Optimal Scheduling Of Virtual Power Plant With Multi-Stakeholders Based On Water Cycle Algorithm

With the exhaustion of fossil energy and the environmental pollution of traditional power plants,the national demand for clean energy is increasing,so distributed energy resources develop rapidly.Due to the influence of spatial distribution,climate change and human activities,the randomness and uncertainty of distributed energy make it difficult to connect to the grid on a large scale.The virtual power plant aggregates various distributed power sources and user-side controllable loads into one entity.It solves the problems of high cost of distributed new energy access and disorderly grid connection by optimizing the dispatch of controllable loads,and at the same time improves the consumption of distributed new energy.Therefore,it is of great significance to study the optimal scheduling of virtual power plants.This paper mainly studies the optimal scheduling of virtual power plants with multi-stakeholders,the main work is as follows:Firstly,in view of the uncertainty of distributed generator and loads in the virtual power plant,typical scenarios and probabilities are obtained using scenario analysis method based on the improved K-means clustering algorithm.According to the distribution function of each distributed generator and load,a large number of scenes are obtained using Latin Hypercube Sampling technology.After that,a margin ranking factor is introduced to improve the K-means clustering algorithm.And finally,the typical scenarios and probability of distributed generator and load are obtained,and the effectiveness of the improved strategy is verified by silhouette coefficients and scene cumulative fitting curves.Secondly,on the basis of obtaining the typical scenarios and probabilities of distributed generator and loads,the electric access point of electric vehicle charging station is planned.The probability model of electric vehicle charging station load is built according to the distribution function of electric vehicle daily mileage,initial charging time and charging power.The Cholesky decomposition method and the Latin Hypercube Sampling technique are used to obtain the 24 time sequence and correlation sample matrix.After that,a scenario probability model of electric access point planning for electric vehicle charging stations was established,which took into account the sequence and correlation.The analysis results show that the electrical access point planning of electric vehicle charging stations considering the sequencea and correlation cana reduce thea brancha lossa and nodea voltagea deviation of the distribution networka,a which is beneficiala to the safea and economica operationa of the distributiona network.Then,in ordera to solvea the multia-objective coordination optimizationa model with high-dimensional mixed-integer nonlinearity,the multiobjective water cycle algorithm is improved.Through analysis of it,it is found that the algorithm has deficiencies such as slow convergence and uneven distribution of the Pareto optimal solution,so three improvement strategies are proposed to address these problems:(1)Use Tent chaotic map to initialize the population;(2)Adaptive iteration step size;(3)Improve the calculation method of crowded distance.And by comparing with typical multi-objective optimization algorithms,the eaffectiveness of the iamproved straategy is veraified.Finally,the optimal scheduling of virtual power plants with multiple stakeholders.According to the operation characteristics of each unit in virtual power plant and the principle of similar interests,different interest subjects are divided.At the same time,a classified dispatching strategy of electric vehicle charging station is proposed,a virtual power plant scheduling model including wind power,photovoltaic,electric vehicle charging station,gas turbine and controllable load is constructed.Then use the improvead mualti-objaective water cycle algorithm to solvae the maodel.The simulation on the IEEE 33 bus system verifies that the optimal scheduling of virtual power plants considering the multi-stakeholder model can not only ensure the maximum net profit of the virtual power plant,but also maximize the benefits of each subject and achieve a win-win situation.