An hybrid evolutionary approach for UC-based market clearing

Abstract

The restructuring of electricity markets has caused significant changes in electric power systems of various countries. In this new scenario, each generation company performs individual dispatch strategies to maximize their financial benefits, while meeting power demand and spinning reserves are no longer mandatory. On the other hand, the system operator is looking for a minimum price of energy while demand and security constraints are met. These two points of view coexist in a competitive environment and are modeled and solved in this work.The simultaneous solution for the profit-based unit commitment (considering the point of view of generating agents) and the security-constrained minimum-cost unit commitment (operator side) problems considering a 24-h planning horizon is formulated in this study. The goal is to obtain the lowest price at which the generating agents are willing to meet the demand of the energy market, considering the network constraints. The algorithm emulates the behavior of the generating agents in offering products for both the energy primary and reserve markets in response to a reference price offered by the market operator. This iterative procedure is completed when the supply of generators is sufficient to meet demand and security constraints.The proposed solution method is based on evolutionary strategies and Lagrange relaxation, resulting in a robust hybrid approach. The algorithm was validated in a six-node system, 7 branches and 10 generating units, considering various scenarios. The results demonstrated the effectiveness of the proposed method, which proved able to solve several models of the unit commitment problem.