Journal of Modern Power Systems and Clean Energy
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ISSN 2196-5625 CN 32-1884/TK
ISSN 2196-5625 CN 32-1884/TK
Yue Yang
State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing 100084, ChinaWenchuan Wu
State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing 100084, ChinaBin Wang
State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing 100084, ChinaMingjie Li
National Electric Power Control Center of State Grid Corporation of China, Beijing, ChinaTao Zhu
Kunming Electric Power Supply Company of Yunnan Power Grid Corporation, Kunming, China1.State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing 100084, China;2.National Electric Power Control Center of State Grid Corporation of China, Beijing, China;3.Kunming Electric Power Supply Company of Yunnan Power Grid Corporation, Kunming, China
This work was supported in part by the National Key R&D Program of China “Technology and Application of wind Power / Photovoltaic Power Prediction for Promoting Renewable Energy Consumption” (No. 2018YFB0904200) and eponymous Complement S&T Program of State Grid Corporation of China (No. SGLNDKOOKJJS1800266).
The correlated renewable energy farms are usually aggregated as a cluster in economic dispatch to relieve computational burden. This strategy can also achieve better performance since the precision of predicting the power generation of a cluster can be higher than those of individual farms. This paper proposes an optimal decomposition method to allocate dispatch schedules among renewable energy farms (REFs) in the cluster under existing stochastic optimization framework. The proposed model takes advantage of probabilistic characteristics of renewable generation to minimize the curtailment and ensure the feasibility of dispatch schedule of the clusters. Approximated tractable formulation and efficient solution method are the proposed to solve the proposed model. Numerical tests show that the proposed method achieves the optimal decomposition of dispatch schedule among REFs and facilitates the utilization of renewable generation.
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