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Multi-objective design of energy storage in distribution systems based on modified particle swarm optimization

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2 Author(s)
Yixing Xu ; Texas A&M University, College Station, TX 77843 USA ; Chanan Singh

The objectives of the movement toward the smart grid include making the power systems more reliable and economically efficient. The rapid development of the large scale energy storage technology, such as sodium sulfur batteries, makes it an excellent candidate in achieving the goals of the smart grid. This paper proposed a modified multi-objective particle swarm optimization approach to solve the energy storage design problem in distribution systems. A Pareto front is provided by the proposed approach for decision makers to determine the desired tradeoff between multiple objectives. Within the energy storage design variables, not only the conventionally considered energy storage capacity and power rate are included, but also the energy storage operation strategy. Three energy storage operation strategies are presented and their impacts on reliability and economy are illustrated. A case study is performed to demonstrate the effectiveness of the proposed approach. Insights based on the case study results are discussed.

Published in:

2012 IEEE Power and Energy Society General Meeting

Date of Conference:

22-26 July 2012