Neural network-based feedforward maximum power point tracking control for IDB converter-supplied PV system

Lower limb amputees can use electrical activity from their residual muscles for myoelectric control of a powered prosthesis. The most common approach for myoelectric control is a finite state controller that identifies behavioral states and discrete changes in motor tasks. An alternative approach to state-based myoelectric control is continuous proportional myoelectric control where ongoing electrical activity has a proportional relationship to the prosthetic joint torque or power. To test the potential of continuous proportional myoelectric control for powered lower limb prostheses, we recruited five unilateral transtibial amputees to walk on a treadmill with an experimental powered prosthesis. Subjects walked using the powered prosthesis with and without visual feedback of their control signal in real time. Amputee subjects were able to adapt their residual muscle activation patterns to alter prosthetic ankle mechanics when we provided visual feedback of their myoelectric control signal in real time. During walking with visual feedback, subjects significantly increased their peak prosthetic ankle power ( p = 0.02, ANOVA) and positive work ( p = 0.02, ANOVA) during gait above their prescribed prosthesis values. However, without visual feedback, the subjects did not increase their peak ankle power during push off. These results show that amputee users were able to volitionally alter their prosthesis mechanics during walking, but only when given an explicit goal for their residual muscle motor commands. Future studies that examine the motor and learning capabilities of lower limb amputees using their residual muscles for continuous proportional myoelectric control are needed to determine the viability of integrating continuous high-level control with existing finite state prosthetic controllers.

The arrangement of diodes in a solar cell array affects the Maximum Power Point (MPP) of the solar cell system. Thus, a pre-wiring method for determining the optimal arrangement of the diodes, which results in the highest MPP, is desirable. This paper proposes a numerical algorithm that predicts the optimal diodes arrangement. A computer program, written in 'Spice', measures the MPP of many different combinations of diode arrangements in a Photovoltaic (PV) array. The program then evaluates the array power harvesting efficiencies. By using the statistics of these results it can then point to the best arrangement of diodes for optimal MPP. A pre-requisite for this method is the knowledge of the electrical characteristics of each photodiode. Simulations and measurements indicate that for an array of 15 diodes (3 parallel columns of 5 diodes in series) the relative improvement achieved by using this method is 15% when compared to the average efficiency of an arbitrarily configured array. One application is for high power PV arrays in which the wiring and optimum arrangement is fixed and the optimal diode arrangement may then be found. Alternatively, for small scale low power PV arrays dynamic real time reconfigurable PV arrays may be realized. Key words: Photovoltaic (PV) array, Maximum Power Point (MPP), spice, Monte-Carlo, module-mismatch.

The aim of this paper is the design of an automatic voltage regulator device for regulating the load voltage supplied by solar cells array (SCA). The device contains DC control circuit (DCCC) and automatic voltage regulating circuit. This circuit senses any deviation of load voltage from that at maximum power point (MPP) of SCA. As the voltage deviated away from the voltage at MPP, the circuit changes its state. Then, the operation of the circuit at this instant changes the performance of DCCC triggering circuit. Consequently, the (DCCC) will return back the load voltage deviated to that equal to the voltage at MPP. Through this paper the proposed construction of the automatic control voltage device is illustrated. Its design procedures as will as its performance are investigated. The proper operation of the proposed regulator shows that it’s very suitable for coupling with photovoltaic power systems and agricultural loads (DC Irrigation pump). In the present paper, a novel circuit, referred to as the generation control circuit (GCC), which enables maximum power to be obtained from all of the PV modules even if some of the modules are prevented from receiving light. The proposed circuit enables the individual PV modules to operate effectively at the maximum power point tracking, irrespective of the series connected PV module system. In addition, the total generated power is shown experimentally to increase for the experimental set-up used in the present study.

The position of MPP of a solar panel changes with changes in weather conditions such as radiation, temperature and partial Shadow. In such a situation, several local MPPs and one GMPP are created in the P-V curve, and the common methods of MPPT(P&O, IC,…) have converged due to the failure to recognise the local MPP. They cause a lot of losses to the photovoltaic system. Therefore, in this article, it has been tried to provide a new method of particle swarm optimisation with variable coefficients, which in combination with the perturb and observe method can reach the GMPP in the fastest possible time. In this proposed method, we first reach the convergence of the GMPP using the VCPSO method, and after converging to it, we go to the P&O method and use P&O until significant changes are made in the system, and if observed Variations To re-examine the GMPP, we return to the VCPSO algorithm. The results of the simulation of the efficiency of the proposed method show that this method was able to reach the GMPP in the shortest time, and the efficiency of the photovoltaic system increases and the effects of partial shading are reduced.

