• Journal of the Korean Solar Energy Society
• /
• v.33 no.5
• /
• pp.69-75
• /
• 2013

To increase the efficiency of the photovoltaic, almost photovoltaic appliances are controlled by Maximum Power Point Tracking(MPPT). Existing most of the PV MPPT techniques have used power which multiplies sensed output current and voltage of the solar cell. However, these algorithms are unnecessarily complicated and too expensive for small and compact system. The other hand, the proposed MPPT technique is only one sensing of the MPPT converter's output current, so there is no need to insert another sensors of battery side. Therefore, this algorithm is simpler compared to the traditional approach and is suitable for low power solar system. Further, the novel proper charge/discharge algorithm for the battery with PV MPPT is developed. In this algorithm, there is CC battery charge mode and load discharge mode of the PV cell & battery dual. Also we design current control to regulate allowable current during the battery charging. The proposed algorithm will be applicable to battery included solar cell applications like solar lantern and solar remote control car. Finally, the proposed method has been verified with computer simulation.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.25 no.10
• /
• pp.47-58
• /
• 2011

This paper proposes the optimal current detect(OCD) maximum power point tracking(MPPT) control of photovoltaic(PV) system for robust with environment changing. The output characteristics of the solar cell is a nonlinear and affected by a temperature, the solar radiation and temperature. Conventional MPPT control methods are tracked the maximum power point by constant incremental value. So these methods are slow the response speed and generated the vibration in steady state and cannot track the MPP in environment condition changing. And power loss is generated because of the self-excitation vibration in MPP region. To solve this problem, this paper proposes the novel control algorithm. Proposed algorithm is detected the optimal current in two control region using the output power and current curve. Detected current is used the converter switching for tracking the MPP. Proposed algorithm is compared output power error to conventional algorithm with radiation and temperature changing. In addition, the validity of the algorithm is proved through the output error response characteristics.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.23 no.5
• /
• pp.72-79
• /
• 2009

Solar energy is desirable due to its renewable and pollution-free properties. In order to utilize the present utility grid infrastructure for power transmission and distribution, a do-dc boost converter and grid connected dc-to-ac inverters are needed for solar power generation. The dc-dc boost converter allows the PV system to operate at high do-link voltage. The single-phase inverter provides the necessary voltage and frequency for interconnection to the grid. In this paper, first, current loop transfer function of a single-phase grid-tie inverter has been systematically derived Second the MPPT of conductance increment method at converter side is proposed to supply the maximum power to the inverter side. Simulation results are shown to access the performance of PV system and its behaviour at the interconnection point.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.20 no.7
• /
• pp.74-80
• /
• 2006

This paper describes a solar energy conversion strategy is applied to grid-connected single phase inverter by the maximum power point of conversion strategy. The maximum power point of tracking is controlled output power of PV(photovoltaic)modules, based on generated circuit control MOSFET switch of two boost converter for a connected single phase inverter with four IGBT's switch in full bridge. The generation control circuit allows each photovoltaic module to operate independently at peak capacity, simply by detecting of the output power of PV module. Furthermore, the generation control circuit attenuates low-frequency ripple voltage. which is caused by the full-bridge inverter, across the photovoltaic modules. The effectiveness of the proposed inverter system is confirmed experimentally and by means of simulation.

• Proceedings of the KIEE Conference
• /
• 2003.07b
• /
• pp.1256-1258
• /
• 2003

The solar cells should be operated at the maximum power point because its output characteristics are greatly fluctuate on the variations of insolation, temperature and loads. To obtain maximum power from solar cell, photovoltaic system cell power system usually requires maximum power point tracking controller. This paper propose Maximum power point tracking method using zero slope of differential value of maximum power. The power compare method traces to maximum power point rapidly but oscillate on the maximum power point largely, when quantity insolation variation is big. The power compare method is traces to maximum power point slowly but oscillate maximum point on the maximum power point smally, when quantity insolation variation is small. To solve two problem of the power compare method, designed zero slope of differential value of maximum power.

