Authors:
Chun-Kit Ngan
;
Alexander Brodsky
;
Erik Backus
and
Nathan Egge
Affiliation:
George Mason University, United States
Keyword(s):
Decision Guidance, Energy Investment, Optimization Model.
Related
Ontology
Subjects/Areas/Topics:
Applications of Expert Systems
;
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Group Decision Support Systems
;
Industrial Applications of Artificial Intelligence
;
Operational Research
;
Problem Solving
;
Scheduling and Planning
;
Strategic Decision Support Systems
Abstract:
We propose a Decision-Guided Energy Investment (DGEI) Framework to optimize power, heating, and cooling capacity. The DGEI framework is designed to support energy managers to (1) use the analytical and graphical methodology to determine the best investment option that satisfies the designed evaluation parameters, such as return on investment (ROI) and greenhouse gas (GHG) emissions; (2) develop a DGEI optimization model to solve energy investment problems that the operating expenses are minimal in each considered investment option; (3) implement the DGEI optimization model using the IBM Optimization Programming Language (OPL) with historical and projected energy demand data, i.e., electricity, heating, and cooling, to solve energy investment optimization problems; and (4) conduct an experimental case study for a university campus microgrid and utilize the DGEI optimization model and its OPL implementations, as well as the analytical and graphical methodology to make an investment dec
ision and to measure trade-offs among cost savings, investment costs, maintenance expenditures, replacement charges, operating expenses, GHG emissions, and ROI for all the considered options.
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