Maximum Power Point Tracking Power Research Articles

A hybrid incremental conductance and sliding mode controller for a PV microgrid system

A new controller is designed for performance improvement of a photovoltaic based microgrid (PVMG) system in this paper. The photovoltaic system is integrated to grid via an H-bridge voltage-source inverter (VSI). To enhance the power conversion from the solar panel, an incremental conductance (I&C) Maximum-Power-Point-Tracking (MPPT) controller is designed. The proposed controller comprises of two units namely for accomplishing power quality improvement and MPPT tasks. We design a sliding mode controller for improving power quality. This controller is designed to control the power-flow injection to the PVMG. The results are compared with that of the proportional-integral+proportional-integral-derivative (PI+PID) hybrid controller to evaluate its effectiveness. From the transient performance analysis, it is found that with the proposed controller, it is faster in response, with lesser harmonics and more robust compared to the PI+PID hybrid controller. Also, this system is capable controlling both active and reactive power of the line.

A novel Lyapunov stable higher order B-spline online adaptive control paradigm of photovoltaic systems

In this paper, research on the control of photovoltaic (PV) using a novel higher order B-spline online adaptive neuro-fuzzy paradigm considering high external uncertainties in weather and load demand is presented. We optimize the existing neuro-fuzzy technique by incorporating third order B-spline membership functions in its antecedent part, which we solve using an on-line learning gradient-decent back propagation method. We fit the system parameters online through adaptive fuzzy rules extracted from the maximum power point tracking (MPPT) error and its derivative. Unlike many existing neuro-fuzzy techniques, our method addresses the trapping in local minima. The proposed controller is demonstrated to be stable using Lyapunov stability analysis. The performance of our control philosophy is checked in terms of output power tracking, efficiency, and MPPT error. Finally, we validate via simulation the high robustness and the self-adaptation ability of the proposed method over other existing traditional and intelligent techniques.

Energy Management and Control of Single-Stage Grid-Connected Solar PV and BES System

In general, Solar Photovoltaic (SPV) is integrated to grid through a DC-DC converter and Voltage Source Converter (VSC) for real power injection (called two-stage conversion). In view of efficiency point, the single-stage conversion becomes popular and in which Maximum Power Point Tracking (MPPT) of SPV and real power injection are achieved with VSC alone. But, if Battery Energy Storage (BES) supported by bidirectional DC-DC converter is presented in the single-stage conversion system, then co-ordination between DC-DC converter and VSC is required to achieve simultaneous operation of MPPT and real power injection. In this paper, a co-ordinated control of single-stage grid connected SPV and BES system is proposed along with energy management. In which, the algorithm coordinates VSC and bidirectional DC-DC converter based on the State of Charge (SoC) of the battery such that MPPT and power injection is achieved simultaneously. The proposed method not only injecting real power, but also works to compensate load reactive power and unbalanced neutral current minimization. Further, an active rectification operation during non-SPV hours is discussed for better utilization of VSC capacity. The multi-functional features of the proposed method are explained using simulation studies and are also validated through experimental studies.

Design of Sub-Gigahertz Reconfigurable RF Energy Harvester From −22 to 4 dBm With 99.8% Peak MPPT Power Efficiency

To overcome the low-efficiency and limited working range of the existing RF energy harvesting (EH) systems for the wireless Internet-of-Things (IoT) sensors, a novel reconfigurable system is proposed with integrated hill-climbing, maximum power point tracking (MPPT) function for wide input power from −22 to 4 dBm. A conceptual linear model with high accuracy is also proposed to analyze the rectifier efficiency for MPPT operations. The rectifier with off-chip matching is designed with a patch antenna at 915-MHz the industrial, scientific and medical (ISM) band. To further improve the end-to-end efficiency, the harvested power is used to power up the circuit block in system on a chip (SoC) directly, avoiding additional conversion loss. Our proposed reconfigurable 12-stage rectifier with matching network achieves −18.1-dBm sensitivity for 1- $\text{M}\Omega $ loading and 36% peak efficiency at 1 dBm. The proposed MPPT function can detect and determine the optimal rectifier stage for loading from 10 $\text{K}\Omega $ to 1 $\text{M}\Omega $ . The measured MPPT accuracy is over 87% from −22 to 4 dBm compared to external tuning conditions. The minimum stand-by power is 20 nW at 0.5 V and the overall MPPT power efficiency is over 72% with a peak value of 99.8% including dissipated power. Measurements also show the system can achieve self-startup and self-sustained functions with a 10- $\mu \text{F}$ external capacitor buffer.

