Fully Decentralized Multi-area Stochastic Dynamic Economic Dispatch for Large-scale Power System

This paper discusses the implementation of a fully decentralized optimization for the multi-area stochastic dynamic economic dispatch (MASDED) of large scale power systems with wind power integrated. Firstly, the volatility of wind power is represented by sampling wind scenarios, and the consensus constraints of boundary buses' phase angles among the forecast scenario and sampling scenarios are built. Secondly, the multi-area power system is decomposed into different areas by duplicating boarder variables. Finally, a bi-level iterative method that combines the modified analytical target cascading (ATC) method and the Benders decomposition method is applied to solve the MASDED in a fully decentralized way, and a coordination center turns out to be not necessary. The forecast scenario sub-problems and the sampling scenarios sub-problems of each area are solved iteratively, and the multipliers are updated in each area respectively. The 3-area IEEE RTS system and a 4-area 2298-bus system are tested to demonstrate the effectiveness of the proposed method.