Research On Time-of-use Pricing Optimization Based On Improved Bird Swarm Algorithm

In the current market economy,the demand for electrical energy is increasing.With the improvement of the electricity market,people pay more and more attention to demand-side resources.As one of the solutions for demand-side management,demand-side response plays an important role in the development of smart grids today.As one of the price-based demand-side responses,Time-of-use pricing can guide users to participate in load regulation,so as to achieve the effect of peak and valley filling.Reasonable time-of-use pricing is of great significance to the safe and stable operation of the power system.First of all,this paper studies and analyzes demand-side management and demand-side response,and at the same time discusses the related theories of fuzzy mathematics and consumer psychology,which lays the foundation for the subsequent period division and the establishment of a mathematical model of the time-of-use pricing.Secondly,the time period of time-of-use pricing is divided by fuzzy membership function and fuzzy clustering method;through consumer psychology theory,user response laws are analyzed,and a user response model is established based on this;A mathematical model of the time-ofuse pricing has been established with the goal of comprehensive user satisfaction.Then,the principle of the bird swarm algorithm is discussed in detail.In view of its shortcomings,an improved bird swarm algorithm is adopted.The improved method is discussed,and the improved algorithm is verified by the test function.Finally,the model is verified through examples.Comparing the improved bird swarm algorithm with the particle swarm algorithm,it is proved that the improved bird swarm algorithm has better optimization effect than the particle swarm algorithm;the improved bird swarm algorithm is used to optimize the model to obtain the optimal time-of-use pricing and verify the model effectiveness and feasibility;considering the effect of distributed photovoltaic power generation on the load curve in the future,the photovoltaic power generation amount and the load curve are combined to obtain an equivalent load curve,and it is optimized to obtain the time-of-use pricing when including photovoltaic power generation.