Power Tracking Method Research Articles

Detuning analysis and power tracking of dual‐ended resonant circuit based on improved variable‐step perturbation observation for wireless power transfer system

AbstractA power tracking method based on improved variable‐step perturbation observation approach has been proposed in this paper. This method is aimed at addressing the detuning issues caused by capacitor parameter drift in MCR‐WPT systems based on S‐S compensation circuits. Compared with traditional tuning methods, the proposed method has fast response, high accuracy, low complexity, and less prone to over‐tracking. Firstly, a mathematical model of the system based on the detuning factor has been established. Secondly, the impact of different detuning conditions on the system at the initial resonant frequency has been studied. Thirdly, the response characteristics of the system to different frequencies under different detuning conditions have been studied. Fourthly, based on the above researches, an improved variable‐step perturbation observation method based on the single‐step power drop factor has been proposed. Finally, an experimental platform was constructed, and relevant experiments were conducted. Experimental results validate the effectiveness of power tracking under different detuning conditions, with the lowest transmission efficiency being 81.51%.

A CC/VC‐based power tracking method for photovoltaic inverter operated in voltage control mode

AbstractThe active power control of photovoltaic (PV) inverters without energy storage can flatten the fluctuating power and support the voltage amplitude and frequency of the grid. When operated in grid‐forming voltage‐control mode, because the PV power can change rapidly and widely, the PV inverter needs to track the power commands quickly and precisely. Traditionally, this goal is achieved with the estimation of PV power curve or PI‐based multiple‐loop feedback control, where flexibility, availability and accuracy are not satisfactory. Therefore, a CC/VC‐based power tracking (CVPT) method is proposed, which only uses single‐loop in control. The proposed method does not need to tune multiple loops and can respond faster, which is important for grid‐forming voltage control. Furthermore, the different operating modes due to the limitation of PV maximum power are analysed, and a mode switch method is proposed. Simulation and experimental results demonstrate that the PV inverter can cope with power disturbances from both the power and grid sides and maintain the quality of grid voltage.

Communication-Free Pulsed Power Distribution and Tracking Method for Hybrid Energy Storage System Based on Active Disturbance Rejection Control

Communication-Free Pulsed Power Distribution and Tracking Method for Hybrid Energy Storage System Based on Active Disturbance Rejection Control

Maximum power tracking method for roof solar cells in intelligent buildings based on particle swarm optimisation

Maximum power tracking method for roof solar cells in intelligent buildings based on particle swarm optimisation

Lyapunov based Control Strategy for DFIG based Wind Turbines to Enhance stability and Power

The Doubly Fed Induction Generators (DFIG) based wind turbine is fed with maximum power point tracking is presented in this paper in proposed technique the proportional coefficient tuned adaptively as per wind changes and compare with traditional approaches. This novel method uses three control laws to adjust the proportional gain adaptively to wind speed variations. The intended electrical torque is determined via feedback linearization in the first control law, which makes the assumption that the power capture coefficient and target rotor speed are instantly determined. The second control law uses a Lyapunov-based analysis to determine the power capture coefficient as per changes in wind speed, and the third control law establishes the required rotor speed. As a result of these control principles, the operating point of the turbine shifts in a direction that increases the power capture coefficient, leading the rotor speed to adaptively adjust in the direction of the desired speed. The proposed maximum power tracking method differentiates itself from the perturb-and-observe strategy by removing the need to include a dither or perturbation signal and reliably slipstram the trajectory of maximum power points even in the circumstance of a sudden change in wind velocity, which can cause the perturb-and-observe practice to fail.

Differential energy pricing of industrial park operator based on potential game considering public loss allocation

With development of industrial aggregation, the industrial park energy operator (IPEO) offers energy supply services to factories with varying energy consumption requirements. Nevertheless, the unified energy pricing model is not conducive to the park operator's ability to attain a justifiable recuperation of energy supply expenses. To address these issues, a differential pricing strategy for the potential game of IPEO is proposed in this paper to achieve clean and efficient operation of industrial electric-heat energy systems (EHES). Firstly, a mechanism for allocating public losses is established in the pricing process, and the power loss of the network is precisely allocated to the user side using the complex power tracking method. Second, a potential game model for IPEO and its users is established based on the different interests of the participants. IPEO releases energy prices to users by maximizing energy sales as a profit function and considering the output of energy production facilities and purchased electricity. The user minimizes the cost of energy by considering the profit function, which takes into account the energy storage discharge and flexible load adjustment. Finally, the feasibility and validity of the proposed model are verified by comparing several cases. The simulation results show that the proposed model can fully consider the autonomy of the game participants and effectively enhance the benefits of each participant.

