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Multi-objective techno-economic-environmental optimisation of electric vehicle for energy services

机译：能源服务电动汽车的多目标技术经济环境优化

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摘要

Electric vehicles and renewable energy sources are collectively being developed as a synergetic implementation for smart grids. In this context, smart charging of electric vehicles and vehicle-to-grid technologies are seen as a way forward to achieve economic, technical and environmental benefits. The implementation of these technologies requires the cooperation of the end-electricity user, the electric vehicle owner, the system operator and policy makers. These stakeholders pursue different and sometime conflicting objectives. In this paper, the concept of multi-objective-techno-economic-environmental optimisation is proposed for scheduling electric vehicle charging/discharging. End user energy cost, battery degradation, grid interaction and CO2 emissions in the home micro-grid context are modelled and concurrently optimised for the first time while providing frequency regulation. The results from three case studies show that the proposed method reduces the energy cost, battery degradation, CO2 emissions and grid utilisation by 88.2%, 67%, 34% and 90% respectively, when compared to uncontrolled electric vehicle charging. Furthermore, with multiple optimal solutions, in order to achieve a 41.8% improvement in grid utilisation, the system operator needs to compensate the end electricity user and the electric vehicle owner for their incurred benefit loss of 27.34% and 9.7% respectively, to stimulate participation in energy services.
机译：电动汽车和可再生能源正在集体开发，作为智能电网的协同实施。在这种情况下，电动汽车的智能充电和车辆到电网技术被视为实现经济，技术和环境效益的一种途径。这些技术的实施需要最终用电用户，电动汽车所有者，系统运营商和政策制定者的合作。这些利益相关者追求的目标有时是相互矛盾的。本文提出了多目标技术经济经济环境优化的概念来调度电动汽车的充放电。在提供频率调节的同时，首次建模并同时优化了最终用户的能源成本，电池退化，电网相互作用和家庭微电网环境中的CO2排放。来自三个案例研究的结果表明，与不受控制的电动汽车充电相比，该方法可将能源成本，电池退化，CO2排放和电网利用率分别降低88.2％，67％，34％和90％。此外，采用多种最佳解决方案，为了实现41.8％的电网利用率改善，系统运营商需要补偿最终用电用户和电动车所有者因其分别产生的27.34％和9.7％的收益损失，以刺激参与度在能源服务中。

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