PurposeTo analyze the operating performance of a fuzzy logic control (FLC) based solar energy conversion modular system controlled by a digital signal processor (DSP) microcontroller.Design/methodology/approachA range of published works relevant to the solar energy conversion modular systems are evaluated and their limitations are indicated in the first section of the paper. The circuit diagram of the panel‐boost converter system is described in the second section. In the third section, a neural network model is suggested for the photovoltaic panel and the model is created in the MATLAB/SIMULINK and then combined with other blocks existing in the system. The design of the FLC method is described in section 4. The simulation and experimental results corresponding to the control of the duty‐cycle of the converter to set the operating point of the solar panel at the maximum power point (MPP) are given in sections 5 and 6, respectively. Section 7, summarizes the results and conclusions of the study.FindingsThe paper suggests a simple dc‐dc boost converter controlled by FLC method. The proposed converter model can be used to obtain maximum power from a photovoltaic panel.Research limitations/implicationsIn preparing this paper, the resources books existing in the library of our university and the resources relative to the solar energy conversion and FLC published in English language and reachable through the internet were researched.Practical implicationsThe paper suggests a neural network model for a solar panel, which can be used in the simulation of the solar energy panel‐boost converter system. The solar energy panel‐boost converter system proposed in this study can be used by the researchers who are working in the solar energy conversion area.Originality/valueThe suggestion of a neural network model for a solar panel and creation of this model in the MATLAB/SIMULINK environment provides researchers to simulate and to analyze the performance of the solar energy panel‐boost converter system using the MATLAB/SIMULINK simulation program. In addition, since the control approach proposed in this paper does not require the information on temperature and solar irradiance that affect the maximum output power, can effectively find the MPP of the solar panel.

Solar panels are a renewable energy power plant that uses sunlight as its main energy source. The power generated by solar panels are determined by the size of the solar panels, solar radiation and temperature. The power of the solar panels is also determined by the output voltage of the solar panels. To get the maximum output power at any time, it is necessary to adjust the output voltage of the solar panel. This study proposes controlling the maximum output power of solar panels, also known as maximum power point tracking (MPPT) by adjusting the output voltage of the solar panels using a buck converter. The buck converter output voltage regulation at the maximum power point of the solar panel is designed with the Perturbation and Observation (PO) algorithm which is implemented using an Arduino Mega 2560. This MPPT control system is applied to 4x50 Watt-Peak (WP) solar panels which are connected in parallel. The experimental results show that the proposed MPPT control system with the PO algorithm has worked well as expected. This can be seen from the output power generated by the solar panels already around the maximum power point at any change in solar radiation and temperature.

Development of Real-Time Couch-Based Tracking System (CBTS) For Image Guided Radiotherapy: A Feasibility Study

Under partially shaded conditions, series connection of PV modules results in the flow of lowest current in the PV string, thus reducing the power output. To maximize power output, it is necessary to ensure that maximum possible current flows in the string. This needs current equalization across the modules. To achieve this, a converter is connected in parallel with each PV module. This converter provides the extra (equalization) current in parallel with the shaded module to make the string current equal to the maximum string current, i.e. the current corresponding to the least shaded PV module. The equalization current supports the PV module to have its voltage regulated at a value that corresponds to its MPP (Maximum Power Point) voltage. However, the existing current equalization schemes use approximate maximum power point voltage and not an exact one. This paper proposes an improvement over the existing schemes by using synchronous fly-back converters to regulate the exact MPP voltage across PV modules in a partially shaded PV array. Unlike existing schemes that operate on similar principle, the proposed scheme makes no assumptions and ensures that each module is regulated at its exact MPP voltage i.e. exact MPP of individual PV module is tracked.

Implementation of the novel temperature controller and incremental conductance MPPT algorithm for indoor photovoltaic system

Currently, Photovoltaic (PV) energy is the most important energy resource in electrical power applications around the world since it is inexhaustible, clean and pollution free. As the output power from the PV arrays changing with solar irradiance and temperature, so it is necessary to operate the photovoltaic (PV) system at the maximum power point (MPP) to increase the power extraction from the solar panel. For this effective operation and maximum power extraction from a PV system, Maximum power point tracking (MPPT) algorithm plays a vital role by operating the PV energy system near the MPP. In this work, amongst several existing well established MPPT algorithms, the open voltage (OV) based algorithm is chosen for simulation of a PV system using Matlab / Simscape. As maximum power point (MPP) can be attained with a certain amount of load from the PV power system, so load matching is an important concept of MPPT algorithms. Here, the performances of this open voltage (OV) based algorithm method is evaluated for different values of solar radiation and battery was used as load to see the charging performance for the algorithm.

