Applied TVA-PSO for optimal energy efficient integration of renewable energy sources based maximizing TEC levels

After the rapid increase in the population demography and industrial revolution, many researchers focus on maintaining the balance between the consumption and the production; in this regard, decentralized production plays an important role to achieve this balance, because of its technical economic aspect such as power losses reduction and voltage profile improvement. These advantages can better exploited through the optimal assessment of Distributed Generation (DG). This paper is interested in the study of the optimal location and size of one and multiple DG based on photovoltaic solar sources PV-DG in Radial Distribution Network (RDN) using the Time Varying Acceleration Particle Swarm Optimization Algorithm (TVA-PSO). This algorithm implemented to maximize the Multi-Objective Functions (MOF) based on the Environmental Pollution Reduction Level (EPRL), the Voltage Deviation Level (VDL), Active Power Loss Level (APLL), the Net Saving Level (NSL), and finally the Short Circuit Level (SCL). The proposed method is tested on the standard IEEE 33-, 69-and 118-bus RDN. Outcomes proves that the proposed TVA-PSO is more efficient to solve the optimal allocation of multiple DGs with high convergence rate and minimum power loss reduction.

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Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).