article · Ain Shams Engineering Journal
Controlling reactive power flow improves electrical system performance, though rising renewable energy penetration and ongoing load growth introduce operational uncertainties. An Adaptive Beluga Whale Optimization algorithm addresses the stochastic optimal reactive power dispatch problem by incorporating photovoltaics, wind turbines, and unified power flow controllers. The method enhances standard optimization mechanisms by integrating a fitness-distance balance selection strategy with territorial solitary male behaviours derived from the Mountain Gazelle Optimizer. Evaluated on the standard IEEE 30-bus test network, the approach demonstrates substantial performance enhancements over alternative methods. Specifically, total expected power losses decrease from 5.3168 megawatts to 3.97985 megawatts when combining optimal renewable and control device integration. In addition, total expected voltage deviation drops from 0.1794 to 0.10689 per unit, while the total voltage stability index improves by decreasing from 0.1289 to 0.0476 per unit.
Modern electricity grids increasingly rely on intermittent wind and solar power alongside shifting consumer demand, which can destabilise voltage levels and increase transmission losses. Computational techniques that successfully account for these fluctuations help preserve network stability, reduce wasted energy during distribution, and allow operators to integrate higher shares of clean generation securely.
This algorithm could assist electricity grid operators, utilities, and network planning engineers in optimising generation dispatch and the placement of power flow control hardware. Because the method was tested exclusively on an IEEE 30-bus simulation, the work represents early-stage algorithm development that requires testing on larger, real-world utility networks before commercial application.
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The electrical system performance can be improved considerably by controlling the reactive power flow in the system. The reactive power control can be achieved by optimal reactive power dispatch (ORPD) problem solution and optimal integration of the FACTS devices. With high penetration of renewable energy sources (RESs) and the load growth, the ORPD solution became a challenging and a complex task due to the stochastic nature of the RERs and the load growth. In this regard, the aim of this paper is to solve the stochastic optimal reactive power dispatch (SORPD) with optimal inclusion of PV units, wind turbines and the unified power flow controller (UPFC) under uncertainties of the load growth and the generated powers. An Adaptive Beluga Whale Optimization (ABWO) is proposed for solving the SORPD which is based on the Fitness-Distance Balance Selection (FDBS) strategy and the territorial solitary males’ strategy of the Mountain Gazelle Optimizer. The proposed ABWO is tested on IEEE 30-bus system and a comparison with other optimization techniques for solving the ordinary ORPD is presented for validating the proposed ABWO. The obtained results reveal that the TEPL is reduced from 5.3168 MW to 3.97985 MW with optimal integration of the RERs and UPFC. Likewise, the TEVD is reduced from 0.1794p.u. to 0.10689p.u. and the TVSI is decreased from 0.1289p.u. to 0.0476p.u.
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DOI: 10.1016/j.asej.2024.102762
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