The many different techniques for maximum power point tracking of photovoltaic (PV) arrays are discussed. The techniques are taken from the literature dating back to the earliest methods. It is shown that at least 19 distinct methods have been introduced in the literature, with many variations on implementation. This paper should serve as a convenient reference for future work in PV power generation.

/pdf/comparison-of-photovoltaic-array-maximum-power-point-2nci76j6n4.pdf

Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques

Maximum power point tracking (MPPT) techniques are used in photovoltaic (PV) systems to maximize the PV array output power by tracking continuously the maximum power point (MPP) which depends on panels temperature and on irradiance conditions. The issue of MPPT has been addressed in different ways in the literature but, especially for low-cost implementations, the perturb and observe (PO moreover, it is well known that the P&O algorithm can be confused during those time intervals characterized by rapidly changing atmospheric conditions. In this paper it is shown that, in order to limit the negative effects associated to the above drawbacks, the P&O MPPT parameters must be customized to the dynamic behavior of the specific converter adopted. A theoretical analysis allowing the optimal choice of such parameters is also carried out. Results of experimental measurements are in agreement with the predictions of theoretical analysis.

/pdf/optimization-of-perturb-and-observe-maximum-power-point-z7a8beok09.pdf

Optimization of perturb and observe maximum power point tracking method

This paper presents a new mixed-integer linear formulation for the unit commitment problem of thermal units. The formulation proposed requires fewer binary variables and constraints than previously reported models, yielding a significant computational saving. Furthermore, the modeling framework provided by the new formulation allows including a precise description of time-dependent startup costs and intertemporal constraints such as ramping limits and minimum up and down times. A commercially available mixed-integer linear programming algorithm has been applied to efficiently solve the unit commitment problem for practical large-scale cases. Simulation results back these conclusions

A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem

Maximum power point tracking (MPPT) techniques are employed in photovoltaic (PV) systems to make full utilization of PV array output power which depends on solar irradiation and ambient temperature. Among all the MPPT strategies, the incremental conductance (INC) algorithm is widely used due to the high tracking accuracy at steady state and good adaptability to the rapidly changing atmospheric conditions. In this paper, a modified variable step size INC MPPT algorithm is proposed, which automatically adjusts the step size to track the PV array maximum power point. Compared with the conventional fixed step size method, the proposed approach can effectively improve the MPPT speed and accuracy simultaneously. Furthermore, it is simple and can be easily implemented in digital signal processors. A theoretical analysis and the design principle of the proposed method are provided and its feasibility is also verified by simulation and experimental results.

/pdf/a-variable-step-size-inc-mppt-method-for-pv-systems-4ppvi6cu8y.pdf

A Variable Step Size INC MPPT Method for PV Systems

Review of the maximum power point tracking algorithms for stand-alone photovoltaic systems

The increased renewable energy utilization, especially photovoltaic panels using solar energy or wind turbine generators (WTGs) using wind energy, has been expected in recent years from view point of CO2 gas emission reduction and environmental conservation. However, the generated power is always fluctuating because the WTGs are driven by fluctuating wind. Therefore, an energy storage system should be installed to compensate these fluctuating elements. The energy capacitor system (ECS) which combined the electric double-layer capacitor (EDLC) and the electronic circuits are now under development. In this paper, control system configuration for active and reactive output power simultaneous control and the bi-directional inverter using current source EDLC are proposed. Moreover, we discusse control methods required in generating-power leveling for WTGs, and show the effectiveness of the proposed system through simulations.

Output Power Leveling of Wind Turbine Generator by EDLC Energy Storage System

The stability problem is the main issue for a wind power generating system. In this paper, the stability assessment is examined with numerical simulations. The formulation for this system is developed at first, and then the simulation block diagram is constructed using MATLAB/SIMULINK. The stability margin is analyzed through simulations for various transmission line faults.

Stability analysis of wind power generating system

Vector control is an effective technique for controlling variable speed drives using brushless DC motors. Conventional vector controllers, however, suffer from electrical machine parameter variations because these controllers depend on the parameters. This paper presents the vector control of a brushless DC motor using a neural network. In the proposed method, a neural network is employed as an online estimator of the nonlinear dynamic equations of a brushless DC motor. The neural network based vector controller has the advantage of robustness against machine parameter variations as compared with the conventional vector controller. Computer simulation results verify the useful of the proposed method.

Vector control of brushless DC motors using neural network

This article presents the procedure to design a cooperative fuzzy controller applying a genetic algorithm (GA) to improve power system transient stability. A remarkable feature of the method lies in the fact that it can quickly provide a global approximately optimal solution for gains and parameters for the fuzzy controller. In real application problems, trial and error method is extensively used to decide the gains and parameters. However, when the system condition or fault location changes, it is necessary to iterate again to obtain an approximately optimal controller. Moreover, if parameters are changed, it is difficult to achieve good dynamic response. Hence, a cooperative controller using a fuzzy-genetic system seems a quite efficient means for controlling electric generators.

Enhancement of transient stability of multi-machine power systems by using fuzzy-genetic controller

This paper presents a maximum power point tracking algorithm for Photovoltaic array using only instantaneous output current information. The conventional Hill climbing method of peak power tracking has a disadvantage of oscillations about the maximum power point To overcome this problem, we have developed an algorithm that will estimate the duty ratio corresponding to maximum power operation of solar cell The estimation of the optimal duty ratio involves, finding the duty ratio at which integral value of output current is maximum. For the estimation, we have used the well know Lagrange's interpolation method. This method can track maximum power point quickly even for changing solar isolation and avoids oscillations after reaching the maximum power point.

/pdf/a-maximum-power-point-tracking-control-for-photovoltaic-4ozberh2fs.pdf

A Maximum Power Point Tracking Control for Photovoltaic Array without Voltage Sensor

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