Chance-Constrained Goal-Programming based day ahead scheduling in wind power integrated system
To mitigate the impact of wind forecasting error uncertainty, a Chance-Constrained Goal Programming (CCGP) based day-ahead scheduling model is proposed in this paper. Compared with the traditional Chance Constrained Programming (CCP) method, the CCGP based model is more flexible, which allows higher violation probability than the predefined probability in necessary situations. In this way, the day-ahead scheduling and the uncertain range covered by reserves can be both optimized. Therefore, the reliability and economy of the system with wind power uncertainty can be considered in details with more flexibilities. In addition, because slack variables in CCGP model have corresponding physical meanings, they can provide more information to system operators. Furthermore, numerical tests are performed with the IEEE 118 bus system with wind power input. Results indicate that the proposed method achieves a good balance of cost and risk. And the total operation cost, especially the unit commitment cost, is reduced by the proposed method. Comparative evaluations of the proposed CCGP method and CCP method are presented in the paper.