基于灵活性矩阵与优劣解距离的新能源功率预测评价方法

doi:10.12204/j.issn.1000-7229.2021.02.005

电力建设 ›› 2021, Vol. 42 ›› Issue (2): 35-42.doi: 10.12204/j.issn.1000-7229.2021.02.005

• 促进高比例新能源消纳的光伏发电功率与负荷预测 ·栏目主持王飞教授 • 上一篇下一篇

基于灵活性矩阵与优劣解距离的新能源功率预测评价方法

尹瑞¹, 时珉¹, 王铁强¹, 李正辉², 刘嘉明², 甄钊²^,³, 郭怀东², 王飞²

1.国网河北省电力有限公司,石家庄市 050021
2.华北电力大学电力工程系,河北省保定市 071003
3.清华大学电机系,北京市 100084

收稿日期:2020-11-17 出版日期:2021-02-01 发布日期:2021-02-09
作者简介:尹瑞(1990),男,博士,工程师,主要研究方向为新能源发电、灵活交流输电与柔性直流输电技术;|时珉(1976),男,学士,高级工程师,主要研究方向为电网调度计划、水电及新能源;|王铁强(1970),男,博士,教授级高级工程师,主要研究方向为电力系统自动化、电网调度运行、新能源并网消纳技术;|李正辉(1996),男,硕士研究生,主要研究方向为电力系统负荷预测与电量预测;|刘嘉明(1996),男,硕士研究生,主要研究方向为新能源功率预测与电网优化运行;|甄钊(1989),男,博士后,主要研究方向为新能源功率预测与智能电网;|郭怀东(1970),男,学士,工程师,主要研究方向为电力系统自动化;|王飞(1973),男,教授,博士生导师,主要研究方向为新能源功率预测、综合能源与能源互联网、电力市场与需求响应。
基金资助:
国家电网公司管理咨询项目“新能源场站功率预测综合评价体系构建及优先调度策略研究”

An Evaluation Method for New Energy Power Prediction Based on Flexibility Matrix and TOPSIS Method

YIN Rui¹, SHI Min¹, WANG Tieqiang¹, LI Zhenghui², LIU Jiaming², ZHEN Zhao²^,³, GUO Huaidong², WANG Fei²

1. State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050021, China
2. Department of Electrical Engineering, North China Electric Power University, Baoding 071003, Hebei Province,China
3. Department of Electrical Engineering, Tsinghua University, Beijing 100084, China

Received:2020-11-17 Online:2021-02-01 Published:2021-02-09
Supported by:
the Management Consulting Project of State Grid Corporation of China “Research on Construction of Comprehensive Evaluation System of New Energy Station Power Forecasting and Priority Dispatch Strategy”

摘要/Abstract

摘要：

鉴于功率预测评价对电力系统运行和调度的重要性,文章充分考虑电网调度实际需求,从不同时期下机组的出力大小和不同时段下电网调度对预测精度的需求2个方面分析现有功率预测评价指标的不合理之处,并提出了新的准确率指标。首先,对不同时期下系统灵活性进行计算得到灵活性矩阵并对其进行预处理;其次,将处理后的灵活性矩阵输入到优劣解距离法(technique for order preference by similarity to an ideal solution,TOPSIS)模型中,根据评价对象与理想化目标的接近程度对不同时段的灵活性进行排序和归一化计算,得到不同时段下的权重系数矩阵,进而形成新的评价指标;最后,将所提的评价指标与其他指标进行对比。仿真结果表明,所提评价指标更能体现系统灵活性对功率预测评价的影响,满足实际调度的需求。

关键词: 功率预测评价, 系统灵活性, 优劣解距离法(TOPSIS)模型, 权重系数矩阵

Abstract:

Considering the importance of evaluation of power prediction for power system operation and dispatching, this paper takes the actual demand of gird dispatching into consideration and analyzes the irrationality of existing prediction evaluation indices from two aspects: the output of units in different periods and the demand of grid dispatching for forecasting accuracy in different periods. And some new evaluation indices are put forward. Firstly, the flexibility matrix of the system in different periods is calculated and pretreated. Secondly, the processed flexibility matrix is input into the technique for order preference by similarity to an ideal solution (TOPSIS) model. According to the closeness of the evaluation object and the idealized target, the flexibility in different periods is sorted and normalized to obtain the weight coefficient matrix, and then a new evaluation index is formed. Finally, the evaluation index proposed in this paper is compared with other indices. The simulation results show that the evaluation indices proposed in this paper can better reflect the influence of system flexibility on power prediction evaluation and meet the requirements of grid dispatching.

Key words: evaluation of power prediction, system flexibility, TOPSIS model, weight coefficient matrix

中图分类号:

TM731

尹瑞, 时珉, 王铁强, 李正辉, 刘嘉明, 甄钊, 郭怀东, 王飞. 基于灵活性矩阵与优劣解距离的新能源功率预测评价方法[J]. 电力建设, 2021, 42(2): 35-42.

YIN Rui, SHI Min, WANG Tieqiang, LI Zhenghui, LIU Jiaming, ZHEN Zhao, GUO Huaidong, WANG Fei. An Evaluation Method for New Energy Power Prediction Based on Flexibility Matrix and TOPSIS Method[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(2): 35-42.

图/表 11

图1 新能源实际与预测出力曲线

Fig.1 Actual and predicted new energy curves

图2 考虑供热季与非供热季对机组运行的影响

Fig.2 The influence of heating season and non-heating season on unit operation

图3 技术流程

Fig.3 Technical flowchart

图4 机组运行场景分析

Fig.4 Analysis of unit operation scenario

图5 总负荷、净负荷和新能源出力曲线

Fig.5 Curves of total load, net load and new energy output

图6 供热季与非供热季各个时段的权重值

Fig.6 The weight index of heating and non-heating season

表1 不同月份下准确率的大小

Table 1 The accuracy in different months%

图7 供热季新能源的出力和系统灵活性曲线

Fig.7 Curves of new energy output and system flexibility in heating season

图8 供热季典型日的准确率指标

Fig.8 Accuracy index of typical days in heating season

图9 新能源的出力和系统灵活性曲线

Fig.9 Curves of new energy output and system flexibility in non-heating season

图10 非供热季典型日的准确率指标

Fig.10 Accuracy index of typical days in non-heating season

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基于灵活性矩阵与优劣解距离的新能源功率预测评价方法

An Evaluation Method for New Energy Power Prediction Based on Flexibility Matrix and TOPSIS Method

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