Bi-Objective Optimization and Emergy Analysis of Multi-Distributed Energy System Considering Shared Energy Storage

Zhaonian Ye, Yongzhen Wang (), Kai Han (), Changlu Zhao, Juntao Han and Yilin Zhu
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Zhaonian Ye: School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100083, China
Yongzhen Wang: School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100083, China
Kai Han: School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100083, China
Changlu Zhao: School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100083, China
Juntao Han: School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100083, China
Yilin Zhu: Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China

Sustainability, 2023, vol. 15, issue 2, 1-23

Abstract: Shared energy storage (SES) provides a solution for breaking the poor techno-economic performance of independent energy storage used in renewable energy networks. This paper proposes a multi-distributed energy system (MDES) driven by several heterogeneous energy sources considering SES, where bi-objective optimization and emergy analysis methods are used for the system’s optimal capacity planning and operating scheduling considering economic, environmental, and sustainable performances, and Nash bargaining is adopted for the reasonable distribution of benefits of MDES. Then, an energy system composed of four different DESs (distributed energy system) considering one Shared Energy Storage Operator (SESO) is taken as an example for further study, namely one to four shared energy storage multi-energy systems, where MDES with and without SESO are compared. The results reveal that the operation cost of MDES considering SESO and Nash bargaining is reduced by 3.03%, while all the distributed energy systems have lower operating costs, and SESO has an additional income of $142.4/day. Correspondingly, the emergy yield ratio, emergy sustainability index, and emergy investment ratio of the corresponding system increase by 5.15%, 3.83%, and 9.94%, respectively, wherein the environmental load rate increases by 1.67% because of the greater consumption reduction of renewable resources than that of non-renewable resources under the premise of reduced emergy consumption.

Keywords: shared energy storage; distributed energy systems; bi-objective optimization; Nash bargaining (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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