Research On Energy Optimization Key Technology Of Smart Industrial Park Of A Certain Area In Shandong Province Grid

Green environmental protection,energy saving and low carbon have become the global energy research topic in the 21st century.With the increasing load,the access of new energy meets the load demand,and its unstable factors bring new challenges to the planning and operation of the distribution network.Therefore,when planning and designing the distribution network,the problems to be considered are more complicated and comprehensive.Using intelligent optimization algorithms to scientifically and reasonably construct and plan the campus distribution network can bring huge economic benefits to the entire power system.This paper first introduces the planning characteristics of urban intelligent parks.Taking a smart industrial park in Shandong as a research case,the real-time high-speed bidirectional communication network of the distribution network in the park is constructed through the system architecture of the park,so that the park main station and dispatching automation system The marketing service system and the electricity information collection system realize the docking,and achieve the real-time interactive demand response and load regulation requirements.In the planning of grid structure,this paper uses multi-scenario method to classify the uncertain factors such as the output and load of distributed generation by using improved KNN algorithm based on nuclear mapping,and classifies the similar days of high frequency meteorological conditions,gives the power values of the output and load consumption of distributed generation on the similar days of each meteorological condition,and calculates the corresponding probability,so as to reflect the power supply under this condition.Probability of output and load consumption.Then the scenarios are divided and calculated to reflect the probability of each scenario in the planning year.A variety of schemes are established for the access of distributed generators and the network structure of distribution network.Cost functions are established based on the investment cost of distributed generators and lines,operation and maintenance cost,operation loss cost and abandoned wind and light loss cost.The genetic algorithm is used to search out the optimal cost scheme.Finally,through MATLAB simulation,a specific example is given for analysis and discussion.The energy optimization of Shandong Province Power Grid Intelligent Industrial Park is realized,which meets the real-time interactive demand response and load regulation requirements,and maximizes the utilization of wind and solar energy.