Reliability Evaluation of an Active Distribution Network Considering DR and Load Reduction Strategies
Year: 2025
Type: article
Abstract: Introduction: Traditional reliability assessment methods are no longer sufficient to cope with the changes triggered by the emergence of microgrids, especially when user-side factors are not sufficiently considered. In this paper, an innovative two-tier load optimization model based on price-responsive Demand Response (DR) and load shedding strategies is proposed to improve the reliability and economic efficiency of distribution networks. Methods: In this paper, a two-layer optimization model is developed. The upper-layer model considers the time-shifting characteristics of demand response to optimize the total electricity costs of users during all time periods after load response. The lower-layer model considers the distance and importance of load reduction to minimize economic losses caused by power shortages. Combined with the two-layer load optimization model and the Sequential Monte Carlo (SMC) algorithm, a reliability assessment process is proposed. Results: An improved reliability assessment index system incorporating economic factors was adopted and validated through simulation in the IEEE RBTS BUS6 F4 system. The simulation results showed that the proposed two-layer load optimization model reduces the system reliability index by 14.38% to 48.9% and the economic index by 40.6%. Discussion: This model overcomes the limitations of traditional methods, which only consider a single load control strategy, achieving coordinated optimization of load shifting and load reduction to enhance system reliability. Conclusion: Compared to existing methods, the proposed two-layer load optimization model demonstrates significant advantages in improving reliability while also considering economic efficiency, thereby achieving a win-win situation for both the power grid and users.
Authors: Weiru Wang, Jinyang Xue, Yechun Xin, Guoqing Li, Yanxu Wang, Hongda Dong, Chenggang Li
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4413179484