• Journal of Power Electronics
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• v.19 no.1
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• pp.244-253
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• 2019

Finite control set model-predictive control (FCS-MPC) has received increasing attentions due to its outstanding dynamic performance. It is being widely used in power converters and multilevel inverters. However, FCS-MPC requires a lot of calculations, especially for multilevel-cascaded H-bridge (CHB) static synchronous compensators (STATCOMs), since it has to take account of all the feasible voltage vectors of inverters. Hence, an improved five-segment space vector pulse width modulation (SVPWM) method based on the non-orthogonal static reference frames is proposed. The proposed SVPWM method has a lower number of switching states and requires fewer computations than the conventional method. As a result, it makes FCS-MPC more efficient for multilevel cascaded H-bridge STATCOMs. The partial cost function is adopted to sequentially solve for the reference current and capacitor voltage. The proposed FCS-MPC method can reduce the calculation burden of the FCS-MPC strategy, and reduce both the switching frequency and power losses. Simulation and experimental results validate the excellent performance of the proposed method when compared with the conventional approach.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1448-1456
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• 2022

This paper studies a model to diagnose efficiency reduction of inverter using Multilayer Perceptron(MLP). In this study, two inverter data which started operation at different day was used. A Multilayer Perceptron model was made to predict photovoltaic power data of the latest inverter. As a result of the model's performance test, the Mean Absolute Percentage Error(MAPE) was 4.1034. The verified model was applied to one-year-old and two-year-old data after old inverter starting operation. The predictive power of one-year-old inverter was larger than the observed power by 724.9243 on average. And two-year-old inverter's predictive value was larger than the observed power by 836.4616 on average. The prediction error of two-year-old inverter rose 111.5572 on a year. This error is 0.4% of the total capacity. It was proved that the error is meaningful difference by t-test. The error is predicted value minus actual value. Which means that PV system actually generated less than prediction. Therefore, increasing error is decreasing conversion efficiency of inverter. Finally, conversion efficiency of the inverter decreased by 0.4% over a year using this model.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.7-14
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• 2016

Recently, as cloud computing technologies are developed, it enable to work anytime and anywhere by smart phone and computer. Also, cloud computing technologies are suited to reduce costs of maintaining IT infrastructure and initial investment, so cloud computing has been developed. As demand about cloud computing has risen sharply, problems of power consumption are occurred to maintain the environment of data center. To solve the problem, first of all, power consumption has been measured. Although using power meter to measure power consumption obtain accurate power consumption, extra cost is incurred. Thus, we propose prediction method about power consumption without power meter. To proving accuracy about proposed method, we perform CPU and Hard disk test on cloud computing environment. During the tests, we obtain both predictive value by proposed method and actual value by power meter, and we calculate error rate. As a result, error rate of predictive value and actual value shows about 4.22% in CPU test and about 8.51% in Hard disk test.

• Advances in Energy Research
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• v.5 no.1
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• pp.79-90
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• 2017

The main objective of load frequency control (LFC) is to keep the frequency value at nominal value and force deviation of the frequency to zero in case of load change. This paper suggests LFC by using a model predictive control (MPC), based on Integral Square Error (ISE) method designed to optimize the damping of oscillations in a two-area power system. The MPC is designed and simulated with a model system in state space, for robust performance in the system response. The proposed MPC is tuned by ISE to achieve superior efficiency. Moreover, its performance has been assessed and compared with the PI and PID conventional controllers. The settling time and overshoot with MPC are extremely minimized as compared with conventional controllers.

• International Journal of Automotive Technology
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• v.6 no.3
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• pp.243-249
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• 2005

To improve the ride comfort and handling characteristics of a vehicle, an active suspension which is controlled by external actuators can be used. An active suspension can control the vertical acceleration of a vehicle and the tire deflection to achieve the desired suspension goal. For this purpose, Model Predictive Control (MPC) scheme is applied with the assumption that the preview information of the oncoming road disturbance is available. The predictive control approach uses the output prediction to forecast the output over a time horizon and determines the future control over the horizon by minimizing the performance index. The developed method is applied to a half car model of four degrees-of-freedom and numerical simulations show that the MPC controller improves noticeably the ride qualities and handling performance of a vehicle.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1241-1250
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• 2018

Parallel three-phase voltage source inverters in a direct connection configuration are widely used to increase system power ratings. A zero-sequence circulating current can be generated according to the switching method; however, the zero-sequence circulating current not only distorts current, but also reduces the system reliability and efficiency. In this paper, a model predictive control scheme is proposed for parallel inverters to drive an interior permanent magnet synchronous motor with zero-sequence circulating current suppression. The voltage vector of the parallel inverters is derived to predict and control the torque and stator flux components. In addition, the zero-sequence circulating current is suppressed by designing the cost function without an additional current sensor and high-impedance inductor. Simulation and experimental results are presented to verify the proposed control scheme.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.74-76
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• 2019

This paper proposes an open-switch fault tolerant strategy based on the model predictive control for a full bidirectional switches indirect matrix converter (FBS-IMC). Compared to the conventional Indirect Matrix Converter (IMC), the FBS-IMC can provide healthy current path when open-switch fault is occurred. To keep the continuous operation, the fault tolerant strategy is developed by means of reversing the DC-link voltage polarity regardless of the faulty switch location in the rectifier or inverter stage. Therefore, the proposed control strategy can maintain the same input and output performances during the faulty condition as the normal condition. The simulation results are given to verify the effectiveness of the proposed strategy.

• Korean Journal of Organic Agriculture
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• v.25 no.3
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• pp.555-567
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• 2017

This study suggests the yield forecast model for chilli pepper using artificial neural network. For this, we select the most suitable network models for chilli pepper's yield and compare the predictive power with adaptive expectation model and panel model. The results show that the predictive power of artificial neural network with 5 weather input variables (temperature, precipitation, temperature range, humidity, sunshine amount) is higher than the alternative models. Implications for forecasting of yields are suggested at the end of this study.

• Proceedings of the KIPE Conference
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• 2001.12a
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• pp.198-203
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• 2001

In this paper, a new predictive control algorithm considering the parameters of series active filter has been proposed to improve the performance. By using the proposed control scheme, the current ripple drastically reduced and an improved steady state performance can be obtained. The proposed method has another advantage in the size. and cost by excluding additional passive fitters. The validity of the proposed method will be proved by the computer simulation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.453-456
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• 2007

The purpose of this study is to explain the importance of Vibration Monitoring Device by introducing an example of Predictive Maintenance System using Condition Monitoring System of Hydro-turbine generator. Confirming vibration of generation equipment is commissioning procedure during equipment completion for checking guaranteed items. Data from Generator output range are used to determine output band to continue the performance of equipment. The Vibration Monitoring System is not absolute method of maintenance, but if it is used well with expert, it will be visible, data-analyzed, scientific maintenance more than others. And also, Condition Monitoring System is very important for remote controlled small hydro-power plant although most of it is installed in Large hydro-power plant.