Collaborative deployment of multiple reinforcement methods for network‐loss reduction in distribution system with seasonal loads - Yizhe Xie; Kai Xing; Lizi Luo; Shuai Lu; Cheng Chen; Xiaoming Wang; Wenguang Zhao; Mert Korkali (Energy Conversion and Economics, 2024)
Abstract The integration of seasonal loads, such as cereal baking and aquatic‐product processing loads, often leads to significant voltage deviations and severe peak loads of the distribution system during specific periods, resulting in increased network losses. Traditional approaches for reducing network losses are becoming less effective and cost‐efficient due to the spatiotemporally uneven distribution characteristics of seasonal loads. To address this issue, this study proposes an optimisation model that collaboratively integrates mobile energy storage, switching capacitors, and tie lines to minimise annual network losses in special planning scenarios affected by seasonal loads. The deployment strategies of multiple reinforcement methods are thoroughly analysed, greatly enhancing the explainability and feasibility of the collaborative deployment model. Then, the proposed model is reformulated to a mixed‐integer linear programming model using the inscribed regular dodecagon approximation approach, thereby making it trackable for state‐of‐the‐art solvers. To illustrate the effectiveness of the model, case studies are conducted on a unique 55‐bus distribution system located in East China, which contains feeders with substantial seasonal variation aquaculture loads and with general loads. The effectiveness of multiple reinforcement methods is thoroughly analysed through detailed numerical results. Furthermore, a sensitivity analysis of the investment budget is conducted.