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Managing the Operation of Energy Aggregators with the Aim of Improving The Use of Electric Vehicles in Distributed Energy Systems

Fatahian Firuzabadi, Mohammad Javad | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57859 (46)
  4. University: Sharif University of Technology
  5. Department: Energy Engineering
  6. Advisor(s): Moeini Aghtaei, Moein
  7. Abstract:
  8. In recent years, electric vehicles (EVs) have emerged as an effective solution to reduce pollution caused by the use of fossil fuels in the transportation sector. While EVs contribute to improved air quality, managing their charging and discharging processes is crucial. To address this, EV aggregators act as intermediaries between EVs and the power grid, primarily responsible for controlling the charging and discharging of a fleet of EVs with the objective of maximizing their profits. On the other hand, to reduce fossil fuel consumption in electricity generation, efforts are underway to transition consumers into prosumers and equip residential complexes with distributed energy resources (DERs). Given the integration of DERs and EVs in smart grids, this study examines the decentralized control of EV charging and discharging within a residential complex. The proposed model considers the comfort of the residents and compensates EVs for battery degradation costs while incorporating distributed energy resources and all energy exchanges between them. The goal is to maximize the aggregator's profit. Moreover, uncertainties affecting the system are identified, scenarios are generated using relevant probability distributions, and scenario reduction is applied before incorporating the results into the model to evaluate their impact on the aggregator's profit. The findings reveal that investing in addressing uncertainties and obtaining precise information about the system under study benefits the aggregator. Additionally, the most influential factor affecting the aggregator's profit is the timing of EVs' arrivals and departures.
  9. Keywords:
  10. Electric Motor Vehicles ; Stochastic Programming ; Renewable Energy Resources ; Aggregator ; Battery Degradation ; Decentralized Energy Management ; Distributed Energy Resorurces (DER)

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