integrated performance. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Combined cooling, heating, and power (CCHP) system is recognized as tri-generation that generates power, heating, and cooling to meet building demand. By placing the power generation unit (PGU) near the site or onsite, a CCHP system can utilize the waste heat expelled by PGU to generate thermal load. Moreover, a CCHP system is highly safe and flexible to be on or off grid [1,2]. A good CCHP system should save primary energy, be energy efficient, economic, and reduce pollution. In general, the above criteria, which are nondimensional analysis, have been used directly or indirectly to evaluate the performance of CCHP systems [3–15]. The performance of a CCHP system is determined according to its design. In the design phase of a CCHP system, operation strategy, which is one of the critical factors, should be taken into account. Different operation strategies could affect the sizes of equipment, and performances and configurations of CCHP systems. In other words, operation strategy governs the overall performance of a CCHP system. Typically, a CCHP system operates in one of the two modes: following the electric load (FEL) and following the thermal load (FTL) [16]. The two modes are also described as electric
∗ Corresponding author. Tel.: +86 411 84708095. E-mail address: [email protected] (H. Mu). http://dx.doi.org/10.1016/j.enbuild.2015.04.030 0378-7788/© 2015 Elsevier B.V. All rights reserved.
demand management (EDM) and thermal demand management (TDM). Numerous researchers have studied the FEL and FTL strategies to evaluate the performance of CCHP systems [4,9,17–22]. When the FEL is executed, the CCHP system will operate to meet the electricity demand of building first, and the additional thermal demand that the heat recovery system cannot afford is satisfied by an auxiliary boiler. On the other hand, if the CCHP system operates under FTL, the system will fulfil the thermal demand of building, and insufficient electricity will be supplied by local grid. Because of different loads of buildings and evaluation criteria, the FEL or FTL strategy yielded better performance than FTL or FEL, and the reference system [4,16]. Nevertheless, some researchers consider that the two basic operation strategies could not yield superior integrated performance at times. Therefore, other strategies based on the FEL and FTL strategies have been developed, such as minimum distance strategy [3] and compromised electric–thermal load strategy [5]. Moreover, two other strategies are known: one is following the seasonal operation strategy (FSS), and the other is following a hybrid electric–thermal load (FHL). The FSS strategy comprises two parts: FEL and FTL [8], defined by a novel parameter called LR, representing the ratio of monthly electric load to thermal load. If LR > 1, i.e., the monthly electric load is higher than the thermal load, the CCHP system will operate under FEL; otherwise, the system will operate following the thermal load.
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Nomenclature ATC ATCR CCHP CDE CDER EDM FEL FHL FLB FSS FTL GA LR NLR PES PGU TDM Symbols a, b, c C COP Crf E F f G Ir J n Q x y ˛, ˇ, ˇ1
annual total cost annual total cost reduction combined cooling, heating and power carbon dioxide emission carbon dioxide emission reduction electric demand management following the electric load following a hybrid electric–thermal load following the electric–thermal load of buildings following seasonal operation strategy following the thermal load genetic algorithm ratio of monthly electric load to thermal load ratio of hourly electric load to thermal load primary energy saving power generation unit thermal demand management coefficients of polynomial equation cost (¥/kW h) coefficient of performance capital recovery factor electricity (kW h) fuel consumption (kW h) ratio of electricity load to the maximum electricity output installed capacity of equipment (kW) interest rate integrated saving ratio service life of equipment thermal energy (kW h) ratio of electric chiller cooling to total cooling load switch node of NLR constant coefficients efficiency emission factor (g/kW h) ratio of the redundant energy of each strategy to the total redundant electricity and heat
Subscripts ab absorption chiller c cooling demand of buildings maximum electricity output cap e electricity ec electric chiller grid electricity grid heating demand of buildings h he heating exchanger type of equipment i max maximum output ng natural gas pgu power generation unit heat recovery system rec user use by buildings w redundant energy ε case operation strategy ϕ Superscript cc capital cost CCHP combined cooling, heating and power reference energy system RE
