Jung-Wook Park

Hybrid load forecasting method with analysis of temperature sensitivities

Load forecasting is essential in the electricity market for the participants to manage the market efficiently and stably. Many techniques for load forecasting, which are, for example, multiple linear regression, stochastic time series, Kalman filter, expert system, and computational intelligences such as fuzzy systems and artificial neural networks, have been investigated so far. This paper proposes a novel hybrid load forecasting algorithm, which combines the fuzzy linear regression method and the general exponential smoothing method with the analysis of temperature sensitivities. The fuzzy linear regression method is used to consider the lower load-demands in weekends and Monday than on weekdays. The normal load of weekdays is forecasted by the general exponential smoothing method. Moreover, the temperature sensitivities are used to improve the accuracy of the load forecasting with the relation to the daily load and temperature. The test results show that the proposed algorithm improves the accuracy of the load forecasting in 1996.

Adaptive critic based optimal neurocontrol for synchronous generator in power system using MLP/RBF neural networks

This paper presents a novel optimal neurocontroller that replaces the conventional controller (CONVC),which consists of the automatic voltage regulator (AVR) and turbine governor, to control a synchronous generator in a power system using a multilayer perceptron neural network (MLPN) and a radial basis function neural network (RBFN). The heuristic dynamic programming (HDP) based on the adaptive critic design (ACD) technique is used for the design of the neurocontroller. The performance of the MLPN based HDP neurocontroller (MHDPC) is compared with the RBFN based HDP neurocontroller (RHDPC) for small as well as large disturbances to a power system, and they are in turn compared with the CONVC. Simulation results are presented to show that the proposed neurocontrollers provide stable convergence with robustness, and the RHDPC outperforms the MHDPC and CONVC in terms of system damping and transient improvement.

New internal optimal neurocontrol for a series FACTS device in a power transmission line

In this paper, the proportional-integral (PI) based conventional internal controller (CONVC) of a power electronic based series compensator in an electric power system, is replaced by a nonlinear optimal controller based on the dual heuristic programming (DHP) optimization algorithm. The performance of the CONVC is compared with that of the DHP controller with respect to damping low frequency oscillations. Simulation results using the PSCAD/EMTDC software package are presented.

Impact of Electric Vehicle Penetration-Based Charging Demand on Load Profile

This paper presents a study the change of the load profile on the power system by the charging impact of electric vehicles (EVs) in 2020. The impact of charging EVs on the load demand is determined not only by the number of EVs in usage pattern, but also by the number of EVs being charged at once. The charging load is determined on an hourly basis using the number of the EVs based on different scenarios considering battery size, model, the use of vehicles, charging at home or work, and the method of charging, which is either fast or slow. Focusing on the impact of future load profile in Korea with EVs reaching up 10 and 20 percentage, increased power demand by EVs charging is analyzed. Also, this paper analyzes the impact of a time-of-use (TOU) tariff system on the charging of EVs in Korea. The results demonstrate how the penetration of EVs increases the load profile and decreases charging demand by TOU tariff system on the future power system.

Indirect Adaptive Neurocontrol Scheme for a Static Compensator Connected to a Power System

Abstract An indirect adaptive neurocontrol scheme for a Static Compensator connected to a power system using two Artificial Neural Networks (ANNs) is presented in this paper. The ANNs are trained online and there is no need for offline data. The neurocontroller has a better performance in adaptively controlling the Static Compensator and damping the system transients, compared to conventional controllers. Preliminary results are provided to show the performance of the neurocontroller for large disturbances.

Kalman-Filter Based Static Load Modeling of Real Power System Using K-EMS Data

So far, the importance for an accurate load model has been constantly raised and its necessity would be further more emphasized. Currently used load model for analysis of power system in Korea was developed 10 years ago, which is aggregated by applying the statistically estimated load compositions to load models based on individual appliances. As modern appliances have diversified and rapidly changed, the existing load model is no longer compatible with current loads in the Korean power system. Therefore, a measurement based load model is more suitable for modern power system analysis because it can accurately include the load characteristics by directly measuring target load. This paper proposes a ZIP model employing a Kalman-filter as the estimation algorithm for the model parameters. The Kamlan-filter based parameter identification offers an advantage of fast parameter determination by removing iterative calculation. To verify the proposed load model, the four-secondinterval real data from the Korea Energy Management System (K-EMS) is used.

