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A Method for Composite Power System Reliability Evaluation Based on Delivery Point Capability Model |
Zhu Jinzhou1, Zhang Yan1, Wang Saiyi2, Hua Yueshen2 |
1. School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 China; 2. State Grid Shanghai Municipal Electric Power Company Shanghai 200122 China |
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Abstract The efficiency of the composite power system (CPS) reliability evaluation can be improved effectively by using the decoupling characteristics between CPS transfer capability and corresponding load (system-load decoupling). There are still some technical defects in the existing methods based on system-load decoupling. Existing transfer capability calculation models consider neither the optimal load shedding under abnormal conditions nor the change of the load level of each delivery point. In addition, there are few researches on the calculation methods of frequency and duration reliability index. By using the system-load decoupling characteristics, a method for CPS reliability evaluation based on delivery point capability model is proposed. Firstly, an optimal decision-making model is presented for calculating delivery points transfer capability of CPS, which is suitable for reliability evaluation. Given that the objective function of the presented optimal model has successively increasing slopes, the corresponding nonlinear model is transformed into a linear programming model to be solved to enhance the computational efficiency. Then, the probability-frequency distribution function of delivery point transfer capability, also named delivery point capability model, is built based on Markov chain by extending the concept of state probability and incremental frequency already used for modeling available capability of generation. Not only the probability but also the frequency and duration reliability index of delivery points and CPS can be obtained by convolution and addition operation between delivery point capability models and corresponding load models. The analysis for RBTS-6 test system demonstrates the validity of the proposed method.
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Received: 19 September 2016
Published: 16 January 2018
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