Optimal Scheduling of Integrated Energy Systems with Combined Heat and Power Generation, Photovoltaic and Energy Storage Considering Battery Lifetime Loss

Yongli Wang, Haiyang Yu, Mingyue Yong, Yujing Huang, Fuli Zhang and Xiaohai Wang
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Yongli Wang: School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China
Haiyang Yu: School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China
Mingyue Yong: State Grid Beijing Electric Power Company, Xicheng District, Beijing 100031, China
Yujing Huang: School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China
Fuli Zhang: School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China
Xiaohai Wang: School of Economics and Management, North China Electric Power University, Changping District, Beijing 102206, China

Energies, 2018, vol. 11, issue 7, 1-21

Abstract: Integrated energy systems (IESs) are considered a trending solution for the energy crisis and environmental problems. However, the diversity of energy sources and the complexity of the IES have brought challenges to the economic operation of IESs. Aiming at achieving optimal scheduling of components, an IES operation optimization model including photovoltaic, combined heat and power generation system (CHP) and battery energy storage is developed in this paper. The goal of the optimization model is to minimize the operation cost under the system constraints. For the optimization process, an optimization principle is conducted, which achieves maximized utilization of photovoltaic by adjusting the controllable units such as energy storage and gas turbine, as well as taking into account the battery lifetime loss. In addition, an integrated energy system project is taken as a research case to validate the effectiveness of the model via the improved differential evolution algorithm (IDEA). The comparison between IDEA and a traditional differential evolution algorithm shows that IDEA could find the optimal solution faster, owing to the double variation differential strategy. The simulation results in three different battery states which show that the battery lifetime loss is an inevitable factor in the optimization model, and the optimized operation cost in 2016 drastically decreased compared with actual operation data.

Keywords: integrated energy system; optimal scheduling; differential evolution; life quantification (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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