Adaptive Protection Algorithm for Overcurrent Relay in Distribution System with DG

This paper proposes the new adaptive protection algorithm for inverse-time overcurrent relays (OCRs) to ensure their proper operating time and protective coordination. The application of the proposed algorithm requires digital protection relays with microcontroller and memory. The operating parameters of digital OCRs are adjusted based on the available data whenever system conditions (system with distributed generation (DG)) vary. Moreover, it can reduce the calculation time required to determine the operating parameters for achieving its purpose. To verify its effectiveness, several case studies are performed in time-domain simulation. The results show that the proposed adaptive protection algorithm can keep the proper operating time and provide the protective coordination time interval with fast response.

Power Loss Modeling of Individual IGBT and Advanced Voltage Balancing Scheme for MMC in VSC-HVDC System

This paper presents the new power dissipation model of individual switching device in a high-level modular multilevel converter (MMC), which can be mostly used in voltage sourced converter (VSC) based high-voltage direct current (HVDC) system and flexible AC transmission system (FACTS). Also, the voltage balancing method based on sorting algorithm is newly proposed to advance the MMC functionalities by effectively adjusting switching variations of the sub-module (SM). The proposed power dissipation model does not fully calculate the average power dissipation for numerous switching devices in an arm module. Instead, it estimates the power dissipation of every switching element based on the inherent operational principle of SM in MMC. In other words, the power dissipation is computed in every single switching event by using the polynomial curve fitting model with minimum computational efforts and high accuracy, which are required to manage the large number of SMs. After estimating the value of power dissipation, the thermal condition of every switching element is considered in the case of external disturbance. Then, the arm modeling for high- level MMC and its control scheme is implemented with the electromagnetic transient simulation program. Finally, the case study for applying to the MMC based HVDC system is carried out to select the appropriate insulated-gate bipolar transistor (IGBT) module in a steady-state, as well as to estimate the proper thermal condition of every switching element in a transient state.

Real-Time Maximum Power Point Tracking Method Based on Three Points Approximation by Digital Controller for PV System

This paper proposes the new method based on the availability of three points measurement and convexity of photovoltaic (PV) curve characteristic at the maximum power point (MPP). In general, the MPP tracking (MPPT) function is the important part of all PV systems due to their power- voltage (P-V) characteristics related with weather conditions. Then, the analog-to-digital converter (ADC) and low pass filter (LPF) are required to measure the voltage and current for MPPT by the digital controller, which is used to implement the PV power conditioning system (PCS). The measurement and quantization error due to rounding or truncation in ADC and the delay of LPF might degrade the reliability of MPPT. To overcome this limitation, the proposed method is proposed while improving the performances in both steady-state and dynamic responses based on the detailed investigation of its properties for availability and convexity. The performances of proposed method are evaluated with the several case studies by the PSCAD/EMTDC ® simulation. Then, the experimental results are given to verify its feasibility in real-time.

A Study on Optimization of Resistive SFCL for Multi-Machine Power System Using Eigenvalue Analysis

【This paper describes the optimization of a resistive superconducting fault current limiter (SFCL) applied to a multi-machine power system. Since the resistive SFCL is useful to provide a quick protection and reduce the fault current with its unique characteristics during a fault, it can be easily known that the transient stability of the entire system is improved effectively. However, when the SFCL is applied to a complex electric power system, especially a multi-machine power system, its direct optimization is difficult only considering fault conditions of the power system. Therefore, the resistive SFCL is optimized systematically by the eigenvalue analysis because it is effective to verify the transient stability and to evaluate the relationship between the parameters of a controller and the stability of the power system. Also, the dynamic effects of the SFCL on all generators of the multi-machine system can be considered synthetically with the eigenvalue analysis. Finally, the performance of the optimized SFCL is evaluated by time-domain simulation, and it is shown that that the optimized SFCL improves aggregately the damping performance of low-frequency oscillations in the entire multi-machine power system.】