Comparisons of Energy Loss Reduction by Phase Balancing in Unbalance Distribution Networks via Metaheuristic Algorithms

Lin, Wei; Huang, Wei-Tzer; Chih, Hsin-Ching; Yao, Kai‐Chao; Li, Zongtai; Ma, Chun-Chiang

doi:10.1109/icpai51961.2020.00049

Cited by 2 publications

(3 citation statements)

References 9 publications

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“…Equations ( 8) and ( 9) ensure that each phase line of a lateral is only assigned to one phase line of a primary feeder. Equations ( 9)- (11) ensure that the same phase sequence (positive sequence) is maintained. Equation ( 12) represents whether or not phase p of the lateral branch l is swapped with phase w of the primary feeder.…”

Section: Milp Formulation Constraintsmentioning

confidence: 99%

“…The water-cycle algorithm has been implemented in a case study to find the optimal phase allocation arrangement [10]. Lin et al propose a metaheuristic algorithm to achieve energy-loss reduction through phase balancing in unbalance distribution networks [11]. The effective power electronics-based dynamic-voltage restorer has been proposed to mitigate the power quality disturbance in secondary distribution networks [12].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Phase Balancing in Electricity Distribution Feeders Using Mixed-Integer Linear Programming

Lin

et al. 2023

Sustainability

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A mixed-integer linear programming (MILP) model that includes reductions in neutral current, feeder energy-loss cost, customer interruption cost, and labor cost is developed to derive the optimal phase-swapping strategy to enhance the phase balancing of distribution feeders. The neutral current of the distribution feeder is reduced by the phase-swapping strategy so that the tripping of the low-energy overcurrent relay can be prevented and customer-service interruption costs and the labor cost to execute the phase-swapping works can be justified by the energy-loss reduction obtained. The novelty of the study is its derivation of the phase-swapping strategy using mixed-integer linear programming to solve the problem of the unbalance of the distribution feeders. A Taipower distribution feeder is used to derive the phase-swapping strategy to demonstrate the proposed MILP model for phase balancing. The comparison of the phase currents and neutral current before phase-swapping reveals that the three-phase balance was not only significantly improved, but that the voltage unbalance was also decreased dramatically using the proposed phase-swapping strategy.

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Section: Milp Formulation Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Phase Balancing in Electricity Distribution Feeders Using Mixed-Integer Linear Programming

Lin

et al. 2023

Sustainability

View full text Add to dashboard Cite

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“…In recent years, intelligent algorithms have experienced observable advancements and such modern approaches are being developed to better tackle engineering issues. Therefore, metaheuristic optimization algorithms, such as Particle Swarm Optimization [26], Genetic Algorithm [22], and Cuckoo Search Optimization (CSO) [27], have been applied for different distribution systems applications. These algorithms have demonstrated their ability to solve engineering problems with near-optimal solutions.…”

Section: Literature Reviewmentioning

confidence: 99%

Community Battery Storage Systems Planning for Voltage Regulation in Low Voltage Distribution Systems

AlRashidi

2022

Applied Sciences

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The regulation of the grid voltage within operational limits becomes increasingly challenging as residential photovoltaic (PV) adoption rises. Therefore, this study proposes a method for the efficient planning of multiple community battery energy storage systems (BESS) in low voltage distribution systems embedded with high residential rooftop PV units. A bi-level optimization method based on a Neural Network Optimization Algorithm is developed to regulate the voltage in grid-connected solar PV. Since BESS characteristics are crucial for the reliable operation of the distribution networks, the objective of the bi-level optimization problem is to optimally place and operate BESS collectively at a distributed system level. The charging/discharging protocol of the batteries management system is obtained utilizing linear programming that minimizes the daily voltage signal. Simulations were carried out on a modified IEEE low voltage test feeder to examine the impact of PV integration and BESS installation on the voltage profile. Experimental results show the efficacy of the proposed method in enabling the utility to determine the optimal location, capacity, and number of BESS in the distribution system to keep the network voltage magnitude within acceptable bounds. In addition, results demonstrate that the network topology, load profiles, and amount of PV power highly influence the BESS characteristics.

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Comparisons of Energy Loss Reduction by Phase Balancing in Unbalance Distribution Networks via Metaheuristic Algorithms

Cited by 2 publications

References 9 publications

Optimal Phase Balancing in Electricity Distribution Feeders Using Mixed-Integer Linear Programming

Optimal Phase Balancing in Electricity Distribution Feeders Using Mixed-Integer Linear Programming

Community Battery Storage Systems Planning for Voltage Regulation in Low Voltage Distribution Systems

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