The number of electric vehicles in the world is gradually increasing. The main problem of most researchers is to make the electric vehicle users charge and discharge orderly and to achieve the peak load shifting of the daily load of the power grid through its orderly charging and discharging behavior. With large-scale electric vehicles connected to the grid, it will lead to voltage drop and harmonic problems. In this paper, a daily load forecasting method for electric vehicles is proposed. On that basis, the discharge management strategy function is constructed with the objective of reducing the peak-valley difference of daily load of electric vehicles. The improved GM (1,1) algorithm is used to solve the constructed multi-objective function. The improved algorithm is compared with the original algorithm and other excellent algorithms. Through the analysis of the simulation data, the effectiveness of the electric vehicle load forecasting algorithm based on the Grey System Theory and the Least Squares Support Vector Machines, the optimization management model and the improved GM (1,1) algorithm are verified.
In this paper, the load forecasting model of electric vehicle charging station is established based on the support vector machine, which considers the daily load forecasting of single node and the influence of historical load of multiple time scales, and predicts and analyzes the load of charging station. The prediction model mainly uses the regression prediction model of support vector machine to predict the short-term load of electric vehicle charging station, then trains the model with the processed data, and finally tests the collected data at multiple time scales through experimental analysis. The results show that the average error of the prediction method proposed in this paper is less than 4% under two conditions. This proves the effectiveness and feasibility of the method in this paper.
GPS technology has the characteristics of high precision, high sampling, real-time, and simultaneous determination of three-dimensional coordinates of points, which can not be compared with other monitoring technologies. It plays a very important role in deformation monitoring. Starting from the composition of GPS positioning system, this paper expounds the three components of GPS positioning system, as well as the association and coordination between each component of the work; then the GPS deformation monitoring mode and several error sources in the monitoring process are introduced. The advantages and disadvantages of GPS technique in deformation monitoring are analyzed and its application trend is predicted. GPS positioning technology is applied in all aspects of our life, creating a lot of social and economic value for us.
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