Simulink is a simulation and model-based design environment for dynamic and embedded systems, which are integrated with MATLAB. Simulink was developed by a computer software company MathWorks.
It is a data flow graphical programming language tool for modelling, simulating and analysing multi-domain dynamic systems. It is basically a graphical block diagramming tool with a customisable set of block libraries.
Furthermore, it allows you to incorporate MATLAB algorithms into models as well as export the simulation results into MATLAB for further analysis.
Electricity is a secondary form of energy. It is produced from different sources of energy. Energy can be renewable or non-renewable. Renewable energy can be renewed or re-generated easily but the non-renewable resources are limited on the earth. They can’t be generated again. Therefore, renewable energy is much better than non-renewable energy.
Sources of Renewable Energy
There are five major sources responsible for generating renewable energy. They are:
Solar energy: Sun is the major source of renewable energy that is termed as solar energy. The light and heat of the sun are used to produce energy. Solar cookers, solar panels, or solar cells are used to utilize solar energy. Scientists are also preparing to launch solar-powered cars.
Wind energy: Wind is also used to produce energy. Windmills run using turbines and generators are constructed to generate wind energy. Wind energy is a good contributor to global energy demand.
Biomass energy: Wastes from plants and animals are used to produce energy, which we call biomass energy. Biomass is an eco-friendly method of energy production. Different methods are used to produce biomass energy from biofuels.
Geothermal energy: Geothermal energy is produced from the heat below the earth’s surface. This energy can be used to produce electricity, heat buildings, bathing, etc.
Hydropower energy: The force of water is used to produce energy and is referred to as hydropower energy. Hydropower is more reliable than other renewable sources. The construction of reservoirs, canals, dams, etc helps to control the flow of water which is later, used to run turbines to produce electricity.
An power system is a network of electrical components deployed to supply, transfer, and use electric power. An example of a power system is the electrical grid that provides power to homes and industries within an extended area. The electrical grid can be broadly divided into the generators that supply the power, the transmission system that carries the power from the generating centers to the load centers, and the distribution system that feeds the power to nearby homes and industries.
Smaller power systems are also present in industries, hospitals, commercial buildings, and households. A single line diagram serves to illustrate this full system. The majority of these systems rely upon three-phase AC power—the standard for large-scale power transmission and distribution across the modern globe. Specialized power systems that do not always rely upon three-phase AC power are found in aeroplanes, electric rail systems, ocean liners, submarines, and vehicles.
In contrast to electronic systems concerned with the transmission and processing of signals and data, substantial amounts of electrical energy are processed in power electronics. An AC/DC converter (rectifier) is the most typical power electronics device found in many consumer electronic devices, e.g. television sets, personal computers, battery chargers, etc. The power range is typically from tens of watts to several hundred watts. In industry, a common application is the variable speed drive (VSD) that is used to control an induction motor. The power range of VSDs starts from a few hundred watts and ends at tens of megawatts.
The power conversion systems can be classified according to the type of the input and output power:
The Supercapacitor has two terminals positive and negative> The positive must be connected to the positive battery and car distribution block and the negative the negative battery. So it will load energy. It is best to charge it on battery instead in a power supply desired voltage as well not spend the battery. If polarized the wrong capacitor also burst the electrolytic capacitor.
The main objective of developing Two Level Cascaded Inverter with Elimination of Low Frequency Harmonics Using Micro Controller is to provide best electrical and electronics project on P89V51RD2 80C51 microcontroller. Chips and micro controllers have been placed in circuit and the out can be displayed on CRO.
Today’s crisis in the field of energy supply, environmental control, population increase, poverty and shortage of food and materials are closely interrelated. Now we see that a 5 % yearly growth in the usage of energy not only refers to fuel depletion, but is also a main cause for increase in pollution level and related disasters. Too many ambitious single-purpose plans are established with little or no regard to the interrelated short and long-term social-economic and environmental repercussions, which has generated alarm about the growing worldwide environmental challenges.
Power Converters Motor drive systems based on diode-rectifier are utilised in many industrial and commercial applications due to their cost-effectiveness and simple topology. However, these diode rectifier-based systems can be affected by power quality and harmonics in distribution networks. Thus, this paper investigates the impact of grid voltage harmonics on the operation of power converters with three-phase diode rectifier using mathematical formulation of the drive voltage and current harmonics based on grid voltage harmonics. Simulation analysis and practical tests have been then carried out to validate the mathematical equations and the impact of grid voltage harmonics on the power converter harmonics.
