Optimal sizing of hybrid Systems for Power loss Reduction and Voltage improvement using PSO algorithm: Case study of Guissia Rural Grid

Djidimbélé, Répélé; Ngoussandou, Bello-Pierre; Kidmo, Dieudonné Kaoga; Kitmo,; Bajaj, Mohit; Raïdandi, Danwé

doi:10.1016/j.egyr.2022.06.093

Cited by 33 publications

(7 citation statements)

References 18 publications

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“…For this reason, photovoltaic generators must undergo extensive testing. Several types of test system have been developed [ 8 ]. One of these is called a PV emulator.…”

Section: Introductionmentioning

confidence: 99%

Optimal sizing and power losses reduction of photovoltaic systems using PSO and LCL filters

F. Elnaggar,

Duvalier Péné,

Boussaibo

et al. 2024

PLoS ONE

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The integration of renewable energy systems into electricity grids is a solution for strengthening electricity distribution networks (SEDNs). Renewable energies such as solar photovoltaics are suitable for reinforcing a low-voltage line by offering an electrical energy storage system. However, the integration of photovoltaic systems can lead to problems of harmonic distortion due to the presence of direct current or non-linear feedback in networks from other sources. Therefore, connection standards exist to ensure the quality of the energy before injection at a point of common coupling (PCC). In this work, particle swarm optimization (PSO) is used to control a boost converter and to evaluate the power losses and the harmonic distortion rate. The test on the IEEE 14 bus standard makes it possible to determine the allocation or integration nodes for other sources such as biomass, wind or hydrogen generators, in order to limit the impact of harmonic disturbances (LIHs). The evaluation of the harmonic distortion rate, the power losses as well as the determination of the system size is done using an objective function defined based on the integration and optimization constraints of the system. The proposed model performs better since the grid current and voltage are stabilized in phase after the photovoltaic source is injected.

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“…For this reason, photovoltaic generators must undergo extensive testing. Several types of test system have been developed [ 8 ]. One of these is called a PV emulator.…”

Section: Introductionmentioning

confidence: 99%

Optimal sizing and power losses reduction of photovoltaic systems using PSO and LCL filters

F. Elnaggar,

Duvalier Péné,

Boussaibo

et al. 2024

PLoS ONE

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“…Te ftness value of the particle can be determined by the ftness function defned by the problem, and then iteratively iterates continuously. Te speed and position of the particle are afected by the historical optimal solution of the particle itself and the global optimal solution of the group [28]. Let the particles explore and develop in the search space, and fnally fnd the global optimal solution, as shown in Figure 3(a).…”

Section: Pso To Csa Optimizationmentioning

confidence: 99%

Research on Risk Identification of Coal and Gas Outburst Based on PSO‐CSA

Peng

Shi

et al. 2023

Mathematical Problems in Engineering

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Aiming at the identification of coal and gas outburst risk, using the advantages of the clone selection algorithm (CSA), such as self-adaptation and robustness, and the characteristics of fast convergence of particle swarm optimization (PSO) algorithm, the complex decoding problem, and mutation process brought by CSA binary coding are used. It is difficult to control the problem. Using PSO optimization, the problem of abnormal detection and identification in coal and gas outburst monitoring is developed and studied, and a CSA coal and gas outburst risk anomaly detection and identification model based on PSO optimization variation is established. The model uses the coal and gas outburst index data as a collection of antigen-stimulated antibodies to achieve abnormal detection and identification of measured data. With the help of the measured data, the verification results show that the model can effectively detect and identify the risk of coal and gas outburst, and the identification results are consistent with the risk of coal and gas outburst in the field. It can be used as an effective risk identification model to guide coal mining work.

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“…To overcome optimization challenges, MA have gained researchers attention in the past few years 15 algorithms are used to replicate the biological behavior of species [16][17][18][19][20][21] . SHO is a novel MA that improves local exploitation with high convergence accuracy and avoidance of local extremum, thus can be used in solving complex optimization problems 22 .…”

Section: Introductionmentioning

confidence: 99%

Optimal Energy Management Applying Load Elasticity Integrating Renewable Resources

Ragab

Ibrahim

Desouki

et al. 2023

Preprint

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Urban growth aimed at developing smart cities confronts several obstacles, such as difficulties and costs in constructing stations and meeting consumer demands. These are possible to overcome by integrating Renewable Energy Resources (RESs) with the help of demand side management (DSM) for managing generation and loading profiles to minimize electricity bills while accounting for reduction in carbon emissions and the peak to average ratio (PAR) of the load. This study aims to achieve a multi-objective goal of optimizing energy management in smart cities which is accomplished by optimally allocating RESs combined with demand response (DR) for creating a flexible load profile under RESs and load uncertainty. A comprehensive study is applied to IEEE 69-bus with different scenarios using Sea-Horse Optimization (SHO) for optimal citing and sizing of the RESs while serving the objectives of minimizing total power losses and reducing PAR. SHO performance is evaluated and compared to other techniques such as Genetic Algorithm (GA), Grey Wolf Optimization (GWO) and Whale Optimization (WO) algorithms. The results show that combining elastic load shifting with optimal sizing and allocation using SHO achieves a global optimum solution for the highest power loss reduction while using a significantly smaller sized RESs than the counterpart.

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Optimal sizing of hybrid Systems for Power loss Reduction and Voltage improvement using PSO algorithm: Case study of Guissia Rural Grid

Cited by 33 publications

References 18 publications

Optimal sizing and power losses reduction of photovoltaic systems using PSO and LCL filters

Optimal sizing and power losses reduction of photovoltaic systems using PSO and LCL filters

Research on Risk Identification of Coal and Gas Outburst Based on PSO‐CSA

Optimal Energy Management Applying Load Elasticity Integrating Renewable Resources

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