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Shanlin Yang - One of the best experts on this subject based on the ideXlab platform.

  • Residential electricity Consumption Behavior: Influencing factors, related theories and intervention strategies
    Renewable and Sustainable Energy Reviews, 2018
    Co-Authors: Guo Zhifeng, Kaile Zhou, Chi Zhang, Wen Chen, Shanlin Yang
    Abstract:

    Abstract The proportion of residential electricity Consumption in the total energy Consumption has increased rapidly in the past decades all over the world. It is becoming increasingly important to promote household energy conservation for the sustainable development of a country in the case of resource constraints. This paper reviews and evaluates the existing research works which are related to the residential electricity Consumption Behavior. Particular attention is given to the following aspects. (1) Factors influencing residential electricity Consumption in social psychology. (2) Theories of social psychology in understanding residential electricity Consumption Behavior. (3) Different interventions aiming at encouraging households to reduce electricity Consumption. Finally, we discuss the challenges and opportunities of research on residential electricity Consumption Behavior in the big data era.

  • Understanding household energy Consumption Behavior: The contribution of energy big data analytics
    Renewable and Sustainable Energy Reviews, 2016
    Co-Authors: Kaile Zhou, Shanlin Yang
    Abstract:

    Abstract Understanding and changing household energy Consumption Behavior are considered as effective ways to improve energy efficiency and promote energy conservation. With the increasing penetration of conventional and emerging information and communication technologies (ICTs) in energy sector, traditional energy systems are being digitized. The energy big data provides a new way to analyze and understand individuals׳ energy Consumption Behavior, and thus to improve energy efficiency and promote energy conservation. We first propose a framework of the interdisciplinary research of energy, social and information science, which includes energy social science, social informatics and energy informatics. Then, different dimensions and different research paradigms of household energy Consumption Behavior are presented. Household energy Consumption Behavior can be analyzed in time dimension, user dimension and spatial dimension. The economic paradigm (including demand response) and the Behavior-oriented paradigm (including intervention strategies) are two major research streams of household energy Consumption Behavior. Finally, the “4V” characteristics (i.e., volume, velocity, variety and value) of energy big data are discussed.

Cao Jinping - One of the best experts on this subject based on the ideXlab platform.

  • cloud computing based analysis on residential electricity Consumption Behavior
    Power system technology, 2013
    Co-Authors: Cao Jinping
    Abstract:

    To research residential electricity Consumption Behavior in intelligent residential area,based on cloud computing platform and parallel k-means clustering algorithm the time series features such as electricity Consumption rate during peak hour,load rate,valley load coefficient,namely the ratio of electricity Consumption during valley hour to total electricity Consumption,and so on are established and the weights of various features are calculated by entropy weight method.Experimental data is from 600 users living in a certain built smart community.Experimental results show that the residential users in the smart community are divided into five categories,i.e.,vacant dwellings,office staff,office staff living with elders,aged families and commercial customer,and the clustering accuracy reaches 91.2%,and thus it is proved that the proposed model for residential electricity Consumption Behavior analysis is correct and effective.

Hu Zhi-bin - One of the best experts on this subject based on the ideXlab platform.

Marie Persson Netz - One of the best experts on this subject based on the ideXlab platform.

  • ICCS (5) - Profiling of Household Residents’ Electricity Consumption Behavior Using Clustering Analysis
    Lecture Notes in Computer Science, 2019
    Co-Authors: Christian Nordahl, Veselka Boeva, Håkan Grahn, Marie Persson Netz
    Abstract:

    In this study we apply clustering techniques for analyzing and understanding households’ electricity Consumption data. The knowledge extracted by this analysis is used to create a model of normal electricity Consumption Behavior for each particular household. Initially, the household’s electricity Consumption data are partitioned into a number of clusters with similar daily electricity Consumption profiles. The centroids of the generated clusters can be considered as representative signatures of a household’s electricity Consumption Behavior. The proposed approach is evaluated by conducting a number of experiments on electricity Consumption data of ten selected households. The obtained results show that the proposed approach is suitable for data organizing and understanding, and can be applied for modeling electricity Consumption Behavior on a household level.

Yingzheng Liu - One of the best experts on this subject based on the ideXlab platform.

  • Analysis of residents' smart electricity Consumption Behavior based on fuzzy synthetic evaluation and the design of interactive mechanism
    Dianwang Jishu Power System Technology, 2012
    Co-Authors: Yihai He, Wayne Xiong, Baolong Wang, Tao Zhang, Yingzheng Liu
    Abstract:

    Under the circumstance of smart grid, the research on smart electricity Consumption Behavior of residents is of great significance to the design and construction of smart grid. Currently, demand response projects are widely carried out. However, current responsiveness of residents is low. The purpose of this research is to propose suggestions on the design of residents' interactive mechanism through the investigation on their attitude to electricity Consumption to make them widely participating in various items of demand responses and playing important role in ensuring stable operation of power grid. Through questionnaire survey and data statistics on smart electricity Consumption situation of urban residents in typical cities, the electricity Consumption situation of residents and key factors influencing residents' smart electricity Consumption are analyzed, and a positive correlation is found between household electricity expenditure and housing area. The fuzzy synthetic evaluation is applied in the quantified scoring of residents' attribute to smart electricity Consumption to find the information and functions of smart electricity Consumption, which are considered as important by residents, and based on residents' preference and analysis on their smart electricity Consumption Behavior some reasonable suggestions for the design of resident interactive mechanism in smart grid environment are put forward.