Maximum Power Point Tracking Mode Research Articles

Fractional order PI control combined with improved frequency droop method for power management in standalone LVDC microgrids

According to increasing growth of DC loads, DC microgrids (MGs) have an effective role in future power systems. Improvement of power management is one of the important issues in DC MGs. In this paper, in order to provide an accurate power management in standalone low-voltage DC (LVDC) MG, including photovoltaics (PVs) and battery energy storage systems (BESSs), an AC component is superimposed to the output voltage of DC-DC converters by inspecting the frequency droop control of the synchronous generators. In addition, two corrective terms based on the calculation of AC active and reactive powers are added to this AC component, which is named improved frequency droop method (IFDM). Different operating modes for PV system comprising maximum power point tracking (MPPT) and voltage control mode (VCM); and BESS consisting of charge, discharge, and idle are considered in the proposed power management scheme based on the state of charge (SoC) of local BESS. On the other hand, the conventional proportional-integral (PI) controllers in DC-DC converters' control structure present poor transient dynamic performance and low loading level. Hence, fractional order PI (FOPI) controllers are designed by optimization of integral time absolute error (ITAE) criteria. The effectiveness of the proposed FOPI controllers combined with IFDM scheme is evaluated by simulations conducted in MATLAB/SIMULINK software. The FOPI-IFDM approach provides accurate current sharing and better voltage regulation without dependence on communication link in comparison with PI-IFDM under load, line impedance, and solar irradiance variations.

Comparisons of Different Maximum Power Point Tracking Strategies with Zeta Converter

Maximum power point tracking (MPPT) strategy is one of the major parameters affecting efficiency in photovoltaic (PV) systems. In this paper, distributed MPPT approaches are compared with central mode MPPT. Advantages and disadvantages of submodule level MPPT technique and module level MPPT approach are shown with simulation studies. Comparisons are made with incremental conductance (IC) algorithm. In this context, non-isolated zeta converter is used as a power processing unit. Effect of the MPPT strategy on the collected energy performance is observed by simulation studies performed in MATLAB/Simulink. It is clear by these studies that energy capture is bigger in submodule level MPPT strategy and module level MPPT with respect to central mode which is seen by simulations. However, central mode MPPT offers cost effective solution because of the low hardware requirements.

Comparative analysis on performance of PV direct-driven refrigeration system under two control methods

The concept of the PV direct-driven refrigeration system has been proposed to reduce the cost of the PV refrigeration system. In the PV direct-driven refrigeration system, the system control method has great impact on system performance. In this paper, a dynamic model of the PV direct-driven refrigeration system is proposed and validated with experimental results. This model contains a PV-compressor coupling model, which can reflect the relationship among solar irradiance, compressor load and compressor speed. Based on the model, two control methods for the PV direct-driven refrigeration system are compared, which are the maximum power point tracking (MPPT) method and the compressor speed prediction (CSP) method. According to the comparison results, the following conclusions can be summarized. Firstly, the MPPT method is more efficient than the CSP method. And the difference of two control methods can be reduced if the control model in CSP mode matches well with the system. Secondly, the drop of solar irradiance causes the decreases of daily operation time and total cooling capacity in both MPPT mode and CSP mode. Finally, the MPPT method is more adaptive to the variations of ambient temperature and water temperature.

Harnessing Maximum Power from PV Module using DC-DC Converter

Solar energy is one of the most potent sources of energy. In the wake of depleting fossil fuel energy sources and growing environmental concerns, world is in a relentless drive towards utilizing natural resources like sun efficiently. The aim of the project is to make the solar module work in MPPT mode (Maximum Power Point Tracking) Mode. At this condition, the system is able to extract maximum power from the module without affecting the PV module. MPPT control here is obtained using boost converter. Applying PWM with proper controlling algorithm will vary the duty ratio of the converter such that system will run in MPP mode.

