This study proposes a novel multi-objective optimization framework for grid-connected microgrids using quantum particle swarm optimization (QPSO) to address the dual challenges of...
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The model is solved using a multi-objective Particle Swarm Optimization (MOPSO) algorithm, which is well-suited for its fast convergence and ability to efficiently identify the Pareto
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To address the issue of high operating costs in microgrids, this study improves upon the traditional Particle Swarm Optimization (PSO) algorithm by optimizing the inertia weight and introducing a
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The control over microgrid energy transaction committing demand flexibility has been designed in this article by a new reward based generalized stochastic Petri nets (RGSPNs) tuned
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Two PSO algorithms were developed in two steps to find the optimal operating set-points. The first PSO algorithm led to the optimal set-points powers of all micro-grid generators that can satisfy the non
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This study proposes a novel multi-objective optimization framework for grid-connected microgrids using quantum particle swarm optimization (QPSO) to address the dual challenges of...
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In this study, we propose a multi-objective particle swarm algorithm-based optimal scheduling method for household microgrids. A household microgrid optimization model is
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A novel hybrid optimization method is proposed that integrates AHA and PSO to tune STATCOM devices for compliance with grid codes, with a particular focus on enhancing LVRT
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Uses Binary Particle Swarm Optimization (BPSO) to solve the Unit Commitment Problem in the context of electric power generation in an idealized microgrid. Features: Good performance BPSO
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The static synchronous compensator (STATCOM) under consideration in this study is tuned using particle swarm optimization (PSO), the artificial hummingbird algorithm (AHA), and a
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By merging particle swarm optimisation (PSO) and the gravitational search algorithm (GSA), a hybrid modified GSA-PSO (MGSAPSO) method is proposed to optimise the load dispatch
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