Dynamic Reactive Power Optimization Of Network With Photovoltaic Power Station

Photovoltaic power generation is a kind of clean and renewable energy generation with the role of environmental protection,in recent years,the electric power system is often the equal access to the power grid in the form of distributed generation.Many academic researchers also deeply discussed the photovoltaic power generation,especially in the mathematical model of photovoltaic power generation and the output ability of power grid.As the economy and the continuous progress of science and technology,photovoltaic power generation into the power system model is relatively stable.In order to raising the level of control and reactive power compensation in power system,many industries established a large number of photovoltaic power stations.But compared with the conventional thermal power,photovoltaic power generation has a certain amount of randomness.This randomness is due to that the solar energy is influenced by environment and climate,bringing the instability for photovoltaic grid.In order to solve the interconnection problem,this paper has established the power system model having photovoltaic randomness and reactive power compensation capacity.The model effectively adjusted the flow of reactive power current in power system,improved the node voltage and reduced the energy loss of the system.Power system reactive power adjustment methods include controlling the output of the generator end voltage,adjusting on-load voltage regulating transformer tap position,and so on.This paper firstly introduced the classification and composition of photovoltaic power generation system and studied the instability of photovoltaic power generation and the reactive power output capacity.This paper selected the classic genetic algorithm(ga),removed the defect of algorithm convergence speed and seeking the optimal solution.According to the time sequence,the dynamic reactive power optimization is transformed into static reactive power optimization,and the improved genetic algorithm is used to search the optimal solution of static reactive power optimization,meaning the number of reactive power compensation device and the system active loss of time.In order to establish the model of dynamic reactive power optimization in power system,the cutting loss of capacitor devices and the output power of photovoltaic grid considering the random power load is used to the static model optimal solution.In order to limit the number of operation times for reactive power compensation and reduce the loss of equipment due to regular action,this article made a schedule of capacitor for cutting on the basis of dynamic programming algorithm to obtain the smallest system active loss within 1 day.Finally,this paper used photovoltaic power grid reactive power optimization in Inner Mongolia as empirical study,and the MATLAB software is used to validate the proposed dynamic reactive power optimization model,and the result showed that this model can effectively reduce the network loss,improve the node voltage,provide theoretic evidence about reactive power optimization with grid-connected photovoltaic,have a certain practical value in the Inner Mongolia power grid photovoltaic power generation of reactive power optimization.The model has got great significance in theory and guidance for the grid of the actual operation in power system.