The result indicates that the FSS strategy has an advantage over FEL and FTL in the perspective of energy saving. In all the strategies reported in Ref. [8], FSS and FEL exhibited the best integrated performance. In Refs. [7,23], an optimized operation strategy, FHL, was applied. The PGU efficiency was assumed to be a constant and the linear relationship between the electricity produced by PGU and the heat recovered by the CCHP system was established. Therefore, the constant was used to determine whether the CCHP system operated following the electric load or thermal load. If a CCHP system operated following this strategy, the energy waste could be avoided under ideal conditions that the efficiency of PGU is constant. The CCHP system yielded the best performance in general offices under the FHL strategy than the FEL and FTL strategies. From the above literatures, it is evident that CCHP systems yielded the greatest savings, which are mainly dependent on operation strategy, loads of buildings, and nominal PGU capacity. In this study, the operation strategy “following the electric–thermal load of buildings” (FLB), which is based on the FSS strategy [8], has been applied to investigate the performance of the CCHP system. This study aims to analyze energy saving, and economic and environmental performance of the CCHP system under five different operation strategies in office and residential buildings. Moreover, redundant energy, i.e., excess electricity and heat produced by the CCHP system, has also been investigated. Section 2 describes the system configuration and analytical model. Three cases and simulation parameters used in the mathematical model are presented in Section 3. Moreover, the results optimized by genetic algorithm (GA) are analyzed in Section 4. Finally, the conclusion is summarized in Section 5. 2. Analysis methodology 2.1. System description To compare with the CCHP system, a typical reference system is shown in Fig. 1. The electricity, heating, and cooling demands in the reference system are provided by the local utility grid, gas boiler, and electric cooling system, respectively. The schematic of the modeled CCHP system is shown in Fig. 2. Electricity is provided by the gas-fired PGU and local utility grid. The waste heat discharged from PGU is recovered by the heat recovery system, which supplies thermal energy to an absorption chiller and a heating exchanger. The cooling demand of buildings is satisfied by the absorption chiller and electric chiller. Space heating and domestic hot water demand is provided by the heating exchanger. When the heat recovery system cannot afford the thermal demand, an auxiliary boiler is used to provide the additional heat. The construction of the CCHP system is applicable to the following five operation strategies. 2.2. Analytical model In this section, the models for the CCHP system under five operation strategies are explained. The basic constraints about energy consumption balance and PGU efficiency curve fitting are described. Moreover, five distinctive operation strategies and evaluation criteria are described and defined. 2.2.1. Basic constraints When a CCHP system operates following the five operation strategies, the electrical or thermal energy balance needs to be satisfied. The electrical energy balance can be described as follows: Euser + Eec = Epgu + Egrid
(1)
L. Li et al. / Energy and Buildings 99 (2015) 231–242
Fig. 1. Schematic of the proposed reference system.
Fig. 2. Schematic of the modeled CCHP system.
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where Euser is the electricity consumed by users, Eec is the electricity consumed by electric chiller, Epgu is the electricity generated by PGU, and Egrid is the electricity provided by the utility grid. The fuel consumption by PGU, Fpgu , can be calculated using the following equation: Fpgu =
Epgu pgu
(2)
where pgu is the efficiency of PGU. As a part-load operation, the PGU efficiency, which varies according to the PGU load, can be expressed as follows [6]: pgu = a + bf + cf 2 f =
(4)
where a, b, and c are constant coefficients as reported in Ref. [6], f is the ratio of PGU load to the maximum electricity output of PGU, and Ecap is the maximum electricity output of PGU. For the PGU with an internal combustion engine, Cho et al. established a common linear relationship between the fuel consumption and electricity generated by PGU [24], and examined a variety of PGUs [25]. It is widely used to study the CCHP systems [14,21,25–27] and estimated as follows: Fpgu = ˛ × Epgu + ˇ
(5)
Also, it can be replaced by Fpgu = ˛ × f + ˇ1 Ecap
Qc − x × Qc Q = + h ab he
⎩
(8)
Qec = Eec × COPec
(9)
where Qrec is the recovered waste heat from PGU, Qboiler is the heat generated from the auxiliary boiler, Qc is the cooling demand, Qh is the heating demand, x is the ratio of electric cooling to the total cooling load [12], ab and he are the efficiencies of absorption chiller and heating exchanger, Qec is the cooling load produced by the electric chiller, and COPec is the coefficient of the performance of electric chiller. In this study, the heating demand includes the space heating load and domestic hot water load, which are assumed to share the same efficiency of the boiler and heating exchanger. The recovered heat can be estimated as follows:
Qrec = Fpgu − Epgu × rec
(10)
where rec is the efficiency of the heat recovery system. Based on Eq. (6), there is a linear relationship between Qrec and Epgu , which can be expressed as follows:
Qrec = ˛ × Epgu − Epgu + ˇ1 × Ecap × rec
(11)
2.2.2. Operational strategies Five operational strategies are discussed, such as following the electric load, following the thermal load, following a hybrid electric–thermal load, following the seasonal operation strategy, and following the electric–thermal load of buildings.
