A multi-objective optimization of electric vehicles energy flows: the charging process

Sizing battery energy storage and PV system in an extreme fast charging station considering uncertainties and battery degradation

“…The normal probability distribution representing the threshold 𝑆𝑂𝐶 𝑖 𝑡ℎ𝑟 is taken from [103] and is 𝒩 3 (30,15). Moreover, to avoid deep-discharge and over-charging and to enhance battery life, the state of charge for all EVs is assumed to be constrained within the range of 10-90%, at all times [104,105]. The 𝑆𝑜𝐶 𝑖 * 𝑡𝑎𝑟𝑔𝑒𝑡 also follows a normal distribution 𝒩 4 (80,10) [106].…”

We got the power: Predicting available capacity for vehicle-to-grid services using a deep recurrent neural network

“…There are likely to be multiple objectives in deciding on the best opportunities, for example: availability of the required capacity at the required time; the predicted margin of available capacity for those not using all the fleets reserves; revenue potential of the opportunity; and the ability of the fleet to recharge and support potential demands from ancillary services or additional trades in the near-future. In this way, the trained model effectively becomes part of a fitness function for a multi-objective optimisation algorithm [34,35], a technology that also has potential for optimising the design of the model [36].…”

Active Building as an Energy System: Concept, Challenges, and Outlook

“…The transportation sector is responsible for about 22% of the GHGs globally and therefore extensive works have been done in order to evaluate EVs impact on this issue [66]. EVs are the other promising technologies on the demand-side and usually at the building and houses and act like a prosumer.…”