智能用电环境下家庭电力能效评估及节能策略研究

Smart power utilization technology is an important part of building a strong and smart grid, the quality of its construction is directly related to grid's energy using efficiency, economic operation and orderly power. Building a smart grid is not just to the upgrade and transform the traditional grid and system, it also need to implement demand-side response, to promote the use of demand-side management technology, to change the user's way of use energy, to promote energy conservation and to improve the proportion of clean electricity in final energy consumption. With the construction and development of smart power utilization, household power utilization information which was collected through demand-side management technology is increasingly abundant. How to do a scientific assessment according to this information and to targetedly formulate a best energy-saving program are the current problems that needed to be solved...The purpose of this project is to resolve a number of key technologies about energy efficiency assessment of household power utilization and energy-saving strategy. First of all, a daily load curve model separated by category based on period analysis is created to get each electrical load information in real-time. Secondly, we fusing the data collected for assessment by Data Fusion methods, as well as researching the method for quickly remove "abnormal data" and fasting access technique of multi-dimensional data. Then building household power utilization energy efficiency assessment index system and assessment model, through the adaptive technology and the detail information of electrical equipment coming true reasonably automatic selected method. Finally established potential energy-saving programs based on comparative factors method, therefore according to user's individual differences, automatically develop the best energy-saving strategy...Using family as a unit, the research of this project will form a new theory about efficiency assessment of household power utilization and form a new method of energy-saving diagnosis. These theory and method can effectively guide household to scientifically,economically and efficiently use electricity thereby strengthen the management of demand-side household power utilization.

随着智能用电技术发展，智能家居渐入人们日常生活，通过量测控制技术获取大量家庭用电信息已成为可能。如何充分利用这些信息进行能效评估，并有针对性地制订家庭节能方案是电力需求侧管理中亟待解决的问题。本项目的目标是攻克家庭电力能效评估与节能策略中的若干关键技术。首先，基于时段分析建立日负荷曲线按类别分离模型，实现每个电器负荷信息的实时获取；其次，通过数据融合方法对评估所需数据信息进行优化整合，并研究"异常数据"快速剔除方法和多维数据快速存取技术；然后，构建家庭用电能效评估指标体系和评估方法库，运用自适应技术，依据用电设备的具体信息，智能化选择评估方法构建评估模型；最后，提出基于因素对比的节能潜力分析方法，实现个性节能策略的自动编制。本项目的研究将形成较为完善的家庭用电能效评估体系、节能诊断方法，能够有效的指导家庭用户科学、经济、节能地用电，提高智能用电环境下需求侧管理水平。

伴随着智能用电技术的快速发展，智能家居渐入人们日常生活，通过量测控制技术获取大量家庭用电信息已成为可能。如何充分利用这些信息进行能效评估，并有针对性地制订家庭节能方案以指导用户合理用电是电力需求侧管理中亟待解决的问题。.电力能效评估与节能管理技术是电力需求侧管理中一个重要研究领域，目前能效评估的研究重点多是以企业用户为对象，缺乏针对家庭用户的相关研究，尚未形成一套科学、完整的家庭用电能效评估理论体系，包含评估的指标体系、评估模型、评估方法、节能策略。.本项目从智能用电技术发展现状出发，深入分析当前智能家居的电器指标特性及未来发展趋势，攻克了家庭用电能效评估中若干关键技术，解决如何针对家庭用电进行能效评估，并自动编制家庭节能方案的问题。研究的主要成果有：（1）提出基于开启瞬时负荷特征的家电负荷识别方法，并建立负荷曲线分离模型，实现每个电器负荷信息的实时获取；（2）提出非侵入式负荷分解方法，实现评估所需的数据信息优化整合，以及多维数据的快速存取与“异常数据”的快速剔除；（3）建立家庭用电能效评估指标体系，利用统计学中的效度系数法验证了指标体系的有效性和可靠性，确保了该评估指标体系的准确性；（4）综合采用层次分析法和贝叶斯方法对家庭电力指标体系进行能效评估建模，提高了评估模型的针对性和准确性；（5）提出基于云计算的家庭智能用电策略，基于家庭用户的用电行为及用电特征时间段， 合理转化处理用户用电行为序列，挖掘出了用户用电行为间的关联规则，进而对家庭用电时间分布进行合理规划，给出了行之有效的智能用电策略;（6）提出了一种基于用户用电习惯的家庭用电策略，该策略把用户习惯作为首要考虑因素，构建用户满意度函数，结合分时电价环境下的费用函数制定用电策略目标函数，最后找出用电方案中电器的最佳开启时间。