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Dan Xu, Zhi Cai, Qian Cheng, Guodong Huang, Jingyang Zhou, Junjie Tang. Security-constrained Transmission Maintenance Optimization Considering Generation and Operational Risk Costs[J]. Journal of Modern Power Systems and Clean Energy, 2024, 12(3): 767-781.
Citation: Dan Xu, Zhi Cai, Qian Cheng, Guodong Huang, Jingyang Zhou, Junjie Tang. Security-constrained Transmission Maintenance Optimization Considering Generation and Operational Risk Costs[J]. Journal of Modern Power Systems and Clean Energy, 2024, 12(3): 767-781.

Security-constrained Transmission Maintenance Optimization Considering Generation and Operational Risk Costs

  • With the large-scale integration of renewable energy, the traditional maintenance arrangement during the load valley period cannot satisfy the transmission demand of renewable energy generation. Simultaneously, in a market-oriented operation mode, the power dispatching control center aims to reduce the overall power purchase cost while ensuring the security of the power system. Therefore, a security-constrained transmission maintenance optimization model considering generation and operational risk costs is proposed herein. This model is built on double-layer optimization framework, where the upper-layer model is used for maintenance and generation planning, and the lowerlayer model is primarily used to address the operational security risk arising from the random prediction error and N-1 transmission failure. Correspondingly, a generation-maintenance iterative algorithm based on a defined cost feedback is included to increase solution efficiency. Generation cost is determined using long-term security-constrained unit commitment, and the operational risk cost is obtained using a double-layer N-1 risk assessment model. An electrical correlation coupling coefficient is proposed for the solution process to avoid maintenance of associated equipment simultaneously, thereby improving model convergence efficiency. The IEEE 118-bus system is used as a test case for illustration, and test results suggest that the proposed model and algorithm can reduce the total cost of transmission maintenance and system operation while effectively improving the solution efficiency of the joint optimization model.
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