Short-Term Wind Power Prediction Using Fuzzy Clustering and Support Vector Regression

A sustainable production of electricity is essential for low carbon green growth in South Korea. The generation of wind power as renewable energy has been rapidly growing around the world. Undoubtedly, wind energy is unlimited in potential. However due to its own intermittency and volatility, there are difficulties in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. To cope with this, many works have been done for wind speed and power forecasting. In this paper, an SVR （support vector regression） using FCM （Fuzzy C-Means） is proposed for wind speed forecasting. This paper describes the design of an FCM based SVR to increase the prediction accuracy. Proposed model was compared with ordinary SVR model using balanced and unbalanced test data. Also, multi-step ahead forecasting result was compared. Kernel parameters in SVR are adaptively determined in order to improve forecasting accuracy. An illustrative example is given by using real-world wind farm dataset. According to the experimental results, it is shown that the proposed method provides better forecasts of wind power.

Development of Fault Management Dispatcher Training Simulator for TDAS in Korea

A fault management dispatcher training simulator for large-scale Distribution Automation System (TDAS) is developed to train operators in distribution control center. This simulator is composed of independent simulation server and operator consoles and can be used for network analysis, network operation, fault management and evaluation. TDAS DB is duplicated online to the simulation server keeping the data security. The system can model distribution network penetrated with distributed generations (DG) using the real data from the TDAS DB. Network fault scenarios are automatically generated by calculating fault current and generating fault indicators. Also, manual entry of cry wolf alarm is available. Moreover, operation solution for scenario of fault isolation and service restoration is generated automatically so that trainee can check their operation result. Operator actions during training session are saved and can be played back as well as displayed on one-line diagram pictures.

CIM Model Extension for Intelligent DAS of Smart Power Grid in Korea

The CIM （common information model） is an abstract information model that can be used to model an electrical network and various equipments used on the network. By using a common model, utilities and vendors can reduce their integration costs, which should allow more resources to be applied toward increased functionality for managing and optimizing the electrical system. As a part of smart grid, the SPG （smart power grid） was built on Jeju Island. The SPG consists of IDAS （intelligent distribution automation system）, substation automation system, intelligent transmission system, and active telemetrics system. To integrate these systems which have different operating systems and platforms CIM standard was used. But IDAS has many functions and advanced algorithms not defined in CIM. In this paper, the authors introduce how to develop and extend the CIM model for managing the IDAS.

KoNA:Korean Nucleotide Archive as A New Data Repository for Nucleotide Sequence Data

During the last decade,the generation and accumulation of petabase-scale high-throughput sequencing data have resulted in great challenges,including access to human data,as well as transfer,storage,and sharing of enormous amounts of data.To promote data-driven biological research,the Korean government announced that all biological data generated from government-funded research projects should be deposited at the Korea BioData Station(K-BDS),which consists of multiple databases for individual data types.Here,we introduce the Korean Nucleotide Archive(KoNA),a repository of nucleotide sequence data.As of July 2022,the Korean Read Archive in KoNA has collected over 477 TB of raw next-generation sequencing data from national genome projects.To ensure data quality and prepare for international alignment,a standard operating procedure was adopted,which is similar to that of the International Nucleotide Sequence Database Collaboration.The standard operating procedure includes quality control processes for submitted data and metadata using an automated pipeline,followed by manual examination.To ensure fast and stable data transfer,a high-speed transmission system called GBox is used in KoNA.Furthermore,the data uploaded to or downloaded from KoNA through GBox can be readily processed using a cloud computing service called Bio-Express.This seamless coupling of KoNA,GBox,and Bio-Express enhances the data experience,including submission,access,and analysis of raw nucleotide sequences.KoNA not only satisfies the unmet needs for a national sequence repository in Korea but also provides datasets to researchers globally and contributes to advances in genomics.The KoNA is available at https://www.kobic.re.kr/kona/.