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Optimizing Voltage and Reactive Power Compensation in a Distribution Grid Using Metaheuristic Technique

Authors: Ilo, F. C.;

Optimizing Voltage and Reactive Power Compensation in a Distribution Grid Using Metaheuristic Technique

Abstract

The availability of consistent, reasonably priced, and efficient power is a key determinant for the development and sustainability of every society's economy. However, the distribution grid is affected by persistent voltage collapse and power losses. Power losses are caused by various challenges, including reactive power burden, unbalanced loading, and harmonic distortions due to non-linear loads and technical inefficiency. This study uses metaheuristic method, a simple yet effective optimization solution to determine the optimal sizing and placement locations of reactive power compensators (RPC) for voltage optimization and power loss reduction in the distribution grid. It also examined the power distribution network in southeast Nigeria, while the scope covered the New Haven 33kV/11kV distribution grid, modelled with 40 buses, 43 branches, and 26 loads. The study demonstrated average losses of 40.3% (comprising 3.1% active and 37.2% reactive) at the buses, with branch losses accounting for 2.5% active and 3.8% reactive losses, and transformers contributing significantly with 19.7% active and 89.8% reactive power losses. Implementation of Reactive Power Compensators (RPCs) resulted in a voltage improvement of 5.43% for 11 kV and 3.16% for 33 kV, along with an enhanced power factor from 89.19% to 99.15%. This optimization increased the system's maximum loading capacity from 73.54 MW to 103.44 MW and reduced the reactive power burden from 37.29 Mvar to 13.55 Mvar. The cost-benefit analysis indicates potential annual cost savings of approximately $1,933,500 (over 773.4 million naira at $/N400) within the proposed 5-year planning period, with a payback period of less than 11 months.

Keywords

Optimizing Voltage, Metaheuristic Technique, Reactive Power Compensation, Distribution Grid

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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