Generation Scheduling Optimization of Wind-Storage Combined Generation System Based on Combined Empirical Mode Decomposition (CEMD)

Incorporating Energy Storage System (ESS) with wind farm to establish Wind-Storage Combined Generation System is a promising solution to improve the dependability of integrated wind power. Reliable system generation scheduling optimization is the key point to improve the economy and efficiency of system integration. In this paper, based on Empirical Mode Decomposition (EMD), the fluctuation feature of real-time wind power output is studied to propose a Hybrid Energy Storage System (HESS) model aiming to obtain the economic capacity as well as maximum charging/discharging power in every generation scheduling circle (10min). Besides, the algorithm of Combined EMD (CEMD) is proposed to minimize the deviation between generation scheduling plan and actual integrated power of Combined Generation System. The optimization results of case study shows that the proposed CEMD performs well for generation scheduling optimization, and the sizing method can reduce invest cost.