article · Energy Reports
Modern electrical distribution networks face operational challenges due to fluctuating renewable energy generation and shifting consumer demand. To address this, an operational approach using the Horned Lizard Optimization Algorithm coordinates network reconfiguration, photovoltaic systems, and distribution static compensators. Tested on a standard IEEE 33-bus distribution network, the model accounts for uncertainties in solar generation, electricity prices, and electrical loads. The evaluation assessed three scenarios, comparing standalone photovoltaic integration against combined systems. Integrating solar units, static compensators, and network reconfiguration delivered the strongest performance. Compared to the base case, this combined strategy reduced overall costs by 45.6 per cent, decreased active power losses by 66.3 per cent, improved voltage deviations by 71.04 per cent, and cut emissions by 36.72 per cent, showcasing the benefits of coordinating physical grid adjustments with dynamic reactive power compensation.
Integrating large amounts of intermittent solar power into power grids can trigger voltage instability, higher energy losses, and increased operational costs. Demonstrating that algorithmic network reconfiguration combined with static compensators can stabilize voltage, reduce energy waste, and lower emissions offers grid operators a viable method to accommodate expanding renewable generation without undermining distribution reliability.
The method is early-stage research demonstrated via simulation on a standard IEEE 33-bus benchmark network. It is relevant to electricity distribution utilities, microgrid operators, and energy management software vendors. Transitioning to commercial deployment would require integrating the algorithm into operational grid control software and advanced distribution management systems to manage automated switching and compensation hardware in real-time.
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The optimal operation of Distribution Networks (DNs) using network reconfiguration has become more critical in the modern power system due to the widespread use of Renewable Energy Sources (RESs) and the imbalance between load demand and energy provided by RESs. However, attaining the most efficient functioning while integrating RESs is a challenging endeavor due to the unpredictability of the electrical system and the complexities associated with network reconfiguration. Integrating Distribution Static Compensators (D-STATCOMs) with network reconfiguration is powerful for improving voltage deviation reducing overall costs, and minimizing active power losses, while successfully accommodating the fluctuating characteristics of renewable energy sources. To tackle these difficulties, we offer the Horned Lizard Optimization Algorithm (HLOA), a new approach for optimizing the operation of DNs. The efficacy of HLOA is showcased on the IEEE 33-bus DN, to minimize costs, voltage deviations, real power losses, and emissions in the presence of unpredictable factors like photovoltaic (PV) uncertainties, price changes, and load demand. The analysis encompasses three case studies: one focused on optimizing operation solely with PV integration, another using both PV and D-STATCOM integration, and a third incorporating PV, D-STATCOMs, and network reconfiguration. The results indicate that the combination of PV, D-STATCOMs, and network reconfiguration significantly decreases overall cost by 45.6 %, real power losses are reduced by 66.3 %, and voltage variations are improved by 71.04 %. Emissions are mitigated by 36.72 % compared to the base case.
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DOI: 10.1016/j.egyr.2024.07.050
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