文章摘要
杨 恺,姚 宇,孙 可,惠恒宇,李 黎,鲍卫东,叶承晋,王曦冉.考虑用户满意度的温控负荷能效综合指标模型和调峰策略[J].电力需求侧管理,2022,24(5):36-43
考虑用户满意度的温控负荷能效综合指标模型和调峰策略
Energy efficiency assessment model and peak shaving strategy for TCLs considering consumer satisfaction
投稿时间:2022-06-28  修订日期:2022-07-29
DOI:10. 3969 / j. issn. 1009-1831. 2022. 05. 007
中文关键词: 温控负荷  能效指标模型  用户满意度  模糊子集方法  调峰容量评估
英文关键词: thermostatically controlled loads  energy efficency rutio model  user satisfaction  fuzzy set method  peak shaving capacity estimating
基金项目:国网浙江省电力有限公司科技项目(B311JY22000B)
作者单位
杨 恺 国网浙江省电力有限公司 经济技术研究院杭州 310008 
姚 宇 浙江大学 电气工程学院杭州 310058 
孙 可 国网浙江省电力有限公司 经济技术研究院杭州 310008 
惠恒宇 浙江大学 电气工程学院杭州 310058 
李 黎 国网浙江省电力有限公司 经济技术研究院杭州 310008 
鲍卫东 国网浙江省电力有限公司 义乌供电公司浙江 义乌 322099 
叶承晋 浙江大学 电气工程学院杭州 310058 
王曦冉 国网浙江省电力有限公司 经济技术研究院杭州 310008 
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中文摘要:
      电力系统峰谷差的不断加大,使得电力系统需要更多的调峰容量。温控负荷作为需求响应的重要资源,可以为电力系统提供调峰容量。为帮助调度侧实现基于能效管理的温控负荷调峰,提出了考虑用户满意度的温控负荷能效综合指标模型和调峰策略。首先,基于模糊子集方法,提出考虑用户满意度的温控负荷能效(energy efficiency ratio consideringsatisfaction,EERCS)的计算模型,帮助调度侧对大规模温控负荷能效水平进行评估。然后,建立温控负荷调峰容量评估模型,用于在调峰时估计温控负荷调峰容量。最后,在此基础上制定调峰策略。调度前,确认温控负荷是否可接受调度,并计算温控负荷的EERCS值和调峰容量;调度时,根据EERCS值对用户进行排序,优先调用EERCS 值低的温控负荷,提高温控负荷群的用户满意度水平,进而提高温控负荷群的能效水平。接着,基于中国东部某城市585户电力用户的真实数据,仿真了在不同功率缺额下的调峰结果。该算例表明,所提的调峰策略可有效提高温控负荷群的综合能效水平。
英文摘要:
      The peakvalley difference is increasing in the power system, which requires more capacity to keep the power balance. As a significant demand response resource, thermostatically controlled loads can provide peak shaving capacity.In this context,an energy efficiency ratio considering consumer satisfaction and a peak shaving strategy are proposed, which helps the system operators regulate the thermostatically controlled loads based on energy efficiency management. Firstly, based on the fuzzy set method, a model is proposed to calculate the energy efficiency ratio considering consumer satisfaction of thermostatically controlled loads. This model helps the system operators to estimate the energy efficiency rate of mass thermostatically controlled loads without installing hardware. Then, a fitting model is built to estimate the peak shaving capacity. Based on the above models, the peak shaving strategy is developed. Before the peak shaving, the system operatorscheck whether the thermostatically controlled loads can participate in the peak shaving and calculate energy efficiency ratio considering consumer satisfaction and capacity. The system operators may regulate-thermostatically controlled loads whose energy efficiency ratio considering consumer satisfaction is low. Therefore, the satisfaction of society and the comprehensive energy efficiency will improve when providing the peak shaving capacity. The case uses realistic data,which contains consumers’electricity consumption data in an eastern city in China and its temperature data.The results indicate that the comprehensive energy efficiency improves obviously after adopting the proposed strategy.
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