Day-Ahead Stochastic Scheduling Model Considering Market Transactions in Multi-Energy System

Abstract

The large-scale renewable energy(RE) integration into power systems in China poses an additional challenge to the day-ahead stochastic scheduling due to the uncertainty. Moreover, when power markets are considered, trading energy in day-ahead scheduling cannot be disregarded. In this paper, a two-stage stochastic day-ahead scheduling model considering market transactions is established, with the goal to use the most economical way to ensure the safe and reliable operation of the power grid and maximize the consumption of new energy. Mid- and long-term electricity contract decomposition, ancillary service transactions, and inter-provincial transactions are considered in the proposed model. Finally, a numerical example based on a real system of a province of China verifies the reasonableness of the proposed model. Four cases are analyzed to understand the effect of market transactions on the consumption of new energy. Furthermore, the results show the superiority of the stochastic method over an equivalent deterministic model.