Optimizing Energy Operation and Planning using Ring Cellular Encode-Decode Univariate Marginal Distribution Algorithm

Abstract

Efficient energy management is critical to building inclusive, safe, resilient, and sustainable cities and human settlements. Optimizing the operation and planning of smart grids is crucial in this regard and remains an active research area. The "Competition on Evolutionary Computation in the Energy Domain" has been held annually since 2017. Its 2023 edition focuses on two problems: Risk-based optimization of energy resource management considering the uncertainty of high penetration of distributed energy resources, and Long-term transmission network expansion planning. In this paper, we apply the RCED-UMDA algorithm to solve these problems, and our experimental results demonstrate its superiority over the top three algorithms of the 2022 and 2021 competition editions.