Showing papers on "Maximum power principle published in 2017"

A comprehensive review on solar PV maximum power point tracking techniques

Abstract: In recent years solar energy has received worldwide attention in the field of renewable energy systems Among the various research thrusts in solar PV, the most proverbial area is extracting maximum power from solar PV system Application dof Maximum Power Point Tracking (MPPT) for extracting maximum power is very much appreciated and holds the key in developing efficient solar PV system In this paper, a state of the art review on various maximum power point techniques for solar PV systems covering timeworn conventional methods and latest soft computing algorithms is presented To date critical analysis on each of the method in terms of (1) tracking speed, (2) algorithm complexity, (3) Dynamic tracking under partial shading and (4) hardware implementation is not been carried out In this regard the authors have attempted to compile a comprehensive review on various solar PV MPPT techniques based on the above criteria Further, it is envisaged that the information presented in this review paper will be a valuable gathering of information for practicing engineers as well as for new researchers

A Novel MPPT Algorithm Based on Particle Swarm Optimization for Photovoltaic Systems

Abstract: This paper describes a new maximum-power-point-tracking method for a photovoltaic system based on the Lagrange Interpolation Formula and proposes the particle swarm optimization method. The proposed control scheme eliminates the problems of conventional methods by using only a simple numerical calculation to initialize the particles around the global maximum power point. Hence, the suggested control scheme will utilize less iterations to reach the maximum power point. Simulation study is carried out using MATLAB/SIMULINK and compared with the Perturb and Observe method, the Incremental Conductance method, and the conventional Particle Swarm Optimization algorithm. The proposed algorithm is verified with the OPAL-RT real-time simulator. The simulation results confirm that the proposed algorithm can effectively enhance the stability and the fast tracking capability under abnormal insolation conditions.

A Novel Flower Pollination Based Global Maximum Power Point Method for Solar Maximum Power Point Tracking

Abstract: To maximize solar photovoltaic (PV) output under dynamic weather conditions, maximum power point tracking (MPPT) controllers are incorporated in solar PV systems. However, the occurrence of multiple peaks due to partial shading adds complexity to the tracking process. Even though conventional and soft computing techniques are widely used to solve MPPT problem, conventional methods exhibit limited performance due to fixed step size, whereas soft computing techniques are restricted by insufficient randomness after reaching the vicinity of maximum power. Hence, in this paper, a new flower pollination algorithm (FPA) with the ability to reach global peak is proposed. Optimization process in FPA method performs global and local search in single stage and it is a key tool for its success in MPPT application. The ruggedness of the algorithm is tested with zero, weak, and strong shade pattern. Further, comprehensive performance estimation via simulation and hardware are carried out for FPA method and are quantified with conventional perturb and observe and particle swarm optimization (PSO) methods. Results obtained with FPA method show superiority in energy saving and proved to be economical.

Slow Dynamics and Thermodynamics of Open Quantum Systems.

Abstract: We develop a perturbation theory of quantum (and classical) master equations with slowly varying parameters, applicable to systems which are externally controlled on a time scale much longer than their characteristic relaxation time. We apply this technique to the analysis of finite-time isothermal processes in which, differently from quasistatic transformations, the state of the system is not able to continuously relax to the equilibrium ensemble. Our approach allows one to formally evaluate perturbations up to arbitrary order to the work and heat exchange associated with an arbitrary process. Within first order in the perturbation expansion, we identify a general formula for the efficiency at maximum power of a finite-time Carnot engine. We also clarify under which assumptions and in which limit one can recover previous phenomenological results as, for example, the Curzon-Ahlborn efficiency.

MPPT of Photovoltaic Systems Using Sensorless Current-Based Model Predictive Control

Abstract: Variability in the solar irradiance level and ambient temperature of photovoltaic (PV) systems necessitates the use of maximum power point tracking (MPPT) of PV systems to ensure continuous harvesting of maximum power This paper presents a sensorless current (SC) MPPT algorithm using model predictive control (MPC) The main contribution of this paper is the use of model-based predictive control principle to eliminate the current sensor that is usually required for well-known MPPT techniques such as perturb and observe (P&O) By predicting the PV system states in horizon of time, the proposed method becomes an elegant, embedded controller that allows faster response and lower power ripple in steady state than the conventional P&O technique under rapidly changing atmospheric conditions This becomes possible without requiring expensive sensing and communications equipment and networks for direct measurement of solar irradiation changes The performance of the proposed SC-MPC-MPPT with reduced load sensitivity is evaluated on the basis of industrial European Efficiency Test, EN 50530, that assesses the performance of PV systems under dynamic environmental conditions The proposed control technique is implemented experimentally using dSPACE DS1007 platform to verify the simulation results

