A self-adaptive robust day-ahead optimization scheduling method for a light storage charging tower

Abstract

The invention discloses a self-adaptive robust day-ahead optimization scheduling method for an optical storage charging tower, and the method comprises the steps: firstly, building a day-ahead energy-standby collaborative optimization scheduling model by taking the minimum daily operation total cost of the optical storage charging tower as a target; considering Influence of photovoltaic output andload uncertainty on day-ahead scheduling, and taking day-ahead energy-standby collaborative optimization scheduling and the real-time energy balance adjustment as a first-stage decision and a second-stage decision, and establishing an adaptive robust three-layer optimization scheduling model; Secondly, describing the uncertainty set by adopting a representative scene, introducing an auxiliary variable to replace the operation cost of the worst scene in the second stage, and realizing decoupling of inner layer min-max problem, so that three-layer optimization is converted into a single-layer robust optimization model containing a limited number of scenes; And finally, testing and solving are carried out in an actual optical storage charging tower system. According to the method, the systemuncertainty can be effectively processed, the complexity of a three-layer optimization model is reduced, meanwhile, a charging tower day-ahead scheduling strategy is obtained, and the obtained resulthas robustness.

Description

technical field [0001] The invention belongs to the technical field of power system optimal dispatching, and relates to an adaptive robust day-ahead optimal dispatching method for an optical storage charging tower. Background technique [0002] In recent years, the energy crisis and environmental pollution problems have become increasingly severe. Renewable energy and electric vehicles have developed rapidly due to their advantages in energy saving and emission reduction, and will become an effective way to deal with energy shortages and environmental pollution in the future. With the continuous growth of the scale of electric vehicles, when electric vehicles are connected to the charging station for centralized charging, it will cause a certain impact on the power grid; consider a new type of charging facility, photovoltaic system, energy storage system (energy storage system, ESS), etc. The solar storage charging tower provides a new idea for effectively solving the chargi...

AI Technical Summary

Problems solved by technology

On the one hand, the traditional stochastic programming method can obtain the optimal solution in the sense of probability, but it is difficult to obtain the probability distribution information of random variables accurately, and the calculation amount is large. On the other hand, the traditional static robust optimization has the advantage of not needing to obtain the accurate probability distribution of uncertain parameters , but its scheduling decision results are slightly conservative

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