Impact of Energy Storage Useful Life on Intelligent Microgrid Scheduling

Carlo Baron, Ameena S. Al-Sumaiti and Sergio Rivera
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Carlo Baron: Electric Engineering Department, Universidad Nacional de Colombia, Bogotá 111321, Colombia
Ameena S. Al-Sumaiti: Advanced Power and Energy Center, Electrical Engineering and Computer Science Department, Khalifa University, Abu Dhabi 27788, UAE
Sergio Rivera: Electric Engineering Department, Universidad Nacional de Colombia, Bogotá 111321, Colombia

Energies, 2020, vol. 13, issue 4, 1-23

Abstract: Planning the operation scheduling with optimization heuristic algorithms allows microgrids to have a convenient tool. The developments done in this study attain this scheduling taking into account the impact of energy storage useful life in the microgrid operation. The scheduling solutions, proposed for the answer of an optimization problem, are obtained by using a metaheuristic algorithm called Differential Evolutionary Particle Swarm Optimization (DEEPSO). Thanks to the optimization that is conducted in this study, it is possible to formulate dispatches of the existent microgrid (MG) by always looking for the ideal dispatch that implies a lower cost and provides a greater viability to any project related to renewable energy, electric vehicles and energy storage. These advances oblige the battery manufacturers to start looking for more powerful batteries, with lower costs and longer useful life. In this way, this paper proposes a scheduling tool considering the energy storage useful life.

Keywords: Economic dispatch; electric vehicles; energy storage; Metaheuristic Algorithm; microgrid; renewable energy; uncertainty cost (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: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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