article · IEEE Access
Modern distribution network operators require methods to boost system efficiency while accommodating variable renewable energy sources. A new optimisation formulation addresses this challenge by combining distribution network topology reconfiguration with the strategic reallocation of capacitors. This model accounts for fluctuating daily load profiles throughout an entire year as well as wind power uncertainties using Monte Carlo simulations. To solve the complex network problem, an improved sunflower optimisation algorithm was developed. The approach was evaluated using the standard IEEE 33-node feeder, a practical 84-node network from Taiwan Power Company, and a large-scale 118-node system. The results demonstrate that the method successfully balances operational savings from reduced network energy losses against the capital costs of moving capacitors, outperforming several recent optimisers in computational comparisons.
Integrating intermittent renewable power such as wind into electricity grids can cause network strain and financial inefficiencies. By jointly adjusting grid layout and capacitor placement, network operators can cut down on wasted energy and manage capital expenses. This computational approach offers utility managers a structured way to maintain reliable, cost-effective power delivery under fluctuating demand and generation conditions.
The primary users are electrical distribution network operators and utility planning engineers seeking to reduce operating losses and plan capacitor investments. The research presents an algorithmic tool evaluated on standard benchmark models and utility network data, placing it at the applied simulation and testing stage rather than ready for immediate commercial deployment.
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All over the world, the operators of the power distribution networks (DNs) are still looking for improving the efficiency of their networks. The performance of DNs and lifetime of its component have been significantly affected by its capability of varying their topologies with accurate load gathering via smart grid functions. This paper investigates making use of the smart DNs features and proposes a model of handling the capability of re-allocating the capacitors integrating with configuring the DNs topology. Using the developed formulation, the efficiency of DNs can be improved not only by minimizing the operational costs related to the network losses but also by optimizing the investment costs associated with capacitor re-allocations. Also, various load patterns are employed in the developed formulation to imitate the daily load variations over a year. The improved sunflower optimization algorithm (ISFOA) is proposed in this paper to get the optimal solution of the presented problem. The standard IEEE 33-node feeder and practical 84-node system of Taiwan Power Company (TPC) are the considered test systems. Besides, the uncertainties due to a distributed generation of wind power are investigated via Monte Carlo simulation involved with the proposed ISFOA. Furthermore, to verify the ability of ISFOA to obtain better solutions compared with different recent optimizers, a statistical comparison is carried out based on a large scale 118-node distribution systems. The simulation results reveal that significant technical and economic benefits are obtained by applying the proposed algorithm with higher superiority and effectiveness.
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DOI: 10.1109/access.2020.3047671
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