An NNwC MPPT-Based Energy Supply Solution for Sensor Nodes in Buildings and Its Feasibility Study

Sensors for data collecting are vital in the development of IoT and intelligent systems. High power consuming current and voltage monitors are indispensable in conducting maximum power point tracking (MPPT) in traditional PV energy wireless sensor nodes. This paper presents a sensor node system based on Neural Network MPPT with cloud method (NNwC) which utilizes information sharing process that is specific to sensor networks. NNwC uses a few sample sensor nodes to collect environmental parameter data such as light intensity (L) and temperature (T) to build the MPPT regression model by Neural Network. Then all other functional sensor nodes implement the model with their environmental parametervalues to conduct MPPT. As a result, the new sensor node system reduces energy consumption as well as the size and cost of the harvester. Then, this paper provides a SPICE simulation to estimate the percentage of power consumption reduced in the new sensor node system and also estimates the percentage of loss in neural network MPPT power generation compared with the perfect MPPT. Finally, the study compares the economic and environmental performance of the proposed system and the traditional ones through a case in a real building situation.

Circuit Simulation for Wind Power Maximum Power Point Tracking with Four Switch Buck Boost Converter

Wind turbines have maximum mechanical power at certain wind speeds. Maximum Power Point Tracking (MPPT) is an electronic system capable of extracting maximum wind turbine power. The purpose of this research is to improve wind power efficiency through MPPT wind power design with four switch buck boost converter and Fuzzy control algorithm. Fuzzy control has two inputs are power changes and voltage changes and one output feeding to the pulse width modulation generator to control FSBB. Simulation results with Matlab simulink shows that wind power without MPPT produce 89% power efficiency, wind power MPPT with two switch buck boost converter yield 90% power efficiency and emerging high ripple current. The last simulation of wind power MPPT with FSBB produces the highest efficiency of 91% with low ripple current.

Fault Ride-Through Enhancement for Grid-Tied PV Systems With Robust Control

In this paper, a new control structure is proposed for grid-tied photovoltaic (PV) systems where the dc bus voltage is regulated by the dc/dc converter controller, whereas the maximum power point tracking (MPPT) function and the power flow control are embedded into the dc/ac converter controller. A PV voltage-regulation is designed to build the linkage between MPPT function and power flow control. In this way, the dc/dc converter controller and the dc/ac converter controller are decoupled, which naturally provides the dc bus voltage protection. In particular, an uncertainty and disturbance estimator (UDE)-based current-mode controller (CMC) is proposed for accurate voltage regulation of the dc/dc converter. And a bounded-voltage power flow control strategy is proposed for the dc/ac converter to improve the existing UDE-based robust power flow control for ac voltage protection. The effectiveness of the proposed method is experimentally validated in a lab-environment grid-tied PV system platform with the fault ride-through capabilities. In addition, simulation studies are also provided to demonstrate the need of the PV voltage-regulation between MPPT and power flow control, and the advantages of the bounded-voltage design in the power flow control.

Electricity generation from a biomass cookstove with MPPT power management and passive liquid cooling

An electrical power generator for use with biomass cooking stoves has been developed. The design is intended for users in developing countries who lack regular access to electricity. Electricity is generated based on the thermoelectric effect. A bespoke heat collector captures heat from the combustion chamber of the cooking stove and transfers it to a single thermoelectric generator (TEG) module. To maintain a sufficiently high temperature difference across the TEG, heat is dissipated using a passive single phase liquid thermosiphon system. This cooling system eliminates the requirement for mechanical components such as fans or pumps, which are unreliable and draw significant electrical power. In a controlled laboratory setting, a maximum power of 5.8 W has been produced from a single TEG installed into a low cost ceramic cooking stove currently disseminated in large numbers in Malawi, Africa. The TEG power is controlled using a maximum power point tracking (MPPT) conditioning circuit with an estimated efficiency of ~70%. The circuit provides a stable 5 V output via a USB connector for charging mobile phones, lights, power banks and other devices. Experiments have shown that the device is capable of performing for extended periods without significant reduction in performance. The magnitude of the power generated by this passive cooling system is observed to be comparable to that delivered by similar TEG-stove systems driven by active cooling. An average power generation of over 4 W was achieved which, including circuit efficiency, provided ~10 W·h of useful electrical energy over a 4 h burning interval, which is sufficient for charging low powered electrical appliances. Five prototypes fitted with data measurement and acquisition were deployed to families in rural Malawi in order to evaluate real-life performance of the technology. Initial field-trial results have advocated the viability of the TEG-stove technology for charging low powered electronic devices typically used in developing countries such as Malawi.

