Abstract
Many traditional distribution systems (TDSs) flaws and weaknesses are fixed when renewable distributed generations (RDGs) is integrated into them. Some of the forces that have driven work on the integration of renewable sources into modern conventional power systems are the effective strategies for increasing system efficiency and reducing total cost. This paper introduces the particle swarm optimization (PSO) method for solving problems related to optimal power flow (OPF) that involve solar photovoltaics (PVs) and wind turbines (WT). The aim is to improve the algorithm’s ability to conduct comprehensive searches for the best possible solution. Therefore, a modified investigation into the impact of such integration on power losses and cost reduction at a large conventional power grid approach using PSO to choose the hourly best load flow in the 118 bus IEEE system and utilize MATPOWER for power grid simulations for communication network modeling with RDG integration under various operational situations. Simulation results confirmed that the algorithm can be an efficient choice to solve the OPF problem, minimize the number of generators (Gs), power losses, and cost compared to the fuel source. This provides a deep analysis of how to combine the benefits of solar and wind power to increase the sustainability and economics of a power grid, with salient conclusions for the energy industry aiming to improve grid performance.
Funding Information
  • King Khalid University (RGP2/419/46)

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