TY - JOUR
T1 - Distributionally Robust Co-Optimization of Power Dispatch and Do-Not-Exceed Limits
AU - Ma, Hongyan
AU - Jiang, Ruiwei
AU - Yan, Zheng
N1 - Funding Information:
Manuscript received August 6, 2018; revised March 23, 2019 and July 17, 2019; accepted September 5, 2019. Date of publication September 16, 2019; date of current version February 26, 2020. This work was supported in part by the U.S. National Science Foundation (ECCS-1845980) and 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) under Grant 2018YFB0904200. Paper no. TPWRS-01222-2018. (Corresponding author: Ruiwei Jiang.) H. Ma and Z. Yan are with the Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China (e-mail: hahaha91644@sjtu.edu.cn; yanz@sjtu.edu.cn).
Publisher Copyright:
© 1969-2012 IEEE.
PY - 2020/3
Y1 - 2020/3
N2 - To address the challenge of the renewable energy uncertainty, the ISO New England (ISO-NE) has proposed to apply do-not-exceed (DNE) limits, which represent the maximum nodal injection of renewable energy the grid can accommodate. Unfortunately, it appears challenging to compute DNE limits that simultaneously maintain the system flexibility and incorporate a large portion of the available renewable energy at the minimum cost. In addition, it is often challenging to accurately estimate the joint probability distribution of the renewable energy. In this paper, we propose a two-stage distributionally robust optimization model that co-optimizes the power dispatch and the DNE limits, by adopting an affinely adjustable power redispatch and an adjustable joint chance constraint that measures the renewable utilization. Notably, this model admits a second-order conic reformulation that can be efficiently solved by the commercial solvers (e.g., MOSEK). We conduct case studies based on modified IEEE test instances to demonstrate the effectiveness of the proposed approach and analyze the trade-off among the system flexibility, the renewable utilization, and the dispatch cost.
AB - To address the challenge of the renewable energy uncertainty, the ISO New England (ISO-NE) has proposed to apply do-not-exceed (DNE) limits, which represent the maximum nodal injection of renewable energy the grid can accommodate. Unfortunately, it appears challenging to compute DNE limits that simultaneously maintain the system flexibility and incorporate a large portion of the available renewable energy at the minimum cost. In addition, it is often challenging to accurately estimate the joint probability distribution of the renewable energy. In this paper, we propose a two-stage distributionally robust optimization model that co-optimizes the power dispatch and the DNE limits, by adopting an affinely adjustable power redispatch and an adjustable joint chance constraint that measures the renewable utilization. Notably, this model admits a second-order conic reformulation that can be efficiently solved by the commercial solvers (e.g., MOSEK). We conduct case studies based on modified IEEE test instances to demonstrate the effectiveness of the proposed approach and analyze the trade-off among the system flexibility, the renewable utilization, and the dispatch cost.
KW - Power dispatch
KW - affine policy
KW - do-not-exceed limit
KW - renewable energy uncertainty
KW - robust optimization
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U2 - 10.1109/TPWRS.2019.2941635
DO - 10.1109/TPWRS.2019.2941635
M3 - Article
AN - SCOPUS:85081046720
SN - 0885-8950
VL - 35
SP - 887
EP - 897
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 2
M1 - 8839433
ER -