According to experts, the average temperature of the planet has increased at an unprecedented and alarmingly high rate over the last fifty (50) years. Carbon emissions have been found to be a major catalyst for climate change and the energy sector one of the highest emitters globally. Thus any significant reduction in energy related emissions would have a significant impact on global carbon emissions and consequently global warming. UN-Habitat estimates that approximately 56% of energy produced in most African nations is consumed in buildings. There is a need for energy efficiency and possibly conservation in buildings since they represent the single largest consumer of energy on the continent. Net Zero Energy Buildings (NZEBs), a possible solution for reducing the energy footprint of buildings, represents the evolution of buildings in the near future. The Zero energy concept has a major impact on the design and construction of future buildings. This paper focuses on the review and development of existing Load Match Indicators for zero energy buildings. Four indicators are provided and discussed (i.e. self-consumption, self-production, loss of load probability, and coverage rate indicators). For the purpose of this paper, Predis-MHI (a platform of G2ELab) was used as a case study. Data was collected from the platform’s living lab and was used in the calculation and evaluation of these indicators. The results indicate the relevance of each indicator in evaluating the energetic performance of a building and also highlight the practical difficulties faced in evaluating the platform.
[1]
George Baird,et al.
Energy Performance Buildings
,
2017
.
[2]
A. Nilsson,et al.
Effects of continuous feedback on households’ electricity consumption: Potentials and barriers
,
2014
.
[3]
Chee Wei Tan,et al.
A review of renewable energy development in Africa: A focus in South Africa, Egypt and Nigeria
,
2018
.
[5]
Frédéric Wurtz,et al.
GreEn-ER living lab: A green building with energy aware occupants
,
2016,
2016 5th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS).
[6]
Kathryn B. Janda,et al.
Buildings don't use energy: people do
,
2011
.
[7]
Tuan Anh Nguyen,et al.
Energy intelligent buildings based on user activity: A survey
,
2013
.
[8]
Hanh Truong,et al.
Occupant perceptions of building information model-based energy visualizations in eco-feedback systems
,
2018,
Applied Energy.
[9]
Antonio Paone,et al.
The Impact of Building Occupant Behavior on Energy Efficiency and Methods to Influence It: A Review of the State of the Art
,
2018
.
[10]
Jaume Salom,et al.
Understanding net zero energy buildings: Evaluation of load matching and grid interaction indicators
,
2011
.
[11]
Yg Sandanayake,et al.
Building energy consumption factors : a literature review and future research agenda
,
2012
.
[12]
Nan Li,et al.
The Impact of Eco-Feedback on Energy Consumption Behavior: A Cross-Cultural Study
,
2016
.