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1. Figure 1.1 A typical CCHP system
2. Figure 1.2 Capstone C200 micro-turbine with power output of 190 kW
3. Figure 1.3 Absorption process
4. Figure 1.4 Separation process
5. Figure 1.5 Existing CHP/CCHP sites classified by prime movers
6. Figure 1.6 US CHP/CCHP development from 1970 [220]
7. Figure 1.7 The installed capacity of CHP/CCHP plants classified by applications in the US
8. Figure 1.9 The CHP/CCHP installed capacity in the UK [223]
9. Figure 1.9 The installed capacity of CHP plants classified by applications in the UK [223]
10. Figure 1.10 The installed capacity of CHP in China [225]
11. Figure 1.11 Share of CHP capacity in thermal power generation [225]
12. Figure 2.1 Schematic of a typical SP system
13. Figure 2.2 Schematic of a typical CCHP system
14. Figure 2.3 Flow chart of the decision-making process of the proposed optimal switching operation strategy for the CCHP system based on two operating modes
15. Figure 2.4 Hourly cooling, heating and power loads of the hypothetical hotel in representative days of spring/autumn, summer and winter
16. Figure 2.5 Space division of operating modes for the hypothetical CCHP system: (a) Equal-Loads Interface; and (b) Equal-Modes Interface
17. Figure 2.6 Scheduled status of operating modes and energy supply for representative days' energy requirements of the hypothetical CCHP system: (a) scheduled by the proposed strategy; and (b) scheduled by the HETS
18. Figure 2.7 Relative values of PEC, COST, and CDE, and daily EC values
19. Figure 3.1 The CCHP system with hybrid chillers implemented
20. Figure 3.2 Space of , , and
21. Figure 3.3 One year energy consumption of a hypothetical hotel in Victoria, BC, Canada
22. Figure 3.4 function value of CCHP system without capacity limit
23. Figure 3.5 function value of different PGU capacities from 1 to 500 kW
24. Figure 3.6 function value with 96 kW PGU
25. Figure 3.7 Variation of electric cooling to cool load ratio in a whole year
26. Figure 4.1 Comparison of three strategies in a summer day
27. Figure 4.2 Comparison of three strategies in a winter day
28. Figure 4.3 Comparison of three strategies in a spring day
29. Figure 4.4 of PGU capacity from 0 to 200 kW
30. Figure 4.5 of PGU capacity from 0 to 200 kW
31. Figure 4.6 Variation of the electric cooling to cool load ratio
32. Figure 5.1 OLS-TSRLS algorithm flowchart
33. Figure 5.2 Heating loads correlogram
34. Figure 5.3 Electrical loads correlogram
35. Figure 5.4 Cooling loads correlogram
36. Figure 5.5 Comparison between forecasted and actual heating loads
37. Figure 5.6 Error between forecasted and actual heating loads
38. Figure 5.7 Comparison between forecasted and actual electric loads
39. Figure 5.8 Error between forecasted and actual electrical loads
40. Figure 5.9 Comparison between forecasted and actual cooling loads
41. Figure 5.10 Error between forecasted and actual cooling loads
42. Figure 5.11 Comparison of PES
43. Figure 5.12 Comparison of ATC
44. Figure 5.13 Comparison of CDE
45. Figure 5.14 Case distribution
46. Figure 6.1 Structure diagram of a CCHP-ORC system
47. Figure 6.2 Schematic of a basic ORC system
48. Figure 6.3 Decision-making process of optimal operation strategy for normal load cases
49. Figure 6.4 Hourly cooling, heating and power loads of the hypothetical hotel in representative days of spring, summer, autumn, and winter
50. Figure 6.5 Hourly outputs of the electric chiller and ORC in representative days of spring, summer, autumn, and winter
51. Figure 6.6 Radar charts of three criteria for the CCHP-ORC system and the CCHP system in representative days of spring, summer, autumn, and winter

