In this paper we present an agent-based model of aggregated fuel cell vehicles in a car park participating in the day-ahead market through an aggregator. Price-based vehicle-to-grid (V2G) contracts between drivers and the aggregator define the conditions under which the aggregator may use the cars for V2G. Using price forecasts, the aggregator places V2G offers in the day-ahead market. Whenever prices are expected to be low, the aggregator places bids to buy electricity and operate an electrolyzer, to produce hydrogen. Drivers refill their cars using the hydrogen storage operated by the aggregator. When cars are parked and plugged-in, the aggregator can use them for V2G under the conditions defined in the contract. Under different wind penetration scenarios, the maximum profits in a population of 100 drivers resulted in a range between 15.09 to 671.95 Euro in a year.

The vehicle-to-grid (V2G) service is slowly gaining momentum in its capacity to engage as a means of distributed generation. An aggregator's role is pivotal in the need to coordinate vehicles for V2G and maintain the security of supply of its customer base. The paper focuses on comparing the performance of the energy system when an aggregator adopts different strategies in selecting the vehicles for participating in V2G under varying scenarios. A deterministic model is formulated to gauge the extent to which a vehicle can contribute to energy valley filling, in a system powered only by renewables. The difference in the selection strategy results in having an impact on the performance of the energy system. The presentation of different scenarios and their perceived benefits can help an aggregator in decision making and formalizing its strategies.

In this paper we present the results of different contract types and specifications for vehicle-To-grid supply. We developed a classification of contract types and specifications for vehicle-To-grid supply based on demand response literature. Such contracts provide rules and agreements between electric vehicle drivers and aggregators regarding the operation of the car for supplying power when parked. Applying the contract concepts to a microgrid with fuel cell electric vehicles that supply power, we compare the static volume-based contract to the control-based approach which was assumed in previous work. Using agent-based modeling and simulation we explore the effect of these two contract types on the requirements for drivers and the system performance of the microgrid. The results show that with volume-based contracts, the plug-in hour requirements and supplied V2G per car are lower on average, and that 91% of the residual load can be supplied with vehicles.

This paper presents a community microgrid with renewable generation, storage, and Fuel Cell Electric Vehicles (FCEV) that are used when renewable sources are scarce. To fairly distribute the demand for FCEV power among cars, a Vehicle-to-Grid (V2G) power scheduling mechanism is implemented using as a criterion the number of times every car has been started up for power generation. It can be concluded that with the fair scheduling mechanism the system can be self sufficient most of the months. At the end of a year, this results in a bell-shaped distribution of the number of start-ups per car and in using, on average, each FCEV about three times per week.

Fuel cell electric vehicles convert chemical energy of hydrogen into electricity to power their motor. Since cars are used for transport only during a small part of the time, energy stored in the on-board hydrogen tanks of fuel cell vehicles can be used to provide power when cars are parked. In this paper, we present a community microgrid with photovoltaic systems, wind turbines, and fuel cell electric vehicles that are used to provide vehicle-to-grid power when renewable power generation is scarce. Excess renewable power generation is used to produce hydrogen, which is stored in a refilling station. A central control system is designed to operate the system in such a way that the operational costs are minimized. To this end, a hybrid model for the system is derived, in which both the characteristics of the fuel cell vehicles and their traveling schedules are considered. The operational costs of the system are formulated considering the presence of uncertainty in the prediction of the load and renewable energy generation. A robust min-max model predictive control scheme is developed and finally, a case study illustrates the performance of the designed system.

Vehicle-to-Grid and a microgrid are emerging concepts which are expected to replace the conventional energy and transportation systems with more efficient and flexible ones. There have been research on the integration of these technologies, but a microgrid with fuel cell vehicles (FCVs) have hardly been studied at the moment in spite of the several technical advantages of FCVs as generating units. This paper therefore presents the mathematical model of a microgrid which includes FCVs, on-site hydrogen stations, solar photovoltaic systems and a wind turbine. The optimal scheduling of hydrogen production, hydrogen refueling to FCVs and electricity supply from FCVs which minimizes the power imported from the main grid is obtained by solving a mixed integer linear programming problem. The computation results of a test case indicate that the model can be used for identifying a bottleneck in the energy flow of a microgrid. The presented model can be extended by including important factors to consider for further research on the integration of microgrids and FCVs.