MPPT Control Research Articles

A Multiple Time Scales Rolling Coordinative Dispatching Method for an Island Microgrid with High Proportion Tidal Current Energy Access and Demand Response Resources

Currently, the ocean energy strategy is rapidly developing, and a high proportionate tidal current energy grid connection presents significant obstacles to the planning and secure and stable operation of an island microgrid. For an island microgrid with high proportion tidal current energy access and demand response resources, this research suggests a multiple time scales rolling coordinative dispatching method. An MPPT control based on Q-Learning algorithm is first developed for real-time maximum power tracking of tidal current energy generation after the island microgrid’s topology has been examined. Following that, a multiple time scales rolling coordinative dispatching’s fundamental architecture and implementation method are provided, with equal time intervals coordinated in a step-by-step recursive way. In the example analysis of an island microgrid, we consider the rigid demand load that does not participate in the demand side response, and the ship load and controllable load that participate in the demand side response. On sea islands, ship loads on the long timeframe achieve traffic and energy interaction, and dispatchable loads on the short timescale participate in supply and demand balancing. This is due to the multiple time scales properties of demand response resources. In addition, a multiple time scales rolling coordinative dispatching model for an island microgrid is developed. It includes day-ahead, intraday, and real-time components. Finally, example analysis is used to confirm the dispatching method’s usefulness and advancement, and we conclude that the tidal current energy consumption rate of the island microgrid is increased by 17.08%.

Research on photovoltaic MPPT control Strategy based on improved sliding mode control

MPPT intelligent control strategy algorithm is complex and practical application is difficult, So an improved sliding mode controller is proposed, which can improve engineering application, but also quickly and stably track the maximum power point of the system. In this paper, Boost circuit as the carrier, by increasing the amount of control in the controller, to build a new sliding mode control algorithm, Lyapunov stability theory analysis to demonstrate the correctness of the design algorithm, and through Simulink modeling and simulation, verify the feasibility of the control algorithm. The results show that the controller can quickly and stably track the maximum power of solar cells with small chattering and strong anti-disturbance ability regardless of the change of ambient temperature or light intensity.

Modeling and parameter estimation of solar photovoltaic based MPPT control using EKF to maximize efficiency

In this paper, we focus on the design, modeling and implementation of a MPPT controller based maximum power tracking of photovoltaic system. The electrical characteristic of The PV system is non-linear and changes with the solar irradiation and the ambient temperature. Therefore, the incremental conductance (IC) method control is known for its stability and robustness, and is used to extract the maximum energy from the PV source using a boost converter topology. It provides a strong basis for the improvement and optimization of control parameters of a photovoltaic system. Implementing MPPT algorithm usually need the use of a lot of sensors if accuracy of the system has to be increased. However, IC method with an extended Kalman filter (EKF) can be utilized in order to estimate some parameters to reduce the number of Sensors. The EKF is deployed in the optimal position to estimate both current and the capacitor voltage, thus allowing to eliminate two sensors devise from the entire PV system, which increases the system efficiency and reliability, simplifies the control method and decreases the system cost. The performance of the proposed technique is validated by experimental and simulation results under different operating conditions and load changes.

태양광 발전효율 증대를 위한 최대전력추종 시스템에서 Anti-windup 적용의 효과 분석

In this paper, application and comparative analysis of anti-windup method for improving the response of voltage control of MPPT method in photovoltaic generation system is proposed. In the case of MPPT, PI control can be mainly used to control a target voltage from a reference voltage that continuously changes according to changes in the surrounding environment for optimal control of PV power production. However, its PI controller has accumulated saturation of errors in the process of integrating the errors, so it is necessary to consider the integrator windup. This problem could affect the power production efficiency when performing MPPT control, so this paper sought to verify its effect by applying the follow-up anti-windup technique to MPPT control to improve the integral windup phenomenon. It could be confirmed from the results of the presented simulation that the application of the proposed algorithm mixed is more effective to improve the control performance of the photovoltaic system.