1. Table 1.1 Comparisons among different prime movers
2. Table 1.2 Comparisons among different thermally activated technologies
3. Table 1.3 Comparisons among different system configurations
4. Table 2.1 Primary parameters of the hypothetical hotel using EnergyPlus
5. Table 2.2 System coefficients
6. Table 2.3 Performance criteria of the whole heating season with different systems and optimal operation strategies
7. Table 3.1 Construction parameters of the hypothetical hotel
8. Table 3.2 System coefficients
9. Table 3.3 EC values of SP and CCHP systems
10. Table 4.1 System coefficients
11. Table 5.1 Average normed error of different models using six sets of , , and
12. Table 5.2 Performance of different systems using forecasted data obtained from the proposed prediction method
13. Table 5.3 Performance of different systems using 1-lag forecasted data
14. Table 5.4 Performance of different systems using TSLS forecasted data
15. Table 6.1 Technical parameters of the CCHP-ORC system and the CCHP system for the hypothetical hotel
16. Table 6.2 Equipment capacities and unit prices of the CCHP-ORC system and the CCHP system
17. Table 6.3 Daily values of performance criteria for the CCHP-ORC system and the CCHP system in representative days

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The authors would like to thank all those who have helped in accomplishing this book.

Combined cooling, heating, and power (CCHP) systems are known as trigeneration systems. They are designed to supply cooling, heating, and electricity simultaneously. The CCHP system has become a hot topic for its high system efficiency, high economic efficiency, and low greenhouse gas (GHG) emissions in recent years. The efficiency of the CCHP system depends on the appropriate system configuration, operation strategy, and facility selection. Due to the inherent and inevitable energy waste of traditional operation strategies, high-efficiency operation strategies are urged. To achieve the highest system efficiency, facilities in the system should be appropriately sized to match with the corresponding operation strategy.

In Chapter 1, the state-of-the-art of CCHP research is surveyed. First, the development and working scheme of the CCHP system is presented. Some analyses of the advantages of this system and a brief introduction to the related components are then given. In the second part of Chapter 1, we elaborately introduce various types of prime movers and thermally activated facilities. Recent research progress on the management, control, system optimization, and facility selection is summarized in the third part. The development of the CCHP system in representative countries and the development barriers are also discussed in Chapter 1.

The operation strategy has a direct impact on the CCHP system performance. To improve the operational performance, in Chapter 2, based on two conventional operation strategies, that is, following electric load (FEL) and following thermal load (FTL), a novel optimal switching operation strategy is proposed. Using this strategy, the whole operating space of the CCHP system is divided into several regions by one to three border surfaces determined by energy requirements and the evaluation criteria (EC). Then the operating point of the CCHP system is located in a corresponding operating mode region to achieve improved EC. The EC simultaneously considers the primary energy consumption, the operational cost, and the carbon dioxide emissions. The proposed strategy can reflect and balance the influences of energy requirements, energy prices, and emissions effectively.

Most of the improved operation strategies in the literature are based on the “balance” plane, matching of the electric demands with the thermal demands. However, in more than 95% energy demand patterns, the demands cannot match with each other on this exact “balance” plane. To continuously use the “balance” concept, in Chapter 3, the system configuration is modified from the one with a single absorption chiller to be the one with hybrid chillers, thus expanding the “balance” plane to a “balance” space by tuning the electric cooling to cool load ratio. With this new “balance” space, an operation strategy is designed and the power generation unit (PGU) capacity is optimized according to the proposed operation strategy to reduce the energy waste and improve the system efficiency. A case study is conducted to verify the feasibility and effectiveness of the proposed operation strategy.

In Chapter 4, a more mathematical approach to scheduling the energy input and power flow is proposed. By using the concept of energy hub, the CCHP system is modeled in a matrix form. As a result, the whole CCHP system is an input–output model. Setting the objective function to be a weighted summation of primary energy savings (PES), hourly total cost savings (HTC), and carbon dioxide emissions reductions (CDER), the optimization problem, constrained by equality and inequality constraints, is solved to obtain the optimal operation strategy. The PGU capacity is also sized under the proposed optimal operation strategy. In the case study, compared with FEL and FTL, the proposed optimal operation strategy saves more primary energy and annual total cost, and can be more environmentally friendly.

Chapter 5

The electricity to thermal energy output ratio is an important impact factor for the operation strategy and performance of CCHP systems. If the energy requirements of users are managed to just match this ratio, the system efficiency would reach the maximum. However, due to the randomness of users' demand, this situation is rarely achieved in practice. To solve this problem, a complementary CCHP-organic Rankine cycle (CCHP-ORC) system is configured in Chapter 6. The salient feature of this system is that its electricity to thermal energy output ratio can be adjusted by changing the loads of the electric chiller and the ORC dynamically. For such a system, an optimal operation strategy and a corresponding implemented decision-making process are presented within a wide load range. Case studies are conducted to verify the efficacy of the developed CCHP-ORC system.