0 ≤ f < 25%
Euser + Eec ,
25% ≤ f ≤ 100%
Ecap ,
100% < f
⎫ ⎬
(12)
⎭
where the threshold, 25%, is assumed to be the on–off coefficient [6,28]. If PGU cannot satisfy the electricity demand, electricity from the utility grid is supplied to the buildings. Therefore,
Egrid =
Euser + Eec − Epgu ,
Euser + Eec > Epgu
0,
otherwise
(13)
Under the FEL strategy, the thermal load is satisfied using a heat recovery system and an auxiliary gas boiler in the CCHP system. The gas consumption of the boiler, Fboiler , can be calculated using the following equation:
Qboiler =
⎧ ⎨ (Qc − x × Qc ) + ⎩
ab
Qh − Qrec , he
0,
⎫
Qh (Qc − x × Qc ) + > Qrec ⎬ ab he
⎭
otherwise
(14)
Fboiler =
(7)
Qec x= Qc
Epgu =
⎧ ⎨ 0,
(6)
where ˛, ˇ,and ˇ1 are constant coefficients. ˛ and ˇ1 can be estimated using Eqs. (2)–(6). The linear relationship between fuel consumption and electricity output from PGU is presented in Section 3.2 (Fig. 6). The thermal balance of the CCHP system can be expressed as follows:
2.2.2.1. Following the electric load For the FEL strategy, the CCHP system operates using Eq. (1) to meet the electricity demand. Because of the low efficiency of PGU, the CCHP system could not achieve a satisfactory integrated performance. Therefore, the CCHP system operates in a cutoff scenario in this study. The on–off status is shown as follows:
(3)
Epgu Ecap
Qrec + Qboiler
Two basic operation strategies, FEL and FTL, have been frequently studied by researchers. Moreover, two strategies, FHL and FSS, have been developed based on FEL and FTL. FLB is a novel operation strategy presented in this study.
Qboiler b
(15)
where b is the efficiency of the boiler. Importantly, redundant heat, which is the excess heat generated by the CCHP system under the FEL strategy and discharged into atmosphere, can be expressed as follows: Qw = Qrec −
Q (Qc − x × Qc ) − h ab he
(16)
where Qw is the redundant heat generated by the CCHP system. Therefore, the total energy consumption under the FEL strategy, CCHP , can be estimated using the following equation: FFEL CCHP FFEL = Fpgu + Fboiler +
Egrid
(17)
e grid
where e is the electricity generation efficiency of the grid and grid is the transmission efficiency of the utility grid. 2.2.2.2. Following the thermal load For the FTL strategy, the CCHP system should operate using Eq. (7) to satisfy the thermal load. Similarly to the FEL strategy, a low PGU efficiency could reduce the overall performance of a CCHP system. Therefore, the part-load operation of the CCHP system under the FTL strategy was considered and differed significantly from the earlier studies, whose efficiency of PGU was constant when the CCHP system operated under the FTL strategy. Based on the satisfaction of the thermal demand, the electricity generated by PGU, Ereq , can be calculated using Eq. (11) as follows:
Ereq =
(Qc − x × Qc )/ab rec + Qh /he rec − ˇ1 × Ecap ˛−1
(18)
L. Li et al. / Energy and Buildings 99 (2015) 231–242
235
Fig. 3. Optimization procedure of the CCHP system.
