Entry Date:
November 20, 2013

Integrated Energy Decision Support System (IEDSS)

Principal Investigator Olivier de Weck

Co-investigators Carlo Ratti , John Williams , Anas Faris Alfaris

Saudi Arabia’s domestic oil consumption has rapidly increased in recent years, primarily for electricity production. Electricity sales are expected to reach 600 TWh by 2032 which will require large investments to meet these growing demands. Due to uncertainties regarding the future of supply and demand and lack of reliable information about the power system growth, clear and educated decisions are difficult to achieve. As a result, ad hoc decisions and inefficient planning could lead to adverse environmental and economic impacts. Additionally, energy infrastructures in KSA are not controlled by a single stakeholder but by a network of organizations which leads to complex decision making processes. Therefore, it is necessary to perform adequate studies on the intricacies of the energy system in an effort to build a decision support tool that will help decision makers visualize the impact of their supply and demand policies on economic, environmental and performance metrics.

The Integrated Energy Decision Support System (IEDSS) is designed to facilitate a collaborative decision making process between multiple stakeholders and capture the complex interactions and effects of one stakeholder’s decision on others as well as the power industry as a whole. In addition, IEDSS will help decision makers explore the possible energy mixes, through rapid prototyping of possible “what if” scenarios, of both conventional and renewable technologies in order to meet the future growing energy demands of the kingdom. IEDSS employs the concept of “serious gaming” by running simulations of real-world scenarios used for strategizing and problem solving.

The analytical and predictive capabilities of the tool are generated by representing the supply and demand dynamics of the power sector that are embedded at the heart of the software. These models are developed using an integrated resource planning (IRP) approach and are integrated through space and time using Geographic Information System (GIS) and System dynamics (SD). Equipped with a new generation of web technologies, the web client graphically visualizes geospatial and temporal big data as well as offers a platform to simulate, query, and aggregate the models.