A Probabilistic Risk-Based Coordinated Scheduling Model for Power Systems with Renewable Energy Considering Coupling of Transmission and Distribution Networks

Traditional scheduling strategy operates the power system independently at different levels and zones, with coal-fired generator units responsible for all power peaking. However, the increasing stochasticity and volatility of renewable energy sources (RESs) present a significant challenge to the flexibility operation of coal-fired generator units. To fully enhance the flexibility of the power system, the coordinate operation between transmission and distribution (T&D) networks becomes an effective solution for enhancing the flexibility of generator units and consuming RESs. A probabilistic risk-based T&D co-operation model is proposed to quantitatively analyze the impact of uncertainty on T&D co-operation decisions and better manage operational risks. This paper considers two types of exogenous uncertainties in RESs output and establish a moment-based probability distribution fuzzy set for uncertainties. The real-time T&D co-operation model quantifies the risk of overruns by using distributionally robust chance constraints (DRCC), and the uncertainty is assigned using a linearized affine strategy, which effectively alleviate the pressure of generator units peaking. The DRCC model can be transformed into a second-order conic programming (SOCP) problem based on the moment information of the distribution set. Example analysis proves the effectiveness of the proposed probabilistic risk-based T&D co-operation approach.