Table 1 Three simulation cases with two types of building combinations. Floor area of buildings (m2 )
Cases
Office Case 1 Case 2 Case 3
60,000 0 30,000
Residence 0 60,000 30,000
The operational constraints under the FTL strategy can be described as follows: Epgu =
⎧ ⎨ 0, ⎩
0 ≤ f < 25%
Ereq ,
25% ≤ f ≤ 100%
Ecap ,
100% < f
⎫ ⎬ ⎭
to provide additional heat. Therefore, the expressions of Qboiler and Fboiler are the same as Eqs. (14) and (15). The electricity from utility grid can be expressed as Eq. (13). Redundant electricity, Ew , which is the surplus electricity produced by PGU under the FTL strategy can be estimated as follows: Ew = Epgu − Euser − Eec
CCHP , can be Furthermore, the total energy consumption, FFTL expressed as follows:
CCHP FFTL = Fpgu + Fboiler +
(19)
where f is defined as the ratio of Ereq to Ecap under the FTL strategy. If the heat recovery system cannot satisfy the thermal demand of buildings when Epgu = 0 or Epgu = Ecap , an auxiliary boiler is used
(20)
Egrid e grid
(21)
2.2.2.3. Following a hybrid electric–thermal load The CCHP system operated under FEL and FTL strategies produced a large amount of redundant heat or electricity. Mago et al. [23] achieved a better performance using the FHL strategy than FEL
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Fig. 4. Heating, cooling, and electricity demands of office buildings.
Fig. 5. Heating, cooling, and electricity demands of residential buildings.
and FTL. They found a relationship between electricity generated by PGU and recovered heat, which can be expressed as follows: Epgu =
pgu
rec 1 − pgu
Qrec
(22)
The pgu has been assumed as a constant value to determine whether the CCHP system operates under FEL or FTL. However, under the part-load scenario, pgu cannot be deduced without the electricity output and nominal capacity of PGU. Therefore, in this study, FHL was modified by switching between FEL and FTL based on the principle of no redundant electricity and heat, and can be calculated by Eqs. (16) and (20). No superfluous
electricity or heat is produced by PGU. The procedure of a new FHL strategy can be represented as follows:
text conditions FHL = FTL Ew
Ew ≤ 0,
FTL
Ew > 0,
FEL
(23)
Eq. (23) also can be expressed as follows:
text conditions FHL = FEL Qw
Qw ≤ 0,
FEL
Qw > 0,
FTL
(24)
This indicates that the CCHP system operates following the thermal load or following the electric load first and then switches to the
L. Li et al. / Energy and Buildings 99 (2015) 231–242
Fig. 6. Linear relationship between Fpgu /Ecap and f
Table 2 Coefficients and goodness of fit. Function Fpgu Ecap
Coefficients
= ˛ × f + ˇ1
˛ = 2.578 ˇ1 = 0.7027
Epgu /Ecap .
Table 3 Input values for CCHP system and reference system simulation. SSE
0.007384
R-square
0.9987
Adjusted R-square
RMSE
0.9986
0.02297
Item
Parameter
Symbol
CCHP system [6]
Coefficient of performance of absorption chiller Efficiency coefficients of PGU
COPab
other strategy if redundant electricity or heat is produced, as Ew > 0 or Qw > 0. Therefore, Ew and Qw are always less than or equal to 0 under the FHL strategy. 2.2.2.4. Following the seasonal operation strategy In the seasonal operation strategy, a parameter named the load ratio LR is defined [8] as follows: LR =
237
monthly electric load monthly thermal load
Reference energy system [6]
(25)
If LR < 1, the CCHP system operates under the FTL strategy during the month. In contrast, the system operates under the FEL strategy. Under the FSS strategy, the CCHP system reported in Ref. [8] achieved a better primary energy saving performance than FEL and FTL; however, there is no economic and environmental merit.
Unit price of equipment [11] (¥/kW)a Emission factor [11,27] (g/kW h) a
Efficiency of boiler Efficiency of heating exchanger Efficiency of heat recovery system Live time of equipment, year Coefficient of performance of electric chiller Efficiency of boiler Efficiency of heating exchanger Generation efficiency Transmission efficiency of electric grid Absorption chiller Electric chiller Boiler Power generation unit Electricity emission factor Natural gas emission factor
1 ¥ = 0.16 $ (US dollar).
