| 引用本文: | 张丽,张涛,王福忠,祁鑫.基于柔性负荷响应特性的超短期预测方法[J].电力系统保护与控制,2019,47(9):27-34.[点击复制] |
| ZHANG Li,ZHANG Tao,WANG Fuzhong,QI Xin.Ultra-short-term forecasting method based on response characteristics of flexible load[J].Power System Protection and Control,2019,47(9):27-34[点击复制] |
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| 摘要: |
| 在自动需求响应系统(ADRS)中，当大量的用电负荷数据被自动实时采集时，受节假日、天气、温度等因素的影响，用户侧负荷用电特性会随着响应策略的变化而发生变化。传统负荷预测方法的预测精度也将会被降低，不再满足ADRS要求。针对这一问题，基于柔性负荷的响应特性，将“预测-调度-响应”各环节视为一个闭环控制系统，把自动响应(AD)信号作为一个输入变量引入系统。基于丰富的负荷用电数据，采用“黑匣子”思想建立了闭环超短期负荷预测模型，并用仿真结果验证了模型的有效性。结果表明，该模型与传统预测模型相比，预测精度明显提高。 |
| 关键词: 自动需求响应系统 柔性负荷 负荷预测 自动响应 黑匣子 |
| DOI：10.7667/PSPC180625 |
| 投稿时间：2018-05-24修订日期：2018-08-05 |
| 基金项目:国家自然科学基金项目(61703144);河南省开放实验室项目(KG2016-7);河南省高等学校重点科研项目(18A470014);河南理工大学博士基金(B2017-20) |
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| Ultra-short-term forecasting method based on response characteristics of flexible load |
| ZHANG Li,ZHANG Tao,WANG Fuzhong,QI Xin |
| (School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, China) |
| Abstract: |
| In the Automatic Demand Response System (ADRS), the electrical load characteristics of the user's side will vary with the change of the response strategy due to the influence of holidays, weather, temperature and other factors, when a large amount of power load data is collected automatically in real time. The prediction accuracy will be reduced using the traditional load forecasting method, which will no longer meet the requirement of ADRS. In this paper, based on the response characteristic of flexible load and the rich load power data of ADRS, the Automatic Demand (AD) response signal is introduced into the system as an input variable when each link of "predictive- dispatch -response" is consided as a closed loop control system. The closed loop ultra-short-term forecasting model is established by using the "black box" idea. The validity of the model is verified by simulation results. The results show that the prediction accuracy of the model is higher than that of the traditional prediction model. This work is supported by National Natural Science Foundation of China (No. 61703144), Henan Open Laboratory Project (No. KG2016-7), Key Scientific Research Project of Colleges and Universities in Henan Province (No. 18A470014) and Doctoral Fund of Henan Polytechnic University (No. B2017-20). |
| Key words: automatic demand response system (ADRS) flexible load load forecasting automatic demand black box |