High Performance MPPT Controller for Solar Photovoltaic System under Variable Solar Irradiations

High Performance MPPT Controller for Solar Photovoltaic System under Variable Solar Irradiations

COMPARATIVE PERFORMANCE ANALYSIS ON ARTIFICIAL NEURAL NETWORK BASED MPPT CONTROLLER WITH CONVENTIONAL CONTROLLER FOR GRID CONNECTED WIND ENERGY CONVERSION SYSTEM

This paper focuses on the development of ANN based MPPT interfaced Permanent magnet synchronous generator (PMSG) for wind energy conversion system (WECS). It focuses on design and modeling aspects of the completely different elements of the WECS like the fundamental model of ANN based MPPT controller, MLI, wind turbine, optimum maximum power point tracking system utilizing MATLAB/Simulink. Major object is to extract the maximum energy from the wind which confirms a highest efficiency of developed system. The thesis shows the model of wind turbine together with the model of PMSG. The ANN based mostly MPPT approach used right here is predicated on Perturbation and observation (P&O). To complete the process of modeling and simulation the platform of MATLAB/Simulink is utilized. Developed ANN are most efficient technique compared to conventional methods. It achieves maximum power with more stability, precision and better performance with good dynamic response under variable wind speed conditions. It exhibits the enhancements for the developed system and control action for balance/unbalanced steady state in addition to transient, dynamic response circumstances.

Conception and Hardware Implementation of MPPT Controller for Partially Shaded Photovoltaic Panels using Backstepping and Neural Network based Particle Swarm Optimization

Conception and Hardware Implementation of MPPT Controller for Partially Shaded Photovoltaic Panels using Backstepping and Neural Network based Particle Swarm Optimization

ANFIS-based MPPT Controller Design on Boost Converter to Improve Photovoltaic System Performance

The efficiency of the photovoltaic system is very low ranging from 9-17% in areas with low irradiation while the investment costs are quite high. In addition, the power output of the photovoltaic system is highly volatile due to changes in irradiation due to weather and cloud movement, and temperature change. This research proposes the MPPT method based on ANFIS in the photovoltaic system for transient behavior analysis and system efficiency improvement. The results of the proposed method were compared with the MPPT Perthub & Observe (P&O) method. Each MPPT method was applied to a boost converter connected to a photovoltaic module with a capacity of 150 Wp to adjust the duty cycle using Simulink simulation in MATLAB. The irradiation and temperature data for 3 consecutive days were from Saturday to Monday, September 4 to 6, 2021. The simulation results show that the transient time of ANFIS MPPT is 6.23 times faster than that of P&O MPPT. The efficiency of ANFIS-based MPPT is higher than MPPT P&O. At 917.3 W/m2 of irradiation, the output power of the boost converters are 132.09, and 111.69 Watt for the ANFIS-based MPPT controller, and the P&O method MPPT, respectively.

Integration of solar power to the electric grid: A case study

As the demand of electricity is increasing with each passing day and the conventional sources of energy are depleting, it becomes mandatory to include various renewable or non- conventional sources of energy for the generation of power. Solar energy is one of the promising sources of renewable energy in the modern day. In this paper integration of the solar power to the electric grid has been discussed. MPPT controller and a boost converter are used to obtain maximum power at the output and further synchronization of Voltage Source Inverter's output with the electric grid is presented.

Solar photovoltaic Maximum Power Point Tracking controller optimization using Grey Wolf Optimizer: A performance comparison between bio-inspired and traditional algorithms

Solar photovoltaic systems are widely used; however, their performance is bound to weather conditions, depending on irradiation, temperature, and the effect of shadows. Maximum Power Point Tracking techniques have been developed to solve this issue. Standard methods use mainly-two algorithms: Perturb and Observe and Incremental Conductance. However, such algorithms perform differently when the Solar photovoltaic system works under sudden solar irradiation changes, temperature, and load changes. This research proposes an optimized Maximum Power Point Tracking controller based on the Grey Wolf Optimization algorithm using the MATLAB/Simulink software as an alternative to the traditional techniques. Global efficiency and Root Mean Square Error evaluate the controller's performance. The response time is analyzed using the Grey Wolf Optimizer algorithm, Wolf Optimizer Algorithm, Simulated Annealing, and Particle Swarm Optimization. These four metaheuristic algorithms are compared to the Perturb and Observe, and Incremental Conductance algorithms. The models are analyzed for the transient state and full-day operation scenarios for constant and variable irradiations, temperatures, and loads. The comparative results show that the Maximum Power Point Tracking controller optimized by the Grey Wolf Optimizer algorithm has superior performance, giving an average 6% output power higher than the other controllers under the test scenarios evaluated. The efficiency of the proposed model was, on average, 3% higher than the Incremental Conductance and Perturb & Observe controllers. For the MPPT controller tunning stage, the Grey Wolf Optimizer Algorithm had the best performance with an RMSE of 255.3549 with a compute time of 27.3 min; the worst performing was the Particle Swarm Optimization with an RMSE of 332.4075 and 27.8 min computation time. The proposed GWO optimized MPPT controller had the faster settling time for each irradiation level compared, with an average of 0.175 s. Also, results showed an improvement of the system response throughout the Maximum Power Point Tracking controller optimized by the Grey Wolf Optimizer algorithm since a lower curling effect is obtained at power converter outputs.