2.2.2.5. Following the electric–thermal load of buildings In this paper, the LR in Eq. (25) is redefined as follows: NLR =
hourly electric load hourly thermal load
(26)
According to Eq. (25), the switch node, 1, is changed to an optimized value, y. If NLR < y, the CCHP system operates following the thermal load during that hour. Otherwise, the system operates following the electric load. 2.3. Evaluation criteria The performance of a CCHP system compared to the reference system under different operation strategies can be evaluated in terms of annual total cost reduction (ATCR), primary energy saving (PES), and carbon dioxide emission reduction (CDER). The ATCR, PES, and CDER can be expressed as the following equations: ATCR =
ATCRE − ATCCCHP ATCRE
(27)
Table 4 Parameters of genetic algorithm. Parameter
Value
Number of individuals Maximum generation Precision of variables Generation gap Crossover probability Mutation probability
60 100 20 0.9 0.7 0.01
Search field PGU capacity (kW) x y
0–2000 0–1 0–100
Value 0.7
a b c b he rec
0.1 0.4 −0.2 0.8 0.8 0.8
n COPec
20 3
b he e grid Cicc
grid ng
0.8 0.8 0.35 0.92 1200 970 300 6800 1200 220
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L. Li et al. / Energy and Buildings 99 (2015) 231–242
Fig. 7. Time of use tariff for office buildings.
Fig. 8. Graduated power tariff for residential buildings.
PES =
F RE − F CCHP F RE
CDER =
(28)
CDERE − CDECCHP
(29)
CDERE
where ATC is the annual total cost, F is the total energy consumption, and CDE is the carbon dioxide emission. ATC, F, and CDE are specified in the following equations. ATC = Crf ×
i
Cicc × Gi +
charge of natural gas and grid electricity, respectively. Crf is the capital recovery factor, which can be computed as follows:
hour
×Cng + Egrid,hour × Ce,hour
Fboiler + Fpgu
(30)
where i is the type of equipment, Cicc is the capital cost of equipcap ment, Gi is the nominal capacity, and Cng and Ce,hour are the hourly
Crf = Ir ×
1+
1
(31)
(1 + Ir )n − 1
where Ir is the interest rate, n is the service life of equipment. It is assumed that all types of equipment have the same value of Ir and n. FCCHP was calculated using Eqs. (17) and (21), and FRE is the total energy consumption of the reference system, which can be expressed as follows: F RE =
Euser + EpRE + Qc /COPec e grid
+
Qh /he b
CDE = (Fpgu + Fboiler ) × ng + Egrid × grid
(32) (33)
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Fig. 9. Performance of CCHP systems in office buildings.
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Fig. 11. Performance of CCHP systems in complex buildings.
Genetic algorithm was applied to solve the optimal problems. The procedure of optimization by GA is shown in Fig. 3. 3. Case study 3.1. Energy load profiles
Fig. 10. Performance of CCHP systems in residential buildings.
where ng and grid are the emission factors of natural gas and grid electricity, respectively. 2.4. Solution method
In Dalian, many mixed areas comprising office and residential buildings exist within neighboring districts. The occupancy rate of residential buildings is relatively low during the working time, whereas that of the office buildings is opposite. Therefore, an obvious difference exists between the load demand of office and residential buildings. Moreover, the demand load characteristics of buildings could affect the performance of different operation strategies in the CCHP system. For comparing more different buildings loads, two types of buildings and three cases have been assumed as shown in Table 1. Hypothetical office and residential buildings were simulated in Dalian, which is located at a latitude of 39.03◦ N and a longitude of 121.46◦ W. Both the thermal and electricity demands of the above buildings fluctuated hourly in the entire year. The heating, cooling, and electricity demands of the hypothetical buildings are the same as that reported in Ref. [15]. The demands of the buildings with a floor area of 60,000 m2 are shown in Figs. 4 and 5. 3.2. Simulation parameters
The weight method was applied in this paper to analyze multiple objective issues. The integrated performance of the CCHP system can be estimated as follows: Jmax = ı1 × ATCR + ı2 × PES + ı3 × CDER
(34)
where ı1 , ı2 , and ı3 are the weights of ATCR, PES, and CDER, respectively. In this paper, the three weights are all considered to be equal to 1/3 [3,11].
For reasonable results, the nonlinear efficiency of PGU has been studied considering the part-load scenario. A common linear relationship exists between the fuel consumption and electricity generated by PGU [25]. The curve fitting of the functional relationship is shown in Fig. 6. The black points were computed using Eqs. (2) and (3), and the blue line was fitted using Eq. (6). The coefficients and goodness of fit were applied to the following calculation, as shown in Table 2.
