Optimal stochastic power flow using enhanced multi-objective mayfly algorithm

For the classical multi-objective optimal power flow (MOOPF) problem, only traditional thermal power generators are used in power systems. However, there is an increasing interest in renewable energy sources and the MOOPF problem using wind and solar energy has been raised to replace part of the the...

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Vydáno v:Heliyon Ročník 10; číslo 5; s. e26427
Hlavní autoři: Zhu, Jianjun, Zhou, Yongquan, Wei, Yuanfei, Luo, Qifang, Huang, Huajuan
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Elsevier Ltd 15.03.2024
Elsevier
Témata:
algorithms
electric potential difference
energy costs
Ephemeroptera
Metaheuristic
Multi-objective mayfly algorithm
prediction
Renewable energy
solar energy
Stochastic power flow
Weibull statistics
wind
Multi-objective mayfly algorithm
Stochastic power flow
Metaheuristic
Renewable energy
ISSN:2405-8440, 2405-8440
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Shrnutí:For the classical multi-objective optimal power flow (MOOPF) problem, only traditional thermal power generators are used in power systems. However, there is an increasing interest in renewable energy sources and the MOOPF problem using wind and solar energy has been raised to replace part of the thermal generators in the system with wind turbines and solar photovoltaics (PV) generators. The optimization objectives of MOOPF with renewable energy sources vary with the study case. They are mainly a combination of 2–4 objectives from fuel cost, emissions, power loss and voltage deviation (VD). In addition, reasonable prediction of renewable power is a major difficulty due to the discontinuous, disordered and unstable nature of renewable energy. In this paper, the Weibull probability distribution function (PDF) and lognormal PDF are applied to evaluate the available wind and available solar power, respectively. In this paper, an enhanced multi-objective mayfly algorithm (NSMA-SF) based on non-dominated sorting and the superiority of feasible solutions is implemented to tackle the MOOPF problem with wind and solar energy. The algorithm NSMA-SF is applied to the modified IEEE-30 and standard IEEE-57 bus test systems. The simulation results are analyzed and compared with the recently reported MOOPF results.
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ISSN:2405-8440
2405-8440
DOI:10.1016/j.heliyon.2024.e26427