Publication | Open Access
Remuneration Sensitivity Analysis in Prosumer and Aggregator Strategies by Controlling Electric Vehicle Chargers
15
Citations
26
References
2022
Year
EngineeringIncluding Vehicle-to-gridNumerical ResultsOperations ResearchRemuneration Sensitivity AnalysisElectric VehiclesNew FormsSystems EngineeringElectricity SupplyQuantitative ManagementEnergy Demand ManagementAggregator StrategiesElectrical EngineeringEconomicsMarketingElectricity MarketSmart GridEnergy ManagementSustainable EnergyEnergy TransitionElectric Vehicle ChargersEnergy PolicyBusinessDemand ResponsePower Grid Regulation
The efficient use of energy resources is profoundly changing power grid regulation and policy. New forms of power generation coupled with storage and the presence of new, increasingly flexible loads such as electric vehicles enable the development of multi-agent planning systems based on new forms of interaction. For instance, consumers can take advantage of flexibility by interacting directly with the grid or through aggregators that bridge the gap between these end-users and traditional centralised markets. This paper aims to provide insight into the benefits for aggregators and end-users from a financial perspective by proposing a methodology that can be applied to different scenarios. End-users may provide flexibility services related to private vehicle charging stations or battery storage systems. The paper will analyse different remuneration levels for end-users by highlighting the most beneficial scenarios for aggregators and end-users and providing evidence on potential conflict of interests. The numerical results show that some consumers may benefit more from aggregation. This is because if taken individually, consumption habits do not allow the same flexibility when considering clusters of consumers with different behaviour. It is also shown that there are cases in which consumers do not seem to benefit from the presence of intermediate parties. We provide extensive numerical results to gain insight for better decision making.
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