An overall Control of BDFIG using Direct Power Control for WECS under Unbalanced Grid Voltage Conditions

The paper presents the complete modelling and control strategy of variable speed wind turbine system (WTS) driven brushless doubly fed induction generators (BDFIG). A back-to-back converter is employed for the power conversion exchanged between BDFIG and grid. The wind turbine is operated on the maximum power point tracking (MPPT) mode its maximum efficiency. The control strategy of CW stator side converter (MSC) combines the technique of MPPT and conventional direct power control. In the control system of the grid side converter (GSC) the direct power control based an improved switching table (IST-DPC has been used to maintain a constant DC-Link voltage and the reactive power is set to zero. In addition, the behaviours of BDFIG under unbalanced grid voltage conditions are studied and a power compensation scheme is developed to improve the power quality generation. Simulations results using MATLAB/SIMULINK are presented and discussed on a 3.5 KW BDFIG wind generation system based an cascaded doubly fed induction generator  demonstrate the effectiveness of the proposed control. several advantages, particularly providing sinusoidal line current when the supply voltage is not ideal.

Irradiance-Adaptive PV Module Integrated Converter for High Efficiency and Power Quality in Standalone and DC Microgrid Applications

The strive for efficient and cost-effective photovoltaic (PV) systems motivated the power electronic design developed here. The work resulted in a dc-dc converter for module integration and distributed maximum power point tracking (MPPT) with a novel adaptive control scheme. The latter is essential for the combined features of high energy efficiency and high power quality over a wide range of operating conditions. The switching frequency is optimally modulated as a function of solar irradiance for power conversion efficiency maximization. With the rise of irradiance, the frequency is reduced to reach the conversion efficiency target. A search algorithm is developed to determine the optimal switching frequency step. Reducing the switching frequency may, however, compromise MPPT efficiency. Furthermore, it leads to increased ripple content. Therefore, to achieve a uniform high power quality under all conditions, interleaved converter cells are adaptively activated. The overall cost is kept low by selecting components that allow for implementing the functions at low cost. Simulation results show the high value of the module integrated converter for dc standalone and microgrid applications. A 400-W prototype was implemented at 0.14 Euro/W. Testing showed efficiencies above 95 %, taking into account all losses from power conversion, MPPT, and measurement and control circuitry.

Efficiency analysis of maximum power point tracking techniques for photovoltaic systems under variable conditions

With the rapid increase in development of solar energy, researchers are concentrated on developing the maximum power point tracking (MPPT) techniques for extracting the power efficiently. It was environmentally friendly, low maintenance cost, no noise, used in remote areas, and long-lasting life. The output power of PV module is depending on the solar irradiance and temperature. So, to extract more power MPPT techniques are employed. This paper describes the comparative analysis of various MPPT's like perturb and observe (P&O), incremental and conductance (IC), fuzzy logic (FL) controller, and neuro-fuzzy (NF) technique. The controlled output is fed as input to the boost DC-DC converter and the effective performance of the MPPT's are checked under different irradiations and constant temperature. And also, this paper gives mathematical analysis, design and operation of converter and MPPT techniques. In addition, steady state and dynamic performance of MPPT techniques are also analysed. The simulations are performed under MATLAB/Simulink environment.

A Complete Modeling and Control for Wind Turbine Based of a Doubly Fed Induction Generator using Direct Power Control

<span lang="EN-US">The paper presents the complete modeling and control strategy of variable speed wind turbine system (WTS) driven doubly fed induction generators (DFIG). A back-to-back converter is employed for the power conversion exchanged between DFIG and grid. The wind turbine is operated at the maximum power point tracking (MPPT) mode its maximum efficiency. Direct power control (DPC) based on selecting of the appropriate rotor voltage vectors and the errors of the active and reactive power, the control strategy of rotor side converter combines the technique of MPPT and direct power control. In the control system of the grid side converter the direct power control has been used to maintain a constant DC-Link voltage, and the reactive power is set to 0. Simulations results using MATLAB/SIMULINK are presented and discussed on a 1.5MW DFIG wind generation system demonstrate the effectiveness of the proposed control.</span>

Grid-Interfaced DFIG-Based Variable Speed Wind Energy Conversion System With Power Smoothening

