Optimal scheduling of electric vehicle charging and vehicle-to-grid services at household level including battery degradation and price uncertainty

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Modeling of Lithium-Ion Battery Degradation for Cell Life Assessment (2018, background): “rated in optimization models [22], [52], it is widely accepted that the cycle DoD has a nonlinear impact on degradation.”
Optimal Participation of an Electric Vehicle Aggregator in Day-Ahead Energy and Reserve Markets (2016, methodology): “The value of is estimated from manufacturer datasheets [8].”
Model-Free Real-Time EV Charging Scheduling Based on Deep Reinforcement Learning (2019, background): “For instance, in order to handle the uncertainty in electricity price, Ortega-Vazquez [7] developed a robust optimization approach for residential EV charging scheduling.”
Routing and Scheduling of Mobile Power Sources for Distribution System Resilience Enhancement (2019, background): “, tr∼t′ pir), the second term is the transportation cost due to MPS travels [32], [42], and the third term is the battery lifecycle degradation cost of MESSs and EVs [25], [43].”
Enhancing Distribution System Resilience With Mobile Energy Storage and Microgrids (2019, methodology): “degradation cost is computed as explained in [26] and depends on charging (pch kbts) and discharging (p dis kbts) decision variables and technology-specific degradation slope parameter h.”