Authors:
Roberto Levy
;
Alexander Brodsky
and
Juan Luo
Affiliation:
George Mason University, United States
Keyword(s):
Decision Support, Decision Guidance, Optimization, HRES, Electric Power Network.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Operational Research
;
Scheduling and Planning
;
Strategic Decision Support Systems
Abstract:
This paper focuses on developing an approach and technology for actionable recommendations on the operation of electric power network components. The overall direction of this research is to model the major components of a Hybrid Renewable Energy System (HRES), including power generation, transmission/distribution, power storage, energy markets, and end customer demand. First, we propose a conceptual diagram notation for power network topology, to allow the representation of an arbitrary complex power system. Second, we develop a formal mathematical model that describes the HRES optimization framework, consisting of the different network components, their respective costs, and associated constraints. Third, we implement the HRES optimization problem solution through a mixed-integer linear programming (MILP) model by leveraging IBM Optimization Programming Language (OPL) CPLEX Studio. Lastly, we demonstrate the model through an example of a simulated network, showing the ability to su
pport sensitivity / what-if analysis, to determine the behavior of the network under different configurations.
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