Robust low-carbon energy and reserve scheduling considering operational risk and flexibility improvement

Abstract

With the increase in wind power integration, significant uncertainty leads to enormous requirements for the flexibility and robustness of system operation. To enhance the flexibility of the power system, this paper proposes a robust low-carbon optimization method for energy and reserve scheduling. The system flexibility is improved by various flexible resources including conventional thermal units (CTUs), carbon capture plants (CCPs), energy storage systems (ESSs), and demand response (DR). The operation and regulation characteristics of multiple types of flexible resources are jointly formulated. Moreover, the carbon-capturing mechanism of CCPs is considered to reduce carbon emissions. The operational risk is measured by the conditional value-at-risk (CVaR) to coordinate the wind power accommodation and operational economy. A two-stage robust scheduling model with a flexible uncertainty set is established, which optimizes the energy and reserve scheme in the first stage and checks the feasibility of re-dispatch in the second stage. The column-and-constraint generation (C&CG) algorithm is utilized to solve the proposed robust model. Simulation results on two different scale systems verify the feasibility and effectiveness of the proposed method.