Dual Stochastic Dual Dynamic Programming for Multi-Stage Economic Dispatch With Renewable Energy and Thermal Energy Storage
Xiaosheng Zhang, Tao Ding, Chenggang Mu, Ouzhu Han, Yuhan Huang, Mohammad Shahidehpour
Abstract
The rapid growth of renewable energy sources brings great challenges to the economic dispatch of the modern power system. Retrofitting thermal power plants with thermal energy storage (TES) can improve the operational flexibility of the plants to handle the uncertainty of renewable energy sources. An economic dispatch model which considers retrofitted coal-fired power plants with thermal energy storage is proposed to promote the proliferation of uncertain renewable energy resources. A multi-stage stochastic programming (MSSP) model is constructed to accommodate the uncertainties of renewable energy resources, which provides a higher level of flexibility as compared with the traditional two-stage stochastic programming solutions. In addition, dual stochastic dual dynamic programming is employed, and a new policy is proposed to enhance the computational efficiency of the proposed MSSP model. Numerical results for a practical regional power system in China are presented and analyzed to verify the effectiveness of the proposed solution method for the economic dispatch model.