Power Reserves Control for PV Systems With Real-Time MPP Estimation via Curve Fitting

Abstract: In order for a photovoltaic (PV) system to provide a full range of ancillary services to the gird, including frequency response, it has to maintain active power reserves. In this paper, a new control scheme for the dc/dc converter of a two-stage PV system is introduced, which permits operation at a reduced power level, estimating the available power (maximum power point—MPP) at the same time. This control scheme is capable of regulating the output power to any given reference, from near-zero to 100% of the available power. The proposed MPP estimation algorithm applies curve fitting on voltage and current measurements obtained during operation to determine the MPP in real time. This is the first method in the literature to use the nonsimplified single-diode model for the determination of the MPP and the five model parameters while operating at a curtailed power level. The developed estimation technique exhibits very good accuracy and robustness in the presence of noise and rapidly changing environmental conditions. The effectiveness of the control scheme is validated through simulation and experimental tests using a 2-kW PV array and a dc/dc converter prototype at constant and varying irradiance conditions.

An Enhanced MPPT Method Combining Fractional-Order and Fuzzy Logic Control

Abstract: A fractional-order fuzzy logic control (FOFLC) method for maximum power point tracking (MPPT) in a photovoltaic (PV) system is presented. By combining the robustness of fuzzy logic with the accuracy of fractional order, the proposed method can improve the tracking accuracy in weather variations compared with the conventional fuzzy MPPT. First, the fractional-order factor is carefully selected according to the dynamic range of the fuzzy controller. It takes a bigger alpha factor in the first place to expand the fuzzy domain and shortens the time of searching for the MPP. When the maximum power point is approached, it uses a smaller the alpha factor to contract the fuzzy domain and eliminates the oscillations at the MPP. Therefore, the FOFLC in a PV system has rapid dynamic responses under environment variations and high tracking accuracy of the maximum power point. Second, MATLAB/Simulink software is employed to simulate a PV power system and verify the proposed algorithm by various simulations. The enhanced MPPT algorithm has been implemented on a field programmable gate array (FPGA) board. Finally, a boost dc–dc converter experiment has been carried out to evaluate the system performance. The simulation and experiment results show that this method can improve the transient and steady-state performance simultaneously.

Energy-Efficient Autonomous Solar Water-Pumping System for Permanent-Magnet Synchronous Motors

Abstract: This paper presents a novel stand-alone solar-powered water-pumping system, especially suited for usage in rural or remote areas. The system is primarily designed to reduce both cost and complexity, while simultaneously guaranteeing optimal utilization of the photovoltaic generator. The use of standard hardware and control architectures ensures ease of installation, service, and maintenance. The proposed solution consists of a water pump driven by a permanent-magnet synchronous motor, controlled by a conventional field oriented control scheme. The photovoltaic array is directly connected to the dc bus of the inverter, with no intermediate power conversion stages. A perturbation based extremum-seeking controller adjusts the motor speed reference to attain the maximum power point operation of the photovoltaic array. Both simulations and experimental results on a full-scale prototype support the effectiveness of the proposed system.

Fuzzy Logic Based MPPT Controller for a PV System

Abstract: The output power of a photovoltaic (PV) module depends on the solar irradiance and the operating temperature; therefore, it is necessary to implement maximum power point tracking controllers (MPPT) to obtain the maximum power of a PV system regardless of variations in climatic conditions. The traditional solution for MPPT controllers is the perturbation and observation (PO the reason why improving the results obtained with this algorithm has become an important goal to reach for researchers. This paper presents the design and modeling of a fuzzy controller for tracking the maximum power point of a PV System. Matlab/Simulink (MathWorks, Natick, MA, USA) was used for the modeling of the components of a 65 W PV system: PV module, buck converter and fuzzy controller; highlighting as main novelty the use of a mathematical model for the PV module, which, unlike diode based models, only needs to calculate the curve fitting parameter. A P&O controller to compare the results obtained with the fuzzy control was designed. The simulation results demonstrated the superiority of the fuzzy controller in terms of settling time, power loss and oscillations at the operating point.

