TY - JOUR
T1 - A Wasserstein Distance-Based Distributionally Robust Chance-Constrained Clustered Generation Expansion Planning Considering Flexible Resource Investments
AU - Chen, Baorui
AU - Liu, Tianqi
AU - Liu, Xuan
AU - He, Chuan
AU - Nan, Lu
AU - Wu, Lei
AU - Su, Xueneng
AU - Zhang, Jian
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2023/11/1
Y1 - 2023/11/1
N2 - This paper proposes a distributionally robust chance-constrained (DRCC) model for the clustered generation expansion planning (CGEP) of power systems. The proposed two-stage model minimizes the first-stage total cost along with the second-stage expected penalty cost with the worst-case probability distribution of renewable energy generation. A unit commitment model with flexibility constraints is embedded into the planning model, and the uncertainty is modeled via a Wasserstein distance (WD)-based ambiguity set. Demand-side resources (DSR) and concentrating solar power (CSP) plants are considered as candidates in the DRCC-CGEP model to enhance system flexibility, and the solution efficiency is improved through unit clustering. Furthermore, based on strong duality theory along with affine decision rule and conditional-value-at-risk approximation method, the proposed planning model is reformulated as a tractable mixed-integer linear programming problem. Numerical results show that the proposed WD-based DRCC-CGEP model is effective in improving the economics of the planning decisions while ensuring system reliability and maintaining computational efficiency.
AB - This paper proposes a distributionally robust chance-constrained (DRCC) model for the clustered generation expansion planning (CGEP) of power systems. The proposed two-stage model minimizes the first-stage total cost along with the second-stage expected penalty cost with the worst-case probability distribution of renewable energy generation. A unit commitment model with flexibility constraints is embedded into the planning model, and the uncertainty is modeled via a Wasserstein distance (WD)-based ambiguity set. Demand-side resources (DSR) and concentrating solar power (CSP) plants are considered as candidates in the DRCC-CGEP model to enhance system flexibility, and the solution efficiency is improved through unit clustering. Furthermore, based on strong duality theory along with affine decision rule and conditional-value-at-risk approximation method, the proposed planning model is reformulated as a tractable mixed-integer linear programming problem. Numerical results show that the proposed WD-based DRCC-CGEP model is effective in improving the economics of the planning decisions while ensuring system reliability and maintaining computational efficiency.
KW - Generation expansion planning
KW - Wasserstein distance
KW - concentrating solar power
KW - demand-side resources
KW - distributionally robust chance-constrained optimization
KW - unit clustering
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U2 - 10.1109/TPWRS.2022.3224142
DO - 10.1109/TPWRS.2022.3224142
M3 - Article
AN - SCOPUS:85144057758
SN - 0885-8950
VL - 38
SP - 5635
EP - 5647
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 6
ER -