Socio-technical smart grid optimization via decentralized charge control of electric vehicles

摘要

Electrical vehicles (EVs) play a key role in the sustainability of theenvironment as they contribute to the reduction of carbon emissions and theharness of natural resources. However, when the Smart Grid powers the chargingof EVs, high energy costs and power peaks challenge system reliability withrisks of blackouts. This is especially the case when the Smart Grid has tomoderate additional uncertainties such as the penetration of renewable energyresources or energy market dynamics. In addition, social dynamics such as theparticipation in demand-response programs, discomfort experienced fromalternative suggested usage of the EVs and even the fairness in thedemand-response among the participating citizens perplex even further theoperation and regulation of the Smart Grid. This paper introduces a fullydecentralized mechanism for charging control of EVs that regulates three SmartGrid socio-technical aspects: (i) robustness, (ii) discomfort and (iii)fairness. By exclusively using local knowledge, a software agent generatesenergy demand plans in each EV that encode different charging patterns. Agentsinteract to make collective decisions of which plan to execute so that powerpeaks and energy cost are reduced. The impact of improving robustness ondiscomfort and fairness is empirically shown using real-world data under avaried level of EV participation. The findings are used to project the effectof optimization in a future forecasting scenario with mass adoption of EVscharged from the Smart Grid.