Multi-Agent based Model for Studying Electric Grid Transition to Distributed Energy Resources
Abstract
The increasing adoption of small-scale technologies for generating power represents a transition from centralized electricity systems to distributed energy resources (DER). This paper develops a multi agent-based model (ABM) to study the dynamic behaviors that influence DER investment decisions. The proposed model accounts for both local utilities (and load serving entities "LSE") and power generating plants. DER is introduced into the model by allowing LSE customers to invest in a particular photovoltaic systems. Consequently, the model forecasts electricity market outcomes and PV system adoption. Using an illustrative hypothetical case study, results show that customer demand in most LPCs cut in half, annual capacity factors at coal-fired power plants reduced by more than 60 percent, and sharp decreases in locational marginal prices. Ultimately, this research will result in a decision-support tool that will identify least cost strategies that utility companies can use to respond to increasing penetration of DER.
Recommended Citation
I. H. El-adaway et al., "Multi-Agent based Model for Studying Electric Grid Transition to Distributed Energy Resources," Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019, pp. 538 - 545, American Society of Civil Engineers (ASCE), Jun 2019.
The definitive version is available at https://doi.org/10.1061/9780784482421.068
Meeting Name
ASCE International Conference on Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience, i3CE 2019 (2019: Jun. 17-19, Atlanta, GA)
Department(s)
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Agent-based modeling; distributed energy; electric grid; infrastructure systems
International Standard Book Number (ISBN)
978-078448242-1
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2019 American Society of Civil Engineers (ASCE), All rights reserved.
Publication Date
01 Jun 2019