A novel loss allocation method applicable for any desired network topology

Due to the expansion of power networks in response to the increase in total load demand, the complexity regarding power systems transmission networks’ configuration has been increased. Similarly, with the advent of local energy markets and transactive energy concept, power distribution networks are undergoing a fundamental change. In this respect, numerous agents are transacting power within both distribution and transmission networks. Therefore, as more power is transacted among agents in different energy networks, power networks face higher power losses. Dealing with the financial outcomes of these losses, a general accurate yet fast method for loss allocation in power networks is of utmost importance. In response, this paper proposes a novel loss allocation framework based on the power tracking method that is applicable for any desired network topology within both transmission and distribution networks. In this regard, at first, a new method is proposed to obtain how the optimal scheduled generation of each production unit should be allocated to each specific load of the network. Then, it is obtained that how these transactions are flown in each line of the network. In the next step, the exact losses in each line resulted from distinct transactions between each pair of agents in the network are obtained. Finally, how each specific transaction contributes to the total losses of the network can be calculated. By implementing the proposed framework on a modified IEEE 14-bus test system and a 69-bus IEEE distribution network, the applicability and effectiveness of the proposed method is demonstrated by the numerical results. The results indicate that the proposed method can be implemented in any network and with any scale.

Consensus control for distributed power tracking by device-level digital twin agents

Abstract: The development of electronics and software has resulted in the ability of twin agents to act as digital counterparts for the optimization, control, and monitoring of real power grids. When increasing regulation resources are connected to the power grid, is challenging for independent system operators to use a centralized controller to achieve power tracking and balance. Therefore, the present study applied device-level-based digital twins to monitor physical signals for computer-aided design for power tracking. Moreover, a consensus control-based distributed power tracking system is proposed for the physical-model simulation of the power grid. A communication network was also designed for realistic signal exchange. The combination of the proposed distributed power tracking method and communication network can accelerate computational efficiency and protect the privacy of the regulation resources. Finally, the performance of the proposed distributed power tracking method is validated in a simulation system with 10 regulation resources.

Design of Control System for Multistage Distillation Seawater Desalination Device Driven by Photovoltaic-Thermal

This research proposes a seawater desalination system driven by photovoltaic and solar thermal energy for remote regions such as islands and seaside villages where fresh water is not accessible. The performance of this system is demonstrated through experiments, and the main concerns are the output of the photovoltaic power generation system, power quantity, water yield, and the loads under different solar irradiance and temperature. In this system, a PLC is used as the controller to adjust the water pump by the collection and processing of sensor data. A load switching time system is designed to select different operating schemes under different environments in order to save energy. The control method of this system is developed to ensure that the photovoltaic power generation system does not undervoltage while maintaining the normal operation of the desalination system. An improved Perturbation and Observation (P&O) algorithm is also proposed as a new Maximum Point Power Tracking (MPPT) method to solve the problem of misjudgment and oscillation after tracking the maximum power point (MPP) in the traditional P&O algorithm. The simulation test in the MATLAB/Simulink environment shows that when external irradiance changes, the improved P&O algorithm can track the MPP faster than the traditional P&O algorithm, and the amplitude of oscillation on the MPP is smaller. The hardware experiments show that this system can operate stably and flexibly, and it is capable of producing 5.18 kWh of electric energy and 335.81 kg of freshwater per day. The maximum yield of the unit can reach 565.75 kg per day and the maximum daily power generation is 8.12 kWh.

Analog Maximum Peak Power Tracking Techniques for Small Satellites

This work describes the implementation of three Maximum Peak Power Tracking methods devised for small satellites. The three methods are the Analog oscillating Maximum Power Point Tracking, the Analog Global Maximum Peak Power Tracking and the Analog Global Maximum Output Power Tracking. An interplanetary mission (Mars-Asteroid belt) with complex power-voltage solar array characteristics, including several local maximum power points, is considered to evaluate each peak power tracking technique. The three peak power tracking techniques have been integrated in an unregulated battery bus topology using synchronous buck converters as solar array regulators. High reliability design is achieved using analog electronic parts with space-qualified counterparts. Each peak power tracking method has been optimized individually for the best performance and then compared with the others. The experimental validation suggests that the preferred method strongly depends on the expected power-voltage solar array characteristics and mission parameters.