• New & Renewable Energy
• /
• v.8 no.3
• /
• pp.14-22
• /
• 2012

Performance of photovoltaic (PV) generator systems relies on its operating conditions. Maximum power extracted from PV generators depends strongly on solar irradiation, load impedance, and ambient temperature. A most maximum power point tracking (MPPT) algorithm is based on a perturb and observe method and an incremental conductance method. It is well known the latter is better in terms of dynamics and tracking characteristics under condition of rapidly changing solar irradiation. However, in case of digital implementation, the latter has some error for determining a maximum power point. This paper presents a PID based MPPT algorithm for such PV systems. We use neural network technique for determining PID parameters by online learning approach. And we construct a boost converter to regulate the output voltage from PV generator system. Computer simulation is carried out to evaluate the proposed MPPT method and we accomplish comparative study with a perturb and observe based MPPT method to prove its superiority.

• Journal of Power Electronics
• /
• v.19 no.6
• /
• pp.1566-1574
• /
• 2019

Maximum power point tracking (MPPT) under the partial shading condition is a challenging research topic for photovoltaic systems. Shaded photo-voltaic module result in complex peak patterns on the power versus voltage curve which can misguide classical MPPT algorithms. Thus, various kinds of global MPPT algorithms have been studied. These have typically consisted of partial shading detection, global peak search and MPPT. The conventional partial shading detection algorithm aims to detect all of the occurrences of partial shading. This results in excessive execution of global peak searches and discontinuous operation of the MPPT. This in turn, reduces the achievable power for the PV module. Based on a theoretical investigation of power verse voltage curve patterns under various partial shading conditions, it is realized that not all the occurrences of partial shadings require a global peak search. Thus, an intelligent partial shading detection algorithm that provides exact identification of global peak search necessity is essential for the efficient utilization of solar energy resources. This paper presents a new partial shading determinant algorithm utilizing adaptive threshold levels. Conventional methods tend to be too sensitive to sharp shading patterns but insensitive to smooth patterns. However, the proposed algorithm always shows superb performance, regardless of the partial shading patterns.

• Journal of KIISE:Software and Applications
• /
• v.41 no.7
• /
• pp.481-491
• /
• 2014

The power production using renewable energy is more important because of a limited amount of fossil fuel and the problem of global warming. A concentrative photovoltaic system comes into the spotlight with high energy production, since the rate of power production using solar energy is proliferated. These systems, however, need to sophisticated tracking methods to give the high power production. In this paper, we propose a hierarchical tracking system using modular Bayesian networks and a naive Bayes classifier. The Bayesian networks can respond flexibly in uncertain situations and can be designed by domain knowledge even when the data are not enough. Bayesian network modules infer the weather states which are classified into nine classes. Then, naive Bayes classifier selects the most effective method considering inferred weather states and the system makes a decision using the rules. We collected real weather data for the experiments and the average accuracy of the proposed method is 93.9%. In addition, comparing the photovoltaic efficiency with the pinhole camera system results in improved performance of about 16.58%.

• Journal of Digital Convergence
• /
• v.12 no.3
• /
• pp.243-248
• /
• 2014

Recently, solar energy is expanding to combination of computing in real time by tracking the position of the sun to estimate the angle of inclination and make up freshly correcting a part of the solar radiation. Solar power is need that reliably linked technology to power generation system renewable energy in order to efficient power production that is difficult to output predict based on the position of the sun rise. In this paper, we analysis of prediction model for solar power generation to estimate the predictive value of solar power generation in the development of real-time weather data. Photovoltaic power generation input the correction factor such as temperature, module characteristics by the solar generator module and the location of the local angle of inclination to analyze the predictive power generation algorithm for the prediction calculation to predict the final generation. In addition, the proposed model in real-time national weather service forecast for medium-term and real-time observations used as input data to perform the short-term prediction models.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.16 no.4
• /
• pp.281-292
• /
• 2016

The proposed scheme is based on the modified perturb and observe (P&O) algorithm combined with the sliding mode technique. A modified P&O algorithm based sliding mode controller is developed to study the effects of partial shade, temperature, and insolation on the performance of maximum power point tracking (MPPT) used in photovoltaic (PV) systems. Under partially shaded conditions and temperature, the energy conversion efficiency of a PV array is very low, leading to significant power losses. Consequently, increasing efficiency by means of MPPT is particularly important. Conventional techniques are easy to implement but produce oscillations at MPP. The proposed method is applied to a model to simulate the performance of the PV system for solar energy usage, which is compared to the conventional methods under non-uniform insolation improving the PV system utilization efficiency and allowing optimization of the system performance. The modified perturb and observe sliding mode controller successfully overcomes the issues presented by non-uniform conditions and tracks the global MPP. Compared to MPPT techniques, the proposed technique is more efficient; it produces less oscillation at MPP in the steady state, and provides more precise tracking.