2014•Unpublished venueRequires access

Robust SCUC with load and wind uncertain intervals

Bingqian Hu, Lei Wu

Open publisher page 4 citations

Abstract

With the increasing penetration of variable wind generation resources, independent system operators (ISOs) are faced with new challenges on the secure and economic operation of power systems. This paper proposes an efficient approach for deriving robust solutions to the security-constrained unit commitment (SCUC) problem, in which load and wind uncertainties are simulated via interval numbers. Instead of exploring the worst case scenario in terms of the highest minimum operating cost in most robust optimization based SCUC approaches in literature, the objective of the proposed robust SCUC is to minimize the operating cost for the base case, while guaranteeing that the robust solution could securely adjust generation dispatches for handling all uncertain intervals. The proposed robust SCUC model is solved by Benders decomposition, which decomposes the original problem into a master unit commitment (UC) problem for the base case and subproblems for the base case network evaluation and the security checking for all uncertain intervals. Feasibility cuts are generated and fed back to the master problem when violations are identified in subproblems. Numerical studies on a 6-bus system and the modified IEEE 118-bus system illustrate the effectiveness of the proposed robust SCUC model.

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What this paper is about

With the increasing penetration of variable wind generation resources, independent system operators (ISOs) are faced with new challenges on the secure and economic operation of power systems. This paper proposes an efficient approach for deriving robust solutions to the security-constrained unit commitment (SCUC) problem, in which load and wind uncertainties are simulated via interval numbers. Instead of exploring the worst case scenario in terms of the highest minimum operating cost in most robust optimization based SCUC approaches in literature, the objective of the proposed robust SCUC is to minimize the operating cost for the base case, while guaranteeing that the robust solution could securely adjust generation dispatches for handling all uncertain intervals. The proposed robust SCUC model is solved by Benders decomposition, which decomposes the original problem into a master unit commitment (UC) problem for the base case and subproblems for the base case network evaluation and the security checking for all uncertain intervals. Feasibility cuts are generated and fed back to the master problem when violations are identified in subproblems. Numerical studies on a 6-bus system and the modified IEEE 118-bus system illustrate the effectiveness of the proposed robust SCUC model.

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Available abstract

With the increasing penetration of variable wind generation resources, independent system operators (ISOs) are faced with new challenges on the secure and economic operation of power systems. This paper proposes an efficient approach for deriving robust solutions to the security-constrained unit commitment (SCUC) problem, in which load and wind uncertainties are simulated via interval numbers. Instead of exploring the worst case scenario in terms of the highest minimum operating cost in most robust optimization based SCUC approaches in literature, the objective of the proposed robust SCUC is to minimize the operating cost for the base case, while guaranteeing that the robust solution could securely adjust generation dispatches for handling all uncertain intervals. The proposed robust SCUC model is solved by Benders decomposition, which decomposes the original problem into a master unit commitment (UC) problem for the base case and subproblems for the base case network evaluation and the security checking for all uncertain intervals. Feasibility cuts are generated and fed back to the master problem when violations are identified in subproblems. Numerical studies on a 6-bus system and the modified IEEE 118-bus system illustrate the effectiveness of the proposed robust SCUC model.

Key concepts: Benders' decomposition, Power system simulation, Robustness (evolution), Mathematical optimization, Wind power, Computer science, Interval (graph theory), Electric power system

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