基于负荷台阶的工业需求响应用户优选方法

A Method for Optimal Selection of High-Capacity Industrial Users for Demand Response Based on Load Step Data Processing Mode

在未来高比例新能源渗透下,供需平衡不确定性逐步增加,需求响应是通过挖掘用户侧灵活性资源保障系统电力电量平衡的重要手段。在电力部门进行需求响应工作时,需要使用历史数据来初步评估负荷响应潜力,以便选择潜力高的用户并展开动员工作。面向表征工业用户用能特点的负荷台阶,对其进行了定义并给出了数学表达,进而提出了基于负荷台阶的工业需求响应用户优选方法。首先,构建了基于负荷台阶的工业用户多时间尺度需求响应潜力指标体系;然后,构建了需求响应用户优选模型,实现对不同用户响应潜力的初评估,并利用k-means算法和近邻传播算法进行群体划分,在不同时间尺度对用户进行优选;最后,基于水泥、造纸等4个行业的多个工业用户实际负荷数据进行算例分析,呈现了所提方法下工业需求响应的用户优选结果。

In the context of future high penetration of new energy,the uncertainty of supply-demand balance gradually increases.Demand response is an important means of ensuring the balance of power and electricity in the system by tapping into user-side flexible resources.When power sector works on demand response,historical data is needed for an initial assessment of load response potential,so as to select the users with high potential and initiate mobilization efforts.This article focuses on defining and providing a mathematical expression for load step that represents the energy consumption characteristics of industrial users.And then a user selection method for industrial demand response based on load step is proposed.Firstly,an index system for the potential of industrial users'demand response across multiple time scales based on load step is proposed.And then,a user selection model is established to conduct an initial evaluation of different users'response potential,and the k-means algorithm and the nearest neighbor propagation algorithm are used to divide groups,allowing for user selection across different time scales.Finally,a case study is presented based on actual load data from several industrial users in industries such as cement and paper,illustrating the user selection results for industrial demand response using the proposed method.