• Environmental and Resource Economics Review
• /
• v.28 no.4
• /
• pp.467-495
• /
• 2019

Uncertainty of renewable energy such as photovoltaic(PV) power is detrimental to the flexibility of the power system. Therefore, precise prediction of PV power generation is important to make the power system stable. The purpose of this study is to forecast PV power generation using meteorological data including particulate matter(PM). In this study, PV power generation is predicted by support vector machine using RBF kernel function based on machine learning. Comparing the forecasting performances by including or excluding PM variable in predictor variables, we find that the forecasting model considering PM is better. Forecasting models considering PM variable show error reduction of 1.43%, 3.60%, and 3.88% in forecasting power generation between 6am~8pm, between 12pm~2pm, and at 1pm, respectively. Especially, the accuracy of the forecasting model including PM variable is increased in daytime when PV power generation is high.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.1
• /
• pp.65-75
• /
• 2016

Aiming at analyzing the power flow of the distribution systems with distribution transformer (DT) branches and PV nodes, a hybrid three-phase power flow methodology is presented in this paper. The incidence formulas among node voltages, loop currents and node current injections have been developed based on node-branch incidence matrix of the distribution network. The method can solve the power flow directly and has higher efficiency. Moreover, the paper provides a modified method to model DT branches by considering winding connections, phase shifting and off-nominal tap ratio, and then DT branches could be seen like one transmission line with the proposed power flow method. To deal with the PV nodes, an improved approach to calculate reactive power increment at each PV node was deduced based on the assumption that the positive-sequence voltage magnitude of PV node is fixed at a given value. Then during calculating the power flow at each iteration, it only needs to update current injection at each PV node with the proposed algorithm. The process is very simple and clear. The results of IEEE 4 nodes and the modified IEEE 34 nodes test feeders verified the correctness and efficiency of the proposed hybrid power flow algorithm.

• Journal of Power Electronics
• /
• v.14 no.3
• /
• pp.444-457
• /
• 2014

This paper presents the design and realization of a digital PV simulator with a Push-Pull Forward (PPF) circuit based on the principle of modular hardware and configurable software. A PPF circuit is chosen as the main circuit to restrain the magnetic biasing of the core for a DC-DC converter and to reduce the spike of the turn-off voltage across every switch. Control and I/O interface based on a personal computer (PC) and multifunction data acquisition card, can conveniently achieve the data acquisition and configuration of the control algorithm and interface due to the abundant software resources of computers. In addition, the control program developed in Matlab/Simulink can conveniently construct and adjust both the models and parameters. It can also run in real-time under the external mode of Simulink by loading the modules of the Real-Time Windows Target. The mathematic models of the Push-Pull Forward circuit and the digital PV simulator are established in this paper by the state-space averaging method. The pole-zero cancellation technique is employed and then its controller parameters are systematically designed based on the performance analysis of the root loci of the closed current loop with $k_i$ and $R_L$ as variables. A fuzzy PI controller based on the Takagi-Sugeno fuzzy model is applied to regulate the controller parameters self-adaptively according to the change of $R_L$ and the operating point of the PV simulator to match the controller parameters with $R_L$. The stationary and dynamic performances of the PV simulator are tested by experiments, and the experimental results show that the PV simulator has the merits of a wide effective working range, high steady-state accuracy and good dynamic performances.

• Proceedings of the KIPE Conference
• /
• 2003.07a
• /
• pp.204-207
• /
• 2003

PV model is presented based on the shockley diode equation. The simple model has a photo-current source, an single diode junction and a series resistance and includes temperature dependences. An accurate PV module electrical model is presented, matching with boost converter MPPT strategy and demonstrated in Matlab for a typical general purpose solar cell. Given solar insolation and temperature, the model returns current vector and MPP.

