Cooperative Scheduling Optimization Strategy of Smart Park Distribution Network Considering Source-Load-Storage-Charge Interaction

Addressing the power time scale mismatch between source and load in a park and high PV curtailment, a day-ahead and intraday cooperative scheduling optimization strategy is proposed integrating source-load-storage-charging interactions. First, aiming to analysis the amount of EV response under different price subsidies, a cloud model of EV response uncertainty is constructed based on price incentives in the park distribution network. Second, in the day-ahead scheduling stage, the charging scheduling of energy storage and EVs are optimized based on daily forecasts of park loads and PV combined with time-sharing tariffs for reducing the energy cost and PV abandonment. Then, in the intraday scheduling stage, the day-ahead scheduling plan deviation is corrected by real-time rolling based on the 4-hour forecast results. Finally, for the model is solved with YALMIP and Gurobi. The simulation results show that the optimal scheduling method can effectively alleviate the PV abandonment problem, reduce the operation cost, and realize the interactive regulation of source-load-storage-charge.

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Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/icips64173.2024.10900195
Primary Topic
Smart Grid Energy Management
Type
article
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Cooperative Scheduling Optimization Strategy of Smart Park Distribution Network Considering Source-Load-Storage-Charge Interaction

Tingxian Xu, Weihan Li, Nan Hu, Rui Dong
Smart Grid Energy Management
article

Cooperative Scheduling Optimization Strategy of Smart Park Distribution Network Considering Source-Load-Storage-Charge Interaction

Tingxian Xu, Weihan Li, Nan Hu, Rui Dong
article en

Abstract

Addressing the power time scale mismatch between source and load in a park and high PV curtailment, a day-ahead and intraday cooperative scheduling optimization strategy is proposed integrating source-load-storage-charging interactions. First, aiming to analysis the amount of EV response under different price subsidies, a cloud model of EV response uncertainty is constructed based on price incentives in the park distribution network. Second, in the day-ahead scheduling stage, the charging scheduling of energy storage and EVs are optimized based on daily forecasts of park loads and PV combined with time-sharing tariffs for reducing the energy cost and PV abandonment. Then, in the intraday scheduling stage, the day-ahead scheduling plan deviation is corrected by real-time rolling based on the 4-hour forecast results. Finally, for the model is solved with YALMIP and Gurobi. The simulation results show that the optimal scheduling method can effectively alleviate the PV abandonment problem, reduce the operation cost, and realize the interactive regulation of source-load-storage-charge.

Shanghai Electric (China) (CN)
Openalex Percentile: Top 74%
Smart Grid Energy Management
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Cooperative Scheduling Optimization Strategy of Smart Park Distribution Network Considering Source-Load-Storage-Charge Interaction — Tingxian Xu, Weihan Li, et al. · (2024) | TGRS Research Map | TGRS