Maximum Power Tracking Method of Photovoltaic Sequence Based on Nonlinear Particle Swarm Optimization Algorithm

Maximum Power Tracking Method of Photovoltaic Sequence Based on Nonlinear Particle Swarm Optimization Algorithm

A hybrid adaptive-prediction maximum power point tracking method for the smart city with massive photovoltaic

The partial shadow condition seriously affects the efficiency of the photovoltaic system in the modern city with dense built and other occlusions. From this, the characteristic curve of the photovoltage system shows multi-peak, which further increases the difficulty of getting photovoltaic systems to operate at maximum efficiency. As an efficient technique, the intelligent optimized maximum power point tracking method relies on initialization information and is difficult to balance the tracking performance. Therefore, a hybrid adaptive-prediction maximum power tracking method is proposed in this paper. Firstly, the neighborhood range of the maximum power points is located by the fuzzy predicted mechanism at the upper layer. Secondly, on the bottom layer, based on improving the Cuckoo search algorithm, the proposed method uses an interpolation function fitting curve to guide the particles to converge accurately on the bottom layer. At the same time, the output voltage of the system under an open loop is directly controlled by the duty cycle of the control signal, which improves the universality of the method. Finally, the simulation results show that the proposed method is superior to other advanced methods in tracking speed and with smaller power oscillations and comparable tracking accuracy, for which the proposed method is suitable for the city with complex environments and dense buildings.

Collaborative power tracking method of diversified thermal loads for optimal demand response: A MILP-Based decomposition algorithm

Thermal load is an important type of demand response (DR) resources to maintain the power balance of regional electricity-heating energy systems. However, the diversity of power-consuming patterns and time series coupling of production processes arise challenges for precisely tracking the scheduled command of industrial and domestic thermal loads. This paper proposes a feasible solution to achieving collaborative scheduling of diversified thermal loads meanwhile optimizing the tracking performance of scheduled power, via a mixed integer linear programming (MILP) based decomposition algorithm. The power-temporal granularity is firstly introduced and modeled to characterize the available regulated capacity of diversified thermal loads in each power regulation event. Then, the time series coupling model among multiple thermal devices is established to describe the coupling relationship in production processes. On this basis, the diversified thermal loads are co-regulated in the considered system to accomplish the decomposition objectives and without taking up extra generation and storage regulation resources. Case studies based on real data of a regional thermal loads are conducted, which demonstrates the feasibility and effectiveness of proposed method in improving comprehensive benefits and reducing power deviation.

Maximum Power Point Tracking Algorithm for Advanced Photovoltaic Systems

Photovoltaic (PV) systems are the major nonconventional sources for power generation for present power strategy. The power of PV system has rapid increase because of its unpolluted, less noise and limited maintenance. But whole PV system has two main disadvantages drawbacks, that is, the power generation of it is quite low and the output power is nonlinear, which is influenced by climatic conditions, namely environmental temperature and the solar irradiation. The natural limiting factor is that PV potential in respect of temperature and irradiation has nonlinear output behavior. An automated power tracking method, for example, maximum power point tracking (MPPT), is necessarily applied to improve the power generation of PV systems. The MPPT methods undergo serious challenges when the PV system is under partial shade condition because PV shows several peaks in power. Hence, the exploration method might easily be misguided and might trapped to the local maxima. Therefore, a reasonable exploratory method must be constructed, which has to determine the global maxima for PV of shaded partially. The traditional approaches namely constant voltage tracking (CVT), perturb and observe (P&O), hill climbing (HC), Incremental Conductance (INC), and fractional open circuit voltage (FOCV) methods, indeed some of their improved types, are quite incompetent in tracking the global MPP (GMPP). Traditional techniques and soft computing-based bio-inspired and nature-inspired algorithms applied to MPPT were reviewed to explore the possibility for research while optimizing the PV system with global maximum output power under partially shading conditions. This paper is aimed to review, compare, and analyze almost all the techniques that implemented so far. Further this paper provides adequate details about algorithms that focuses to derive improved MPPT under non-uniform irradiation. Each algorithm got merits and demerits of its own with respect to the converging speed, computing time, complexity of coding, hardware suitability, stability and so on.

Intelligent Control for Islanded Operation of Doubly Fed Induction Generator based Wind Energy Conversion System coupled to DC Micro-Grid

A single parameter based fuzzy model for controlling the Doubly Fed Induction Generator (DFIG) based Wind Energy Conversion System (WECS) to operate in islanded mode is discussed in this paper. The system employs Rotor Side Converter (RSC) and Stator Side Converter (SSC) connected back-to-back to a dc micro grid. The control scheme for both RSC and SSC employ cascaded control loops: Outer speed and inner current loop for RSC and Outer voltage and inner current loop for SSC respectively so as to provide better response during dynamic conditions. In both control schemes, the outer loop is processed and the error along with its derivative is found to produce a single variable for feeding the fuzzy model. As only one variable is involved, less memory occupancy, less complex control and computation is faster. The RSC control employs the speed reference obtained through power calculator based maximum power tracking method which is novel in its kind. The SSC employs the terminal voltage at PCC for the outer voltage loop. The simulation of the system under constant and variable wind speeds is carried out using Simpower Systems toolbox of MATLAB. The results indicate that the efficacious working of the system with faster response to dynamic variations.

