基于频谱分析的电力负荷峰谷特性研究及需求响应评价

Yu Cheng, Nan Dong, Yangkai Ren
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引用次数: 8

摘要

随着经济形势和产业结构的快速发展,电力负荷变得越来越复杂;特别是电力负荷曲线的峰谷特性波动越来越大。需求响应评价的基础是负荷曲线的峰谷特性。然而,目前对电力负荷峰谷特性的研究较少,传统的负荷特性指标如负荷因子、峰谷差因子等在全面估计电力负荷峰谷特性方面存在不足。频谱分析方法将电力负荷的时间序列划分为不同幅度、相位和频率的周期分量的叠加。通过测量各周期分量的重要性,可以找出电力负荷变化中的主周期分量。本文采用频谱分析方法对电力负荷进行分析,并提出两个指标来描述负荷曲线的峰谷特征。在此基础上,对需求响应的效果进行了评价。最后通过算例验证了在光谱分析的基础上提出的新方法。通过频谱分析方法,将负荷特性研究和需求响应评价从时域转移到频域。根据电力负荷曲线的频谱特征,可以更有效地分析负荷曲线波动的本质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigation on electric load peak and valley characters and demand response evaluation based on spectral analysis
Along with rapid development of economic situation and industrial structure, electric loads become more and more complex; especially the peak and valley characters of electric load curves fluctuate more and more severely. The foundation of demond response evaluation is peak and valley characteristics of load curves. However, study on electric load peak and valley characters right now is few, conventional indexes of electric load characteristics such as load factor and peak-valley difference factor have shortages in estimating electric load peak and valley characters comprehensively. Spectral analysis method divides the time series of electric load into superposition of periodic components with different amplitude, phase and frequency. By means of measuring the importance of each periodic component, the main-cycles components in the change of power load can be found out. The paper uses spectral analysis method to analyze power load and pulls out two indexes to describe peak and valley characters of load curves. On basis of these indexes, the paper evaluates the effect of demand response. Finally the example has confirmed this new method developed on the basis of spectral analysis. Through spectral analysis method, research on load characteristics and demand response evaluation is transferred from time domain to frequency domain. In accordance with the spectrum characters of electric load curves, we can analyze the essence of load curves' fluctuation more effectively.
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