Aggregate demand models for electric vehicles in a smart electricity grid

In the future, EVs (electric vehicles) will constitute a non-neglectable percentage of the daily electrical load. Because EVs are idle during a large part of the day, they offer a lot of charging exibility for controlled charging. Large-scale controlled charging is particular challenging; millions of EVs may need to be managed, which requires scalable models and fast scheduling algorithms. To address this challenge, we are designing aggregate demand models. An aggregate demand model is able to represent any number of EVs with a fixed amount of data. The main advantage of an aggregate demand model is the usage of algorithms with a short calculation time, independent of the number of EVs. In evaluation, our aggregate demand models are compared with benchmark solutions. In these benchmark solutions, all available data of EVs is gathered, and exact charging plans for each EV are calculated. Evaluation experiments show that solutions based on our aggregate demand models perform comparable to the benchmark solutions, while improving computational scalability.

Publication year:2013

Accessibility:Open