Optimizing Energy Storage Capacity in Islanded Microgrids Using Immunity-Based Multiobjective Planning

Ying-Yi Hong, Yong-Zhen Lai, Yung-Ruei Chang, Yih- Der Lee and Chia-Hui Lin
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Ying-Yi Hong: Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan 32023, Taiwan
Yong-Zhen Lai: Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan 32023, Taiwan
Yung-Ruei Chang: Nuclear Instrumentation Division, Institute of Nuclear Energy Research, Taoyaun 32546, Taiwan
Yih- Der Lee: Nuclear Instrumentation Division, Institute of Nuclear Energy Research, Taoyaun 32546, Taiwan
Chia-Hui Lin: Nuclear Instrumentation Division, Institute of Nuclear Energy Research, Taoyaun 32546, Taiwan

Energies, 2018, vol. 11, issue 3, 1-15

Abstract: Microgrid operation is challenging because the amount of electricity that is produced from renewables is uncertain and the inertia of distributed generation resources is very small. Energy storage systems can regulate energy, improve the reliability of the power system and enhance the transient stability. This paper determines the optimal capacities of energy storage systems in an islanded microgrid that is composed of wind-turbine generators, photovoltaic arrays, and micro-turbine generators. The energy storage system can enhance the reliability of the microgrid and eliminate the unnecessary load shedding when a severe transient (such as a generator outage) occurs in the islanded microgrid. The studied problem is expressed as a multi-objective programming formulation, which is solved using an immunity-based algorithm. Four objective functions are optimized: minimum of energy storage capacity, minimum of load shedding, maximum of the lowest swing frequency, and minimum of the Customer Average Interruption Duration Index (CAIDI). These four objective functions are subject to both steady-state constraints and the transient-state equality constraint. The steady-state constraints include the total shed load limit, the feasible range of energy storage capacities while the transient-state equality constraint is expressed by the dynamic equation. The Pareto optimums are explored and optimality of the problem is investigated. The simulation results based on an islanded 15-bus microgrid show the applicability of the proposed method.

Keywords: evolutionary algorithm; energy storage; microgrid; Pareto optimum (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 (7)

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