LAPSE:2019.0098
Published Article
LAPSE:2019.0098
Multi-Objective Optimal Sizing for Battery Storage of PV-Based Microgrid with Demand Response
Nan Zhou, Nian Liu, Jianhua Zhang, Jinyong Lei
January 7, 2019
In order to solve the influence of uncertain photovoltaic power (PV) on the stable operation of microgrid (MG), demand response (DR) and battery energy storage system (BESS) need to be introduced simultaneously into the operation optimal scheduling of PV-based microgrid (PV-MG). Therefore, it is of great significance for commercial investment decisions of PV-MG to consider the influence of DR on BESS optimal sizing. Under the peak-valley time-of-use (TOU) price, this paper builds cross-time DR models based on price elasticity matrix. Furthermore, through the introduction of DR and BESS into PV-MG scheduling optimization, the MG investment and benefit model is proposed. Considering the constraint condition such as co-ordination of supply and demand, electricity price elasticity and energy loss of storage system, the improved non-dominated sorting genetic algorithm II (NSGA-II) is utilized to solve the multi-objective optimal allocation model of the BESS with the target of maximum PV consumptive rate and annual net profits. The optimization method was applied to a PV-MG in Guangdong. Through the regulation and control effect of demand response and BESS on load distribution, the uncertainties PV power can be suppressed so as to improve the PV system consumptive level, which is of great guiding significance for BESS optimal sizing under this situation.
Keywords
battery energy storage system (BESS), investment and benefit model, multi-objective optimization, multi-period demand response (DR), non-dominated sorting genetic algorithm II (NSGA-II) algorithm, photovoltaic consumptive rate, time-of-use (TOU) price
Suggested Citation
Zhou N, Liu N, Zhang J, Lei J. Multi-Objective Optimal Sizing for Battery Storage of PV-Based Microgrid with Demand Response. (2019). LAPSE:2019.0098
Author Affiliations
Zhou N: State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Changping District, Beijing 102206, China
Liu N: State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Changping District, Beijing 102206, China [ORCID]
Zhang J: State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Changping District, Beijing 102206, China
Lei J: Electric Power Research Institute, China Southern Power Grid Co., Ltd., Guangzhou 510080, Guangdong Province, China
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Journal Name
Energies
Volume
9
Issue
8
Article Number
E591
Year
2016
Publication Date
2016-07-28
Published Version
ISSN
1996-1073
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PII: en9080591, Publication Type: Journal Article
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LAPSE:2019.0098
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doi:10.3390/en9080591
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Jan 7, 2019
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Calvin Tsay
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