Abstract
This study aims to investigate multi-objective configuration optimization of a hybrid energy storage system (HESS). In order to maximize the stability of the wind power output with minimized HESS investment, a multi-objective model for optimal HESS configuration has been established, which proposes decreasing the installation and operation & maintenance costs of an HESS and improving the compensation satisfaction rate of wind power fluctuation. Besides, fuzzy control has been used to allocate power in the HESS for lengthening battery lifetime and ensuring HESS with enough energy to compensate the fluctuation of the next time interval. Instead of converting multiple objectives into one, a multi-objective particle swarm optimization with integration of bacteria quorum sensing and circular elimination (BC-MOPSO) has been applied to provide diverse alternative solutions. In order to illustrate the feasibility and effectiveness of the proposed model and the application of BC-MOPSO, simulations along with analysis and discussion are carried out. The results verified the feasibility and effectiveness of the proposed approach.
Highlights
Wind power generation and its techniques have attracted increasing worldwide attention because of their effective reduction in environmental pollution, fossil fuel consumption, and the costs of overall electricity generation [1]
In order to promote grid penetration capability and meet standard requirements for integration of renewable distributed generations, it’s necessary to apply appropriate allocation of distributed energy storage systems (ESSs) for decreasing negative effects on the grid that are brought about by fluctuating power and improving the power quality and system stability of the distribution network penetrated with such RDGs
Function of hybrid energy storage system (HESS) is realized through compensating the fluctuation of wind power, PWD, with its real-time output power, PSC + PB
Summary
Wind power generation and its techniques have attracted increasing worldwide attention because of their effective reduction in environmental pollution, fossil fuel consumption, and the costs of overall electricity generation [1]. Its technology has been considered as another one of the most mature renewable distributed generations (RDGs) and widely applied as a mean to reach emission reduction with the increasing concern of environmental protection In order to investigate the compensation of power fluctuation of distributed generation with intermittent characteristics, and reasonably allocate HESS for balancing the compensation effect and investment economy, this study establishes a multi-objective model for optimally allocating HESS considering wind power generation, in which the objectives are to minimize the installation, operation, and maintenance costs and to maximize the satisfaction rate of power fluctuation compensation. Fuzzy control [8] is introduced to optimally schedule the power output of each ESS for avoiding destroy the SOC limits, lengthening the battery lifetime, and ensuring HESS with enough energy to compensate the fluctuation of the time interval. Numerical simulation along with discussion has been carried out to demonstrate advantages of the proposed model and effectiveness of the application of BC-MOPSO
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