Table 5 Ratios of the redundant energy of different strategies to the total redundant electricity and heat in each case. Cases
Case 1 (ε = 1) Case 2 (ε = 2) Case 3 (ε = 3)
Ratios of the redundant energy, ε,ϕ FEL (ϕ = 1) (%)
FTL (ϕ = 2) (%)
FHL (ϕ = 3)
FSS (ϕ = 4) (%)
FLB (ϕ = 5) (%)
Summation (%)
32.35 29.55 27.80
2.56 13.08 11.14
0 0 0
32.58 28.05 33.23
32.51 29.32 27.83
100 100 100
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The simulation parameters applied in this study are shown in Table 3. Among them, the efficiency coefficient of PGU and the efficiency of other equipment in CCHP and reference system are derived from Ref. [6], the unit price of equipment is reported in Ref. [11] and emission factor is reported in Refs. [11,27]. The tariff of natural gas is 0.22 ¥/kW h for all the users. Moreover, the office and residential buildings adopt the time of use tariff and graduated power tariff in Dalian, respectively. The tariff structures are shown in Figs. 7 and 8. The parameters of genetic algorithm are listed in Table 4. 4. Results 4.1. Performance of different operation strategies To study different operation strategies, three criteria comprising the annual total cost reduction, primary energy saving ratio, and carbon dioxide emission reduction of the CCHP systems were analyzed under three cases, as shown in Figs. 9–11. This shows that FLB and FEL are superior to other operation strategies in all the three cases. In case 1, the integrated saving ratios (‘J’ in Figs. 9–11) of the CCHP systems under FEL, FTL, FHL, FSS, and FLB were 22.92%, 13.47%, 13.72%, 21.15%, and 23.12%, respectively. Fig. 9 shows that the FLB strategy yields the best integrated performance, and FLB and FEL showed relatively better performance in all the three evaluation criteria. The ATCR and CDER of the CCHP systems operating under FLB and FEL are almost double than those under FTL and FHL. This is because the CCHP systems operating under the two strategies consume less grid electricity than the other strategies. Because the tariff and carbon dioxide emission factor of grid electricity are higher than those of natural gas under equivalent conditions, the operational cost and carbon dioxide emission of the CCHP system can be relatively reduced. Irrespective of the operation strategy, the residential buildings have a relatively lower ATCR than case 1 shown in Fig. 10. The main reason is the unbalanced ratio of the electricity demand to the thermal demand of residential buildings. It can result in the electricity from grid accounting for a large proportion in electricity consumption under the five strategies. In case 2, the gap of integrated saving ratios among the five strategies is not large. Under the FLB and FEL
strategies, the integrated performance of the CCHP systems yields the highest saving ratios, equal to 12.04%. The CCHP system under FTL still achieved a poor saving ratio of 9.53%. Obviously, the CCHP system under the FHL strategy has the biggest economic merits in residential buildings based on the current evaluation criteria. In case 3, same as case 1, the best operation strategy is FLB. Fig. 11 shows that the saving ratios of the CCHP systems under FLB and FEL are 23.91% and 23.89%, respectively, providing better performance in terms of energy saving and economic and environmental merits among the five strategies in complex buildings. Clearly, the CCHP system operating under the FTL strategy yields the poorest integrated performance in all the three cases. In general, in the CCHP system under either strategy in either case, the environmental benefit is notable than the reference energy system. It can be concluded that the FLB is the best operation strategy in all the three cases. The switch nodes of NLR in the three cases, y, are 3.97%, 0.25%, and 3.46%, respectively. According to Eq. (23), it can be deduced that if the CCHP system operates under FLB, the FEL strategy accounts for a large part of the entire year operation. Owing to the electricity and thermal load profiles of buildings, the FEL strategy is more suitable than FTL in most of the operating time. Therefore, it is the main cause of minor differences in the integrated saving ratios between FLB and FEL in the present study. 4.2. Redundant energy of CCHP systems under different operation strategies Based on the current policy in China and assumption in the present study, the surplus electricity and heat cannot be transferred back to the grid or other users. Therefore, the redundant energy of the CCHP systems, comprising redundant electricity and heat, was analyzed under the five operation strategies. To study the redundant energy of the CCHP systems, the ratios of the redundant energy of different strategies to the total redundant electricity and heat in each case (the same load characteristics), , can be expressed as the following equation: ε,ϕ =
Ew,ε,ϕ + Qw,ε,ϕ
Ew,ε,ϕ + Qw,ε,ϕ
ϕ
Fig. 12. Ratios of grid electricity consumption to total gas consumption.
