Multi-objective Optimisation of Distributed Generation Units in Unbalanced Distribution Systems

Ramsami, Pamela; King, Robert

doi:10.1007/978-3-030-18240-3_7

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…Overall, the previous studies [30][31][32] mostly focused on the consideration of the multiobjective function. However, the efectiveness of the multiobjective function has not been clearly and accurately evaluated.…”

Section: Proposals Novelties and Contributionsmentioning

confidence: 99%

Optimal Placement of Photovoltaic Distributed Generation Units in Radial Unbalanced Distribution Systems Using MATLAB and OpenDSS-Based Cosimulation and a Proposed Metaheuristic Algorithm

Pham

Nguyen

Kien

2022

International Transactions on Electrical Energy Systems

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In this paper, an improved slime mould algorithm (ISMA) is proposed for finding the optimal location and sizing of photovoltaic distributed generation units (PVDGUs) in unbalanced distribution systems (UDSs). The proposed method is developed by changing the control variable update mechanism of the original slime mould algorithm (SMA). Total power losses on distribution lines and voltage deviation index of all buses are minimized under the consideration of various constraints. The location and sizing of PVDGUs found by ISMA are added into the cosimulation between MATLAB and OpenDSS for reaching other remaining parameters of UDSs. In addition, sunflower optimization (SFO), social-ski drive (SSD), cuckoo search algorithm (CSA), salp swarm algorithm (SSA), bonobo optimizer (BO), and SMA are also run for finding PVDGUs placement solution on the unbalanced three-phase IEEE 123-bus test feeder. As a result, the proposed ISMA can reduce the power loss up to 78.88% and cut the voltage deviation up to 1.4779 pu while that of others is from 69.10% to 78.87% and from 1.5759 to 1.4996 pu. Thus, ISMA should be used to place PVDGUs in UDSs meanwhile the cosimulation between MATLAB and OpenDSS should be applied as a power flow calculation tool for UDSs.

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Section: Proposals Novelties and Contributionsmentioning

confidence: 99%