Research on system resource optimization of distribution network producer-consumer system considering resilience and economy

• Published in: IEEE access 2023-01, Vol.11, p.1-1
• Main Authors: Xu, Xu, Chenguang, He, Chenya, Su, Jian, Ma
• Format: Article
• Language: English
• Subjects: Distribution network; Distribution networks; Economic impact; Electrical loads; Electrical networks; Energy consumption; Genetic algorithms; Hurricanes; Indicators; Load modeling; Multiple objective analysis; NSGA-II; Optimization; Optimization models; Optimization of system resources; Power grids; Power supply; Producer-consumer system; Resilience; Resilient power grid; Sorting algorithms; Tropical cyclones; Wind speed
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2023.3286371

This article proposes a resource optimization strategy for the production-consumption system of a distribution network, which is based on both resilience and economic efficiency of electrical networks in the face of typhoon impacts. Firstly, based on the concept of producer-consumer groups, this paper has constructed a Distribution Network producer-consumer system (DN-PCs) unit model, including energy consumption, system control, and end-user loads. At the same time, this paper has put forward models for typhoon-distribution network line faults, resilience curves, and a resilience evaluation process to quantify resilience indicators of the distribution network. Furthermore, a multi-objective optimization model is developed with the objectives of minimizing economic losses and maximizing resilience indicators. The model is solved using the elitist mechanism Non-dominated sorting genetic algorithm (NSGA-II) and membership degree function to obtain compromise solutions. Finally, to validate the effectiveness of the proposed strategy, this paper has conducted a simulation analysis, take the IEEE 33-node system as an example. The results demonstrate that it is practical to enhance the resilience of electrical networks against typhoon disasters and improve the power supply capacity by configuring PCs units and controlling different flexible loads in the distribution network. Meanwhile, this strategy can improve the economic efficiency of the system. In the future, this strategy will provide power companies with a solution to enhance the power supply capacity of distribution networks.