Integration of Distributed Generating Systems for Non-Linear Loads

The independent small-scale networks including sustainable power sources have been used in remote regions around the globe. Nonetheless, the irregularity of vitality sources may cause an enormous variance of the miniaturized scale framework recurrence. Because of consistently expanding vitality utilization, rising open familiarity with ecological assurance, and relentless advancement in power deregulation, distributed generation (DG) frameworks have pulled in expanded intrigue. Wind and photovoltaic (PV) power age are two of the most encouraging sustainable power source advancements. Fuel cell (FC) frameworks likewise show incredible potential in DG utilizations of things to come because of their quick innovation improvement and numerous benefits they have, for example, high effectiveness, zero or low outflow (of contamination gases), and adaptable measured structure. In proposition investigated work Integration of Distributed Generating Systems for Non-straight Loads will be proposed. A run-of-the-mill wind-PV-diesel reconciliation which comprises of diesel generator, PV framework, wind turbine generator (WTG), BESS, and burden, is utilized for the proposed models and controllers. We reenact and Integration Distributed Generating Systems for Non-straight Loads on the MATLAB/SIMULINK and portions of coordinated vitality frameworks are analyzed. The coordinated PV framework is normally controlled to work in the maximum power point tracking (MPPT) mode. The battery vitality stockpiling framework is worked inconsistent force charging or releasing mode. So as to give an incorporated vitality framework associated with lattice relying upon singular vitality necessities, the Integrated Energy Systems can be extra to a current vitality source to lessen petroleum product utilization or an independent for complete non-renewable energy source uprooting Through the broad joining of vitality foundations it is conceivable to upgrade the supportability, adaptability, steadiness, and productivity of the general vitality framework. The reproduction of incorporated vitality frameworks is done in MATLAB/SIMULINK. And all framework results will be done by Matlab reproduction is proposed for disconnected smaller scale matrices with sustainable sources. In the exhibited method, the pitch point controller is intended for wind turbine generator (WTG) framework to smooth breeze power yield. The proposed procedure is tried in a regular secluded incorporated small-scale network with both PV and wind turbine generators.

Innovative Energy Management System for MVDC Networks with Black-Start Capabilities

Medium voltage DC (MVDC) networks are attracting more attention amid increased renewables penetration. The reliability of these DC systems is critical, especially following grid contingencies to maintain critical loads supply and provide ancillary services, such as black-start. This paper proposes an innovative energy management system (EMS) to maintain reliable MVDC network operation under prolonged AC grid contingencies. Similar EMS designs in literature tend to focus on limited operating modes and fall short of covering comprehensive elongated blackout considerations. The proposed EMS in this paper aims to preserve the distribution network functionality of the impacted MVDC system through maintaining a constant DC bus voltage, maximizing critical load supply duration, and maintaining the MVDC system black-start readiness. These objectives are achieved through controlling generation units between Maximum Power Point Tracking (MPPT) and Voltage Regulation (VR) modes, and implementing a smart load shedding and restoration algorithm based on network parameters feedback, such as storage State of Change (SoC) and available resources. Practical design considerations for MVDC network participation in AC network black start, and the following grid synchronization steps are presented and tested as part of the EMS. The proposed system is validated through simulations and scaled lab setup experimental scenarios.

RBF neural network based backstepping terminal sliding mode MPPT control technique for PV system.

The energy demand in the world has increased rapidly in the last few decades. This demand is arising the need for alternative energy resources. Solar energy is the most eminent energy resource which is completely free from pollution and fuel. However, the problem occurs when it comes to efficiency under different atmospheric conditions such as varying temperature and solar irradiance. To achieve its maximum efficiency, an algorithm of maximum power point tracking (MPPT) is needed to fetch maximum power from the photovoltaic (PV) system. In this article, a nonlinear backstepping terminal sliding mode control (BTSMC) is proposed for maximum power extraction. The system is finite-time stable and its stability is validated through the Lyapunov function. A DC-DC buck-boost converter is used to deliver PV power to the load. For the proposed controller, reference voltages are generated by a radial basis function neural network (RBF NN). The proposed controller performance is tested using the MATLAB/Simulink tool. Furthermore, the controller performance is compared with the perturb and observe (P&O) MPPT algorithm, Proportional Integral Derivative (PID) controller and backstepping MPPT nonlinear controller. The results validate that the proposed controller offers better tracking and fast convergence in finite time under rapidly varying conditions of the environment.

