• International Journal of Computer Science & Network Security
• /
• v.22 no.5
• /
• pp.5-10
• /
• 2022

Photovoltaic systems provide a reliable green energy solution. The sustainability and low-maintenance of Photovoltaic systems motivate the integration of Photovoltaic systems into the electrical grid and further contribute to a greener environment, as the system does not cause any pollution or emissions. Developing methodologies based on machine learning techniques to assist in reducing the burden of studies related to integrating Photovoltaic systems into the electric grid are of interest. This research aims to develop a methodology based on a unsupervised machine learning algorithm that can reduce the burden of extensive studies and simulations related to the integration of Photovoltaic systems into the electrical grid.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.24 no.2
• /
• pp.111-119
• /
• 2019

In this study, constant power generation (CPG) algorithms are introduced for whole range power point tracking in photovoltaic systems. Currently, maximum power point tracking (MPPT) algorithm is widely used for high-power photovoltaic systems. However, MPPT algorithm cannot flexibly control such systems according to changing grid conditions. Maintaining grid stability has become important as the capacity of grid-connected photovoltaic systems is increased. CPG algorithms are required to generate the desired power depending on grid conditions. A grid-connected photovoltaic system is configured, and CPG algorithms are implemented. The performances of the implemented algorithms are compared and analyzed by experimental results.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.5
• /
• pp.805-811
• /
• 2015

Floating photovoltaic systems have been developed by the construction process such as design, construction, operation and management. Therefore, the power of floating photovoltaic systems has been calculated by using simple formulas and the optimal tracking interval is set by operation experience. But, flow characteristics have a decisive effect on it unlike land based PV systems. In this paper, a tracking floating photovoltaic system is modeled by using Matlab/simulink. The modeling for the floating photovoltaic system is verified through applying the flow characteristics based on actual operating data of 100㎾ class tracking floating photovoltaic.

• Proceedings of the KIPE Conference
• /
• 2005.07a
• /
• pp.61-63
• /
• 2005

Utility interactive photovoltaic systems is one of the most premising applications of photovoltaic systems. These systems are employed in applications where utility service is already available. In this case, there is no need for battery storage because utility power may be used to supplement photovoltaic systems when the load exceeds available PV generation. The load receives electricity from both the photovoltaic array and the utility inter-tied. In this paper, Principle and operating characteristic of Utility Interconnected Photovoltaic System is presented. For the purpose of optimal utility Inter-tied photovoltaic system design and installation. It is that demonstrate throughout the installed 3 PV system respectively, 3kW utility interconnected residential system.

• Journal of the Institute of Convergence Signal Processing
• /
• v.12 no.3
• /
• pp.212-216
• /
• 2011

Fault detection technique for photovoltaic power systems is significant to dramatically reduce economic damage in industrial fields. This paper presents a novel fault detection approach using Fourier neural networks and stochastic decision making strategy for photovoltaic systems. We achieve neural modeling to represent its nonlinear dynamic behaviors through a gradient descent based learning algorithm. Next, a general likelihood ratio test (GLRT) is derived for constructing a decision malling mechanism in stochastic fault detection. A testbed of photovoltaic power systems is established to conduct real-time experiments in which the DC power line communication (DPLC) technique is employed to transfer data sets measured from the photovoltaic panels to PC systems. We demonstrate our proposed fault detection methodology is reliable and practicable over this real-time experiment.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.7
• /
• pp.1007-1013
• /
• 2012

Modeling of photovoltaic power systems is significant to analytically predict its dynamics in practical applications. This paper presents a novel modeling algorithm of such system by using probability and statistic theories. We first establish a linear model basically composed of Fourier parameter sets for mapping the input/output variable of photovoltaic systems. The proposed model includes solar irradiation and ambient temperature of photovoltaic modules as an input vector and the inverter power output is estimated sequentially. We deal with these measurements as random variables and derive a parameter learning algorithm of the model in terms of statistics. Our learning algorithm requires computation of an expectation and joint expectation against solar irradiation and ambient temperature, which are analytically solved from the integral calculus. For testing the proposed modeling algorithm, we utilize realistic measurement data sets obtained from the Seokwang Solar power plant in Youngcheon, Korea. We demonstrate reliability and superiority of the proposed photovoltaic system model by observing error signals between a practical system output and its estimation.