Real time simulation of MPPT algorithms for PV energy system

It is possible to give a valuable estimation for an entire solar array IV curve, based only on a single working point (current and voltage) measurement, on panels of solar cells, when several of their parameters are known and environmental parameters also known. The estimations were performed using Matlab/Simulink and the simulation is based on the 10 parameter solar cell model. The estimated curves only slightly deviate from the actual measured curves of real solar panels. The average short circuit current error is less than 5%, when the worst case simulated of just 33% of full lighting is also included in that average. When the open circuit voltage drops in error, the short circuit current grows in error and vice verse, so the MPP error is smaller. It is shown that this approach could be used to evaluate, on line, the Maximum Power Point (MPP) of solar panels, while even two or more local maxima could exist. The average relative MPP errors seem to be less than 2% with a full illumination (1 sun), less than 2.5% for 2/3 illumination and less than 3% for less than 1/3 illumination. After the MPP of solar cells, which are not in their optimal working point, has been evaluated, then by this new MPP, they can be classified for re-meandering. Such a procedure would require evaluation of the entire I/V and I/P curves of the cell/panels. It would effectively eliminate the problem of local maxima on the I/P curve. Once the MPP has been evaluated for each panel, it is possible to evaluate the MPP of an entire solar field after re-meandering. Once this is knows, the inverter could be controlled to project the MPP voltage towards the solar field, thus eliminating the need to use a MPPT module (dc/dc converter).

The subject of variable step size maximum power point tracking (MPPT) algorithms has been addressed in the literature. However, most of the addressed algorithms tune the variable step size according to two variables: the photovoltaic (PV) array voltage (<TEX>$V_{PV}$</TEX>) and the PV array current (<TEX>$I_{PV}$</TEX>). Therefore, both the PV array current and voltage have to be measured. Recently, maximum power point trackers that arc based on a single variable (<TEX>$I_{PV}$</TEX> or <TEX>$V_{PV}$</TEX>) have received a great deal of attention due to their simplicity and ease of implementation, when compared to other tracking techniques. In this paper, two methods have been proposed to design a variable step size MPPT algorithm using only a single current sensor for stand-alone battery storage PV systems. These methods utilize only the relationship between the PV array measured current and the converter duty cycle (D) to automatically adapt the step change in the duty cycle to reach the maximum power point (MPP) of the PV array. Detailed analyses and flowcharts of the proposed methods are included. Moreover, a comparison has been made between the proposed methods to investigate their performance in the transient and steady states. Finally, experimental results with field programmable gate arrays (FPGAs) are presented to verify the performance of the proposed methods.

"Photovoltaic panel maximum power point tracker". As the name implied, it is a photovoltaic system that uses the photovoltaic array as a source of electrical power supply and since every photovoltaic (PV) array has an optimum operating point, called the maximum power point, which varies depending on cell temperature, the insolation level and array voltage. A maximum power point tracker (MPPT) is needed to operate the PV array at its maximum power point. The objective of this paper is to build MPPT to charge a 12-volts lead acid battery by using a (TBP1275) 74 - watts PV panel. A technique for efficiency extracting the maximum output power from a solar panel under varying meteorological conditions is presented. The methodology is based on connecting a pulse width modulated dc/dc SEPIC converter, which is controlled by a micro controller based unit. The main difference between the method used in the proposed MPPT systems and other technique used in the past is that PV array output power is used to directly control the dc/dc converter thus reducing the complexity of the system. The resulting system has high efficiency, low cost and can be easily modified. This approach ensured maximum power transfer under all conditions by using micro controller for calculation. The tracking capability of the proposed technique has been verified experimentally with a 74 W solar panel at different insolation levels.

With the advancement of the Moon exploration and deep space exploration missions, aiming at the solar cell array adopting low temperature,low light intensity and severe radiation for deep space detection, and based on the analysis of solar cell arrays of Mars and Juption exploration missions,the solar cell array selection methods, array design and advices on verification tests are presented according to the analysis of mission environment, providing reference for solar cell array design of deep space exploration missions in China.