• Proceedings of the KIEE Conference
• /
• 2004.07e
• /
• pp.110-113
• /
• 2004

PV model is presented based on the shockley diode equation. The simple model has a photo-current source, an single diode junction and a series resistance and includes temperature dependences. An accurate PV module electrical model is presented, matching with boost converter MPPT strategy and demosnstarted in Matlab for a typical general purpose solar cell. Given solar insolation and temperature, the model returns current vector and MPP.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2004.05c
• /
• pp.17-20
• /
• 2004

PV model is presented based on the shockley diode equation. The simple model has a photo-current source, an single diode junction and a series resistance and includes temperature dependences. An accurate PV module electrical model is presented, matching with boost converter MPPT strategy and demosntarted in Matlab for a typical general purpose solar cell. Given solar insolation and temperature, the model returns current vector and MPP.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.11
• /
• pp.239-249
• /
• 2019

Recently, the Korean government has implemented a policy to expand renewable energy sources. Large-scale PV systems are being actively interconnected with the distribution system. On the other hand, when a large-scale PV system is installed and operated, the customer voltages could violate the allowable voltage limit due to reverse power flow of the PV system. To overcome these problems, an enhancement method for hosting the capacity of the PV system in a distribution system is being actively conducted. Therefore, to improve the hosting capacity of the PV system, this paper proposes a model of a reconfiguration of the distribution system, which is composed of three sections and three connections based on PSCAD/EMTDC S/W, and proposes an evaluation algorithm for the feeder reconfiguration to maximize an adaption of the PV system. In addition, this paper presents the optimal method of the feeder reconfiguration section to evaluate the maximum capacity of the PV system to keep customer voltages within the allowable voltage limits based on various operation scenarios, such as the capacity of a PV system and section of feeder reconfiguration. From the simulation results based on the PSCAD/EMTDC modeling and evaluation algorithm, it was confirmed that they are a useful and practical tool to enhance hosting the capacity of a PV system in a distribution system.

• Korean Journal of Construction Engineering and Management
• /
• v.20 no.6
• /
• pp.126-131
• /
• 2019

The estimation of available solar energy at particular locations is critical to find and assess suitable locations of PV sites. The amount of PV power generation is however affected by various geographical factors (e.g., weather), which may make it difficult to identify the complex relationship between affecting factors and power outputs and to apply findings from one study to another in different locations. This study thus undertakes a regression analysis using data collected from 172 PV plants spatially distributed in Korea to identify critical weather conditions and estimate the potential power generation of PV systems. Such data also include solar radiation, precipitation, fine dust, humidity, temperature, cloud amount, sunshine duration, and wind speed. The estimated PV power generation is then compared to the actual PV power generation to evaluate prediction performance. As a result, the proposed model achieves a MAPE of 11.696(%) and an R-squred of 0.979. It is also found that the variables, excluding humidity, are all statistically significant in predicting the efficiency of PV power generation. According, this study may facilitate the understanding of what weather conditions can be considered and the estimation of PV power generation for evaluating and determining suitable locations of PV facilities.

• IE interfaces
• /
• v.25 no.4
• /
• pp.441-449
• /
• 2012

Solar PV(photovoltaic) is paid great attention to as a possible renewable energy source to overcome recent global energy crisis. However to be a viable alternative energy source compared with fossil fuel, its market competitiveness should be attained. Grid parity is one of effective measure of market competitiveness of renewable energy. In this paper, we forecast the grid parity timing of solar PV energy in Korea using two factor learning curve model. Two factors considered in the present model are production capacity and technological improvement. As a result, it is forecasted that the grid parity will be achieved in 2019 in Korea.

• 한국신재생에너지학회:학술대회논문집
• /
• 2011.11a
• /
• pp.62.2-62.2
• /
• 2011

To guarantee 20-25 years to the lifetime of the PV modules without failure, reliability test of the module is very important. Field-aged test of the outdoor environment is required. However, due to time constraints, accelerated testing is required to predict the lifetime of PV modules and find causes of failure. Failure is caused by many complex phenomena. In this study, we experimented two accelerated tests about corrosion and fatigue, respectively. First, temperature cycling test for fatigue were tested and Coffin-Manson equation was analyzed. Second, damp heat test for corrosion were tested and Eyring equation were analyzed. Finally, using two-mode failure model, we suggest a new lifetime model that analyze the phenomenon by combining two kinds of data.