Impacts of equipment off-design characteristics on the optimal design and operation of combined cooling, heating and power systems
Introduction
Combined cooling, heating and power (CCHP) system is broadly regarded as an efficient and economic approach for simultaneous provision of cooling, heating and electricity. CCHP can increase the overall energy efficiency of an energy system by recovering a large proportion of waste heat produced in power generation. However, the expected performance of CCHP cannot be achieved without appropriate combination and operation of machinery, due to the fluctuating heating, cooling and electricity demands that the system faces. Many mathematical models for the design and/or operation of CCHP systems have been developed to obtain a better performance of such systems. A key difference amongst these models lies in their different methods in dealing with the off-design characteristics of equipment. Most models assume that the efficiency or coefficient of performance (COP) of equipment do not change while operating at off-design levels (Arcuri et al., 2007, Cho et al., 2009, Ren and Gao, 2010). This assumption can greatly simplify modelling work, but it also leads to less accurate results based on which systems design or operation strategies are made. In some other studies, more complex models are developed considering off-design characteristics of equipment (Li, Nalim et al. 2006). However, these models usually pose significant or even formidable computational challenges due to their nonlinear nature.
In this work, we illustrate the extent of negative impacts of the constant efficiency assumption on the accuracy of CCHP modelling. We present two mathematical models for the optimal design and operation of CCHP systems with the target of minimizing the total annual cost. For comparison purposes, one model is formulated to represent the performance of a CCHP system running at design conditions, i.e., with constant energy efficiency. The other model considers both the design and off-design characteristics of all key equipment in a CCHP system. These two optimization models are applied to configure an optimal CCHP system for a hotel in Beijing. The impacts of equipment off-design characteristics on the optimal design and operation of CCHP systems are discussed based on the modelling results.
Section snippets
System configuration of a CCHP system
A typical configuration of CCHP systems is shown in Fig. 1. In the system, internal combustion engines (ICE) are used in the power generation unit (PGU) for simultaneous production of electricity and heat. Recovered heat in the PGU is used to meet the heating and cooling demands together with gas boilers (GB). Cooling demand is met via absorption chillers (AC). When the amount of electricity generated by the PGU is not enough, extra electricity can be drawn from a power grid. A thermal storage
Mathematical formulation of the optimization models
Two mathematical models are developed with the target of minimizing the total annual cost of a CCHP system, covering capital cost, operation and maintenance (O&M) cost and fuel cost. One model adopts the constant efficiency assumption, whilst the other one considers the off-design characteristics of equipment. Equipment performance curves adopted in this study are obtained from (Li et al., 2006). Sizes of equipment are standardized thus cannot be changed, but installation of multiple pieces of
Case study
The baseline case is a typical hotel in Beijing with an area of 60 thousand square meters. We also include a 30 thousand square meters case and a 90 thousand square meters case for sensitivity analysis. The hourly electricity, heating, cooling and hot water demands of three representative days in winter, summer, and transitional seasons of the baseline case are shown in Fig. 2 (Jin et al., 2008).
Besides the demands information, both models also require technological and economic information of
Results and discussions
The optimal total annual costs generated by both models are presented in Fig. 3. It shows that the constant effiency assumption has a rather small impact on the optimal results, and the relative differences between these two types of models in the three cases are all less than 5 percent. Moreover, the relative difference gets smaller as the building area increases. The reasons for this small difference and the dimishing relative difference are explained next.
Conclusions
The constant efficiency assumption of the optimization model for the design and operation of CCHP systems has a small impact on the optimization results. Multiple pieces of equipment operate together and thermal storage and grid connection can prevent energy generation technologies from working in inefficient zone in a CCHP system. This proves that the results generated by an optimization model with the constant efficiency assumption are credible.
Acknowledgements
The authors gratefully acknowledge the financial support from National Natural Science Foundation (project No. 51106080), from BP company in the scope of the Phase II Collaboration between BP and Tsinghua University, and from the IRSES ESE Project of FP7 (contract No: PIRSES-GA-2011-294987).