article · Energies
Using solar photovoltaic inverters as static synchronous compensators, known as PV-STATCOM devices, during the night can enhance power distribution network performance. A hunter-prey optimization algorithm was formulated to determine the optimal placement and sizing of these devices under variable twenty-four-hour load conditions. The method aims to reduce electrical energy losses and enhance voltage profiles across distribution grids. Testing on standard thirty-three-node and sixty-nine-node distribution systems demonstrated significant operational gains compared to alternative algorithms such as particle swarm optimization and differential evolution. In both test networks, energy losses fell by roughly fifty-eight percent, and voltage variance dropped by over forty percent. Across the entire daily cycle, all network nodes consistently maintained voltage levels above the ninety-five percent operating threshold, highlighting the reliability of the bio-inspired algorithm in managing grid support resources.
Solar installations often sit idle at night, but repurposing their inverters for grid voltage control can resolve persistent power quality challenges. By using intelligent optimization to position these assets correctly, network operators can prevent voltage drops and substantially reduce wasted electrical energy without needing to invest in dedicated, expensive reactive power equipment.
This methodology is an applied computational tool relevant to distribution network operators and smart grid software developers seeking to enhance grid stability. It offers a framework to maximise existing solar inverter infrastructure during off-peak generation hours. Because the approach has been tested solely in simulated benchmark networks, the technology represents early-stage development that requires testing in utility-grade management platforms before reaching commercial deployment.
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Incorporating photovoltaic (PV) inverters in power distribution systems via static synchronous compensators (PV-STATCOM) during the nighttime has lately been described as a solution to improve network performance. Hunter prey optimization (HPO) is introduced in this study for efficient PV-STATCOM device allocation in distribution systems. HPO generates numerous scenarios for how animals could act when hunting, some of which have been expanded into stochastic optimization. The PV-STATCOM device allocation issue in distribution networks is structured to simultaneously minimize the electrical energy losses and improve the voltage profile while accounting for variable 24 h loadings. The impacts of varying the number of installed PV-STATCOM devices are investigated in distribution systems. It is tested on two IEEE 33-node and 69-node distribution networks. The effectiveness of the proposed HPO is demonstrated in comparison to the differential evolution (DE) algorithm, particle swarm optimization (PSO), artificial rabbits algorithm (ARA), and golden search optimizer (GSO). The simulation results demonstrate the efficiency of the proposed HPO in adequately allocating the PV-STATCOM devices in distribution systems. For the IEEE 33-node distribution network, the energy losses are considerably decreased by 57.77%, and the voltages variance sum is significantly reduced by 42.84%. The energy losses in the IEEE 69-node distribution network decreased by 57.89%, while voltage variations are reduced by 44.69%. Additionally, the suggested HPO is highly consistent than the DE, PSO, ARA, and GSO. Furthermore, throughout the day, the voltage profile at all distribution nodes surpasses the minimum requirement of 95%.
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DOI: 10.3390/en16062790
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