Yong-Beum Yoon

Comparison of transient stability analysis and large-scale real time digital simulation

The KEPS Real Time Digital Simulator (RTDS/sup (R)/) is the largest real time power system simulator ever built. A power system which includes 320 (3-phase) buses and 90 generators has been modeled and run in real time. Since such large-scale systems were involved, it was not practical to validate them using nonreal time electromagnetic transient programs such as EMTDC/sup TM/ or EMTP. Instead, the results of the real time electromagnetic transient simulation were validated by comparing transient stability simulations run using PTIs PSS/E/sup TM/ program. The comparison of results from the two programs were in almost all cases very good. However, as expected, some differences did exist and were investigated. The differences in the results were primarily traced to the fact that the electromagnetic transient solution algorithm provides more detail and therefore greater accuracy than the transient stability algorithm. After finding very good comparison of results between the RTDS Simulator and PSS/E, and after investigating the discrepancies found, KEPCO gained the necessary confidence to use the large-scale real time simulator to analyze and develop their power system.

Case study of customer baseline(CBL) load determination in Korea based on statistical method

Load management program in Korea is classified into two classes. One is related with load management equipments, such as demand controller, remote control air-conditioner, and thermal storage systems et al. The other is related with incentive for load reduction by customers willingness. Typical element for incentive is the determination of customer basehne(CBL) of customer load. It is the load forecasting of each customer. Two methods have been proposed to get this solution, regression or statistical method. It is suggested that statistical method is better than regression at very random loads. This paper proposes case study analysis of the statistical method in real Korean customers.

Development of Reliability Contribution Function of Power System including Wind Turbine Generators combined with Battery Energy Storage System

Abstract - This paper presents a study on reliability assessment and new contribution function development of power system including Wind Turbine Generator(WTG) combined with Battery Energy Storage System(BESS). This paper develops and proposes new reliability contribution function of BESS installed at wind farms. The methodology of reliability assessment, using Monte Carlo Simulation(MCS) method to simulate sample state duration, is proposed in detail. Forced Outage Rate(FOR) considered probabilistic approach for conventional generators is modelled in this paper. The penetration of large wind power can make risk to power system adequacy, quality and stability. Although the fluctuation of wind power, BESS installed at wind farms may smooth the wind power fluctuation. Using small size system as similar as Jeju island power system, a case study of reliability evaluation and new proposed contribution function of power system containing WTG combined with BESS is demonstrated in this paper, which would contributes to BESS reliability contribution and assessment tools of actual power system in future. Key Words : Wind turbine generator(WTG), Battery energy storage system(BESS), Monte carlo simulation(MCS), Reliability evaluation, ESS reliability contribution † Corresponding Author : Dept. of Electrical Eng., RIGET, ERI, Gyeongsang National University, Korea E-mail : jschoi@gnu.ac.kr* Dept. of Electrical Engineering, Gyeonsang National University , Korea ** KEPRI, KEPCO*** Dept. of Electrical Engineering, Daejin University, Korea Received : September 9, 2015; Accepted : February 19, 2016

Reliability Evaluation with Wind Turbine Generators and an Energy Storage System for the Jeju Island Power System

This paper proposes probabilistic reliability evaluation model of power system considering Wind Turbine Generator(WTG) integrated with Energy Storage System(ESS). Monte carlo sample state duration simulation method is used for the evaluation. Because the power output from WTG units usually fluctuates randomly, the power cannot be counted on to continuously satisfy the system load. Although the power output at any time is not controllable, the power output can be utilized by ESS. The ESS may make to smooth the fluctuation of the WTG power output. The detail process of power system reliability evaluation considering ESS cooperated WTG is presented using case study of Jeju island power system in the paper.

Determining wind farm locations, allocation of wind farm capacity, and sizing of energy storage for 17 GW new wind power capacity in Korea

The Korean government plans to install 17 GW of wind power capacity by 2027. However, wind farm locations, individual wind farm generation capacities, and the strategies for minimizing wind power variability have not yet been defined. In this paper, the best locations are identified based on annual wind speeds and availability, and the generation capacity of the wind farms at each selected location are allocated by using a weighted evaluation method. In addition, the strategies proposed in this paper for minimizing wind power variability are aggregation of wind farms (to take advantage of the smoothing effect) and integration of energy storage systems (to smoothen power output and provide ancillary services). Wind data was obtained from the Korea Meteorological Association, and wind power outputs were calculated using the power curve of a 2 MW Vesta wind turbine as a model for each generation unit. Sizing of ESS capacity was done by using Discrete Fourier Transform analysis and probability density analysis.

Margin calculation of VSC HVDC modules based on MMC

This paper deals with the reliability of VSC HVDC valve of MMC(Modular Multilevel Converter) based HVDC system. The final destination of this paper is to determine the redundancy of MMC valve. For this, several prediction methods were introduced, finally, the used method is “binomial failure method”. To evaluate an availability and a reliability prediction of MMC valve, which was composed of DC/DC converter, gate driver, capacitor and IGBTs, the used failure datum of MMC module were tracking data, that is, based on the experimental results. The highlight of this is to use the simplified equation to find the valve redundancy, that is, transforming binomial function to De Moivres formula. This method is the first trial to find the valve margin.