Global Maximum Power Point Tracking Method for Photovoltaic Arrays Under Partial Shading Conditions

Abstract: The power–voltage characteristic of photovoltaic (PV) arrays displays multiple local maximum power points when all the modules do not receive uniform solar irradiance, i.e., under partial shading conditions (PSCs). Conventional maximum power point tracking (MPPT) methods are shown to be effective under uniform solar irradiance conditions. However, they may fail to track the global peak under PSCs. This paper proposes a new method for MPPT of PV arrays under both PSCs and uniform conditions. By analyzing the solar irradiance pattern and using the popular Hill Climbing method, the proposed method tracks all local maximum power points. The performance of the proposed method is evaluated through simulations in MATLAB/SIMULINK environment. Besides, the accuracy of the proposed method is proved using experimental results.

A comprehensive overview of maximum power extraction methods for PV systems

Abstract: The power generated by photovoltaic (PV) system depends on environment irradiance and temperature parameters. Hence, PV panels have nonlinear characteristics. In uniform condition, there is only one maxima point called maximum power point (MPP) where the PV system operates in maximum efficiency. However, in non-uniform condition such as partial shading effects, the PV system presents multiple maxima points on the correspondence P-V curve due to bypass diodes which makes more difficult to estimate global MPP. That is why it makes maximum power point tracking (MPPT) more important for PV systems to operate in maximum efficiency. In the literature, various types of MPPT technique and alternative solutions are used to detect true global MPP point among the other local MPPs. In addition, different PV array topologies, architectures and configurations are proposed to remove local maxima on the P-V curve. In this paper, most popular and used MPPT techniques, PV array configurations, system architectures and circuit topologies are discussed. In this context, this paper provides an overview of the operating principles discusses advantages and disadvantages and makes a general comparison between different solutions of each method.

Internal resonance and low frequency vibration energy harvesting

Abstract: A nonlinear vibration energy harvester with internal resonance is presented. The proposed harvester consists of two cantilevers, each with a permanent magnet on its tip. One cantilever has a piezoelectric layer at its base. When magnetic force is applied this two degrees-of-freedom nonlinear vibration system shows the internal resonance phenomenon that broadens the frequency bandwidth compared to a linear system. Three coupled partial differential equations are obtained to predict the dynamic behavior of the nonlinear energy harvester. The perturbation method of multiple scales is used to solve equations. Results from experiments done at different vibration levels with varying distances between the magnets validate the mathematical model. Experiments and simulations show the design outperforms the linear system by doubling the frequency bandwidth. Output voltage for frequency response is studied for different system parameters. The optimal load resistance is obtained for the maximum power in the internal resonance case. The results demonstrate that a design combining internal resonance and magnetic nonlinearity improves the efficiency of energy harvesting.

A Novel Grid-Connected PV System Based on MMC to Get the Maximum Power Under Partial Shading Conditions

Abstract: In the case of partial shading, the output power of the unshaded PV modules will be decreased by the influence of the shaded PV modules in one branch. In order to solve this problem, this paper proposes a novel topology for a PV power generation system by connecting a PV module to the capacitor in each submodule of a modular multilevel converter parallel. As partial shading occurs, the maximum power can be extracted by regulating the capacitor voltage to the maximum power point voltage. With this proposed topology, the maximum power tracking controller, the redundancy module controller, the voltage stability controller, and the grid-connected controller are studied. Simulation and experiment results show that comparing to the traditional topology, the proposed topology can greatly improve the output power of the PV system under the conditions of partial shading and features with low-voltage stress and high efficiency.

