Intelligent Power Control in Smart Photovoltaic Systems Using M5‐Pruned Decision Tree for Enhanced Grid Voltage Modulation

The direct power control (DPC) strategies are classified as two main control modes: DPC based on switching table hysteresis method and DPC based on space vector modulation (SVM) method, which are named STH_DPC and SVM_DPC, respectively. Compared with the two DPC strategy modes, this paper presents a new DPC mode of single phase PWM rectifier by using constant frequency hysteresis method, named constant frequency hysteresis DPC (CFH_DPC). Compromising the two classical DPC strategies features, the advantages of the proposed control strategy are summarized as follows: it can gain fast dynamic performance by using two power hysteresis comparators instead of proportion- integration (PI) controllers, and achieve a constant switching frequency by using SVM. Experimental tests have been conducted to verify effectiveness of the proposed CFH_DPC strategy.

ABSTRACTOne of the important factors to be considered in an electric power system is to maintain the frequency constant, so that power stations run satisfactorily in synchronise among the connected pool of power generation systems. The main purpose of load frequency control (LFC) is to reduce the frequency deviation and net interchange of power flow between electrical power generating units and for achieving steady-state error to be zero. This research paper proposes the way to improve the LFC by employing energy storage systems (battery energy storage systems and superconducting magnetic energy storage (SMES)) during change in load demand. The energy storage devices are acting quickly and they are effectively damp electro mechanical oscillations in a power system. Moreover, they provide storage capacity and the kinetic energy of the generator shares the sudden changes in power requirement. An integrated hybrid BES and SMES energy storage systems along with LFC minimise the deviation of frequency by contribution of additional power requirement. Investigating the performance of the LFC with storage system under step change of load (∆Pd) has been analysed by employing proportional-integral (PI) and fuzzy logic controller (FLC) for frequency regulation and load tracking. Even, the PI controller attains zero steady-state error in system frequency, it has unsatisfied dynamic (overshoots and settling time) performance followed by disturbances. The mismatch power in the power system makes frequency deviation followed by the change in load demand and electrical power generation and it is balanced by employing of an energy storage system with proper controller. The simulation results are illustrated that the performance of LFC system is enhanced by BES storage system which effectively reduces frequency deviation than SMES system. The comparative analysis has been made for LFC with BES, SMES and hybrid storage system employing FLC and PI controller design also. A significant improvement in the frequency profile has been obtained with FLC controller than PI controller followed by the step load changes.

This paper presents a new approach of direct power control (FLC-DPC) strategy for to three phase PWM converters. In this novel strategy the fuzzy logic control (FLC) has been used. The converter lookup table is based on fuzzy logic rules, using the instantaneous active and reactive power errors and the position of grid voltage vector. The basic idea of fuzzy rules synthesis is based on the knowledge of the instantaneous variation of active and reactive power flows to the grid. The main advantages of the improved approach of DPC strategy are that it is not necessary to use hysteresis comparators, smooth control of active and reactive power flows and maintaining the dc-bus voltage of the converter close to the reference value. The robustness of the FLC-DPC to sampling frequency variations, line inductance variations and tracking capability are also presented. Results have proven excellent performance, and verify the validity of the proposed DPC strategy which is much better than the classical direct power control strategies.

In order to improve the power quality of wind power generation system, a direct power control (DPC) strategy of open-winding brushless doubly-fed generator (BDFG) system based on dual converters is presented in this paper. The control method is divided into two parts: the grid side converter control and the machine side converter control. In terms of the grid side converter, a model predictive-based SVPWM direct power control(MP-DPC) is used. In comparison with the traditional voltage oriented direct power control(VO-DPC) strategy, the switching frequency can be fixed and harmonic content can be reduced, and at the same time the grid side converter can achieve basically constant DC bus voltage. In the machine side converter, the open winding structure of BDFG is used and the control accuracy of active and reactive powers is improved. The simulation of the proposed control strategy is carried out through Matlab/Simulink software and the simulation results prove the correctness and feasibility of the DPC strategy for the open-winding BDFG system on the grid and machine sides.

Multiport DC-DC converters have been most commonly used in stand-alone renewable power systems to provide smooth and constant power to the loads. To supply the load without any interruption under various disturbances, the centralised controller in various typologies of multiport converter has been implemented only by using conventional proportional integral (PI) controller. This study presents the output voltage control of the three-port full-bridge converter interfacing photovoltaic (PV) system with three different controllers. The dynamic response of the proposed converter is analysed with the PI controller, fuzzy logic controller (FLC), and the sliding mode controller (SMC). The state space model of the three-port full-bridge converter is developed to analyse the performance using SMC. PI, FLC, and SMC-based control scheme is developed using the MATLAB/Simulink environment. The response of the PI, FLC, and SMC are analysed for line regulation, load voltage regulation, and for the converter parameter variation. The simulation results illustrate that the SMC gives a better steady state and dynamic response when compared with the PI and FLC. The results are presented to confirm the proposed control schemes.

