Source-load coordinated dispatching model taking into account the similarity between renewable energy and load power

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks Pub Date : 2024-08-13 DOI:10.1016/j.segan.2024.101499

Jingjie Huang , Zhiyao Zhang , Liang Yuan , Hongming Yang , Zhaoyang Dong , Renjun Zhou

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Abstract

With the deployment of renewable energy, the load curve is expected to follow the renewable energy output curve to minimize the fluctuation of thermal power output in the source-load coordinated dispatching. The traditional indicators for the load curve are no longer enough to describe the load characteristics. A new load indicator called the source-load similarity distance is proposed by improving the similarity measurement method of the time series and calculating the similarity distance between the renewable energy output curve and the load curve. By combining the Euclidean distance with the improved dynamic time warping, the source-load similarity distance is obtained and the data distribution and morphological fluctuation characteristics can be simultaneously considered. The source-load coordinated dispatching model is also established to minimize the source-load similarity distance. The simulation results show that the source-load similarity distance can effectively describe the similarity characteristics of the renewable energy output curve and the load curve. Increasing the source-load similarity distance can reduce the thermal power operation cost by 56.2 % and the cost of demand response by 25.3 %, and increase the utilization rate of wind power by 4.6 % compared to the dispatching model with the standard deviation indicator.

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考虑到可再生能源与负载功率相似性的源-负载协调调度模型

随着可再生能源的部署，负荷曲线有望跟随可再生能源输出曲线，从而在源-荷协调调度中将火电输出的波动降至最低。传统的负荷曲线指标已不足以描述负荷特性。通过改进时间序列的相似性测量方法，计算可再生能源输出曲线与负荷曲线之间的相似性距离，提出了一种新的负荷指标--源-负荷相似性距离。通过将欧氏距离与改进的动态时间扭曲相结合，得到了源荷相似度距离，并可同时考虑数据分布和形态波动特征。同时还建立了源负载协调调度模型，以最小化源负载相似度距离。仿真结果表明，源荷相似度距离能有效描述可再生能源输出曲线与负荷曲线的相似性特征。与采用标准差指标的调度模型相比，提高源-荷相似度距离可降低火电运行成本 56.2%，降低需求响应成本 25.3%，提高风电利用率 4.6%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Sustainable Energy Grids & Networks Energy-Energy Engineering and Power Technology

CiteScore

7.90

自引率

13.00%

发文量

206

审稿时长

49 days

期刊介绍： Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.