An agent-based energy management approach for V2X-capable charger clusters

Abstract

To deal with the intermittency problem of renewable-based distributed generation, flexible energy assets such as electrical batteries are widely considered. In line with the localization trend in the energy sector, electric mobility is becoming mainstream. The additional load demand that comes with the penetration of EVs will raise the need for additional electricity generation. In particular, aggregated charging load of electric vehicles cause overload in the distribution network. With the management of EV charging, overload can be avoided and grid reliability can be ensured. At this point, smart grid applications promise to help make the addition of electric vehicles to the grid more sustainable with concepts such as V2X (vehicle to everything). On the other hand, as the plug-in EV fleet grows, an effective energy management system is needed to avoid adverse effects such as voltage fluctuations and increased electricity losses. By combining several flexible energy assets, a bidirectional EV charger cluster can have a local balancing capacity and therefore be operated without demanding energy from the grid for a specified period of time. The aim of this thesis is to manage EV charging in clustered systems and to obtain energy neutral charger clusters by increasing the local balancing capabilities of clusters and to efficiently use V2X functions with the proposed energy management algorithm. With this thesis, it is also aimed to reduce the peak-to-average ratio and to provide a balanced and efficient load profile. To achieve the objectives, an agent-based energy management concept has been proposed. In the proposed concept, each bidirectional charging unit with a connected EV at the charging station is represented by an agent. This approach provides a decentralized structure and swarm control in line with the agents' local targets. In this algorithm all power producers and consumers are represented as agents. First, the agents calculate their operation range and current power demand or production, i.e. their flexibility. Energy consumers and producers then interact and negotiate with each other, thus providing self-consumption by meeting each power consumption with an equivalent power generation. This allows flexible power transfer between EVs with a collaborative perspective on the charging system. In this way, the peak-to-average ratio decreases and self-consumption increases. In the study, the negotiation and decision-making processes of the agencies are discussed in detail. Simulation studies performed on the proposed concept for local balancing show that this application has the potential to provide effective and sustainable solutions for energy management.