A novel robust model reference adaptive MPPT controller for Photovoltaic systems

A novel robust model reference adaptive MPPT controller for Photovoltaic systems

Design and implementation of zeta converter for LED driver applications

The objective of this study is to analyze the design and operation of low power, stand-alone active led driver applications. The system is powered by solar PV panels with a maximum input power of 125 W. The chosen converter supports continuous conduction mode. The device seems to have a switching frequency of 20 kHz. The duty cycle of a converter is controlled by the MPPT controller, which keeps the dc bus voltage constant. MPPT employs an incremental conductance method. The intention of this converter used to control the voltage at 48 V. The preferred converter is verified in both Matlab/Simulink and its performance is evaluated on hardware prototype of 25 W. While PV module efficiency is low and power output is dependent on solar irradiation and ambient temperature, maximizing power output while increasing efficiency is of key significance. The resulting system is highly efficient, low cost and able to track power faster.

A Novel Asymmetric Multilevel Inverter with Reduced Number of Switches for Grid-tied Solar PV System

Background & Objective: In single-phase solar PV applications, the module voltage level is limited; therefore, a coupled step up transformer is mandatory portion to interconnect into the grid. However, due to presence of transformer, the overall cost and size of the single-phase grid tied solar PV system is higher. Multilevel inverter is an alternative solution to solve these issues, but it requires more number of switches. Methods: In order to overcome this drawback, this particular paper proposes a novel asymmetric multilevel inverter (AMLI) with reduced number of switches for solar PV grid-tied system. The operational details of the proposed converter are explained in this paper. In addition, the MPPT control has been implemented in the proposed novel AMLI and presented in this paper. The hysteresis current control mechanism is applied to the proposed converter and corresponding control blocks are reported in this paper. Results: Finally, to validate the proposed system, the simulation results are performed and correlated with theoretical approach Furthermore, to verify the feasibility of proposed converter for solar PV grid-tied system, the experimental setup was made and experimental results have been measured and presented in this paper. Conclusion: From the measured results, it is concluded that the proposed asymmetric MLI can be most promising converter for solar PV grid connected system.

Performance evaluation of thermoelectric generator employing SEPIC converter and incremental conductance maximum power point tracking for electric vehicles

This article introduced a unique MPPT controller for thermoelectric generators. Our method uses a modified incremental conductance (IC) algorithm to track MPP efficiently. The proposed method is simple to install, fast-tracking, and stable. Traditionally, MPPT trades off steady-state and transition-state properties. Various designs flows are explored. The study’s common parameters are fast convergence, efficiency, and low oscillations. Use a proposed strategy that effectively handles these difficulties. The proposed methodology improves TEG MPPT efficiency and convergence times.

PV FED ZETA-SEPIC based Integrated Converter for Street Light System

Abstract: This paper proposes an efficient cost-effective PV fed zeta-Sepic integrated converter for street lighting system. Generally, two separate power electronics converters are used for charging and discharging of battery.in proposed system zetaSepic converter is used as a single power electronics interface for the complete operation. Fractional order incremental conductance (FO-INC) algorithm is used for MPPT control. The integrated converter has at least components compared to those existing converter which have stepping up and stepping down capability in all modes. The proposed street light system is designed and modeled such that the performance is not affected under dynamic conditions. The suitability of proposed system at practical operation condition is demonstrated through simulation result using MATLAB/Simulink followed by an experimental validation

Optimalisasi Pengisian Accu Pada Sistem Pembangkit Listrik Tenaga Surya (PLTS) Dengan Solar Charge Controller (MPPT)

The use of renewable energy is currently one of the alternative energies to support the decline in fossil energy in Indonesia. Solar energy is the right choice for now, as a solar power plant (PLTS), which is a renewable technology, which can convert solar thermal energy into electrical energy. The solar power generation system has various components, one of which is the Solar charge controller. The purpose of this research is to optimize battery charging using the MPPT Solar charge controller type. MPPT solar charge controller, has better characteristics and is able to charge the battery (accu) faster. In this study also pay attention to the effect of light intensity and temperature on the power output generated by the solar cell. The results showed that the MPPT Solar charge controller was able to work better and faster in charging the battery (accu) than other Solar charge controllers. It is proven by the results of the average voltage, current and output power of the MPPT controller of 13.79 volts, 3.06 amperes and 42.26 watts of power, for high light intensity and temperature do not always affect the results of high voltage, current and power, because environmental factors also affect the output of the solar cell.

