Alivarani Mohapatra

Comparative study on single diode photovoltaic module parameter extraction methods

This paper compares the different approaches for extraction of PV module parameters. The trust-region-doleg method is proposed here for extraction of five parameters such as series resistance (Rs), shunt resistance (Rp), diode ideality factor (a), dark saturation current (I0) and photo-generated current (Ipv) under standard test conditions (STC). The comparative analysis is made by taking Villalvas iterative method and proposed trust-region-dogleg method. Two parameters Rs and Rp are extracted by Villalvas iterative method whereas all five unknown parameters can be extracted by proposed trust-region-dogleg method. The accuracy of parameters calculation depends on tolerance band and initial conditions are tabulated. The PV module behavior at different temperature and irradiance is also forecasted.

Parameters estimation of photovoltaic module using nonlinear least square algorithm: A comparative study

This paper compares different methods for extraction of photovoltaic (PV) module parameters. Nonlinear least-square method based on trust-region algorithm is proposed here to extract five unknown parameters such as series resistance (Rs), shunt resistance (Rp), diode ideality factor (a), dark saturation current (I0) and photo-generated current (Ipv) under standard test conditions (STC) of PV module. Comparative analysis has been drawn between the proposed method and two other popular methods such as Villalvas iterative method and modified Newton-Raphson method. The principle of trust-region algorithm is briefly reviewed. Two parameters Rs and Rp are only extracted by Villalvas iterative method whereas all five unknown parameters can be extracted by the proposed method and by modified Newton-Raphson method. The accuracy of estimated parameters depends on tolerance band and initial conditions. The time of computation for parameter extraction of different methods has been compared.

Current based novel adaptive P&O MPPT algorithm for photovoltaic system considering sudden change in the irradiance

Optimum utilization of photovoltaic (PV) energy is possible if PV system is operated at its maximum power point (MPP). Since the MPP varies with change in irradiation and temperature, appropriate algorithm must be incorporated in the PV system to track the MPP. There are number of maximum power point tracking (MPPT) algorithms available in the literature with its own merits and demerits. Among different MPPT methods, perturb and observe (P&O) method is most popularly used for its easy implementation and simple structure. But conventional P&O method is sluggish in nature due to its fixed perturb amplitude. To overcome this, an adaptive P&O algorithm is proposed here based on current perturbation which has faster dynamics compared to the conventional P&O method. The effectiveness of the proposed method is verified using MALAB/Simulink both in steady as well as changing irradiation.

Model validation and maximum power point tracking of photovoltaic module

For efficient operation of a photovoltaic (PV) system accurate model of the PV module is required. In this paper a PV simulation model has been developed and has been validated with experimental results of a commercial PV module, ELDORA-40. Maximum power point tracking (MPPT) must be incorporated in the PV system to get maximum power from the PV system. Maximum power of PV depends on two external parameters, temperature and solar irradiation. Since solar irradiation has faster dynamics than temperature an effort has been given to track maximum power of a PV module using perturb and observe (P&O) MPPT for change of insolation. The study has been carried out in MATLAB-Simulink graphical user interface environment.

Selection criteria of dc-dc converter and control variable for MPPT of PV system utilized in heating and cooking applications

Abstract This paper deals with the selection of dc-dc converter and control variable required to track the maximum power of photovoltaic (PV) array, to optimize the utilization of solar power. To reduce the maintenance cost and to simplify the model, the battery has not been used in the proposed PV system mainly used for cooking and heating applications. Since the battery has not been used, selection of dc-dc converter is an important consideration of the PV system in standalone applications. In the proposed system converter is selected based on maximum power transfer theorem which is dependent on load resistance. Different load resistance is considered for maximum power point tracking (MPPT) with different converter topologies, and it has been observed that buck-boost converter is suitable for any load resistance connected in the PV system. An effort has been taken to suitably choosing the control variable which is the output signal of the maximum power point (MPP) tracker. Control variable which is dependent on inputs of MPP tracker is decided based on the stability of the system. Two MPP trackers are designed based on neural-network (NN) controller and perturb and observe (P&O) algorithm. The tracking capabilities of both NN controller and the P&O algorithm is compared with the variation of irradiation and found that tracking capability of NN controller is better than P&O method. The system is simulated using MATLAB/Simulink environment, and the results show that NN controller tracks MPP at a faster rate with reduced oscillation.

Performance improvement in MPPT of SPV system using NN controller under fast changing environmental condition

Solar photovoltaic (SPV) energy have become an attractive renewable energy source because it is freely available, need less maintenance and pollution free. Since characteristics of SPV module is nonlinear in nature and varies with environmental condition, to extract maximum power from the PV module appropriate maximum power point tracking (MPPT) algorithm must be incorporated in the PV system to track the maximum power point (MPP). Although tracking performance of conventional MPPT method is high it suffers a lot in case of rapidly changing environmental condition. This paper proposes the improvement in tracking performance of a SPV module using neural network (NN) controller under fast changing environmental condition. The tracking performance of NN controller is compared with conventional perturb and observe (P&O) MPPT controller. The slow tracking of P&O and wrong tracking during changing weather condition is eliminated using NN controller. The large drooping characteristic of P&O under fall of irradiation is also eliminated. The result is verified using MATLAB-Simulink software package under fast changing irradiation and temperature.

Parameter estimation of single diode PV module based on Nelder-Mead optimization algorithm

Purpose This paper proposes a simple, derivative free novel method named as Nelder-Mead (NM) optimization algorithm to estimate the unknown parameters of the PV module considering the environmental conditions. Design/methodology/approach At a particular temperature and irradiation, experimental current-voltage (I-V) and power-voltage (P-V) characteristics are drawn and considered as a reference model. The PV system model with unknown model parameters is considered as the adaptive model whose unknown model parameters are to be adapted so that the simulated characteristics closely matches with the experimental characteristics. A single diode (Rsh) model with five unknown model parameters is considered here for the parameter estimation. Findings The key advantages of this method are (i) parameters are estimated considering environmental condition (ii) experimental characteristics are considered for parameter estimation which give accurate results (iii) the parameters are estimated considering both I-V and P-...