A quantum-dot heat engine operating close to the thermodynamic efficiency limits

Abstract: Cyclical heat engines are a paradigm of classical thermodynamics, but are impractical for miniaturization because they rely on moving parts. A more recent concept is particle-exchange (PE) heat engines, which uses energy filtering to control a thermally driven particle flow between two heat reservoirs. As they do not require moving parts and can be realized in solid-state materials, they are suitable for low-power applications and miniaturization. It was predicted that PE engines could reach the same thermodynamically ideal efficiency limits as those accessible to cyclical engines, but this prediction has not been verified experimentally. Here, we demonstrate a PE heat engine based on a quantum dot (QD) embedded into a semiconductor nanowire. We directly measure the engine's steady-state electric power output and combine it with the calculated electronic heat flow to determine the electronic efficiency $\eta$. We find that at the maximum power conditions, $\eta$ is in agreement with the Curzon-Ahlborn efficiency and that the overall maximum $\eta$ is in excess of 70$\%$ of the Carnot efficiency while maintaining a finite power output. Our results demonstrate that thermoelectric power conversion can, in principle, be achieved close to the thermodynamic limits, with direct relevance for future hot-carrier photovoltaics, on-chip coolers or energy harvesters for quantum technologies.

Distributed Laser Charging: A Wireless Power Transfer Approach

Abstract: Wireless power transfer (WPT) is a promising solution to provide convenient and perpetual energy supplies to electronics. Traditional WPT technologies face the challenge of providing Watt-level power over meter-level distance for Internet of Things (IoT) and mobile devices, such as sensors, controllers, smart-phones, laptops, etc.. Distributed laser charging (DLC), a new WPT alternative, has the potential to solve these problems and enable WPT with the similar experience as WiFi communications. In this paper, we present a multi-module DLC system model, in order to illustrate its physical fundamentals and mathematical formula. This analytical modeling enables the evaluation of power conversion or transmission for each individual module, considering the impacts of laser wavelength, transmission attenuation and photovoltaic-cell (PV-cell) temperature. Based on the linear approximation of electricity-to-laser and laser-to-electricity power conversion validated by measurement and simulation, we derive the maximum power transmission efficiency in closed-form. Thus, we demonstrate the variation of the maximum power transmission efficiency depending on the supply power at the transmitter, laser wavelength, transmission distance, and PV-cell temperature. Similar to the maximization of information transmission capacity in wireless information transfer (WIT), the maximization of the power transmission efficiency is equally important in WPT. Therefore, this work not only provides the insight of DLC in theory, but also offers the guideline of DLC system design in practice.

Output Predictor-Based Active Disturbance Rejection Control for a Wind Energy Conversion System With PMSG

Abstract: Considering the internal and external disturbances in wind energy conversion systems, a predictive active disturbance rejection control (PADRC) strategy for a direct-driven permanent magnet synchronous generator (PMSG)-based wind energy conversion system, is proposed to maximize the wind power extraction in this paper. First, the proposed PADRC method can successfully deal with the effects of the uncertainties in the internal dynamics, modeling error, external forces and the variety of wind speeds, since it inherits the merits of active disturbance rejection control (ADRC). Second, the introduction of Smith Predictor can overcome the time delay in wind turbine system to guarantee the maximum power tracking performance for different wind speeds. Finally, simulation studies are conducted to evaluate power tracking performances of the proposed control strategy. It is shown that the proposed PADRC strategy exhibits significant improvements in both maximum power tracking performance and anti-disturbance ability compared with the traditional ADRC approach.

Global maximum power point tracking based on ANFIS approach for PV array configurations under partial shading conditions

Abstract: The classical algorithms for maximum power point tracking ensure proper operation under uniform irradiance conditions. However, when photovoltaic (PV) array is subject to partial shading conditions (PSC), several local maxima appear on the P-V characteristics curve of the PV array which are due to the use of the bypass diodes to avoid hot spots effect. The appearance of these multiple peaks on the characteristics of PV array makes the tracking more difficult under these conditions and requires the integration of a more efficient power control system which is able to discriminate between local and global maxima to harvest the maximum possible energy and therefore increase the efficiency of overall system. In addition to implementing a global maximum power point tracking strategies, the mismatch losses associated to the shading effect can further be reduced by using alternative PV arrays’ configurations such as Total-Cross-Tied (TCT), Bridge Linked (BL) and Honey-Comb (HC). For this purpose, the main aim of this paper is to design an intelligent MPPT controller that allows predicting and extracting the global maximum power point (GMPP) from PV array under partial shading conditions (PSC) whatever is the used configuration or its size. This intelligent MPPT controller is based on adaptive neuro-fuzzy inference system (ANFIS). The adopted ANFIS network has two inputs and one output. The two inputs of the proposed ANFIS consist of voltage and current while, the output is the output power of each configuration. The ANFIS network is trained using the data derived from performances analysis of different PV array configurations. Furthermore, the ANFIS network uses a hybrid learning algorithm that combines the least-squares estimator and the gradient method. The Bishop model of a PV module which describes best the solar cell behavior at negative voltages is considered in this paper for modeling the PV arrays, and it is implemented by using the Simulink and SimPower software. The effectiveness of the proposed method is investigated for TCT configuration under partial shading conditions for various shading scenarios and sudden irradiance change. The results show that the proposed algorithm can track the global MPP effectively and is robust to various shading patterns. Simulation results show high tracking performances in terms of efficiency, tracking speed and system stability. The results are also presented for different configurations such as HC, BL and Series-Parallel (SP) to show the ability of the proposed technique to detect the right peak regardless of the used configuration.

