Electric vehicles (EVs) have been receiving greater attention as a tool for frequency control due to their fast regulation capability. The proliferation of EVs for primary frequency regulation is hampered by the need to simultaneously maintain industrial microgrids dispatch and EV state of charge levels. The current research aims to examine the operative and dominating role of the charging station operator, along with a vehicle to grid strategy; where, indeterminate tasks are executed in the microgrid without the EVs charging/discharging statistics. The role of the charging station operator in regulation is the assignment of the job inside the primary frequency control capacity of electric vehicles. Real-time rectification of programmed vehicle to grid (V2G) power ensures electric vehicles’ state of charge at the desired levels. The proposed V2G strategy for primary frequency control is validated through the application of a two-area interconnected industrial micro-grid and another microgrids with renewable resources. Regulation specifications are communicated to electric vehicles and charging station operators through an electric vehicle aggregator in the proposed strategy. At the charging station operator, V2G power at the present time is utilized for frequency regulation capacity calculation. Subsequently, the V2G power is dispatched in light of the charging demand and the frequency regulation. Furthermore, V2G control strategies for distribution of regulation requirement to individual EVs are also developed. In summary, the article presents a novel primary frequency control through V2G strategy in an industrial microgrid, involving effective coordination of the charging station operator, EV aggregator, and EV operator.

The number of electric vehicles and renewable energy resources integrated into the power system is increasing day by day. The objective behind the development of electric vehicles and renewable energy sources is to build a sustainable and green power system. The renewables either don't possess system inertia or have less system inertia, therefore, they don't effectively respond to the load variations. The battery storage system of electric vehicles is used as the first line of defense to counter the effect of load/frequency variations and make the system stable. As active power is inversely proportional to the system frequency, for this purpose electric vehicles are included in the microgrid environment. In this paper, an isolated microgrid having a reheat turbine system, wind turbine system, photovoltaic system, and electric vehicles is studied. The output of the renewables is not controlled to utilize its maximum output power. Therefore, adaptive droop control and fuzzy PI control mechanisms are implemented to cater to the frequency variations of the isolated microgrid; the former regulates the power of electric vehicles while maintaining the energy needs of each EV and the later controls the output power of reheat turbine system according to the frequency variation. Furthermore, the genetic algorithm optimization toolbox is utilized to optimize the parameters of the adaptive and fuzzy PI controllers. The proposed model is developed in MATLAB/Simulink which shows that these control techniques effectively sustained the system frequency of isolated microgrid in the desired limits. INDEX TERMS Adaptive droop control, electric vehicles, frequency regulation, fuzzy PI control, GA optimization technique, renewable energy sources, reheat turbine system.

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After nearly a century with internal combustion engines dominating the transportation sector, it now appears that electric vehicles (EVs) are on the brink of enjoying rapid development due to numerous useful features they possess, such as less operational cost and reduced carbon emissions. EVs can act as load as well as source, by utilizing the technique known as Vehicle-to-Grid (or Grid-to-Vehicle technique if EVs are used as a load). This technique adds key features to an industrial microgrid in the form of primary frequency control and congestion management. In this paper, two controllers (grid regulation and charger controller) are proposed by considering different charging profiles, state of charge of electric vehicle batteries, and a varying number of electric vehicles in an electric vehicle fleet. These controllers provide bidirectional power flow, which can provide primary frequency control during different contingencies that an industrial microgrid may face during a 24-hour period. Simulation results prove that the proposed controllers provide reliable support in terms of frequency regulation to an industrial microgrid during contingencies. Furthermore, simulation results also depict that by adding more electric vehicles in the fleet during the vehicle-to-grid mode, the frequency of an industrial microgrid can be improved to even better levels. Different case studies in this article constitute an industrial microgrid with varied distributed energy resources (i.e. solar and wind farm), electric vehicles fleet, industrial and residential load along with diesel generator. These test cases are simulated and results are analyzed by using MATLAB/SIMULINK.

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