Non-uniform distributed energy storage systems allocation in unbalanced distribution networks

Document Type

Conference Proceeding

Publication Title

2022 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)

Publisher

IEEE

School

School of Engineering

Funders

Murdoch University

Comments

Zhang, D., Shafiullah, G. M., Das, C. K., & Wong, K. W. (2022, December). Non-uniform distributed energy storage systems allocation in unbalanced distribution networks [Paper presentation]. 2022 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), Gold Coast, Australia. https://doi.org/10.1109/CSDE56538.2022.10089305

Abstract

The increase in the global energy demand has accelerated the consumption of fossil fuel resources, increased the cost of living, and exacerbated the world's environmental pollution. Therefore, renewable distributed generation (DG), mainly by wind and solar power generation, has developed rapidly in recent years due to its low power generation cost and pollution-free characteristics. However, considering the inherent randomness and intermittency of wind power output, the integration of large-scale renewable distributed generation not only increases the system's complexity but also affects the stable operation of the distribution network, including increased power loss and deteriorated power quality. Connecting the energy storage system (ESS) to the power grid is one of the effective ways to solve the above problems since it plays an active role in stabilizing grid voltage and frequency. In order to improve energy storage utilization efficiency and to reduce the power grid's investment and operation cost, the installation location and capacity optimization of energy storage must be considered. This paper proposes a methodology for the optimal allocation of ESS in the distribution systems to improve the system performance and minimize the investment cost of energy storage. An unbalanced IEEE-33 bus system is modeled with high renewable DGs penetration in DIgSILENT PowerFactory, as an example, to validate the effectiveness of the proposed method. The simulation results confirmed that the proposed method can effectively configure the energy storage with optimal capacity and location and also improve the unbalanced distribution networks' economic efficiency and power quality. © 2022 IEEE.

DOI

10.1109/CSDE56538.2022.10089305

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