The results illustrate that even a small amount of grid voltage harmonics (around 4%) could significantly impact the input current harmonic contents of the three-phase diode rectifier. It is also shown that the phase-angle of grid voltage harmonics plays a crucial role to improve or deteriorate the input current harmonics of the power converters. In the next step, the optimum condition of grid voltage harmonics to minimise the input current harmonics has been evaluated and verified based on different grid codes. Finally, a harmonic mitigation technique in multi-drive systems using Electronic Inductor is proposed to mitigate the current harmonics at the PCC.
Total harmonic distortion
Figure 1. Simulink Model For The Tested Asd Under The Presence Of Voltage Harmonics At The Pcc.
EXPECTED SIMULATION RESULTS:
Figure 2. Simulation Results Of The Three-Phase Input Currents And Vrec In Case: (A) 1, (B) 2, And (C) 3.
Figure 3. Practical Measurements Of The Three-Phase Input Currents And Vrec In Cases: (A) 1, (B) 2, And (C) 3.
Figure 4. Simulation Results Of The Three-Phase Input Currents And Vrec In Cases: (A) Ieee-Min, (B) Ieee-Max.
Figure 5. Practical Measurements Of The Three-Phase Input Currents And Vrec In Cases: (A) Ieee-Min, (B) Ieee-Max.
Figure 6. Simulation Results For Phase “A” Current When U1 Mitigates Harmonics Generated By U2: (A) Case 3, (B) Ieee-Max Case.
Figure 7. Simulation Results For Output Voltage (Vo), Inductor Current, And Phase “A” Inverter Side Current Of U1.
In this paper, the impact of grid voltage distortion on power converter current harmonics emission has been investigated. For that aim, ASDs with conventional diode rectifier has been considered to represent the power electronic system. A mathematical formulation of the rectified voltage, inductor current, and input currents of a three-phase diode rectifier is derived under the presence of voltage harmonics at the PCC. Different cases of voltage harmonics are then considered in the analysis to investigate the behaviour of the rectified voltage and the input current harmonics. The results show that the presence of even a small level of voltage harmonics (4%) at the PCC can change the current THDi by up to 30%. Furthermore, it has been shown that the phase-angle of the voltage harmonics can have a significant impact on the input current harmonics.
Depending on the voltage harmonic phase-angle, the same amount of voltage harmonics could improve or deteriorate the rectified voltage ripple and the input current THDi. Moreover, the voltage harmonic phase-angle could create a phase delay (1) in the diodes conduction time. A positive 1 impacts the displacement power factor negatively, whereas a negative 1 improves that factor. Finally, a harmonic mitigation technique to compensate the high level of current harmonics using Electronic Inductor (EI) is presented.
 B. K. Bose, “Power electronics and motor drives recent progress and perspective,” IEEE Trans. Ind. Electron., vol. 56, no. 2, pp. 581_588, Feb. 2009.
 B. K. Bose, “Energy, environment, and advances in power electronics,” IEEE Trans. Power Electron., vol. 15, no. 4, pp. 688_701, Jul. 2000.
 W. Gray and F. Haydock, “Industrial power quality considerations when installing adjustable speed drive systems,” in Proc. IEEE Cement Ind. Tech. Conf. XXXVII Conf. Rec., San Juan, PR, USA, Jun. 1995, pp. 17_33.
 P. Waide and C. U. Brunner, “Energy-ef_ciency policy opportunities for electric motor-driven systems,” Int. Energy Agency, Paris, France, Work. Paper, 2011, pp. 1_128.
 B. Singh, B. N. Singh, A. Chandra, K. Al-Haddad, A. Pandey, and D. P. Kothari, “A review of three-phase improved power quality AC-DC converters,” IEEE Trans. Ind. Electron., vol. 51, no. 3, pp. 641_660, Jun. 2004.
Wind/PV/Battery Global environmental changes, nuclear power risks, losses in the electricity grid, and rising energy costs are increasing the desire to rely on more renewable energy for electricity generation. Recently, most people prefer to live and work in smart places like smart cities and smart universities which integrating smart grid systems. The large part of these smart grid systems is based on hybrid energy sources which make the energy management a challenging task. Thus, the design of an intelligent energy management controller is required. The present paper proposes an intelligent energy management controller based on combined fuzzy logic and fractional-orderproportional-integral-derivative (FO-PID) controller methods for a smart DC-microgrid.
