This paper proposes a novel power compensation algorithm in three-phase four-wire systems by using p-q-r theory. The p-q-r theory is compared with two previous instantaneous power theories, p-q theory and cross vector theory. The p-q-r theory provides two-degrees of freedom to control the system currents by only compensating the instantaneous imaginary power without using any energy storage element. The definition of powers maintains power conservation, and agrees well with the general understanding of power. Simulation results show the superiority of p-q-r theory both in definition and compensation.

The main contents of this paper are to verify the environmental factors affecting the power generation of floating photovoltaic systems and to present the power generation prediction model considering environmental factors by using regression analysis and neural networks studied during the last decade. This study focused on a comparative analysis of which model is best suited for the power generation prediction of the floating photovoltaic (PV) system. To compare the power generation characteristics of a floating and a land-based PV system, two identical 2.5 kW PV systems were installed—one on the water surface in the Boryeong Dam, Korea, and the other nearby on dry land—and their performances were compared. The solar irradiance of the floating PV system was 1.1% lower than that of the land-based PV. Nevertheless, the floating PV module temperature was 4.9% lower than that of the land-based PV, generating approximately 3% more power. Using the correlation analysis of data mining techniques, environmental factors affecting the efficiency of the floating PV system were investigated. The correlation coefficient between the module temperature and water temperature was $r=0.6317$ which proves that the high efficiency and low module temperature characteristics of the floating PV system, when compared with that of the land-based PV, are due to the water evaporation effect. Considering environmental factors, power-generation prediction models based on regression analysis and neural networks are presented, and their accuracies are compared. This comparison confirms that the accuracy of the power generation prediction model using neural networks was approximately 2.59% higher than that of the regression analysis method. As a result of adjusting the hidden nodes in the neural network algorithm, it was confirmed that a neural network algorithm with ten hidden nodes was most suitable for calculating the amount of power generation.

This paper proposes a multi-functional Photovoltaic (PV) inverter based on the Unified Power Quality Conditioner (UPQC) configuration. Power quality improvement is a difficult issue to solve for isolated areas or islands connected to the mainland through long submarine cables. In the proposed system, the line voltage is compensated for by the series inverter while the shunt inverter delivers the PV generating power to the grid. Depending on the technical conditions of power quality and system environment, it has five different operating modes. Especially during poor power quality conditions, the sensitive load is separated from the normal load to provide a different power quality level by using the microgrid conception. In this paper, the control method and the power flow for each mode are described, and the operational performance is verified through a PSiM simulation so that it can be applied to the power quality improvement of weak grid power systems such as in isolated areas or on islands connected to the mainland by long submarine cables.

This paper proposes the grid synchronization method of inverter using a quasi Proportional+Multi Resonant (P+MR) control-based voltage controller a stationary reference frame. The inverter supplies a non-linear load under the islanded mode. In islanded mode, the inverter is defined as a voltage source to supply the full local load demand without a connection to the grid. On the other hand, if the grid is restored from a previous fault or the strategic islanding is unnecessary, the inverter needs to be synchronized with the phase of the grid before the transfer from islanded mode to grid-connected mode. When the system is modeled and controlled based on the stationary reference frame control, the AC reference voltage, which has a constant voltage and frequency in islanded mode, is substituted to the AC grid voltage. Significant error can occur due to the large phase differences between the phase of reference and that of the measured value. This error also can cause severe voltage dynamic problems. In addition, if any nonlinear local load is connected to the output of the inverter, it becomes more serious due to the harmonics generated from the loads. In this paper, the PR control under a stationary reference frame is used for voltage control under islanded mode considering the harmonic effects from the nonlinear load. The seamless grid synchronization method based on this PR control is proposed to solve the aforementioned problems. The validity of the proposed seamless grid synchronization method is verified through PSiM simulations and experimental results.

Wind power systems are being integrated increasingly into the power grid because of their large capacity and easy access to the transmission grid. The reliability of wind power plants is very important and the elimination of protective relay’s malfunctions is essential to the mitigation of power quality problems due to the frequent starts and stops of high capacity wind generators. In this study, the problem of frequent false operations of the protective relays are analyzed using real data as line voltages, line currents, and wind speed. A new re-coordination of the overcurrent relay (OCR) based on the wind speed is proposed to avoid frequent operations of relays and tested for a grid-connected wind farm. This study verifies that the false actions by the OCRs that are not accompanied by actual electrical faults in the power grid or wind power system can be solved by the appropriate re-coordination of the OCR.