Energy storage system (ESS) possesses tremendous potential to counter both the rapid growth of intermittent renewable energy resources (RESs) and provide frequency support to the microgrid (MG). Since the deployment of ESS has overcome the imbalance between generation and consumption, however, their massive cost, as well as degradation tendency, are the restricting considerations that demand alternative solutions to provide stable microgrid operation. To assist ESS, the electric vehicles (EVs) are incorporated into the system. EVs have been gradually commercially viable and considerable focus has been paid to vehicle-to-grid technologies. Appropriate collaboration between ESS and EVs has good capability to manage the frequency irregularities to ensure the efficient operation of the MG. This article presents a novel combination of two control techniques i.e., model predictive control (MPC) and adaptive droop control (ADC), to tackle the frequency regulation issue in the isolated MG, by effectively controlling the ESS and EVs during the large-scale integration of RESs or huge change in load demand. Firstly, the MPC regulates the ESS according to the system frequency deviation, and secondly, the ADC manages the power of EVs according to system specifications by retaining the least possible power for potential usage of EVs. Moreover, an advanced genetic algorithm is applied to tune the MPC and ADC parameters in order to achieve optimized performance. An isolated MG is modeled and verified in MATLAB/Simulink using the above-mentioned control techniques. Further, different case studies are taken into account to validate the combination of ADC and MPC for frequency regulation of an isolated MG. Additionally, the proposed MPC controller is compared with fuzzy logic proportional-integral (FPI) controller and proportional-integral (PI) controller, the MPC provides better performance results as compared with FPI and PI controllers.

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.

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.

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.

As non-renewable energy sources become depleted, the world is transitioning toward renewable energy sources (RERs), with several significant advantages, including cost savings, large-scale availability, and minimal losses. Pakistan is in the sixth spot among the countries affected by global warming and abrupt climatic conditions. Severe floods, catastrophic rains, and wind gusts have created new challenges in the country regarding resilient and reliable power supply. Due to harsh weather conditions, the power shut down, blackouts, and prolonged fault in the transmission systems are common and cause millions of economic losses annually. The main challenge of providing a reliable power supply while satisfying the climatic conditions to use renewable energy resources has a global significance. This article aims to develop a hybrid power network (PV/Battery/Grid) for King Abdullah Campus, The University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan. The results for the proposed system are compared with the existing system while they are supplying the same power to the load. The cost of energy (COE) from the existing on-grid Hybrid system is Rs.27.32/kWh thus. It can be seen that energy cost is minimized up to Rs.-.251/kWh by the effective use of solar energy. Optimization results conclude that the on-grid hybrid (PV/Battery/Convertor/Grid) is more efficient than all other configurations. Therefore, it is concluded that the proposed hybrid power system for Grid-connected sites is most efficient, stable, cost-effective and environmentally friendly. The ultimate goal is to design an economically feasible hybrid power system and analyze the techno-socio impacts of the PV hybrid system for the campus. Data is initially collected for the desired site and then simulated via the HOMER simulation tool, which determines the net load and feasibility of the proposed system. This techno-economic analysis of the PV hybrid system will enhance the utilization of solar power in other educational or commercial facilities in the region may follow the path in the future.

The advent of renewable energy resources and distributed energy systems herald a new set of challenges of power quality, efficient distribution, and stability in the power system. Furthermore, the power electronic converters integration has been increased in interfacing alternate energy systems and industries with the transmission and distribution grids. Owing to the intermittency of renewable energy resources and the application of power electronic converters the power distribution faces peculiar challenges. The dead-time effects are among the main challenges, which leads to the distortion of third harmonics, phase angle, torque pulsation, and induction motor current, causing severe quality problems for power delivery. To tackle these problems, this paper proposes a novel dead time compensation technique for improving the power quality parameters and improving the efficiency of power converters. The proposed model is simulated in MATLAB and the parametric equations are plotted against the corresponding parametric values. Furthermore, by implementing the proposed strategy, significant improvements are attained in the torque pulsation, speed, and total harmonic distortion of the induction motor. The comparisons are drawn between with and without dead time compensation technique, the former shows significant improvements in all aspects of the power quality parameters and power converters efficiency.