Impact of battery storage on residential energy consumption: An Australian case study based on smart meter data

被引:34
|
作者
Al Khafaf, Nameer [1 ]
Rezaei, Ahmad Asgharian [1 ]
Amani, Ali Moradi [1 ]
Jalili, Mahdi [1 ]
McGrath, Brendan [1 ]
Meegahapola, Lasantha [1 ]
Vahidnia, Arash [1 ]
机构
[1] RMIT Univ, 124 Trobe St, Melbourne, Vic 3000, Australia
基金
澳大利亚研究理事会;
关键词
Smart meter; Energy storage systems; Case study; Big data; Knowledge discovery; Energy consumption; PHOTOVOLTAIC SYSTEMS; COORDINATED CONTROL; DEMAND RESPONSE; PV SYSTEMS; LOAD; IMPROVE; OPTIMIZATION; PERFORMANCE; DEPLOYMENT; VIABILITY;
D O I
10.1016/j.renene.2021.10.005
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Advanced metering infrastructure has been widely recognized as a key enabling factor for delivering a range of benefits to the electricity industry as well as to energy consumers. The data is commonly used for billing and to educate consumers so they can make economically optimal decisions on choosing between electricity retail plans. More importantly, an in-depth analysis of this data can drive the development and implementation of new energy technologies and to enable evidence-based policy decisions to be made. In this paper, an Australian case study is presented on how residential battery installations lead to behavioral changes in the way energy is consumed. Furthermore, data-informed recommendations to both distribution network operators and policy-makers are also provided. The data comprises more than 5000 energy consumers with either distributed generation systems such as Photovoltaics (PV) and Energy Storage Systems (ESS), or without. The methodology focuses on the analysis of energy consumption of consumers with PV and ESS energy consumers and compares them against consumers without ESS. In addition, an economic analysis on the benefit of installing ESS is presented using payback period and internal rate of return. The main finding is that residential energy storage systems provide a range of benefits to the distribution network. It is recommended that Governments should continue supporting the rollout of such systems by subsidy programs and implementing necessary policy directives. (c) 2021 Elsevier Ltd. All rights reserved.
引用
下载
收藏
页码:390 / 400
页数:11
相关论文
共 50 条
  • [21] Electric Vehicle Charging Identification and Profiling Using Australian Residential Smart Meter Data
    Rahman, Mir Toufikur
    Hasan, Kazi N.
    Rosengarten, Gary
    2023 33RD AUSTRALASIAN UNIVERSITIES POWER ENGINEERING CONFERENCE, AUPEC, 2023,
  • [22] Residential battery sizing model using net meter energy data clustering
    Tang, Rui
    Yildiz, Baran
    Leong, Philip H. W.
    Vassallo, Anthony
    Dore, Jonathon
    APPLIED ENERGY, 2019, 251
  • [23] Exploring residential minimum night consumption in a real water distribution network based on smart-meter data
    Samuele Alassio
    Valentina Marsili
    Filippo Mazzoni
    Stefano Alvisi
    Discover Water, 4 (1):
  • [24] Smart meter data analytics: prediction of enrollment in residential energy efficiency programs
    Zeifman, Michael
    2014 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC), 2014, : 413 - 416
  • [25] Operative Benefits of Residential Battery Storage for Decarbonizing Energy Systems: A German Case Study
    Wanapinit, Natapon
    Offermann, Nils
    Thelen, Connor
    Kost, Christoph
    Rehtanz, Christian
    ENERGIES, 2024, 17 (10)
  • [26] Energy Consumption Pattern and Environmental Impact: A Case Study of Residential Sector in India
    Satish, Jangali G.
    Nagesha, N.
    INTERNATIONAL CONFERENCE ON ADVANCES IN MATERIALS AND MANUFACTURING APPLICATIONS (ICONAMMA-2018), 2019, 577
  • [27] Residential electricity consumption and household characteristics: An econometric analysis of Danish smart-meter data
    Andersen, F. M.
    Gunkel, P. A.
    Jacobsen, H. K.
    Kitzing, L.
    ENERGY ECONOMICS, 2021, 100
  • [28] Detecting anomalous energy consumption using contextual analysis of smart meter data
    Ankur Sial
    Amarjeet Singh
    Aniket Mahanti
    Wireless Networks, 2021, 27 : 4275 - 4292
  • [29] Detecting anomalous energy consumption using contextual analysis of smart meter data
    Sial, Ankur
    Singh, Amarjeet
    Mahanti, Aniket
    WIRELESS NETWORKS, 2021, 27 (06) : 4275 - 4292
  • [30] Analysis and Clustering of Residential Customers Energy Behavioral Demand Using Smart Meter Data
    Haben, Stephen
    Singleton, Colin
    Grindrod, Peter
    IEEE TRANSACTIONS ON SMART GRID, 2016, 7 (01) : 136 - 144