This paper deals with the analysis, design, and control of grid-interfaced doubly fed induction generator (DFIG) based variable speed wind energy conversion system (WECS) for power smoothening with maximum power point tracking (MPPT) capability. This DFIG uses rotor position computation algorithm for the sensorless control through rotor position estimation. Power fluctuations due to the unpredictable nature of the wind are eliminated by introducing battery energy storage system (BESS) in the dc link between two back-to-back connected voltage source converters. The design of BESS is presented for feeding regulated power to the grid irrespective of the wind speeds. The control algorithm of the grid-side converter is modified for feeding regulated power to the grid. Rotor-side converter is controlled for achieving MPPT and unity power factor operation at the stator terminals. A prototype of the proposed DFIG-based wind energy conversion system is developed using a digital signal processor (DSP-dSPACE DS1103). This developed DFIG is tested extensively at different wind speeds and also presented some of the steady-state test results. Dynamic performance of this DFIG is also demonstrated for the variable wind speed operation.

Voltage positive feedback based active method for islanding detection of photovoltaic system with string inverter using sliding mode controller

Islanding is an undesirable condition that is potentially dangerous to the maintenance or repair staff and may cause damages to sensitive equipments. Therefore, islanding detection is a mandatory feature for distributed generators (DGs), including grid–connected photovoltaic systems (GCPVSs). This article presents a new active islanding detection method for GCPVSs with string inverter based on sliding mode controller. In the proposed method, a feedback of point of common coupling (PCC) voltage has been inserted to the reference signal of sliding mode controller as a new maximum power point tracking (MPPT) technique. Through applying this voltage positive feedback (VPF), the inverter output power and consequently, the PCC voltage decreases in islanding condition. This procedure is repeated until the PCC voltage falls below the under voltage (UV) relay setting. The conventional VPF technique attempts to increase and decrease the output power in elevated and declined PCC voltage cases after grid disconnection, respectively. However, due to the input power limitation and MPPT in GCPVSs in the PCC voltage raised cases, the output active power cannot be elevated any further. In this study, the active power perturbation has been only applied in deceleration mode, considering the disturbance definition in the inverter voltage control loop. Therefore, unlike the conventional VPF scheme, it has the advantage of not violating the “conservation of energy law”. The performance of the proposed method is evaluated by simulating a GCPVS with string inverter supplying a local load, connected to the grid. Simulation results show troubleshooting the conventional VPF scheme drawbacks as well as successful operation of the proposed method in islanding and non–islanding conditions even in multi–inverter systems.

SiC-Based Bidirectional Ćuk Converter With Differential Power Processing and MPPT for a Solar Powered Aircraft

A silicon-carbide (SiC)-based dc–dc converter is developed for the solarship, a manned solar aircraft for supply delivery in remote locations. The concept of differential power processing (DPP) is utilized to realize a high-efficiency lightweight converter that performs maximum power point tracking (MPPT) to transfer power from the aircraft’s wing-mounted solar array to the high-voltage lithium-battery bus. The isolated Cuk topology is augmented with an unfolder to achieve four quadrant operation and minimize the worst-case processed power. A small-signal model is derived for control design, and it is shown that the compensation strategy differs significantly based on the operating mode. The 2.7-kW prototype is verified at a high frequency (200 kHz), high efficiency ( $>98\%$ ), small mass (0.604 kg), and uses no electrolytic capacitors. MPPT operation is verified on a 376-V commercial solar installation. The DPP Cuk converter is promising for emerging solar aerospace applications.

Micro/small wind turbine power control for electrolysis applications

This paper compares the efficiency of three power converter and maximum power point tracking (MPPT) systems for connecting a micro/small wind turbine to an electrolyser stack: a conventional DC–DC voltage converter with hill-climb search (HCS); a novel variable electrolyser cell load controller where the number of series cells varies to allow MPPT; a novel hybrid DC–DC voltage converter integrated with direct-connect circuitry, variable cell control and lookup-based MPPT. The variable cell and hybrid converters demonstrated superior performance, averaging efficiencies 2–4% higher than the conventional converter, reaching near ideal at a wind speed of 7.7 ms−1 due to direct connection. MPPT function measured electrolyser current as a power reference. HCS performed MPPT at approx. 98% of ideal but requiring very advanced function including variable step size and intelligent perturbation to achieve this during dynamic conditions. The variable cell and hybrid converters produced superior MPPT (based on lookup data) to HCS. This demonstrates alternative novel power control and MPPT approaches for low-cost and efficient hydrogen production from micro/small wind-electrolysis systems.

