Short-Term Forecasting of Power Consumption of Power Supply Companies Based on the Integration of Technologies of Analytical, Simulation and Expert Systems

A. K. Mektepkaliyeva, A. Khanova, L. B. Aminul
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Abstract

Purpose of research is to improve software support and identify regularities in the processes of short-term forecasting of power consumption of power supply companies based on complementary integration of data mining models, system dynamics and expert systems.Methods. The principles of constructing predictive models of power consumption are given. A system analysis has been carried out and an ontological model of the subject area has been built, taking into account the technological and market environment. The classification of forecasting methods has been considered. The features of the information base for short-term forecasting, including data on actual power consumption and weather data, have been described. The requirements for software for making forecasts have been formulated. A block diagram of the system for forecasting power consumption of the market for the day ahead is built based on the complementary integration of data analysis and modeling software.Results. Scenarios for data processing in Loginom have been developed using the Arimax and Neural Network (Regression) processors to build forecasts based on actual power consumption and taking into account meteorological factors. A system dynamics simulation model that allows exploring the influence of meteorological factors (temperature, pressure, precipitation) on power consumption has been developed in Anylogic. Using Wi!Mi mivar constructor of expert systems, the task has been parametrized; indicators, relationships, rules have been set; a logical conclusion of the solution has been obtained.Conclusion. A block diagram of a system for forecasting the market's power consumption for the day ahead has been built. It is based on the analysis of retrospective information on actual power consumption and meteorological factors using data mining methods, system dynamics and expert systems applying Russian Loginom, Anylogic and Wi!Mi software tools.
基于分析、仿真和专家系统集成技术的供电企业短期用电量预测
研究的目的是基于数据挖掘模型、系统动力学和专家系统的互补集成,提高软件支持,识别供电企业短期用电量预测过程中的规律。给出了建立电力消耗预测模型的原理。考虑技术环境和市场环境,进行了系统分析,建立了学科领域的本体论模型。考虑了预测方法的分类。介绍了短期预报信息库的特点,包括实际用电量数据和天气数据。制定了对预报软件的要求。基于数据分析与建模软件的互补集成,构建了未来一天市场用电量预测系统的框图。使用Arimax和神经网络(回归)处理器开发了Loginom的数据处理方案,以根据实际用电量和考虑气象因素建立预测。Anylogic开发了一个系统动力学仿真模型,该模型允许探索气象因素(温度、压力、降水)对功耗的影响。使用Wi !在专家系统构造器中,对任务进行了参数化处理;指标、关系、规则都已经制定;得出了该解决方案的一个合乎逻辑的结论。建立了预测当日市场用电量的系统框图。它是基于对实际电力消耗和气象因素的回顾性信息分析,使用数据挖掘方法,系统动力学和专家系统应用俄罗斯Loginom, Anylogic和Wi!小米软件工具。
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