There has been active research on motor current signature analysis (MCSA) for over the last 30+ years, as it can provide remote monitoring of rotor and load defects using the current sensor available in the motor control center. However, many years of experience has shown that 1) rotor eccentricity and load defects cannot be distinguished, and 2) false rotor cage fault indications are common in the field. There is a recent trend towards integrating “smart” self-diagnostics in electric machines through embedded sensors, especially in applications such as submersible pumps or nuclear plants where motor inspection is difficult. In this work, airgap flux measurement is evaluated as an option for providing sensitive and reliable monitoring of motor and load defects. Analysis of the airgap flux search coil voltage during motor starting is proposed for reliable detection and classification of rotor cage, eccentricity, and mechanical defects in the load. Experimental testing is provided to verify the claims made, for cases where MCSA fails.

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.

In South Korea, Renewable Energy Sources (RES) have been increasing with the application of energy policies, such as Feed in Tariff (FIT) and the Renewable Portfolio Standard (RPS). However, a rapid increase in RES supply leads to an uncertain power supply due to the intermittent output of RES. A representative example is the curtailment of Wind Turbines (WT), which frequently occurs in Jeju Island, South Korea. The proportion of RES power on Jeju Island is 67%, and there are cases where WT is curtailed among the operable sections to maintain the balance of power supply and demand. This paper applies Power-to-Gas (P2G) technology to hydrogenate, store, and utilize unused power to solve this problem. In this paper, Aewol-eup in Jeju Island is selected as a target site for case study. An Integrated Energy System (IES) for various energy operations is designed to control RES output. This paper proposes the optimal facility configuration and finally drives the optimal design and operation solution of IES by analyzing the objective functions and focusing on the Independent Power Producer (IPP) perspective.

Autostrainer is used for the purpose of debris removal in order to increase the efficiency of the heat exchanger by taking the required raw water as a heat source for the pre-cooling hydrothermal system. During the operation of the autostrainer, a pressure drop occurs due to the blockage of the screen in the autostrainer. As a result, the resistance of the pipe network for the intake system is changed, and the operating efficiency point of the pump, valve, heat exchanger, etc., is altered. By calculating the system resistance taking into account the pressure drop caused by the blockage rate of the screen in the autostrainer, the optimum operating efficiency can be expected when the intake system such as a pump, valve or heat exchanger, etc. is constructed. In this study, Computational Fluid Dynamics (CFD) was used to construct a scenario in which screen blockage may occur, predicting pressure drop for the slot cross-section of the screen in the autostrainer to derive a resistance coefficient value. The resistance coefficient value was applied to the porous region corresponding to the screen in the autostrainer’s 3D shape and compared with the experimental value for the pressure drop and headloss coefficient. By predicting the pressure drop for the autostrainer’s screen blockage rate of 0% to 50%, the coefficient of headloss required for the design of the intake system was calculated. Additionally, in order to predict the debris removal rate, which is the original role of the autostrainer, the debris was assumed to be particles, and sedimentation rate was predicted according to the size and weight of the particles. Building on this, when introducing the autostrainer used in pre-cooling into the membrane filtration process, due to the pressure loss caused by the inflow of debris during the use of the autostrainer, this study aims to utilize Computational Fluid Dynamics (CFD) to derive the head loss coefficients according to the screen blockage rate, and use these coefficients to calculate the system’s resistance curve. Additionally, in this study, the term “autostrainer” is used instead of the term “membrane strainer” to align with more popular terminology.

Due to the penetration of renewable energy sources increasing in South Korea, problems related to system reliability have been emerging. Thus, localized control methods have also been gaining attention as one of the measures. However, due to the AOs (asset owners) lacking management experience of coordinating resources between the BESS (battery energy storage system) and the renewable device, there have been multiple issues related to damages caused by fire. Thus, the governmental reliability committee in South Korea has recently mandated an order adding reliability constraints to the SoC (state of charge) management and incentives for the AOs to follow the reliability constraints as specified, despite concerns from the AOs that the order possibly reduces their revenues. Thus, this study provides a structured analysis, for the first time, on how the incentive and the reliability constraints influence and interact with each other in coordinated operating schemes between BESSs and renewables as integrated scheduling systems. In the base case, the current scheduling method was applied. In case 1, profit maximization was introduced to confirm the effectiveness of the structured operation. In case 2, a reliability constraint was added, and a reliability constraint with incentives was added in case 3 to confirm the effects thereafter on the revenue streams.

In this paper, verification of operation and control of a vertical stabilization (VS) converter for a superconducting coil by using a real-time digital simulator is described. The VS converter supplies voltage (±1000V) and current (±22.5kA) to the superconducting coil for plasma current vertical stabilization, and four-quadrant operation must be achieved without a zero-current discontinuous section. To remove any zero-current discontinuous sections, circulation current control is required, but it is hard to analyze and design it because of the characteristics of thyristor nonlinearity. In this paper, delay time of the thyristor and processor is implemented using a zero-order hold, and an equivalent model is designed and analyzed. Circulation current control and difference current control are similarly analyzed, because both equivalent circuits are the same and are satisfied with a 54° phase margin and a 11ms step response. In addition, gamma control is designed to restrict the firing angle to prevent commutation failure, and commutation failure is prevented by the proposed gamma control, even if a short circuit or sag occurs in the grid. To verify the feasibility of the VS converter, a real Zynq-based controller is assembled and a power system, including the VS converter, is implemented in a real-time digital simulator (RTDS) for the hardware-in-the-loop simulation (HILS). Experimental results from using HILS matched the simulation results and analysis.