Risk-profit analysis of regional energy service providers by regularized primal-dual interior point method

Abstract

With the development of the electric market and smart grid, risk management is one of the key issues of optimal dispatch in the interconnected energy system. The uncertainty of market price will lead to the risk for the profit of the regional energy service providers (RESP). This paper firstly defines conditional robust profits (CRP) based conditional value-at-risk and uses it constructs a risk-averse model of a multi-regional interconnected energy system, which includes generator units, demand response, and energy storage system, model named as CRP-RESP. Then by building upon the notion of effective scenarios, the effective scenarios reduction technology (ESRT) is used to reduce the scale of the CRP-RESP model effectively. Besides, efficiently solve CRP-RESP and realize the privacy protection of RESP, CRP-RESP is decomposed by geographical region, and distributed computing is carried out by using regularized primal–dual interior point method (R-PDIPM) with disturbance terms. Finally, the effectiveness and reliability of the risk-averse model are tested with the case study. ESRT can not only effectively reduce the scale of the CRP-RESP model, but also obtain a high-quality risk scheduling scheme compared with other clustering methods. And the convergence ability of R-PDIPM with disturbance terms is verified from both theoretical and experimental aspects.