Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Systems Engineeringarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Systems Engineering
Article . 2015 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
DBLP
Article . 2015
Data sources: DBLP
versions View all 2 versions
addClaim

The Integrated Energy Decision Support System

Authors: Anas Alfaris; Abdulaziz Khiyami; Abdullah Alawad; Adnan Alsaati; Mohammed K. Hadhrawi;

The Integrated Energy Decision Support System

Abstract

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.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    10
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Top 10%
Average
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!