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

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.2
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• pp.103-110
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• 2003

With significant development of power electronics technology, the proliferation of nonlinear loads such as static power converters has deteriorated power quality in power transmission and distribution systems. Notably, voltage harmonics resulting from current harmonics produced by the nonlinear loads have become a serious problem in many countries. Many photovoltaic power generation systems installed in building systems have harmonics that are the worst object for distribution systems as a utility interactive system, and it tends to spread out continuously. Proposed and implemented in this paper is a multi-function inverter control strategy that allows a shunt active filter function to the power inverter of the photovoltaic power generation system established on a building system. The effectiveness of the proposed system is demonstrated through the simulation of a hypothetical power system using PSCAD/EMTDC.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.4
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• pp.579-584
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• 2009

This paper describes a power quality analysis of a photovoltaic generating systems. Prior to the power measurement, domestic and foreign codes related to the photovoltaic generating systems were briefly summarized. After constructing about 5 kW photovoltaic systems, input/output voltages and currents were measured to compare and analyze the power quality by the module type. Based on the measured values, a couple of factors such as active power, power factor, total harmonic distortion(THD) was calculated and analyzed.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.212-216
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• 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 P
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• v.65 no.4
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• pp.335-339
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• 2016

Output power in photovoltaic systems changes steeply with the change of the sun intensity. The change of output power has influence on the electric power quality of the system. This paper proposes a residential distributed generation system using photovoltaic power generation and polymer electrolyte fuel cells(hybrid systems). In order to level the output power which changes steeply the polymer electrolyte fuel cells are connected to the photovoltaic power generation system in parallel. Thus the generated power of all the system can be leveled. However, the steep generated power in the photovoltaic power generation system can not be leveled. Therefore, the electric double layer capacitor(EDLC) is connected in parallel with the hybrid systems. It is confirmed by the simulation that the proposed distributed generation system is available for a residential supply.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.7
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• pp.1007-1013
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• 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
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• v.33 no.4
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• pp.89-93
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• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.412-417
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• 2013

Analytical modeling of photovoltaic power systems has been receiving significant attentions in recent years in that it is easy to apply for prediction of its dynamics and fault detection and diagnosis in advanced engineering technologies. This paper presents a novel probabilistic modeling approach for such power systems with a big data sequence. Firstly, we express input/output function of photovoltaic power systems in which solar irradiation and ambient temperature are regarded as input variable and electric power is output variable respectively. Based on this functional relationship, conditional probability for these three random variables(such as irradiation, temperature, and electric power) is mathematically defined and its estimation is accomplished from ratio of numbers of all sample data to numbers of cases related to two input variables, which is efficient in particular for a big data sequence of photovoltaic powers systems. Lastly, we predict the output values from a probabilistic model of photovoltaic power systems by using the expectation theory. Two case studies are carried out for testing reliability of the proposed modeling methodology in this paper.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.9
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• pp.74-82
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• 2013

This paper presents a novel maximum power point tracking for a photovoltaic power (PV) system with a direct control plan. Maximum power point tracking (MPPT) must usually be integrated with photovoltaic (PV) power systems so that the photovoltaic arrays are able to deliver maximum available power. The maximum available power is tracked using specialized algorithms such as Perturb and Observe (P&O) and incremental Conductance (indCond) methods. The proposed method has the direct control of the MPPT algorithm to change the duty cycle of a dc-dc converter. The main difference of the proposed system to existing MPPT systems includes elimination of the proportional-integral control loop and investigation of the effect of simplifying the control circuit. The proposed method thus has not only faster dynamic performance but also high tracking accuracy. Without a conventional controller, this method can control the dc-dc converter. A simulation model and the direct control of MPPT algorithm for the PV power system are developed by Matlab/Simulink, SimPowerSystems and Matlab/Stateflow.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1342-1348
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• 2015

The objective of this study is to propose a method to calculate prediction intervals for one-day-ahead hourly forecasts of photovoltaic power generation and to evaluate its performance. One year of data of two systems, representing contrasting examples of forecast’ accuracy, were used. The method is based on the maximum likelihood estimation, the similarity between the input data of future and past forecasts of photovoltaic power, and on an assumption about the distribution of the error of the forecasts. Two assumptions for the forecast error distribution were evaluated, a Laplacian and a Gaussian distribution assumption. The results show that the proposed method models well the photovoltaic power forecast error when the Laplacian distribution is used. For both systems and intervals calculated with 4 confidence levels, the intervals contained the true photovoltaic power generation in the amount near to the expected one.