Economic Dispatch in Electrical Systems with Hybrid Generation Using the Differential Evolution Algorithm: A Comparative Analysis with Other Optimization Techniques Under Energy Limitation Scenarios

Jorge Cadena-Albuja, Carlos Barrera-Singaña (), Hugo Arcos and Jorge Muñoz
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Jorge Cadena-Albuja: Department of Electrical Engineering, Universidad Politécnica Salesiana, Quito EC170702, Ecuador
Carlos Barrera-Singaña: Department of Electrical Engineering, Universidad Politécnica Salesiana, Quito EC170702, Ecuador
Hugo Arcos: Faculty of Electrical Engineering, Escuela Politécnica Nacional, Quito EC170525, Ecuador
Jorge Muñoz: Department of Electrical Engineering, Universidad Politécnica Salesiana, Quito EC170702, Ecuador

Energies, 2025, vol. 18, issue 13, 1-25

Abstract: This study focuses on the challenge of short-term economic dispatch in hybrid generation systems, specifically under scenarios where energy constraints arise due to reduced water availability. The primary aim is to compare various generation scenarios to evaluate the influence of renewable energy-based power plants on the overall operating cost of an Electric Power System. The hybrid generation system under analysis comprises hydroelectric, thermoelectric, photovoltaic solar, and wind power plants. The latter two, in particular, play a crucial role, yet their performance is highly dependent on the variability of their primary resources—solar radiation, wind speed, and ambient temperature—which are inherently stochastic. To estimate their behavior, the Monte Carlo method is applied, utilizing probability distribution functions to predict resource availability throughout the planning horizon. Once the scenarios are established, the problem is formulated as a hydrothermal dispatch optimization, which is then tackled using heuristic and metaheuristic approaches, with a strong focus on the Differential Evolution algorithm.

Keywords: economic dispatch; hybrid generation; Monte Carlo; heuristic; metaheuristic (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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