Enterprise Management and Systems Engineering for a Mobile Power Grid

• Published in: 2017 25th International Conference on Systems Engineering (ICSEng) pp. 99 - 105
• Main Authors: Thorisson, Heimir, Almutairi, Ayedh, Wheeler, John P., Slutzky, David L., Lambert, James H.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.08.2017
• Subjects: advanced chargers; Analytical models; Batteries; Commercialization; emerging technologies; resilience; Risk analysis; Robustness; Scenario-based preferences; simulation
• DOI: 10.1109/ICSEng.2017.38

Coordinated mobility of people, goods, and energy is a foremost concern of infrastructure development. For example, deployment of advanced chargers and the associated communications networks will enable electric-vehicle fleets to serve particular needs of the power grid and microgrids. Incorporating plug-in electric vehicles as agents of energy storage in the grid can provide services to ancillary markets including frequency regulation. To prioritize research and development (R&D), this paper quantifies the sensitivity of vehicle-to-grid enterprise initiatives and milestones subject to a variety of emergent and future conditions, and demonstrates how the results of the analysis can be used for further investigation of initiatives. These conditions involve technology innovation (fast bi-directional chargers and related information technologies), environment, market prices, regulations, organizations, behaviors, workforce, etc. The results identify combinations of conditions for which research and development (R&D) are most beneficial. The approach includes scenario-based preferences to inform decision makers which initiatives are robust to variety of emergent and future conditions, thus supporting resilience of plans for electric vehicle fleets in logistics systems. An R&D initiative of particular concern is regional resource planning. An agent-based simulation is performed to forecast the availabilities of the vehicles at hour-long intervals, including route locations, and the state of charge of batteries. The paper has a context in the systems engineering body of knowledge (SEBoK), particularly as methodology for risk analysis and systems engineering.