Online Control of Smart Inverter for Photovoltaic Power Generation Systems in a Smart Grid

The main purpose of this study is to engage in research on a grid-connected photovoltaic (PV) power generation system smart inverter. The research content includes a smart maximum power point tracking (MPPT) controller and an inverter with power regulation. First, use the PSIM software package to establish the simulation environment of the grid-connected photovoltaic power generation system and use the Sanyo HIP-186BA19 photovoltaic module to form a 744 W system for simulation. In order to enable the photovoltaic module array (PVMA) to output the maximum power under different solar insolation and ambient temperature, the architecture is based on the extension theory-based smart MPPT method to improve the dynamic response and steady-state performance of photovoltaic power generation systems compared to perturb and observed (P&O) MPPT. When the sunshine is 1,000 W/m2, the photovoltaic power generation system adopts the extension theory-based maximum power tracking method. The time required to track the maximum power point is only 0.32 s, and the steady-state ripple is only 4.127 W. However, using the traditional P&O method requires 0.741 s to track the maximum power point, and the steady-state ripple reaches 18.131 W. Thus, the dynamic response speed of the maximum power tracking method proposed is 50% faster than that of the P&O method. The steady-state performance is also better compared to the P&O method. At the same time, a simple proportional-integral (PI) controller is used to regulate the DC-link voltage, output voltage, and current of the inverter to make the voltage of the grid-connected point stable at an effective value of 220 V. Then, the voltage-power control technology is added to the photovoltaic grid-connected inverter, and a simple proportional-integral controller is used to regulate the output of the smart inverter reactive power to improve the power quality of grid voltage. Finally, simulation and experimental results are used to verify the effectiveness of the regulation performance of the developed smart inverter.

A new adaptive integral back stepping fractional order sliding mode control approach for PV and wind with battery system based DC microgrid

DC microgrids are very much focused on the present scenario due to the increase of power applications. In this paper, a new adaptive integral back stepping fractional-order sliding mode control (AIBFOSMC) is proposed for the DC microgrid in which renewable distributed energy sources with energy storage systems are presented. Initially, mathematical equations are developed for the proposed DC microgrid and then control equations for PV with wind and battery are derived. To extract the maximum power from the PV and wind systems, an improved incremental conductance (IIC) based maximum power tracking method (MPPT) is introduced in this paper. The main aim of this control is to stabilize the DC bus voltage under different operating conditions such as generation change, DC load change, temperature change and DC faults. The stability of the proposed controller is estimated by the Lyapunov theory. The performance of the proposed controller is tested in terms of chattering elimination in MATLAB/Simulink environment during different uncertainty conditions. The proposed controller superiority is verified by comparing the proposed controller results with the different existing controllers like proportional integral (PI) control and sliding mode control (SMC).

Enhancing the Power Tracking Method in Hybrid System using Artificial Neural Network Integrated with Fuzzy Controller

Objective: To search a point where huge amount of power can be coerced from hybrid system under continuously varying environmental conditions. Methods/Statistical Analysis: Artificial Neural Network integrated with Fuzzy Controller (ANFIS) is proposed to enhance the power tracking method in Hybrid System. This mode of extracting maximum power is highly accurate and it is highly adopted for eco- friendly changes. Due to fast tracking of maximum power, the overall efficiency is highly increased. The projected system has very less settling time and very low overshoot. Findings: This study contributes to a controller design using ANFIS for rapid tracking of maximum power in hybrid system. Application: This controller can be used in all renewable energy based hybrid system which has become a popular electrical energy source. The performance is upgraded by settling time, overshoot and accuracy. Keywords: ANFIS Controller, MPPT, Solar PV Array, Wind Turbine

High Efficiency and Power Tracking Method for Wireless Charging System Based on Phase-Shift Control

The paper presents optimal operating point tracking algorithm for wireless charging system using identical coupling coils providing us to meet simultaneously high efficiency and high transmitted power under varied load and detuning conditions. The proposed method is suitable either for purely resistive load or battery load and it is based on phase-shift control between the primary and the secondary voltage. The paper also gives an intuitive mathematical description of the key control idea and demonstrates its operational abilities. The proposed algorithm is finally implemented into digital signal processor (DSP) and tested on 4 kW laboratory prototype of shielded wireless power transfer system.

Improvement of real‐time power tracking in microgrid using multi‐agent system

A multi‐agent system (MAS) provides flexible and intelligent control schemes for microgrids and their units. However, a certain period of time is required for a controllable source (CS) to change its output power, and the communication delay poses a challenge for real‐time tracking of CS output power in MAS control, an important factor affecting the transient performance of MAS power coordination. In this paper, we propose and emulate a new power tracking method based on the communication inside MAS about the change of output variation speed in every CS together with a timestamp for each change. The MAS emulates and tracks the total output power of all CSs in real time. Compared to the conventional method, the emulation results indicate that this new method has a significantly better real‐time performance, especially for a large number of CS and under more undesirable communication conditions. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.