Optimal real-time distributed V2G and G2V management of electric vehicles

Abstract

This paper exploits the analogy between the electrical grid and modern communication networks to implement Electric Vehicle (EV) battery charging scheduling algorithms inspired by popular communication network techniques. In preliminary works, a similar approach was used to manage the Grid-to-Vehicle (G2V) active power flows. In this paper, we extend this framework to both implement the Vehicle-to-Grid (V2G) concept and to provide reactive power compensation capabilities that do not affect charging times. The ability of the proposed algorithms to optimally share the available/desired power in a fair way, with minimum communication requirements, in a very uncertain, dynamically changing framework, is illustrated through several examples for different scenarios of interest.

Plug-and-Play Distributed Algorithms for Optimized Power Generation in a Microgrid

“…The work can be extended in a number of directions: reference [39] shows in a different context, how AIMD algorithms can be modified to further include reactive power management; reference [43] shows how thermal energy requirements can be further included in the microgrid operation; also, it would be interested to check how the presence of several DERs connected to the same line feeder will affect the performance of the proposed method. Accordingly, current work of the authors is continuing along these lines, and will consider a more realistic scenario to further validate the proposed power generation strategies.…”

“…In practice, this corresponds to assuming that the reactive power is provided by some ancillary services in the power network (e.g., capacitance tanks, reactive Vehicle-to-Grid (V2G) and Grid-to-Vehicle (G2V) services), or bought from the external grid. Note that the AIMD algorithm could be further extended through a double prioritized algorithm to accomplish reactive power management, as shown in the recent [39] in the context of EV charging, and is not shown here due to page limits.…”

Smart grid lab research in Europe and beyond

“…At the the Smart Grid Lab facility of the University of Pisa, Italy, various fields related to smart grids are studied in cooperation with national and international research centers. Among the fields of interest are innovative distributed techniques and algorithms for the analysis and optimal management of large‐scale complex networks, with particular reference to the modeling of energy networks; optimal management of power flows in microgrids/virtual power plants; the development of forecasting and clustering algorithms to support the integration of electricity production from renewable sources; and the development of functionalities to support the development of hybrid/electric vehicles (algorithms for the management of distributed recharging and routing techniques for saving energy consumption) …”

Residential electrical vehicle charging strategies: the good, the bad and the ugly

“…However, this method has a large communication overhead arising from the need for transacting signals between the EVs and a central authority. More sophisticated algorithms are also possible using the AIMD based approach; for instance [52] develop a V2G implementation that provides reactive power compensation capabilities to the grid.…”