Wind/PV/Battery The hybrid energy sources integrated into the DC-microgrid are constituted by a battery bank, wind energy, and photovoltaic (PV) energy source. The source-side converters (SSCs) are controller by the new intelligent fractional order PID strategy to extract the maximum power from the renewable energy sources (wind and PV) and improve the power quality supplied to the DC-microgrid. To make the microgrid as cost-effective, the (wind and PV) energy sources are prioritized. The proposed controller ensures smooth output power and service continuity. Simulation results of the proposed control schema under Matlab/Simulink are presented and compared with the super twisting fractional-order controller.
Energy management control
Fuzzy logic control
Fractional order control
Figure 1. Studied Hybrid System Structure.
EXPECTED SIMULATION RESULTS:
Figure 2. Wind Speed.
Figure 3. Wind Power.
Figure 4. Solar Power.
Figure 5. Sscs Power.
Figure 6. Bss Power.
Figure 7. The Battery Soc.
Figure 8. Dc-Link Voltage.
Figure 9. Load Power.
Figure 10. Load Voltage.
Figure 11. Random Wind Speed.
In this paper, a novel intelligent fractional order PID controller is proposed for the Energy management of hybrid energy sources contacted to a smart grid through a DC-link voltage. The hybrid energy sources integrated to the DC-microgrid are constituted by a battery bank, wind energy, and photovoltaic (PV) energy source. The source side converters (SCCs) are controller by the new intelligent fractional order PID strategy to extract the maximum power from the renewable energy sources (wind and PV) and improve the power quality supplied to the DC-microgrid. To make the microgrid as cost-effective, the (Wind and PV) energy sources are prioritized. The proposed controller ensures smooth output power and service continuity.
Simulation results of the proposed control schema under Matlab/Simulink are presented and compared with the other nonlinear controls. Extensive comparative analysis with super twisting fractional order control, FO-PID and PID is demonstrated in Table 3, where it can be seen that the proposed strategy generates more power and show high performance over the proposed control strategies. From the present comparative analysis, the proposed controller producesC3.15% wind power,C50% PV power,C2.5% load power over the super twisting fractional-order and more when compared to the PID control. Future works will be focused on the experimental validation of the proposed control with a real test bench.
 H. T. Dinh, J. Yun, D. M. Kim, K. Lee, and D. Kim, “A home energy management system with renewable energy and energy storage utilizing main grid and electricity selling,” IEEE Access, vol. 8, pp. 49436_49450, 2020.
 C. Byers and A. Botterud, “Additional capacity value from synergy of variable renewable energy and energy storage,” IEEE Trans. Sustain. Energy, vol. 11, no. 2, pp. 1106_1109, Apr. 2020.
 M. Rizwan, L. Hong, W. Muhammad, S. W. Azeem, and Y. Li, “Hybrid Harris Hawks optimizer for integration of renewable energy sources considering stochastic behavior of energy sources,” Int. Trans. Elect. Energy Syst., vol. 31, no. 2, 2021, Art. no. e12694, doi: 10.1002/2050- 7038.12694.
 Y. Sun, Z. Zhao, M. Yang, D. Jia,W. Pei, and B. Xu, “Overview of energy storage in renewable energy power _uctuation mitigation,” CSEE J. Power Energy Syst., vol. 6, no. 1, pp. 160_173, 2020.
 T. Salameh, M. A. Abdelkareem, A. G. Olabi, E. T. Sayed, M. Al-Chaderchi, and H. Rezk, “Integrated standalone hybrid solar PV, fuel cell and diesel generator power system for battery or supercapacitor storage systems in khorfakkan, united arab emirates,” Int. J. Hydrogen Energy, vol. 46, no. 8, pp. 6014_6027, Jan. 2021.
This paper focuses on designing a disturbance observer-based control (DOBC) system for PMSM drives. The cascade structure of the discrete-time PI-PI control system with tracking anti-windup scheme has been designed for both loops. In this study, high order disturbance observer (HODO) based control is used to improve the speed tracking performance of the control system for the PMSM prototyping kit regardless of the disturbance and unmodelled dynamics. The motion equation was modified in the HODO in which torque losses due to the drug resulting from the time-varying flux, hysteresis, and friction have been taken into account to estimate the total disturbance. The HODO does not require the derivatives of the disturbance to be zero, like in the traditional ones.
It demonstrates its ability to estimate along with a load torque the high order disturbances caused by a cogging torque and a high-frequency electromagnetic noise in the PMSM system. In the real-time experiments, the proposed algorithm with HODO achieves less speed errors and faster response comparing with the baseline controller. The performances with proposed and baseline control have been evaluated under mechanical speed and load torque variation cases. The experimental results have proved the feasibility of the proposed control scheme. The proposed disturbance observer-based control system was implemented with a Lucas-Nuelle 300 W PMSM prototyping kit.