Thermoelectric properties of an interacting quantum dot based heat engine

Abstract: We study the thermoelectric properties and heat-to-work conversion performance of an interacting, multilevel quantum dot (QD) weakly coupled to electronic reservoirs. We focus on the sequential tunneling regime. The dynamics of the charge in the QD is studied by means of master equations for the probabilities of occupation. From here we compute the charge and heat currents in the linear response regime. Assuming a generic multiterminal setup, and for low temperatures (quantum limit), we obtain analytical expressions for the transport coefficients which account for the interplay between interactions (charging energy) and level quantization. In the case of systems with two and three terminals we derive formulas for the power factor $Q$ and the figure of merit $ZT$ for a QD-based heat engine, identifying optimal working conditions which maximize output power and efficiency of heat-to-work conversion. Beyond the linear response we concentrate on the two-terminal setup. We first study the thermoelectric nonlinear coefficients assessing the consequences of large temperature and voltage biases, focusing on the breakdown of the Onsager reciprocal relation between thermopower and Peltier coefficient. We then investigate the conditions which optimize the performance of a heat engine, finding that in the quantum limit output power and efficiency at maximum power can almost be simultaneously maximized by choosing appropriate values of electrochemical potential and bias voltage. At last we study how energy level degeneracy can increase the output power.

A New Approach for Photovoltaic Arrays Modeling and Maximum Power Point Estimation in Real Operating Conditions

Abstract: In this paper, a new approach for photovoltaic (PV) arrays modeling and maximum power point estimation (MPPE) in real operating conditions is presented The PV array polynomial model is developed from its single-diode equivalent circuit, and the parameters of the proposed model are estimated by measuring the voltage and current of three points around the maximum power point (MPP) The maximum power point voltage (MPPV) is then calculated from the proposed model, and the PV array voltage is fixed at MPPV Therefore, unlike the maximum power point tracking (MPPT) algorithms, there is no oscillation around the MPP Using the PV array polynomial model with only three measurements around the operating point, results in less calculation burden, increases the estimation speed and decreases the I–V curve estimation process loss In order to validate the proposed MPPE algorithm, we have compared it with the most commonly used perturb and observe (P&O) MPPT algorithm, a zero oscillation adaptive P&O technique, and a fast MPPT method by simulation and experimental results

Thermal Safe Power (TSP): Efficient Power Budgeting for Heterogeneous Manycore Systems in Dark Silicon

Abstract: Chip manufacturers provide the Thermal Design Power (TDP) for a specific chip. The cooling solution is designed to dissipate this power level. But because TDP is not necessarily the maximum power that can be applied, chips are operated with Dynamic Thermal Management (DTM) techniques. To avoid excessive triggers of DTM, usually, system designers also use TDP as power constraint. However, using a single and constant value as power constraint, e.g., TDP, can result in significant performance losses in homogeneous and heterogeneous manycore systems. Having better power budgeting techniques is a major step towards dealing with the dark silicon problem. This paper presents a new power budget concept, called Thermal Safe Power (TSP), which is an abstraction that provides safe power and power density constraints as a function of the number of simultaneously active cores. Executing cores at any power consumption below TSP ensures that DTM is not triggered. TSP can be computed offline for the worst cases, or online for a particular mapping of cores. TSP can also serve as a fundamental tool for guiding task partitioning and core mapping decisions, specially when core heterogeneity or timing guarantees are involved. Moreover, TSP results in dark silicon estimations which are less pessimistic than estimations using constant power budgets.