Fuzzy Controller for a Voltage-Regulated Solar-Powered MPPT System for Hybrid Power System Applications

This paper presents the design of a fuzzy-logic-based voltage-regulated solar power maximum power point tracking (MPPT) system for applications involving hybrid power systems. The system contains a solar power system and battery as the primary and secondary power sources, respectively. The solar system alone supplies power to the electric motor and maintains the output voltage at a predetermined level when it has sufficient power. When the solar power is insufficient, the solar system is operated at its maximum power point (MPP) and the battery is engaged to compensate for the insufficiency. First, a variant of the incremental conductance MPP condition was established. Under the MPP condition, the voltage-regulated MPPT system was formulated as a feedback control system, where the MPP condition and voltage regulation requirements were used as the system inputs. Next, a fuzzy controller was developed to perform the voltage-regulated MPPT function for the hybrid power system. A simulation model based on Matrix laboratory (MATLAB)/SIMULINK (a block diagram environment for multi-domain simulation and model-based design) and a piecewise linear electric circuit simulation (PLECS) tool for controlling the dc motor velocity was developed to verify the voltage-regulated solar power MPPT system.

A Study on the Fuzzy-Logic-Based Solar Power MPPT Algorithms Using Different Fuzzy Input Variables

Maximum power point tracking (MPPT) is one of the key functions of the solar power management system in solar energy deployment. This paper investigates the design of fuzzy-logic-based solar power MPPT algorithms using different fuzzy input variables. Six fuzzy MPPT algorithms, based on different input variables, were considered in this study, namely (i) slope (of solar power-versus-solar voltage) and changes of the slope; (ii) slope and variation of the power; (iii) variation of power and variation of voltage; (iv) variation of power and variation of current; (v) sum of conductance and increment of the conductance; and (vi) sum of angles of arctangent of the conductance and arctangent of increment of the conductance. Algorithms (i)–(iv) have two input variables each while algorithms (v) and (vi) use a single input variable. The fuzzy logic MPPT function is deployed using a buck-boost power converter. This paper presents the details of the determinations, considerations of the fuzzy rules, as well as advantages and disadvantages of each MPPT algorithm based upon photovoltaic (PV) cell properties. The range of the input variable of Algorithm (vi) is finite and the maximum power point condition is well defined in steady condition and, therefore, it can be used for multipurpose controller design. Computer simulations are conducted to verify the design.

An Optimal Maximum Power Point Tracking Algorithm for PV Systems With Climatic Parameters Estimation

This paper presents a maximum power point tracking (MPPT) method for photovoltaic (PV) systems with reduced hardware setup. It is realized by calculating the instantaneous conductance and the junction conductance of the array. The first one is done using the array voltage and current, whereas the second one, which is a function of the array junction current, is estimated using an adaptive neuro-fuzzy (ANFIS) solar cell model. Knowing the difficulties of measuring solar radiation and cell temperature, since those require two extra sensors that will increase the hardware circuitry and measurement noise, an analytical model is proposed to estimate them with a denoising-based wavelet algorithm. The proposed MPPT technique helps to reduce the hardware setup using only one voltage sensor, while increases the array power efficiency and MPPT response time. The simulation and experimental results are provided to validate the MPPT algorithm operation as well as the climatic parameters estimation capabilities.

An Advanced Universal Power Quality Conditioning System and MPPT method for grid integration of photovoltaic systems

A photovoltaic system usually produces power quality pollutions to the interfaced power systems without a proper functioning of active filters. At present, available active filters are unable to fully suppress power grid harmonics and distortions, worsening power quality conditions within the interfaced system. This paper presents an Advanced Universal Power Quality Conditioning System (AUPQS) to interface photovoltaic systems to a power grid. In the interfaced system, an improved series active filter is designed to generate output voltages to compensate all the source voltage deficiencies and to highly suppress the grid-end current harmonics and distortions, even under unbalanced non-linear load conditions. Also, an independent single-phase inverter is suggested at the load side instead of the source side to regulate the DC-link voltage. Hence, the distortions and harmonics generated by this single-phase inverter are absorbed by the shunt filter of the AUPQS. Finally, a hybrid maximum power point tracking (MPPT) approach is proposed for effective operation of photovoltaic systems even under sudden light intensity changes and solar cells temperature variations. The overall interfaced system is designed and developed using Matlab/Simulink software. The effectiveness of the proposed AUPQS and MPPT method is further validated by simulation results.