(35)
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where Qw and Ew are calculated using Eqs. (16) and (20), ε indicates the cases, and ϕ indicates the operation strategies. The results are shown in Table 5. The CCHP systems operating under the operation strategies that produce less redundant energy may not yield better performance in all the three cases, as FTL and FHL. However, the CCHP systems under FLB and FEL that achieve good integrated performance generate the huge redundant energy. For example, no redundant energy (Qw = 0, Ew = 0) was obtained when the CCHP system operated under the FHL strategy. However, Figs. 9–11 show that the integrated performance of the FHL strategy is poor. Most agree that little redundant energy will promote the primary energy saving ratio or integrated performance; however, the result turns out to be the opposite. Although the FHL strategy did not provide redundant energy in all the three cases, the integrated performance was not good. It is important to highlight here that if the CCHP system operates under the FHL strategy, to avoid redundant energy production, the system will supplement the rest of electricity and heat through a reference energy system (Fig. 1), which obtains electricity from the utility grid and generates heat from the boiler. In contrast to the other strategies, the gas consumption of PGU was reduced, and the ratio of grid electricity consumption to the total gas consumption increased. The consumption ratios of the CCHP systems under different operation strategies are shown in Fig. 12, exhibiting the reverse trend with the integrated performance shown in Figs. 9–11. The high grid electricity consumption ratio is one reason why the CCHP system yields poor integrated performance. Moreover, the little redundant energy results in a high grid electricity consumption ratio based on the current electricity and thermal demand of buildings. Therefore, the CCHP system operating under the FHL strategy yields poor energy and economic and environmental performance. In brief, the redundant energy cannot be a criterion to evaluate the CCHP system, and no direct connection exists between the integrated performance and redundant energy under the current CCHP system configuration.
5. Conclusions This study analyzed the performance of combined cooling, heating, and power systems based on annual total cost reduction, primary energy saving and carbon dioxide emission reduction, and the redundant electricity and heat under different conditions. Five operation strategies such as following the electric load, following the thermal load, following a hybrid electric–thermal load, following the seasonal operation strategy, and following the electric–thermal load of buildings were evaluated in CCHP systems, which provided the electricity, heating and cooling load to office buildings, residential buildings, and the complex of office and residential buildings. The conclusions can be drawn as follows: The FLB strategy yielded the best integrated performance, and the CCHP systems under the FLB and FEL strategies achieved relatively better performance in all the three cases. However, the FTL strategy yielded the poorest integrated performance in all the three cases. In office buildings, the saving ratios of the integrated performance under FLB and FEL were 23.12% and 22.92%, respectively. In residential buildings, under FLB and FEL strategies, the CCHP systems yielded the highest integrated saving ratios, equal to 12.04%. The CCHP system under the FHL strategy has the biggest economic merits in residential buildings. In complex buildings, the saving ratios of the CCHP systems under FLB and FEL strategies were 23.91% and 23.89%, respectively. The switch nodes of the FLB strategy in the three cases, y, were 3.97%, 0.25%, and 3.46%, respectively. Therefore, if the CCHP system operates under FLB, the FEL strategy accounts for a large part of the
