Horizontal decomposition-based stochastic day-ahead reliability unit commitment

This paper presents a progressive hedging (PH) based decomposition algorithm to improve the computational efficiency of stochastic day-ahead reliability unit commitment (RUC). Stochastic programming is introduced into RUC to facilitate a better decision making for market operation efficiency and energy supply reliability. However, the computational burden of stochastic RUC using today's computing power is still significant. We propose to apply progressive hedging (PH) algorithm to decompose the stochastic RUC problem. It is shown that a PH-based algorithm allows parallel computation of stochastic RUC, which can be much faster than conventional stochastic programming methods. A practical power system is used to verify the effectiveness of the proposed computation framework.