Meta-heurísticas aplicadas em problemas de sistemas elétricos de potência com mercado atacadista de energia

Abstract

This paper presents methodologies to address two important issues in the electrical sector: Thermal Unit Commitment and Electric Power Transmission Expansion Planning. Both will be addressed in the context of a decentralized Wholesale Electricity Market, where sellers and buyers freely negotiate energy through hourly auctions on the Power Exchanges (PX) platform. The problem of Profit-Based Unit Commitment (PBUC) will be solved using metaheuristics and priority lists. The solution to this problem aims to maximize the profit of a generation company by selling energy in the Day-Ahead market and selling reserve in the Reserve Capacity market over 24 hours. Modifications are proposed to improve the performance of the metaheuristic Genetic Algorithm (GA) in solving the PBUC. The problem of Transmission Network Expansion Planning in Wholesale Electricity Markets will be solved using the Grey Wolf Optimization (GWO) metaheuristic. For this purpose, a stochastic model is proposed that takes into account uncertainties regarding wind generation supply and Day-Ahead market demand. The objective of this model is to assist the transmission network planner in identifying plans that improve the economic efficiency of the system, prioritizing electricity transactions. Results obtained from test systems show that the proposed methodologies are promising for real-world applications.