This article presents an overview of the agent-based modeling and simulation approach and its recent developments in transport fields, with the purpose of discovering the advantages and gaps and encouraging more valuable investigations and applications of agent-based models. We clarify the agent-based model from agents, the background of development, and the basic structure applied in transport systems. Then, the agent-based transport modeling toolkits are discussed. The applications of agent-based models in transport systems are reviewed in three time scale models followed by an additional discussion of hybrid modeling approaches. The extensive modeling of the beliefs, desires, learning, and adaptability of individuals and the optimization problems using agent-based models are explored. Besides, we point out some limitations in terms of calibration and validation procedure, agents’ behavior modeling, and computing efficiency. In conclusion, some recommendations are given and suggest potential and insightful directions such as Big Data and Digital Twin for future research.

No abstract

This paper presents a new formulation to model a real-time energy balancing market with the local/system reliability requirements. The proposed methodology enables an Independent System Operator (ISO) to perform real-time balancing by issuing both market instructions and Out-of-Market instructions to ensure the system reliability in an integrated optimization based framework. The discussion in this paper is in compliance with California ISO's market rules and procedures and the concepts are applicable to other realtime electricity markets.

No abstract