基于改进自适应遗传算法综合能源规划的研究与分析

为了解决日益严峻的社会环境和资源日趋枯竭的的严峻形势，让不同能源结构能够得到优化配置，本文采用了改进的自适应遗传算法来对能源进行预测分析，借助计量自动化系统提供的大量电力负荷数据，基于用户群体分析与识别，改进自适应遗传算法等大数据技术对负荷进行预测，并对不同行业和部门，不同能源结构进行深入的分析与研究与探讨。对比传统的几种预测算法，得出改进的自适应遗传算法具有更加准确的预测能力，研究结果表明，提前做好相关能源的预测，对能源结构进行过综合的规划是很有必要的，可以引领能源模式走入一种全新的模式，开拓能源互联网新时代。为能源结构的转型升级做好必要的工作。能源的综合规划能缓解现在面临的能源危机和环境污染等严重的问题。

Research and Analysis of Integrated Energy Planning Based on Improved Adaptive Genetic Algorithms

In order to solve the grim situation of increasingly severe social environment and resource exhaustion, and to optimize the allocation of different energy structures, this paper uses the improved adaptive genetic algorithm to predict and analyze energy resources. With the help of a large number of power load data provided by metrology automation system, based on user group analysis and identification, the adaptive genetic algorithm and other data technologies are improved. The load is forecasted, and the energy structure of different industries and departments is deeply analyzed and discussed. Compared with several traditional prediction algorithms, the improved adaptive genetic algorithm has more accurate prediction ability. The research results show that it is necessary to do a good job of related energy prediction in advance and make a comprehensive planning of energy structure. It can lead the energy model into a new mode and open up a new era of energy Internet. To do the necessary work for the transformation and upgrading of energy structure. Comprehensive energy planning can alleviate the serious problems such as energy crisis and environmental pollution.