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entire year operation based on the current load profiles of buildings. This is the main reason of the minor differences in the integrated saving ratios between FLB and FEL in the present study. The redundant energy of CCHP systems was analyzed under five different operation strategies. The CCHP systems operating under the operation strategies that produce less redundant energy may not yield better performance in all the three cases, as FTL and FHL. However, the CCHP systems under FLB and FEL that achieve good integrated performance are accompanied with a huge redundant energy. It can be deduced that the redundant energy cannot be a criterion to evaluate CCHP systems under the current CCHP system configuration. Acknowledgement The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China (71273039). References [1] D.W. Wu, R.Z. Wang, Combined cooling, heating and power: a review, Prog. Energy Combust. Sci.V 32 (5–6) (2006) 459–495. [2] M. Jradi, S. Riffat, Tri-generation systems: energy policies, prime movers, cooling technologies, configurations and operation strategies, Renewable Sustainable Energy Rev. 32 (0) (2014) 396–415. [3] C.Y. Zheng, J.Y. Wu, X.Q. Zhai, A novel operation strategy for CCHP systems based on minimum distance, Appl. Energy 128 (0) (2014) 325–335. [4] J.-J. Wang, Y.-Y. Jing, C.-F. Zhang, Z. Zhai, Performance comparison of combined cooling heating and power system in different operation modes, Appl. Energy 88 (12) (2011) 4621–4631. [5] G. Han, S. You, T. Ye, P. Sun, H. Zhang, Analysis of combined cooling, heating, and power systems under a compromised electric–thermal load strategy, Energy Build. 84 (0) (2014) 586–594. [6] M. Liu, Y. Shi, F. Fang, A new operation strategy for CCHP systems with hybrid chillers, Appl. Energy 95 (0) (2012) 164–173. [7] P.J. Mago, L.M. Chamra, J. Ramsay, Micro-combined cooling, heating and power systems hybrid electric–thermal load following operation, Appl. Therm. Eng. 30 (8–9) (2010) 800–806. [8] P.J. Mago, A.K. Hueffed, Evaluation of a turbine driven CCHP system for large office buildings under different operating strategies, Energy Build. 42 (10) (2010) 1628–1636. [9] M. Ebrahimi, A. Keshavarz, Sizing the prime mover of a residential microcombined cooling heating and power (CCHP) system by multi-criteria sizing method for different climates, Energy 54 (0) (2013) 291–301. [10] A.A. Knizley, P.J. Mago, A.D. Smith, Evaluation of the performance of combined cooling, heating, and power systems with dual power generation units, Energy Policy 66 (0) (2014) 654–665. [11] J. Wang, Z. Zhai, Y. Jing, C. Zhang, Particle swarm optimization for redundant building cooling heating and power system, Appl. Energy 87 (12) (2010) 3668–3679. [12] J.-J. Wang, Y.-Y. Jing, C.-F. Zhang, Optimization of capacity and operation for CCHP system by genetic algorithm, Appl. Energy 87 (4) (2010) 1325–1335. [13] P.J. Mago, A.D. Smith, Evaluation of the potential emissions reductions from the use of CHP systems in different commercial buildings, Build. Environ. 53 (0) (2012) 74–82. [14] M. Hu, H. Cho, A probability constrained multi-objective optimization model for CCHP system operation decision support, Appl. Energy 116 (0) (2014) 230–242. [15] L. Li, H. Mu, W. Gao, M. Li, Optimization and analysis of CCHP system based on energy loads coupling of residential and office buildings, Appl. Energy 136 (0) (2014) 206–216. [16] P.J. Mago, N. Fumo, L.M. Chamra, Performance analysis of CCHP and CHP systems operating following the thermal and electric load, Int. J. Energy Res. 33 (9) (2009) 852–864. [17] S. Sanaye, N. Khakpaay, Simultaneous use of MRM (maximum rectangle method) and optimization methods in determining nominal capacity of gas engines in CCHP (combined cooling, heating and power) systems, Energy 72 (0) (2014) 145–158. [18] X. Teng, X. Wang, Y. Chen, W. Shi, A simple method to determine the optimal gas turbine capacity and operating strategy in building cooling, heating and power system, Energy Build. 80 (0) (2014) 623–630. [19] W. Jiang-Jiang, Z. Chun-Fa, J. You-Yin, Multi-criteria analysis of combined cooling, heating and power systems in different climate zones in China, Appl. Energy 87 (4) (2010) 1247–1259. [20] Y.-Y. Jing, H. Bai, J.-J. Wang, L. Liu, Life cycle assessment of a solar combined cooling heating and power system in different operation strategies, Appl. Energy 92 (0) (2012) 843–853. [21] A. Smith, R. Luck, P.J. Mago, Analysis of a combined cooling, heating, and power system model under different operating strategies with input and model data uncertainty, Energy Build. 42 (11) (2010) 2231–2240.
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