This research validates An Adaptive Fuzzy Logic Controller (AFLC) has been developed for grid-connected photovoltaic (PV) systems. The primary objective of this implementation is to enhance the PV system's power generation efficiency. For achieving this, techniques of Maximum Power Point Tracking (MPPT) are utilized, which are essential to extract the highest possible power outing from PV panels. Recent developments in MPPT methods focus on improving control strategies to ensure efficient operation and smooth integration with the grid. The performance of the AFLC is extensively evaluated and compared with other controllers, like fuzzy-logic controller (FLC) and Proportional Integral (PI). The proposed AFLC controller's performance is evaluated with other methods to verify its effectiveness. To validate this method, the system is tested using MATLAB/Simulink simulations, along with experimental evaluations conducted on the control strategies are executed in real-time utilizing the DSpace DS1104 control. Experimental results show that the AFLC outperforms both the FLC and PI controllers in several key performance areas. Specifically, the AFLC demonstrates faster response times, higher convergence rates, decreased peak overshoot, minimal undershoot, and lower the error of the mean square. Additionally, the Compared to conventional Fuzzy Logic Control (FLC) and PI controllers, the AFLC delivers superior efficiency and transient response, and oscillation reduction. Compared to the FLC, the AFLC enhances tracking of power by 68.26%, and it achieves 86.25% improvement over the PI controller. These findings highlight the AFLC's potential as a highly effective and reliable optimization tool for maximizing the output power of the systems of PV. Furthermore, integral absolute error (IAE) is used as a performance metric for the PV system connected to grid to assess the efficiency of the AFLC. The AFLC demonstrated superior performance over other methods, achieving a 20% increase in PV output power compared to traditional FLC and a 30% improvement over PI controllers. The errors of the PI, FLC and AFLC approaches, each utilizing five controllers, are estimated. The error of mean square is reduced by 79.67% in comparison to PI and by 66.5% in comparison to FLC.

Multiport DC-DC converters have been most commonly used in stand-alone renewable power systems to provide smooth and constant power to the loads. To supply the load without any interruption under various disturbances, the centralised controller in various typologies of multiport converter has been implemented only by using conventional proportional integral (PI) controller. This study presents the output voltage control of the three-port full-bridge converter interfacing photovoltaic (PV) system with three different controllers. The dynamic response of the proposed converter is analysed with the PI controller, fuzzy logic controller (FLC), and the sliding mode controller (SMC). The state space model of the three-port full-bridge converter is developed to analyse the performance using SMC. PI, FLC, and SMC-based control scheme is developed using the MATLAB/Simulink environment. The response of the PI, FLC, and SMC are analysed for line regulation, load voltage regulation, and for the converter parameter variation. The simulation results illustrate that the SMC gives a better steady state and dynamic response when compared with the PI and FLC. The results are presented to confirm the proposed control schemes.

Renewable energy resources has given rise to the systems that transmit and distribute electricity. Recent developments in the wind energy as distribution generation systems in the distribution networks is gaining popularity as a new sources of energy. The integration of renewable energy in to the power system causes severe challenges for the control and protection of the distributed system. A careful operation and design of distribution systems with renewable energy resources should be carried out. This paper describes the dynamic modeling and simulation results of DFIG wind turbine during nonlinear loading. During nonlinear loading the overall performance gets considerably degraded due to the effect of negative sequence component and also the power produced by the DFIG gets considerably derated. To eliminate this effect a suitable control technique should be applied. Direct Power Control (DPC) scheme is implemented along with Proportional Integral (PI) controller. The DPC directly controls the Stator active and reactive powers, while the PI controllers is used to regulate the positive and negative sequence component. The proposed DPC-PI control strategy is verified by the simulation results during nonlinear loading. The models have been developed by means of MATLAB/SIMULINK software.

In this paper, a step-ahead direct power control (DPC) scheme with reduced sensor count for grid-connected active rectifiers with LCL filter is formulated. Compared to classical model predictive control (MPC) schemes, which implement an L filter, the proposed controller is designed to operate with an LCL filter and thus benefit from higher harmonic attenuation and lower component size and weight. In this work, an expression is derived to allow the prediction of the grid-side current by only measuring the dc-bus voltage, grid voltages, and grid-side line currents. As a result, only 6 sensors are required as opposed to 9 or 12 sensors. An extensive digital computer simulation using Matlab/Simulink is used to demonstrate the validity and performance of the proposed step-ahead DPC scheme. The widely used classical proportional integral (PI)-based power controller is used as a reference to benchmark the steady-state and dynamic performance of the proposed control scheme. The results validate the proposed controller and show its sound steady-state performance consisting of high quality grid-side currents with low Total Harmonic Distortion and unity power factor. In addition, robust and rapid dynamic performance is demonstrated when compared to the classical PI-based controller.