Improved krill herd algorithm based sliding mode MPPT controller for variable step size P&O method in PV system under simultaneous change of irradiance and temperature

In recent years, Photovoltaic (PV) systems have been received great attention all over the words as they are sustainable, unlimited and environmentally friendly energy. However, it is required for the PV system to apply a tracking controller to guarantee efficient operation by extracting the maximum power, which named maximum power point tracking (MPPT) method. Due to the simple structure, the conventional perturb and observe (P&O) MPPT algorithm is very popular in the literature. Nevertheless, conventional methods show inaccurate performance, particularly when high variations occur in irradiance, resulting in fluctuations around the MPP. To deal with these challenges, a novel technique on the basis of the variable-step size of P&O MPPT and sliding mode controller (SMC) adjusted by the θ-modified krill herd (θ-MKH) algorithm is presented. The θ-MKH algorithm is utilized to fine-tune the optimal SMC parameters to drive the variable step of the classical P&O algorithm. Simulations are prepared to compare the performance of the suggested scheme with conventional methods by considering simultaneous fast changes of irradiance and temperature. The results show that the suggested scheme have proper performance in both transient and steady-state, particularly under quickly varying climate circumstances.

WITHDRAWN: Constant power generation in single and two stage PVPPS with CPG and MPPT modes of operation

Abstract Photovoltaic Power Plants (PVPPs) functions through the tracking of maximum power point with a view for maximizing the conversion efficiency of the power plants. Grid voltage disturbances, over voltages overloading etc., are some newer challenges faced by the power system operators while operating this photovoltaic power plants. Maximum Power Point Tracking (MPPT) algorithm and Constant Power Generation (CPG) algorithm are used for obtaining maximum output voltage from these power plants. Often the output voltage of the PVPPs varies according with the grid disturbances, overloading and overvoltage conditions. The MPPT and CPG algorithms are introduced in these power plants to stabilize the output voltage levels. This paper of study encapsulates a single algorithm for gaining a maximum stable output voltage with less oscillation and which gives a fast dynamic response. This algorithm is formed by the combination of both MPPT-Perturb and Observe and CPG algorithms (MPPTPO-CPG). This algorithm would be suitable enough to get a constant power output from the Photovoltaic Power Plants (PVPPs) and is suitable for both single-stage and two-stage Photovoltaic Power Plants. The MPPT algorithm is utilized for fetching the maximum power output from the PVPPs. Maximum output voltage; fast dynamic response and higher oscillation are gains of using the MPPT algorithm. Output voltage is destabilized during higher oscillation and hence constant power generation algorithm is introduced, which gives low oscillation and maximum power output, but the dynamic response is slow. Hence these two algorithms are combined to a new algorithm that provides maximum output voltage, efficiency and a fast dynamic response. The boost converter is the eminent component used in the proposed system for achieving CPG and MPPT control.

An Energy Management Strategy for DC Microgrids with PV/Battery Systems

Recently, direct current (DC) microgrids have gained more attention over alternating current (AC) microgrids due to the increasing use of DC power sources, energy storage systems and DC loads. However, efficient management of these microgrids and their seamless integration within smart and energy efficient buildings are required. This paper introduces an energy management strategy for a DC microgrid, which is composed of a photovoltaic module as the main source, an energy storage system (battery) and a critical DC load. The designed MG includes a DC-DC boost converter to allow the PV module to operate in MPPT (Maximum Power Point Tracking) mode or in LPM (Limited Power Mode). Furthermore, the system uses a DC-DC bidirectional converter in order to interface the battery with the DC bus. The proposed control strategy manages the power flow among different components of the microgrid. It takes the battery lifetime into consideration by applying constraints to its charging/discharging currents and state-of-charge (SoC). The proposed system is simple and efficient in supplying DC loads, since as it’s not using complex algorithms either for MPPT or for energy management. The studied DC microgrid is designed and modeled using Matlab/Simulink software. The load demand is satisfied while ensuring good performance and stability of the system. The controller design, analysis, and simulation validation results are presented and discussed under various operating modes.