Research and Application of MPPT Control Strategy Based on Improved Slime Mold Algorithm in Shaded Conditions

A PV maximum power tracking strategy for shaded conditions, based on an improved slime mold algorithm, is proposed in this research. To verify the superiority of the proposed algorithm, four bionomics algorithms—particle swarm optimization (PSO), tuna swarm optimization (TSO), squirrel search algorithm (SSA), and black widow spider algorithm (BWO)—were compared. The output parameter of the five control algorithms was summarized and analyzed. The adaptability of the algorithms was proven by setting different shading conditions. The simulation results demonstrated that the proposed algorithm possessed short response time, good tracking effect and fewer fluctuations. Eventually, the different algorithms were verified in the HIL + RCP physical platform. The experimental outcomes showed that the improved slime mold algorithm possessed the best tracking effect, with fewer power fluctuations.

Performance assessment and validation of inverter control current controllers in reduced sensor maximum power point tracking based photovoltaic‐grid tied system

A relative assessment on conventional and adaptive current controllers used in reduced sensor-maximum power point tracking (MPPT) based photovoltaic (PV)-grid tied inverter systems for the improvement of system power quality is suggested. The steady-state and transients errors produced in the conventional PI and proportional resonant controllers, which are used to generate the references, can be fixed by using an intelligent ADALINE-LMS adaptive controller; moreover, it helps in reducing the %THD (total harmonic distortion) level measured at different power zones. Also, to track the maximum PV power, which is further integrated to DC-bus, a reduced sensor-based technology is added into the circuit that sidesteps the problem of tracking local MPP instead of global MPP and the drawbacks of using current sensors. The use of a reduced sensor-based MPPT controller confirms extraction of maximum PV power and it guarantees a constant DC-link voltage under all the possible test conditions. The overall control architectures and system performances, which are tested under different system dynamics, are validated through MATLAB/Simulink as well as experimental findings obtained using the dSPACE RTI 1202 interfacing kit. These experimental results confirm that the adaptive control technique used in reduced sensor-MPPT based PV-grid tied inverter systems performs unbeatably with balanced load and grid voltages, less harmonics, quick response time etc. under the operation of linear, non-linear and transient loads, whereas, conventional controllers are best only for the linear loads.

Modeling and simulation of novel dynamic control strategy for grid-connected photovoltaic systems under real outdoor weather conditions using Fuzzy–PI MPPT controller

ABSTRACT This paper proposes the modeling and simulation of a novel dynamic control strategy for 2.4 kWp single-phase grid-connected photovoltaic systems under real outdoor weather conditions using an intelligent Fuzzy–PI MPPT controller. The PV array in the first case is fixed and tilted at a 32° angle, whereas the PV array in the second is equipped with dual-axis sun tracking. The objective is to deliver the maximum power from the PV array and to improve the drawbacks of the classical MPPT control. The optimization is performed using a real-time daily profile of Ghardaia, Algeria (32.24°N – 3.24°W). The proposed MPPT controller (Fuzzy PI MPPT) is optimized under different climatic scenarios based on four selected typical days: the first two days in winter and the second two days in summer. An analysis of the performance and simulation of a photovoltaic conversion system associated with a solar tracker, comparing it from an energy point of view with a fixed photovoltaic converter, has been carried out in Matlab/Simulink software. The results show that grid-connected PV with dual solar tracking enhances the PV array output power efficiency by about 25% compared to a similar fixed PV system. The results show that higher injected power quality is achieved and the overall system has higher efficiency.

Performance Analysis of DC-DC converters for Solar PV fed Switched Reluctance motor for Electric Vehicle Applications

This paper describes the performance of a Solar PV-powered switched reluctance motor with low torque ripple in electric vehicle applications. The prominence of switched reluctance motors has become significant in the electric vehicle industry, because of its ineradicable characteristics like simple structure, absence of rotor windings, less maintenance and its self-starting capability. However, the limitation of SRM is its high torque ripple because of its nonlinear characteristics. The performance of a switched reluctance motor with various DC –DC converters is analysed in this work and the results are compared in terms of the speed of the motor and its torque ripple percentage. The switching time of the converter is controlled by the MPPT controller, which uses incremental conductance and the Integrator method. The converters presented in this work are the Boost converter and the Cuk converter. These two types of converters are designed in MATLAB software and their characteristics are analysed while supplying the switched reluctance motor. The suitability of the proposed system with the motor is analysed by simulation results. From the results, it is confirmed that the performance of the Solar PV fed Switched reluctance motor is improved in terms of speed and torque ripple by implementing this type of converter. Hence, it is suitable for electric vehicle applications, which require less torque ripple and mechanical vibrations.