| Zhang Maosong (张茂松)*,Zhang Chunyu*,Hao Shi*,Yang Jie**,Yang Lingxiao***,Wang Xiuqin*.[J].高技术通讯(英文),2026,32(1):97~108 |
|
| Optimal scheduling of active distribution networks based on multi-scenario fuzzy set based charging station resource prediction |
| |
| DOI：10. 3772 / j. issn. 1006-6748. 2026. 01. 010 |
| 中文关键词: |
| 英文关键词: charging station resource prediction, subtractive optimizer algorithm, multi-scenario fuzzy set, two-stage optimal scheduling, distribution network cost optimization |
| 基金项目: |
| Author Name | Affiliation | | Zhang Maosong (张茂松)* | (* School of Electrical Engineering and Automation, Anhui University, Hefei 230601, P. R. China)
(** State Grid Hubei Electric Power Co. , Ltd. Economic and Technological Research Institute, Wuhan 430000, P. R. China)
(*** School of Artificial Intelligence, Anhui University, Hefei 230601, P. R. China) | | Zhang Chunyu* | | | Hao Shi* | | | Yang Jie** | | | Yang Lingxiao*** | | | Wang Xiuqin* | |
|
| Hits: 30 |
| Download times: 31 |
| 中文摘要: |
| |
| 英文摘要: |
| With the large-scale integration of new energy sources, various resources such as energy storage, electric vehicles (EVs), and photovoltaics (PV) have participated in the scheduling of active distribution networks (ADNs), posing new challenges to the operation and scheduling of distribution networks. Aiming at the uncertainty of PV and EV, an optimal scheduling model for ADNs based on multi-scenario fuzzy set based charging station resource forecasting is constructed. To address the scheduling uncertainties caused by PV and load forecasting errors, a day-ahead optimal scheduling model based on conditional value at risk (CVaR) for cost assessment is established, with the optimization objectives of minimizing the operation cost of distribution networks and the risk cost caused by forecasting errors. An improved subtractive optimizer algorithm is proposed to solve the model and formulate day-ahead optimization schemes. Secondly, a forecasting model for dispatchable resources in charging stations is constructed based on event-based fuzzy set theory. On this basis, an intraday scheduling model is built to comprehensively utilize the dispatchable resources of charging stations to coordinate with the output of distributed power sources, achieving optimal scheduling with the goal of minimizing operation costs. Finally, an experimental scenario based on the IEEE-33 node system is designed for simulation verification. The comparison of optimal scheduling results shows that the proposed method can fully exploit the potential scheduling resources of charging stations, improving the operation stability of ADNs and the accommodution capacity of new energy. |
|
View Full Text
View/Add Comment Download reader |
| Close |
|
|
|
