Optimal sizing of hybrid renewable energy systems for reliability enhancement and cost minimization using multiobjective technique in microgrids

Microgrids can meet their electrical energy needs through the use of renewable energy systems and energy storage. Combining hybrid renewable energy system (HRES) with a battery energy storage system (BESS) is the best way to increase the systems reliability while still satisfying load demand. Suitab...

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Veröffentlicht in:Energy storage (Hoboken, N.J. : 2019) N.J. : 2019), 2023-06, Vol.5 (4), p.n/a
Hauptverfasser: Vaka, Srinivas Sandeep Kumar Reddy, Matam, Sailaja Kumari
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Sprache:eng
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Zusammenfassung:Microgrids can meet their electrical energy needs through the use of renewable energy systems and energy storage. Combining hybrid renewable energy system (HRES) with a battery energy storage system (BESS) is the best way to increase the systems reliability while still satisfying load demand. Suitable sizing of microgrid with optimal power allocations of HRES and BESS in terms of capacity and discharge leads to improved reliability. Cost and reliability are two important aspects of microgrid system functioning. While designing the system with HRES and BESS, there must be an appropriate balance between cost and reliability. This paper presents an algorithm for optimal design of HRES with BESS for optimizing levelized cost of electricity (LCOE) and power supply reliability factor (PSRF) Particle swarm optimization and epsilon constraint based multi‐objective PSO algorithms are used to solve the objectives considering 24 hours time horizon. A hybrid Wind‐PV system with Diesel Generator and BESS is considered for the study. In this work, 12 trails of simulation runs are made to obtain accurate values of average levelized cost of electricity and power supply reliability factor along with the optimal power allocations of DGs and BESS. According to the findings, sizing of HRES with BESS optimally lowers the LCOE by reducing the quantity of power drawn from the grid and improves PSRF. ε‐MPSO provides the optimal results in minimizing the LCOE by obtaining proper energy management between HRES and BESS with improved reliability.
ISSN:2578-4862
2578-4862
DOI:10.1002/est2.419