Disturbance observer based control
High-order disturbance observer
Load torque observer
Figure 1. Proposed Dobc Based Control Method Structure.
EXPECTED SIMULATION RESULTS:
Figure 2. Experimental Results Of The Proposed Hodo Based Pi With Novel Anti-Windup Scheme For Case 1. (A) Mechanical Speed Response Of Pmsm; (B) Mechanical Speed Error; (C) Estimated Load Torque Disturbance.
Figure 3. Dq-Axis Currents Of The Proposed Hodo Based Pi With Novel Anti-Windup Scheme For Case 1. (A)Ids And Its Desired Value Idsd; (B) Iqs And Its Desired Value Iqsd
Figure 4. Dq-Axis Voltages Under Proposed Hodo Based Pi With Novel Anti-Windup Scheme For Case 1. (A) Control Input On Q-Axis Vqs; (B) Control Input On D-Axis Vds.
Figure 5. Experimental Results Of The Proposed Hodo Based Pi With Novel Anti-Windup Scheme For Case 2. (A) Mechanical Speed Response Of Pmsm; (B) Mechanical Speed Error; (C) Estimated Load Torque Disturbance.
Figure 6. Dq-Axis Currents Of The Proposed Hodo Based Pi With Novel Anti-Windup Scheme For Case 2. (A) Ids And Its Desired Value Idsd; (B) Iqs And Its Desired Value Iqsd.
Figure 7. Dq-Axis Voltages Under The Proposed Hodo Based Pi With Novel Anti-Windup Scheme For Case 2. (A) Control Input On Q-Axis Vqs; (B) Control Input On D-Axis Vds.
Figure 8. Experimental Results Of The Baseline Control For Case 1. (A) Mechanical Speed Response Of Pmsm; (B) Mechanical Speed Error.
Figure 9. Dq-Axis Currents Of Baseline Control For Case 1. (A) Ids And Its Desired Value Idsd; (B) Iqs And Its Desired Value Iqsd.
Figure 10. Dq-Axis Voltages Of The Baseline Control For Case 1. (A) Control Input On Q-Axis Vqs; (B) Control Input On D-Axis Vds.
Figure 11. Experimental Results Of The Baseline Control For Case 2. (A) Mechanical Speed Response Of Pmsm; (B) Mechanical Speed Error.
In this paper, disturbance observer based control for the PMSM prototyping kit is proposed. The cascade structure of discrete-time PI-PI control system equipped with tracking anti-windup scheme has been utilized for both loops. As the total disturbance estimation with HODO is based on the accurate prediction of the mechanical speed, the detailed motion equation of the PMSM has been derived. The motion equation in the proposed HODO includes terms associated with torque losses due to drag resulting from time-varying flux, friction, and hysteresis.
It has demonstrated its ability to improve the speed tracking performance under the external disturbance and unmodelled dynamics associated with a cogging torque and a high-frequency electromagnetic noise in the PMSM system. The estimated total disturbance is compensated in the speed controller. A zero steady-state errors have been achieved in the real time experiment. The mechanical speed errors were minimized in both operation scenarios. The performances of the proposed and baseline control algorithms have been evaluated under mechanical speed and load torque variations. The performance of the novel control system has shown better robustness to the external disturbances.
 T. D. Do, H. H. Choi, and J.-W. Jung, “Nonlinear optimal DTC design and stability analysis for interior permanent magnet synchronous motor drives,” IEEE/ASME Trans. Mechatronics, vol. 20, no. 6, pp. 2716_2725, Dec. 2015.
 T. D. Do, Y. N. Do, and P. D. Dai, “A robust suboptimal control system design of chaotic PMSMs,” Electr. Eng., vol. 100, no. 3, pp. 1455_1466, Sep. 2018.
 B. Sarsembayev, K. Suleimenov, B. Mirzagalikova, and T. D. Do, “SDRE- based integral sliding mode control for wind energy conversion systems,” IEEE Access, vol. 8, pp. 51100_51113, 2020.
 T. D. Do, “Optimal control design for chaos suppression of PM synchronous motors,” in Proc. 2nd Int. Conf. Control Sci. Syst. Eng. (ICCSSE), Jul. 2016, pp. 88_92.
 J.-W. Jung, V. Q. Leu, T. D. Do, E.-K. Kim, and H. H. Choi, “Adaptive PID speed control design for permanent magnet synchronous motor drives,” IEEE Trans. Power Electron., vol. 30, no. 2, pp. 900_908, Feb. 2015.