Assessment of multiple-based demand response actions for peak residential electricity reduction in Ghana

被引:31
|
作者
Diawuo, Felix Amankwah [1 ,2 ]
Sakah, Marriette [3 ]
du Can, Stephane de la Rue [4 ]
Baptista, Patricia C. [1 ]
Silva, Carlos A. [1 ]
机构
[1] Univ Tecn Lisboa, Inst Super Tecn, Ctr Innovat Technol & Policy Res IN, Ave Rovisco Pais 1, P-1049001 Lisbon, Portugal
[2] Univ Energy & Nat Resources UENR, Sch Engn, POB 214, Sunyani, Ghana
[3] Tech Univ Darmstadt, Darmstadt Grad Sch Energy Sci & Engn, Darmstadt, Germany
[4] Lawrence Berkeley Natl Lab, Energy Technol Area, Energy Anal & Environm Impacts Div, 1 Cyclotron Rd,MS 90R2121, Berkeley, CA 94720 USA
关键词
Household survey; end-use electricity monitoring; peak demand; load curve; voluntary demand response; SIDE MANAGEMENT; ENERGY EFFICIENCY; SUSTAINABLE ELECTRIFICATION; HOUSEHOLD APPLIANCES; CONSUMPTION; IMPACTS; PARTICIPATION; INFORMATION; DEPLOYMENT; SECURITY;
D O I
10.1016/j.scs.2020.102235
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Demand-side management initiatives such as voluntary demand response provide significant energy savings in the residential sector, which is a major peak demand contributor. The potential of such savings remains unexplored in Ghanaian households due to insufficient electricity consumption data, lack of end-user behavior information and knowledge about the cost-effectiveness of such programs. This research combines 80 household survey information and energy use monitoring data of household appliances, to assess the residential demand response potential of Ghana. A bottom-up approach based on modified end-use model is used to develop aggregate hourly load curve. The estimated electricity consumption is categorized based on their degree of control to determine peak demand reduction potential for the period 2018-2050. The average daily peak load reduction ranged between 65-406 MW representing 2-14% for the considered scenarios by 2050. The results show appreciable economic viability for investment in demand response with net present value varying between 28-645 million US$. We find that price, energy security and environment signals influence end-users' electricity use behavior. Authors observe that for energy and cost savings to be realized, utility providers and consumers need effective cooperation on information delivery and feedbacks, and consumers should be incentivized to balance the benefits.
引用
收藏
页数:19
相关论文
共 50 条
  • [1] Categorization of residential electricity consumption as a basis for the assessment of the impacts of demand response actions
    Soares, Ana
    Gomes, Álvaro
    Antunes, Carlos Henggeler
    Renewable and Sustainable Energy Reviews, 2014, 30 : 490 - 503
  • [2] Categorization of residential electricity consumption as a basis for the assessment of the impacts of demand response actions
    Soares, Ana
    Gomes, Alvaro
    Antunes, Carlos Henggeler
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2014, 30 : 490 - 503
  • [4] Estimation on possibility and capacity of residential peak electricity demand reduction by demand response scenario in rural areas of Japan
    Rohman, Abdur
    Kobayashi, Hisashi
    INTERNATIONAL CONFERENCE ON APPLIED ENERGY, ICAE2014, 2014, 61 : 887 - 890
  • [5] Day-Ahead Residential Electricity Demand Response Model Based on Deep Neural Networks for Peak Demand Reduction in the Jordanian Power Sector
    Shaqour, Ayas
    Farzaneh, Hooman
    Almogdady, Huthaifa
    APPLIED SCIENCES-BASEL, 2021, 11 (14):
  • [6] Residential peak electricity demand response-Highlights of some behavioural issues
    Gyamfi, Samuel
    Krumdieck, Susan
    Urmee, Tania
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2013, 25 : 71 - 77
  • [7] Evaluation of potential for peak demand reduction of residential buildings by household appliances with demand response
    Ono, Tetsushi
    Hagishima, Aya
    Tanimoto, Jun
    ELECTRONICS AND COMMUNICATIONS IN JAPAN, 2022, 105 (04)
  • [8] Evaluation of Potential for Peak Demand Reduction of Residential Buildings by Household Appliances with Demand Response
    Ono T.
    Hagishima A.
    Tanimoto J.
    IEEJ Transactions on Electronics, Information and Systems, 2022, 142 (08) : 909 - 918
  • [9] Statistical analysis of drivers of residential peak electricity demand
    Fan, H.
    MacGill, I. F.
    Sproul, A. B.
    ENERGY AND BUILDINGS, 2017, 141 : 205 - 217
  • [10] Demand response for residential buildings based on dynamic price of electricity
    Yoon, Ji Hoon
    Bladick, Ross
    Novoselac, Atila
    Energy and Buildings, 2014, 80 : 531 - 541