Autonomous energy management strategy for a hybrid power system of more-electric aircraft based on composite droop schemes

In this paper, an autonomous energy management strategy is proposed for multiple batteries, photovoltaic (PV) generators and fuel-cells (FCs) s in a promising future power system of more-electric aircraft (MEA). This provides a more comprehensive and generalized approach to coordinate those three types of power sources. The operation of each power source is autonomously coordinated to maintain the balance between power generation and consumption, while ensuring controlled charging/discharging of the batteries in the hybrid power system. To achieve this objective, the dc bus voltage are configured to follow the specifically designed multi-segment V/P characteristic curves. First, a state-of-charge (SoC) based droop control strategy is applied to batteries to support dc bus voltage and balance their SoCs. Second, a novel adaptive power control strategy with a simple algorithm is designed for PV generators, which can seamlessly and rapidly regulate the output power off or return maximum power point tracking (MPPT) mode in accordance with the actual dc bus voltage. Third, the proposed control system releases the stress of batteries, which can extend these lifetime due to the reduced charging/discharging cycles. Furthermore, the stability of the whole hybrid system with the proposed control strategy is analyzed. The effectiveness of the proposed control strategy is validated by the real-time controller hardware-in-loop (HIL) platform.

Wake‐effect aware optimal online control of wind farms: An explicit solution

Wake effects impose significant aerodynamic interactions among wind turbines. To improve the wind farm operating performance, practical wind farm online control considering wake effects becomes very important. To achieve online optimal wind farm control while responding to grid demands, this paper proposes a novel optimal wind farm supervisory control (SC) model and its explicit solutions. From the controller modelling perspective, the two major wind farm operating modes, the maximum power point tracking mode and the set-point tracking mode, are first analysed and unified in one optimisation model while considering wake effects. In this way, wind farm power production and rotor kinetic energy reserve can be simultaneously considered to conveniently modify the operation mode in response to different grid demands. Aside from controller modelling, the collocation method is first introduced to address the online application problem of such wake-effect aware optimal WF control. Although a few optimisation algorithms have been proposed to find the optimum offline, online optimal control is still challenging because of the computational complexity brought by wake model non-linearity and non-convexity. The proposed collocation method explicitly approximates the optimal solutions to the proposed supervisory control model, through which only a direct algebraic operation is required for online optimal control instead of repeated optimisations. Case studies are carried out on different wind farms under various wind conditions, showing that the wind farm power production potential and releasable power reserve are improved compared to traditional greedy control in both modes. The accuracy of the collocation method is verified. A detailed analysis of the wind farm production capacity under different wind speeds and directions is also provided.

Enhanced modelling of doubly fed induction generator in load flow analysis of distribution systems

This paper presents an accurate framework for incorporating the doubly fed induction generator based wind farms in load flow analysis of distribution systems. The proposed model for doubly fed induction generator is based on an accurate equivalent circuit and also takes into consideration the voltage dependent reactive power limits associated with the doubly fed induction generator. In addition, the developed approach is capable of handling a doubly fed induction generator operating in either maximum power point tracking or non-maximum power point tracking modes. The proposed PQ model of doubly fed induction generator easily fits into the forward–backward technique that is typically employed for obtaining the load flow solution of distribution networks. Test results on 19-bus and 133-bus systems are reported to indicate the effectiveness of the proposed approach.

