过程工业用电自动需求响应建模与优化

Demand response in smart grid can promote the optimal balance of power supply and demand, and its latest form, the automatic demand response, can further enhance the participation initiative of electricity users. There is huge potential of electricity demand response in process industrial, but when applying the existing methods to implement demand response in process industrial, a challenge that the contradictory of consistency of power supply and demand and the dynamic of production load distribution under the distributed energy environment is encountered. This project aims to study the automatic demand response model and rolling optimization based multi-scale optimization mechanisms for process industrial: load forecasting model and power supply model are established, on which the behaviors of both supply and demand side are analyzed under demand response mode, and a typical process production, which is the steel rolling production, is proposed as an scenario of the study; with the objective of maximizing social benefits of electricity, the day-ahead scheduling is implemented to coordinate the power purchase planning of supply enterprise and the energy consumption planning of production company, and a stackelberg game based distributed optimization algorithms is proposed to coordinate the day-ahead power supply and demand; considering the mix power supply environment of dynamic pricing and distributed energy, using the optimal day-ahead scheduling decisions as constraints, the real-time optimization of production load distribution is implemented, and a PSO based algorithm for job scheduling is also proposed for dynamic load distribution. Research of this project can enrich the theory and methods of smart grid demand response, and improve the adaptability of intelligent computing in distributed dynamic environment.

智能电网需求响应可以优化电力供需平衡，其最新实现形式自动需求响应则通过增强用户参与主动性进一步提升响应水平。过程工业用电需求响应潜力巨大，但面临分布式能源环境下电力供需调度一致性与生产负荷分配动态性相矛盾的挑战。项目深入研究过程工业用电自动需求响应模型及基于滚动优化思想的电力供需多尺度优化机制：建立供电企业模型和生产负荷预测模型，分析需求响应模式下电力供需双方行为，以典型冶金过程工业中的轧钢生产为实例研究对象；以用电社会效益最大化为目标，通过供电企业购电计划和生产企业用电决策日前调度实现优化电价和协调生产，提出基于主从博弈的电力供需日前调度分布式优化算法；考虑动态电价和分布式能源的混合供电环境，以日前优化调度决策作为约束条件，实施生产负荷分配实时优化调度，提出面向负荷分配的生产作业调度动态粒子群算法。项目研究可以丰富智能电网需求响应理论和方法，并可改进分布式和动态环境下智能计算的适应性。

本项目在智能电网框架下，面向工业电力大用户，深入研究过程工业用电自动需求响应机制：首先，以典型冶金过程工业中的轧钢生产作为过程生产实例研究对象，研究了供电企业模型和过程生产负荷预测模型，分析需求响应下电力供需双方行为；然后，以日前优化调度决策作为约束条件，研究了过程生产企业用电决策的日前优化调度建模及求解；进一步，研究了动态电价、碳排放约束下的发用电一体化调度建模及优化求解。通过以上研究，建立了基于间歇生产负荷调度的过程工业用电自动需求响应机制，为过程工业生产与能源集成管控奠定基础，可帮助企业降低用电成本，并有利于电网调峰。基于本项目支持，研究结果发表基金标注论文6篇，其中SCI期刊2篇，EI期刊1篇，会议论文2篇（待EI收录），CSCD期刊1篇，此外在审和返修论文各1篇；授权发明专利4项，实审专利3项；项目相关研究成果转化应用，获2015年度湖南省专利奖二等奖（排名第1）、科技进步三等奖，项目负责人入选湖南省“湖湘青年英才”支持计划、湘潭市领导联系专家、湘潭市科技专家库专家。