Multi-Objective Optimisation of Photovoltaic Systems and Unified Power Quality Conditioners with Simultaneous Distribution Network Reconfiguration

Ramsami, Pamela; King, Robert

doi:10.1109/elecom49001.2020.9297033

Cited by 4 publications

(3 citation statements)

References 25 publications

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“…1. From the 64 possible switch combinations, only the 48 combinations which generated a radial network structure were used in the simulation [23].…”

Section: Test System 231 the Distribution Systemmentioning

confidence: 99%

“…Although there exist possible interactions among the network structure, DG units and CPDs in the power system, the addition of DG units and CPDs with simultaneous DNR have been barely explored. This paper is an extension of the work originally presented in the 2020 3 rd International Conference on Emerging Trends in Electrical, Electronic and Communications Engineering (ELECOM) [23]. In [23], the multi-objective optimisation of PV systems and UPQC was performed with simultaneous DNR using non-dominated Sorting Genetic Algorithm-II (NSGA-II), Strength Pareto Evolutionary Algorithm-2 (SPEA2) and Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D).…”

Section: Introductionmentioning

confidence: 99%

“…This paper is an extension of the work originally presented in the 2020 3 rd International Conference on Emerging Trends in Electrical, Electronic and Communications Engineering (ELECOM) [23]. In [23], the multi-objective optimisation of PV systems and UPQC was performed with simultaneous DNR using non-dominated Sorting Genetic Algorithm-II (NSGA-II), Strength Pareto Evolutionary Algorithm-2 (SPEA2) and Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D). Three objective functions were considered namely active power loss, voltage deviation and total cost liable to constraints.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Hybrid Frameworks for the Multi-objective Optimization of Distributed Generation Units and Custom Power Devices with Simultaneous Distribution Network Reconfiguration

Ramsami¹,

King²

2022

J. Engg. Res. & Sci.

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The increased penetration of renewable energy sources in the distribution system affects the stability and efficiency of the system. To account for the intermittent nature of these sources, distribution network reconfiguration and the integration of custom power devices are important. This paper aims to identify the optimum location of photovoltaic systems and unified power quality conditioners in the distribution system considering economic and technical aspects. Three metaheuristic algorithms namely nondominated sorting genetic algorithm-II (NSGA-II), strength pareto evolutionary algorithm-2 (SPEA2) and multi-objective evolutionary algorithm based on decomposition (MOEA/D) were employed. Furthermore, three hybrid algorithms were developed by dividing the population into two parts. Multi-objective particle swarm optimisation (MOPSO) was applied in the upper part while NSGA-II, SPEA2 or MOEA/D was used in the lower part of the population resulting in three hybrid algorithms: MOPSO-NSGA II, MOPSO-SPEA2, MOPSO-MOEA/D. The simulation was performed on the IEEE-123 Node Test Feeder system using the OpenDSS and MATLAB environment. The performance of the proposed algorithms was compared according to their computation time and performance metrics such as pure diversity, generational distance and spacing. It was found that the hybrid algorithms enhance the convergence of the solutions to the true Pareto front. Combining SPEA2 or MOEA/D with MOPSO also reduced the complexity of the algorithms resulting in a lower simulation time.

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“…1. From the 64 possible switch combinations, only the 48 combinations which generated a radial network structure were used in the simulation [23].…”

Section: Test System 231 the Distribution Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%