Control and stability analysis of DC microgrid system including wind and solar generation sources and grid‐connected voltage source converter

SummaryThe study system in this paper is a grid‐connected DC microgrid system comprising PV and wind generation sources, resistive and constant power loads (CPLs), and grid‐connected VSC. The VSC keeps the DC link voltage constant, and the wind and PV sources operate in maximum power point tracking (MPPT) mode, and thus, the DC–DC converters related to these sources act such as controlled current sources behaving similar to negative CPLs. The study system suffers from the stability under high CPL penetration and weak AC grid conditions. Hence, this paper investigates and enhances the system stability under both high CPL penetration and weak AC grid conditions. To do this, modal and small‐signal stability analysis of the system is carried out, and then, as the main findings, impacts of the wind and PV sources output powers, CPL power, and AC grid short‐circuit power on the system stability are studied. Next, as the main contribution, VSC control structure is modified by adding stabilizing signals to enhance the system stability under high CPL penetration, reduced output powers of the wind and PV sources, and weak AC grid conditions. At the end, several simulation results verify the theoretical results at different conditions.

A Grid-tied PV Inverter with Sag-severity- independent Low-voltage Ride Through, Reactive Power Support, and Islanding Protection

This paper proposes a grid-tied photovoltaic (PV) inverter capable of low-voltage ride through (LVRT), reactive power support, and islanding protection. Unlike other LVRT inverters, the proposed inverter is independent of sag severity while maintaining the maximum power-point tracking (MPPT) under normal and faulty conditions. The addition of an energy storage buffer stage mitigates the DC-link voltage surge during sags. At the same time, the inverter injects the reactive power during back-to-back sags of variable depths. The control system of the inverter generates the appropriate reference signals for normal, LVRT, and anti-islanding modes while the MPPT continues running. The salient features of the proposed inverter are: (1) active power injection under normal grid conditions; (2) sag-depth independent LVRT with reactive power support; (3) no DC-link fluctuations; (4)continuous MPPT mode; and (5) simultaneous LVRT and anti-islanding support during a grid outage. The inverter demonstrates an uninterrupted operation and seamless transition between various operating modes. Simulations and the experimental prototype have been implemented to validate the efficacy of the proposed PV inverter.

Modified Maximum Power Point Tracking Algorithm under Time-Varying Solar Irradiation

Solar photovoltaic (PV) energy is one of the most viable renewable energy sources, considered less polluting than fossil energy. However, the average power conversion efficiency of PV systems is between 15% and 20%, and they must operate with high efficiency. Photovoltaic cells have non-linear voltage–current characteristics that are dependent on environmental factors such as solar irradiation and temperature, and have low efficiency. Therefore, it becomes crucial to harvest the maximum power from PV panels. This paper aims to study and analyze the most common and well-known maximum power point tracking (MPPT) algorithms, perturb and observe (P&O) and incremental conductance (IncCond). These algorithms were found to be easy to implement, low-cost techniques suitable for large- and medium-sized photovoltaic applications. The algorithms were tested and compared dynamically using MATLAB/Simulink software. In order to overcome the low performance of the P&O and IncCond methods under time-varying and fast-changing solar irradiation, several modifications are proposed. Results show an improvement in the tracking and overall system efficiencies and a shortened response time compared with original techniques. In addition, the proposed algorithms minimize the oscillations around the maximum power point (MPP), and the power converges faster.

An Intelligent Controlling Method for Battery Lifetime Increment Using State of Charge Estimation in PV-Battery Hybrid System

In a photovoltaic (PV)-battery integrated system, the battery undergoes frequent charging and discharging cycles that reduces its operational life and affects its performance considerably. As such, an intelligent power control approach for a PV-battery standalone system is proposed in this paper to improve the reliability of the battery along its operational life. The proposed control strategy works in two regulatory modes: maximum power point tracking (MPPT) mode and battery management system (BMS) mode. The novel controller tracks and harvests the maximum available power from the solar cells under different atmospheric conditions via MPPT scheme. On the other hand, the state of charge (SOC) estimation technique is developed using backpropagation neural network (BPNN) algorithm under BMS mode to manage the operation of the battery storage during charging, discharging, and islanding approaches to prolong the battery lifetime. A case study is demonstrated to confirm the effectiveness of the proposed scheme which shows only 0.082% error for real-world applications. The study discloses that the projected BMS control strategy satisfies the battery-lifetime objective for off-grid PV-battery hybrid systems by avoiding the over-charging and deep-discharging disturbances significantly.

