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

Author

Listed:
  • Muhammad Mutasim Billah Tufail

    (Department of Management Sciences, Bahria University, Karachi Campus, Pakistan,)

  • Mohd Nasrun Mohd Nawi

    (Disaster Management Institute, School of Technology Management and Logistics, Universiti Utara Malaysia, Malaysia,)

  • Akhtiar Ali

    (Wuhan University of Technology, China,)

  • Faizal Baharum

    (School of Housing, Building and Planning, Universiti Sains Malaysia, 11800, Penang, Malaysia,)

  • Mohamad Zamhari Tahir

    (Faculty of Business and Management, DRBHICOM University of Automotive Malaysia, 26607, Pekan, Pahang, Malaysia)

  • Anas Abdelsatar Mohammad Salameh

    (Department of Management Information Systems College of Business Administration, Prince Sattam bin Abdulaziz University, 165 Al-Kharj 11942, Saudi Arabia.)

Abstract
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.

Suggested Citation

  • Muhammad Mutasim Billah Tufail & Mohd Nasrun Mohd Nawi & Akhtiar Ali & Faizal Baharum & Mohamad Zamhari Tahir & Anas Abdelsatar Mohammad Salameh, 2021. "Forecasting Impact of Demand Side Management on Malaysia s Power Generation using System Dynamic Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 11(4), pages 412-418.
    • Handle: RePEc:eco:journ2:2021-04-47
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    References listed on IDEAS

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    Cited by:

    1. Wulfran Fendzi Mbasso & Reagan Jean Jacques Molu & Serge Raoul Dzonde Naoussi & Saatong Kenfack, 2022. "Demand-Supply Forecasting based on Deep Learning for Electricity Balance in Cameroon," International Journal of Energy Economics and Policy, Econjournals, vol. 12(4), pages 99-103, July.

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    More about this item

    Keywords

    Energy forecasting; System Dynamics; Energy efficiency; Energy Demand Side Management;
    All these keywords.

    JEL classification:

    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • Q21 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Demand and Supply; Prices

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