Distributed Optimization Strategy for Multi Area Economic Dispatch Based on Electro Search Optimization Algorithm

TL;DR

This paper introduces an electro search optimization algorithm (ESOA) for solving complex multi-area economic dispatch problems, effectively handling constraints and improving cost minimization across multiple power systems.

Contribution

The paper proposes a novel ESOA-based method for multi-area economic dispatch, demonstrating superior accuracy and robustness over existing approaches.

Findings

ESOA outperforms other methods in accuracy and robustness.

Effective handling of constraints like tie line capacity and prohibited zones.

Validated on systems with up to 40 generators and multiple areas.

Abstract

A new adopted evolutionary algorithm is presented in this paper to solve the non-smooth, non-convex and non-linear multi-area economic dispatch (MAED). MAED includes some areas which contains its own power generation and loads. By transmitting the power from the area with lower cost to the area with higher cost, the total cost function can be minimized greatly. The tie line capacity, multi-fuel generator and the prohibited operating zones are satisfied in this study. In addition, a new algorithm based on electro search optimization algorithm (ESOA) is proposed to solve the MAED optimization problem with considering all the constraints. In ESOA algorithm all probable moving states for individuals to get away from or move towards the worst or best solution needs to be considered. To evaluate the performance of the ESOA algorithm, the algorithm is applied to both the original economic dispatch with 40 generator systems and the multi-area economic dispatch with 3 different systems such as: 6 generators in 2 areas; and 40 generators in 4 areas. It can be concluded that, ESOA algorithm is more accurate and robust in comparison with other methods.