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The Integrated Energy Decision Support System

Author

Listed:
  • Anas Alfaris
  • Abdulaziz Khiyami
  • Abdullah Alawad
  • Adnan Alsaati
  • Mohammed Hadhrawi

Abstract

In this paper we introduce a decision support system framework termed the Integrated Energy Decision Support System (IEDSS). IEDSS was developed for energy planning at national and regional levels to inform energy planners at multiple levels of government. IEDSS employs system dynamics modeling to enable the rapid evaluation of the outcomes of different supply and demand policies at the national level. Agent‐Based models are used to mimic the interactions between different entities when applying the framework at the regional level of government. Within the IEDSS framework policy makers specify a set of policy decisions and choose from a set of uncertain futures to investigate the performance of their policy decisions. Together these form a scenario for which IEDSS computes a set of output parameters that are used to evaluate the resulting outcome. As a model‐driven DSS, IEDSS can be utilized in two ways. The first is as a single‐user DSS that deploys a scenario‐based planning approach which informs decision makers by mapping the solution space and the resultant effects caused by their policy choices. The second is as a group‐based DSS that enhances communication and collaborative decision making between multiple entities. IEDSS is developed on a software platform that utilizes the front‐end computation to handle templates, style sheets, and visualizations, while the backend is focused on data retrieval, models execution, and performance optimization. IEDSS was developed to address the power sector of the Kingdom of Saudi Arabia as a case study, but the framework and capabilities of its platform are applicable to any generalized case.

Suggested Citation

  • Anas Alfaris & Abdulaziz Khiyami & Abdullah Alawad & Adnan Alsaati & Mohammed Hadhrawi, 2015. "The Integrated Energy Decision Support System," Systems Engineering, John Wiley & Sons, vol. 18(5), pages 511-529, October.
    • Handle: RePEc:wly:syseng:v:18:y:2015:i:5:p:511-529
    DOI: 10.1002/sys.21326
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    References listed on IDEAS

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    1. Tolone, William J., 2009. "Interactive visualizations for critical infrastructure analysis," International Journal of Critical Infrastructure Protection, Elsevier, vol. 2(3), pages 124-134.
    2. Alfredo Garcia & Zhijiang Shen, 2010. "Equilibrium Capacity Expansion Under Stochastic Demand Growth," Operations Research, INFORMS, vol. 58(1), pages 30-42, February.
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