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Risk-based_dispatch_optimization_of_microgrids_considering_the_uncertainty_in_EV_driving_patterns.pdf (1.74 MB)

Risk-based dispatch optimization of microgrids considering the uncertainty in EV driving patterns

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conference contribution
posted on 2023-02-08, 03:45 authored by Soheil Mohseni, Alan BrentAlan Brent
The large-scale electrification of the transport sector will result in increasingly 'peaky' loads, which necessitates the system integration of additional capital-intensive storage infrastructure in renewables-rich microgrids of the future. In this context, the vehicle-to-grid (V2G) technology can provide an effective platform to unlock the so-called 'storage on wheels' potential of electric vehicles (EVs), thereby reducing the need for cost-prohibitive grid-scale storage. However, the dispatch optimization of electricity networks integrating a high share of V2G-enabled EVs is challenging given the uncertainties in forecasts of the associated timing of charging and discharging. In response, this paper introduces a novel mixed-integer linear programming-based model for the optimal operation of a grid-connected microgrid (MG) integrating solar photovoltaic and wind turbine generation systems, which are supported by a hydrogen-based energy storage system, whilst assuming a high level of EV penetration. To this end, the information gap decision theory (IGDT) is employed to evaluate the impact of risk-averse (RA) and risk-seeking (RS) strategies against the possible aggregated EV charging/discharging scenarios where limited information is available about relevant driving patterns. Importantly, the simulation results from a test-case community MG system indicate that the RA and RS strategies are associated with a representative daily MG operation profit deviation of-21% and +19% compared to the most-likely risk-neutral strategy, respectively.

History

Preferred citation

Mohseni, S. & Brent, A. C. (2022, January). Risk-based dispatch optimization of microgrids considering the uncertainty in EV driving patterns. In 2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022 2022 17th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) (00 pp. 1-6). IEEE. https://doi.org/10.1109/PMAPS53380.2022.9810595

Conference name

2022 17th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)

Conference start date

2022-06-12

Conference finish date

2022-06-15

Title of proceedings

2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022

Volume

00

Publication or Presentation Year

2022-01-01

Pagination

1-6

Publisher

IEEE

Publication status

Published

ISSN

2642-6730

eISSN

2642-6757

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