• Journal of the Korean Solar Energy Society
• /
• v.33 no.5
• /
• pp.95-104
• /
• 2013

This study set out to devise an optimized system to take into account life cycle cost(LCC) and ton of carbon dioxide($TCO_2$) by applying the weighted coefficient method(WCM) to "public-purpose" facility buildings according to the mandatory 5% and 11% of new renewable energy in total construction costs and anticipated energy consumption, respectively, based on the changes of the public obligation system. (1) System installation capacity is applied within the same new renewable energy facility investment according to the mandatory 5% of new renewable energy in total construction costs. Both LCC and $TCO_2$ recorded in the descending order of geothermal, solar, and photovoltaic energy. The geothermal energy systems tended to exhibit an excellent performance with the increasing installation capacity percentage. (2) Optimal systems include the geothermal energy(100%) system in the category of single systems, the solar energy(12%)+geothermal energy(88%) system in the category of 2-combined systems, and the photovoltaic energy(12%)+solar energy(12%)+geothermal energy(76%) system and the photovoltaic energy(12%)+solar energy(25%)+geothermal energy(63%) system in the category of 3-combined systems. (3) LCC was the highest in the descending order of photovoltaic, geothermal and solar energy due to the influences of each energy source's correction coefficient according to the mandatory 11% of new renewable energy in anticipated energy consumption. The greater installation capacity percentage photovoltaic energy had, the more excellent tendency was observed. $TCO_2$ recorded in the descending order of geothermal, photovoltaic and solar energy with the decreasing installation capacity of photovoltaic energy. The greater installation capacity percentage a geothermal energy system had, the more excellent tendency it demonstrated. (4) Optimal systems include the geothermal energy(100%) system in the category of single systems, the photovoltaic energy(62%)+geothermal energy(38%) system in the category of 2-combined systems, and the photovoltaic energy(50%)+solar energy(12%)+geothermal energy(38%) system and the photovoltaic energy(12%)+solar energy(12%)+geothermal energy(76%) system in the category of 3-combined systems.

• New & Renewable Energy
• /
• v.1 no.3 s.3
• /
• pp.35-41
• /
• 2005

This paper analyses the economics of grid-connected photovoltaic systems. With the 2003 cost of photovoltaic systems, under prevailing capital market conditions, with a system lifetime of 30 years, and under the best climatic conditions, it appears that the cost of production of grid-connected electricity could be of 0.21 US $/kWh, and under medium climatic conditions, European locations, Switzerland, Japan and South Korean could be of 0.28$/kWh. If the lifetime if the system goes up, due to future technological improvements, to a very large value such as 50 years, these costs can be lowered by 10-20%. Competitiveness of grid-connected photovoltaic electricity, while it still cannot be taken for granted, is a possibility, especially if major technological advances further lowers the costs of photo cells and increases their lifetimes.

• Journal of the Korean Solar Energy Society
• /
• v.27 no.1
• /
• pp.11-17
• /
• 2007

The amount of incident rays over inclination according to direction has been widely utilized as important data in installing photovoltaic systems. This is because the performance of the photovoltaic systems in much affected by angle and direction of incident rays. Recognizing that factors mentioned above are of importance, actual experiment on the moving route of the sun have been performed in this research to obtain the angle of inclination with which the maximum incident rays can be absorbed. After all, the standard for designing highly optimized photovoltaic systems will be provided for designers and employees working in the photovoltaic module related industries.

• Journal of the Korean Solar Energy Society
• /
• v.33 no.4
• /
• pp.89-93
• /
• 2013

In recent years, many investigations about photovoltaic power systems have been significantly carried out in the fields of renewable power energy. Such research area generally includes developments of highly efficient solar cells, advanced power conversion systems, and smart monitoring systems. A generic objective of fault detection and diagnosis techniques is to timely recognize unexpected faulty of dynamic systems so that economic demage occurred by such faulty is decreased by means of engineering techniques. This paper presents a novel fault detection approach for photovoltaic power arrays which are electrically connected in series and parallels. In the proposed fault detection scheme, we first measure all of photovoltaic modules located in each array by using electronic sense systems and then compare each measurement in turn to detect location of fault module through statistic computation algorithm. We accomplish real-time experiments to demonstrate our proposed fault detection methodology by using a test-bed system including two 20 watt photovoltaic modules.