A Single Phase Grid Connected PV System working in Different Modes

The current grid standards for the single-phase residential PV system expect it to operate at Maximum Power Point Tracking (MPPT) mode under normal operating conditions and to maintain the voltage profile whenever a grid fault occurs. The proposed system supplies power to the load under stable conditions and the PV system works in MPPT mode. When the fault occurs at the Point of Common Coupling (PCC) and the voltage is reduced, the proposed controller maintains the voltage profile by injecting the current fed by the current controller at the PCC. The controller shifts from MPPT to the faulty mode and maintains voltage as per grid requirements. During islanding conditions, the PV system successfully caters to the requirements of the load by shifting the control from MPPT to islanding mode. When the PV system is in operation the power quality is enhanced

High-Performance Photovoltaic Constant Power Generation Control With Rapid Maximum Power Point Estimation

Photovoltaic (PV) constant power generation (CPG) control is regarded as an advanced active power control by limiting the maximum feed-in power in order to avoid the adverse impacts of high-penetration PV systems such as overloading and overvoltage. Conventional CPG strategies show obvious limitations in terms of the dynamics response, oscillations during the steady state, and the estimation speed of limited power points (LPPs). In this article, a novel CPG control with the rapid approach to LPPs is proposed with the estimation of maximum power point (MPP), which guarantees fast converging speed in response to rapid changes in environmental conditions and low power oscillations for the steady state. Specifically, the proposed control allocates the operating point at the left-hand side of the MPP, which can not only avoid the instability issue but also simplify the MPP and LPP estimation according to the single-diode PV equivalent model. Furthermore, based on the estimated available power $P_{\rm avi}$, the proposed CPG control contributes a direct solution in approaching the region around LPP or MPP, which improves the converging speed under environmental-changing conditions. Thus, regardless of the changes in irradiance or temperature, high-performance and reliable operation are ensured by switching the maximum power point tracking mode and CPG mode smoothly. The proposed control can be directly applied for the existing PV system and no additional hardware devices such as irradiance sensors are required, which is cost effective. A systematic comparison of the proposed control with other advanced CPG strategies was made under various scenarios and the advantages of the proposed control were validated experimentally.

Development and performance analysis of intelligent fault ride through control scheme in the dynamic behaviour of grid connected DFIG based wind systems

As the penetration of wind power increases, the fault ride through requirements imposed by grid code is important in grid connected wind systems. The wind systems should remain connected to the grid during grid faults satisfying the grid code which ensures grid stability during fault and post fault conditions. This paper proposes an intelligent fault ride through strategy for Doubly Fed Induction Generators (DFIG) based Wind Energy Conversion Systems (WECS) to achieve real and reactive power control during grid faults. The transient behaviour of the system is investigated under normal conditions and during grid faults. A fuzzy based wind speed estimation method in Maximum Power Point Tracking (MPPT) mode under normal conditions and coordinated Genetic Algorithm based Real-Reactive (GA-PQ) controller with DC chopper in Fault Ride Through (FRT) mode during grid faults is developed in this work. The proposed control scheme provides smooth operation of DFIG during grid faults by controlling the rotor and grid side converters, providing reactive power support to the grid and relieving stress on power converters thereby achieving system stability. The proposed strategy maintains the system parameters during the grid faults by suppressing the rotor and stator over current, dc link voltage overshoot, power oscillations and support the grid voltage under both balanced and unbalanced grid fault conditions with different voltage dips at PCC. Computer simulations in time-domain are performed by verifying the MPPT and FRT capability of the proposed strategy for 6.5MW grid connected DFIG based WECS in MATLAB/SIMULINK 2018b. The proposed coordinated intelligent PQ and DC chopper FRT strategy is compared against existing FRT schemes like crowbar, SDBR, DC Chopper, PQ controller and its hybrid combinations which yields satisfactory results. The proposed scheme is also validated in Opal-RT hardware for LLG fault at 75% dip in voltage. The simulation and real time results observed in the work station demonstrates the effectiveness of the proposed strategy in enhancing the FRT capability of the system.