Research On Electric Power Optimization Operation Based On Energy Saving Generation Dispatching And Demand Side Management

Electric power industry as an important branch of the energy industry has become the foundation of the national economy industries,economic development and an important guarantee for social progress.The energy-saving operating mechanism for electricity power industry is the inevitable choice in order to achieve sustainable development.In the current power system mechanism,power grid companies are still responsible for the improvement of the electric power industry efficiency.How to promote the power grid companies to play the main role in actively using the energy-saving power generation dispatching,demand-side management and so on to build the energy-saving energy operating model has become a forefront problem,which needed to be solved urgently.Therefore,studying on the establishment of energy-saving optimization dispatching methods,the development of demand-side management measures,as well as construction of evaluation index system and evaluation model for energy-saving electric power system operating ability has important theoretical value and practical significance.The primary innovations are as follows:1.The middle-long power load forecasting method based on co-integration and support vector machine is set up.Firstly,the long-term equilibrium relationship of the variables in energy system is established by means of co-integration technology.The co-integration relationship and error correction model are used to forecast.Secondly,the support vector machine is used to predict the forecasting error of the co-integration and to make the further amendment.The forecasting results show that this model improves the reliability and accuracy.Based on the forecasting results the energy-saving potential of China's future projections is analyzed.2.The index system of energy saving power generation dispatching is set up.The optimization method for power generation dispatching based on entropy and improved poly-particle swarm algorithm is set up to achieve the optimal scheduling of power generation side resources.The index system includes power supply cost,power supply coal consumption,and reliability of power plant and power consumption rate.The entropy is used to calculate the weights of upper four indexes.Then the objective function is set up.At last,the poly-particle swarm optimization algorithm is used to realize the optimal dispatching.The results show that this method is the best among genetic algorithm and simulated annealing algorithm.Meanwhile,the amount of the total coal consumption is reduced without the other indicators for the purpose have too many losses.3.The evaluation index system for power system energy-saving operating ability is set up from power supply ability,power transmission and distribution ability,and power demand-side electricity usage ability.The index system helps to assess the status of power grid companies,and helps to promote the construction of energy-saving mechanism for electricity operators to enhance the sustainability.4.A sequence and progressive combined evaluation method is set up.The thinking of this method as follows:Firstly,using single evaluation methods to evaluate.If the evaluation results aren't same,the Spearman rank correlation coefficient is used to calculate the correlation among the results of single evaluation methods.Based on the results,the traditional combined evaluation methods are used to combine the results of the single evaluation method.If the results of the upper combined methods are not same. Here the combined method evaluation indexes,such as Spearman rank correlation coefficient,correlation degree,the max deviation,average deviation,are used to evaluate the upper four combined evaluation methods.The entropy method is used to calculate the weights,and then get the final evaluation result.In this paper,using the indexes system and the data of them,the sequential progressive combined evaluation method is testified.This method overcomes the comprehensive evaluation method of a single one-sidedness and inconsistency,so that evaluation results from a more authentic.