Study On Power Consumption Prediction & Optimization Of Power Load In Cement Manufacturing

Energy consumption problem is the key to enterprise development all along, which is related to national economic development and social sustainable development as well. And the energy consumption of building material industry accounts for 13 percent of the total national industry. Among this, the energy consumption of cement manufacturing has summed up to about 76 percent of the total energy consumption of building materials industry. Thus, the problem of energy consumption of cement enterprise management research is urgently needed. The main energy of cement manufacturing is coal and electric power. As the automation degree of production process is increasing day by day, the coal consumption index of cement enterprises has come to decline year by year, but the electric power consumption still shows a trend of increasing with high electricity expenses.In response to these circumstances, a typical cement plant in Shandong Province was analyzed as the research object in this paper to provide effective means of data analysis and prediction technology. A power consumption prediction model was established to gain reasonable configuration and use of energy. Besides, an optimization model of enterprise load under Time-of-use(TOU) power price was established for load scheduling to achieve the lowest cost of daily electricity under the premise of ensuring the output production. Through the implementation of this topic, the effectiveness of energy supply can be finally achieved to improve the overall energy efficiency with lower consumption and lower cost.First of all, starting with practice, this paper analyzed the current situation of the development of cement industry in China, and made further study of the cement production industrial process, on basis of which to summarize the power distribution and its typical indexes. In addition, since there were too much data and complex characteristics of energy consumption in cement enterprises, the energy management system in cement enterprises was further introduced, especially the principle and implementation of data acquisition system for the latter parts. Secondly, principal component analysis(PCA) was brought in to get several key factors of cement production power consumption, replacing the original tens of influence variables, to reduce the complexity of the model. At the same time, a cement consumption prediction model based on improved multivariate nonlinear algorithm was proposed in this paper to improve the prediction precision of the model. Afterwards, an optimization model of cement enterprise load under TOU power price was established. And on this basis, three methods-pattern search method, simplex method and genetic algorithm(GA)-were adopted for its solution, with respective superiority and inferiority being compared. Finally, the running schedules of main power link devices were achieved according to the power consumption forecast for future.In this paper, since the estimated values were highly closed to the actual power consumptions, then the power consumption prediction model, as well as the validity of the improved algorithm was verified through the numerical example analysis. In other words, a theoretical basis for cement plants power consumption forecasting management was provided with important reference significance. Moreover, in the case of an enterprise in Tianjin, for instance, the electricity consumption data has demonstrated the validity of the optimization scheduling model and the superiority of Matlab in finding solutions as well. In short, linear programming theory is applied to help energy-intensive enterprises optimize the allocation of resources to save energy and reduce costs, which has strong practical value.