article · IEEE Systems Journal
A multiobjective salp swarm optimizer has been developed to improve both the technical and economic performance of electrical distribution networks. The approach addresses critical operational challenges by cutting power losses, lowering associated expenditure, stabilising voltage profiles, and reducing the investment costs required for shunt capacitor allocation, while also accounting for uncertain power demand. The algorithm accommodates a combination of continuous, discrete, and integer control variables, converging effectively towards optimal trade-offs on the Pareto front. Evaluated on two Egyptian distribution systems and a large-scale 118-node radial network, the method demonstrates scalable performance and reliable convergence. Testing confirms annual cost savings between 20,000 and 25,000 US dollars across single and multiobjective configurations, alongside minimal voltage deviations from baseline operational targets.
Electricity grid operators constantly balance network reliability against operational expenses. By optimising where and how equipment such as capacitors is deployed, this method cuts costly energy losses and maintains steady voltage levels even when power demand fluctuates. This helps utilities run more efficient distribution systems and lowers the capital and operational expenses needed to keep electrical grids stable.
This tool is relevant to distribution system operators and grid software vendors seeking to automate capacitor planning and loss reduction. Having been applied and tested on data from two Egyptian networks and a 118-node benchmark system, the methodology is at an applied research stage. To reach commercial deployment, it would require integration into commercial utility distribution management software or power flow analysis platforms.
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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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DOI: 10.1109/jsyst.2020.2964743
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