Introduction. This paper focuses on a renewable energy system coupled to a dual purpose power grid via a parallel active power filter for injecting photovoltaic energy into the grid and improving the power quality in the presence of the non-linear load. The novelty of the work consists in the combination of two advanced techniques – Fuzzy Logic Controller (FLC) and the optimized Anti-Windup Fractional Order Proportional-Integral Differentiator (AW-FOPID) regulator based on Particle Swarm Optimization with the Spreading Factor (PSO-SF) algorithm, applied to the improved Direct Power Control (DPC) strategy under different conditions related to climate changes and healthy or infected electrical network. Purpose. Its main role is to improve the power quality and reject the perturbations deforming the electrical network under distorted, unbalanced and balanced grid voltage conditions. Besides, the FLC is employed the Maximum Power Point Tracking (MPPT) under any weather conditions. In addition, the optimized AW-FOPID controller leads to keep the DC bus voltage at its reference value with small undershoots and overshoots in the voltage with a short response time in steady or dynamic states. Methods. The rejection of disturbances affecting the grid is offered by the improved DPC. On the other hand, an intelligent method based on fuzzy logic was used MPPT under any weather conditions. Furthermore, an AW-FOPID regulator based on PSO-SF algorithm is used to keep the DC bus voltage at its reference value with small undershoots and overshoots in the voltage, while keeping a fast response time. Results. The proposed system control is evaluated in various states of power source: distorted, unbalanced, and balanced by simulation using MATLAB/Simulink. The simulation results illustrate the effectiveness and performance of the studied control strategies. References 26, tables 8, figures 16.

In order to regulate the instantaneous active and reactive powers of the rectifier in an optimized approach, a novel fuzzy-based and voltage-oriented direct power control strategy (FVO-DPC) is proposed in this study. The proposed strategy is based on the principle of the direct power control (DPC) strategy in three-phase voltage source pulse width modulations (PWM) rectifier. In the proposed FVO-DPC system, the active and reactive powers are controlled by a fuzzy logic controller and a fuzzy-based switching table. The fuzzy logic controller is run through introducing the errors between command and estimate values of the instantaneous active and reactive power. The switching loss, the control precision and the dynamic characteristics are taken into consideration simultaneously in the process of setting the switching states of the fuzzy-based switching table. The simulation model established under matlab/simulink environment is validated by comparing with the classical control scheme. The comparisons show that a near unit power factor and better transient and steady performance can be achieved with the proposed FVO-DPC.

In this paper, direct power control strategy used in three-level neutral point clamped (NPC) converters is discussed. With the theory of instantaneous power, it gets the deep relations between power (active power and reactive power) and space voltage vectors. After the analysis, considering the special issues in three-level NPC converters, such as the excessive dv/dt and fluctuation of neutral point potential, a direct power control (DPC) strategy for three-level NPC converters is proposed. Simulation results show the correctness of the new DPC control strategy.

Herein, we report the comparative analysis of a proposed fuzzy logic controller with conventional incremental conductance algorithm for maximum power point tracking (MPPT) with proportional integral (PI) controller of a unity power factor grid-connected photovoltaic (PV) inverter. In the conventional controller, incremental conductance MPPT algorithm with PI controller has been implemented. In the fuzzy logic controller, inputs and outputs are chosen for this study, rules relating them are written and the simulation is performed. Simulation model of a 40 W solar panel using single diode model is developed and results are obtained for PI controller and fuzzy logic controller for different irradiation and temperature conditions. Results show the ability of fuzzy logic controller to give a performance nearly similar to that of incremental conductance algorithm with increased robustness. Also it is inferred that when the conditions become low, PI controller shows poor performance when compared to fuzzy logic controller.

One of the most commonly used control methods for three phase converters is the so-called Direct Power Control (DPC), which is based on an appropriate selection of converter switching states via predefined switching table. One important feature of Direct Power Control strategy is the variable switching frequency due to the absence of Pulse Widths Modulation (PWM) block. However, a PWM generator can be included to improve the dynamic performance of traditional DPC scheme. In this paper, a simple DPC scheme for a grid connected photovoltaic system is established. Firstly, the mathematical model of the overall photovoltaic system is developed. Then, a DPC control scheme that assures a decoupled control of active and reactive powers is presented: two Proportional-Integral (PI) regulators control directly the instantaneous active and reactive power flow. While, the outer voltage loop acts on the amplitude of active power reference. The tuning of PI parameters of DC link voltage controller is achieved using the Particle Swarm Optimization (PSO) algorithm. The PSO algorithm performs offline search of the best PI parameters that give less overshoot and minimal steady state error. The simulation results, obtained in Matlab/Simulink environment, show fast transient response and good dynamic performance.

This paper presents a comparison in efficiency between a fuzzy logic controller (FLC) and a proportional-integral (PI) controller based interior permanent magnet synchronous motor (IPMSM) drive incorporating an online loss minimization algorithm (LMA). The LMA is developed based on the motor model. In order to maximize the operating efficiency the d-axis armature current is controlled optimally based on the developed LMA. A novel fuzzy logic controller (FLC) is developed, in such a way that it can simultaneously control both torque and flux of the motor while maintaining current and voltage constraints. Thus, the FLC extends the operating speed limits for the motor. The LMA is incorporated with the FLC so that the motor can operate over a wide speed range while maintaining the high efficiency. A performance comparison of the LMA based IPMSM drive with FLC and PI controller is provided. Simulation results demonstrate the higher efficiency and better dynamic response of the FLC based drive as compared to the PI controller over a wide speed range. The complete drive is also experimentally implemented using DSP board DS1104 although the complete experimental tests are yet to be done.