Building Energy Index: A Case Study of Three Government Office Buildings in Malaysia

Tahir, Mohamad Zamhari; Nawi, Mohd Nasrun Mohd; Rajemi, Mohamad Farizal

doi:10.1166/asl.2015.6239

Cited by 22 publications

(24 citation statements)

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“…Performance Indicator (KPI) regarding energy use in a building. Therefore, EEI can be called the Building Energy Index (BEI) (Tahir et al, 2017), or it can also be called the Energy Performance Index (EPI) (De Ruggiero et al, 2017). The basic definition of EEI as in (1) is the energy input ratio to the factor related to the energy-using component (Abidin et al, 2017).…”

Section: Energy Efficiency Index (Eei)mentioning

confidence: 99%

“…Factor related to the energy performance consists of eight components, (1) the weight of product produced, (2) The number of items produced, (3) weight of raw material used, (4) period of production, (5) period of plant usage, (6) number of in-patient bed per night (hospital building), ( 7) number of occupied rooms per night (hotel building), ( 8) floor area of building (Abidin et al, 2017;Malaysia, 2012). Buildings are affected by electrical loads such as heating, ventilation, and air-conditioning systems (HVAC) (Bakar et al, 2015), lighting (Tahir et al, 2017).…”

Section: Energy Efficiency Index (Eei)mentioning

confidence: 99%

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Energy Management Strategy in Campus Towards a Green Campus Through Promoting Carbon Footprint and Energy Efficiency Index Improving

Busaeri

Giriantari

Ariastina

et al. 2021

IJEEP

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The energy management strategy is the key to increasing the energy efficiency index (EEI) and controlling buildings' carbon emissions. This article discusses the energy policy strategy at Siliwangi University based on four main components of green campus: the profile of the electricity load, energy consumption, the rate of the number of vehicles, and vehicle activity in the campus environment. We propose four scenarios to meet the EEI and carbon emissions standards in 2025. The analysis of carbon emission production uses the UI Green Metric approach by referring to the carbon emission strategy from the Climate Action Tracker (CAT) and the profile of the world bank. Simultaneously, the EEI analysis uses the ASEAN-USAID standard, which is also used in the Indonesian National Standard (SNI). The conclusion is that even with the highest scenario to meet the target EEI level in 2025, Siliwangi University can only reach the EEI level in the "Extremely Efficient" category for the area with AC facilities and Extremely-Inefficient class for the area with AC facilities. The analysis results show that the most considerable contribution of carbon emissions is from motorbikes, 66%, cars and buses 33% and electricity use only 1.4%. Although the use of electricity does not have a significant emission impact, the EEI analysis results show a tendency towards electricity waste. Siliwangi University must immediately implement electric vehicles on campus to reduce carbon emissions from the mobility of motorbikes, cars, and buses.

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Section: Energy Efficiency Index (Eei)mentioning

confidence: 99%

Section: Energy Efficiency Index (Eei)mentioning

confidence: 99%

Energy Management Strategy in Campus Towards a Green Campus Through Promoting Carbon Footprint and Energy Efficiency Index Improving

Busaeri

Giriantari

Ariastina

et al. 2021

IJEEP

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“…To accomplish the target of being a developed nation by 2020; Malaysia is focusing more on sustainable growth and development (Tahir et al, 2015). In this regard, Malaysia has targeted to achieve 6% annual growth in its gross domestic product (GDP) compliance with the requirement of 11 th national action plan (EPU, 2015).…”

Section: Overview Of Malaysian Electricity Sectormentioning

confidence: 99%

Forecasting Impact of Demand Side Management on Malaysia’s Power Generation Using System Dynamic Approach

Tufail

Nawi²,

Ali³

et al. 2021

IJEEP

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Rapid economic growth, increasing population, industrialization and high living standards have increased the electricity demand more than ever before. Efficient energy planning and management is always considered as the greatest challenge in all over the world. Among the other factors availability of electricity is the main bottleneck to the economic growth and industrial revolution. Considering this fact, it becomes necessary for academicians, government agencies and electricity companies to construct more efficient methodologies and procedures to predict long-term electricity demand. The objective of this article represents the initiative towards understanding and analyzing the importance of demand-side management (DSM) in forecasting electricity demand by using a system dynamics approach. This study examines the long term impact of demand-side management variables including HER (Home energy report), MEPS (Minimum Energy Performance Standards) and NEEAP (National Energy Efficiency Action Plan). The future installation capacity of Malaysia's power generation is evaluated considering the factors of population, per capita electricity consumption, efficiency, capacity margin and DSM. The forecasting horizon of the simulation model is 15 years from 2016 to 2030.

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“…Moreover, this type of index may be used to detect abnormal behaviors at selected time scales [25]. These indexes may be developed not only for health care facilities, but also for educational, office and residential buildings [26,27].…”

Section: Building Sustainability Energy Indexes and Annual Electricmentioning

confidence: 99%

Electrical Consumption Profile Clusterization: Spanish Castilla y León Regional Health Services Building Stock as a Case Study

et al. 2018

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Health Services building stock is usually the top energy consumer in the Administrative sector, by a considerable margin. Therefore, energy consumption supervision, prediction, and improvement should be carried out for this group in a preferential manner. Most prior studies in this field have characterized the energy consumption of buildings based on complex simulations, which tend to be limited by modelisation restrictions and assumptions. In this paper, an improved method for the clusterization of buildings based on their electrical energy consumption is proposed and, then, reference profiles are determined by examining the variation of energy consumption over the typical yearly consumption period. The temporary variation has been analyzed by evaluating the temporary evolution of the area consumption index through data mining and statistical clusterization techniques. The proposed methodology has been applied to building stock of the Health Services in the Castilla y León region in Spain, based on three years of historical monthly electrical energy consumption data for over 250 buildings. This building stock consists of hospitals, health centers (with and without emergency services) and a miscellaneous set of administrative and residential buildings. Results reveal five distinct electrical consumption profiles that have been associated with five reference buildings, permitting significant improvement in the demand estimation as compared to merely using the classical energy consumption indicators.

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Building Energy Index: A Case Study of Three Government Office Buildings in Malaysia

Cited by 22 publications

References 0 publications

Energy Management Strategy in Campus Towards a Green Campus Through Promoting Carbon Footprint and Energy Efficiency Index Improving

Energy Management Strategy in Campus Towards a Green Campus Through Promoting Carbon Footprint and Energy Efficiency Index Improving

Forecasting Impact of Demand Side Management on Malaysia’s Power Generation Using System Dynamic Approach

Electrical Consumption Profile Clusterization: Spanish Castilla y León Regional Health Services Building Stock as a Case Study

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