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The power system is dominated by the renewable energy resources since last two decades. The main cause behind this enormous deployment of RES is to combat the global warming and to decrease dependency on fossil fuels. Wind energy is one of the abundant available sources of energy throughout the world. However, the huge deployment of wind energy in the power system cause vulnerability to the system. The main cause is the lack of system inertia in RES which cannot effectively respond during the power imbalance condition. To counter this effect, the virtual synchronous generators are deployed in the RES based power system. The VSG mimics the synchronous generator features and therefore it possesses the ability to provide the inertial support to system. In this paper, a wind base multiple VSG system is proposed to counter the frequency irregularities of the system. Furthermore, a comparison with classical droop control is done based on load variation. Moreover, the genetic algorithm is used to optimize the values of damping and inertia of the VSG. The performance of the proposed system is validated in MATLAB/Simulink 2019.

Due to the strong nonlinearities of the boiler-turbine system, feasibility and high response capability are hard to realize using traditional linear controllers. Advanced controllers that can ensure stability and feasibility without violating system constraints, and enhance the system’s dynamic output performance, are needed. Therefore, this paper proposes a stable input/output feedback linearization (IOFL) model predictive controller (MPC) technique for the boiler-turbine system. This nonlinear system is decoupled using the IOFL method into a novel linearized model, which is then used for constituting the proposed stable IOFL MPC problem. The proposed scheme uses a constraint mapping method that converts actual input limits into limits on the basis of the control output variable to ensure a feasible solution over the whole prediction horizon. Moreover, a min-max MPC technique in the form of linear matrix inequality with the realization of the input rate-of-change constraints is utilized to ensure the boiler-turbine unit’s stability. The process model and proposed control scheme are executed using MATLAB and the simulation results demonstrate that the proposed controller has an enhanced dynamic output performance compared with an advanced control scheme under various load variations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The major concern of modern power plants is changing from tracking control to environmental and economic issues. The economic model predictive control (EMPC) scheme, which incorporates the boiler-turbine unit's dynamic tracking and economic optimization into one online framework, can well enhance the dynamic economic performance. Considering the strong nonlinearity that existed in the boiler-turbine system, this paper presents an advanced EMPC scheme based on the input/output feedback linearization (IOFL) approach. The boiler-turbine dynamics are converted via the IOFL method to a linear form, which can be readily used to constitute the standard EMPC scheme. A dual-mode method is adopted in this paper to guarantee the stability of the IOFL EMPC strategy for the boiler-turbine system, in which the first-mode optimizes the economic objective function while preserving the states of the system within a feasible region, and the second-mode moves the system state to the optimum operating point using an auxiliary controller. The simulations under the MATLAB environment demonstrate that the application of the IOFL-based EMPC scheme enhances the economic and dynamic output performance under load demand changes in comparison with fuzzy hierarchical MPC and fuzzy economic MPC schemes. • A stable economic model predictive control is proposed for boiler-turbine unit. • The nonlinear model is transferred to a new linear form via feedback linearization. • Linear matrix inequalities are constructed to guarantee the system stability. • The proposed scheme enhances dynamic economic performance for boiler-turbine unit. [ABSTRACT FROM AUTHOR]

The isolation between the microstrip patches has a great significance to examine the performance of the multiple-input-multiple-output (MIMO) antennas. The patch antennas are placed on the top of 1.46 mm thick Rogers RO3003 substrate having a length of 60 mm, a width of 50 mm, and relative permittivity of 3. The distance between the resonators is 0.06λ and they are stimulated by two coaxial probes extended from the bottom ground layer. The defective ground structure of the H-shape slot is inserted on the bottom ground layer to achieve high isolation (mutual coupling reduction). The proposed MIMO antenna operates at 5.3 GHz frequency, which can be used for WiMAX, Wi-Fi, and future 5G services all over the world. The results of the designed structure have been simulated in a finite element method-based solver high-frequency structure simulator (HFSS). The simulated results show that the reflection coefficient (S11) and isolation (S21) at the desired frequency are −32 dB and −41 dB, respectively. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

With the gradual increase in the installed capacity of wind turbines, more and more attention has been paid to the economy of wind power. Economic model-predictive control (EMPC) has been developed as an effective advanced control strategy, which can improve the dynamic economy performance of the system. However, the variable-speed wind turbine (VSWT) system widely used is generally nonlinear and highly coupled nonaffine systems, containing multiple economic terms. Therefore, a nonlinear EMPC strategy considering power maximization and mechanical load minimization is proposed based on the comprehensive VSWT model, including the dynamics of the tower and the gearbox in this paper. Three groups of simulations verify the effectiveness and reliability/practicability of the proposed nonlinear EMPC strategy. [ABSTRACT FROM AUTHOR]