A Multiobjective Salp Optimization Algorithm for Techno-Economic-Based Performance Enhancement of Distribution Networks

Enhancing the performance of distribution systems is crucial work for their operators. It involves the high necessity for reducing the power losses besides their related costs, enhancing the voltage profile, and minimizing the investment costs of allocated shunt capacitors. Uncertain power demand is...

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Vydáno v:IEEE systems journal Ročník 15; číslo 1; s. 1458 - 1466
Hlavní autoři: Shaheen, Abdullah M., El-Sehiemy, Ragab A.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.03.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Capacitor reallocation
Capacitors
Continuity (mathematics)
Convergence
Cost allocation
Economics
Electric potential
Investment
Loading
losses
Mathematical analysis
medium voltage (MV) distribution networks
Multiple objective analysis
Operators (mathematics)
Optimization
Performance enhancement
Reactive power
Reliability
salp swarm optimizer (SSO)
Shunt capacitors
Voltage
Voltage control
ISSN:1932-8184, 1937-9234
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Shrnutí:Enhancing the performance of distribution systems is crucial work for their operators. It involves the high necessity for reducing the power losses besides their related costs, enhancing the voltage profile, and minimizing the investment costs of allocated shunt capacitors. Uncertain power demand is also augmented to achieve reliable operation of distribution systems. To fulfill the previous techno-economic merits, this article proposes a multiobjective framework. In this line, a multiobjective salp swarm optimizer (MSSO) is developed. MSSO is characterized by its simplicity, good convergence, and high capability of driving the solutions toward true optimal Pareto front. The developed MSSO optimizes the technical and economical objective functions considering integer, discrete, and continuous natures of control variables. The proposed MSSO is successively tested on two Egyptian distribution networks. Significant merits are achieved with reduction of 20-25 k/year in the total costs for single and multiobjective cases. In addition, it preserves the voltage deviations at very low levels compared with the flat value. The superiority and scalability of the proposed MSSO are satisfied for large-scale 118-node radial system. Best compromise solutions at acceptable convergence rates and competitive statistical indices are achieved.
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content type line 14
ISSN:1932-8184
1937-9234
DOI:10.1109/JSYST.2020.2964743