Multi-level Optimization and Scheduling Strategy for Power Grid Considering Adjustable Resource Participation in Real-time Regulation

The access of a large amount of adjustable resources to the power grid for participation in dispatching has promoted the transformation of the traditional ‘source-following load’ mode to a collaborative ‘source-load interaction’ mode. A multi-level optimization scheduling strategy for power grids considering the participation of adjustable resources in real-time regulation is proposed in this paper. Firstly, the adjustment characteristics of different types of adjustable resources are analyzed, and based on historical output data, the output situation of various resources during different time periods of the day is predicted. Then, a dispatching model is constructed with the goal of minimizing the comprehensive operating cost of the system, and the scenario-based stochastic programming (SSP) method is used to obtain the day-ahead dispatching plan. Secondly, based on the day-ahead dispatching plan, the intraday optimization is carried out with the goal of minimizing the dispatching cost. The Niche Chaotic Particle Swarm Optimization (NCPSO) algorithm is used to solve the multi- objective optimization problem, and the intra-day dispatching plan is obtained. Based on the day-ahead and intra-day dispatching plans, the demand for real-time regulation of the power grid is considered, and a model is established with the goal of minimizing the deviation between the dispatchable amount and the dispatching demand. The Model Predictive Control (MPC) is used to formulate the real-time optimization dispatching strategy for adjustable resources. Finally, the feasibility of the method proposed in this article is verified through case analysis.