디지털변전소는 IEC 61850 기반 상위운영장치와 IED(Intelligent Electric Device)로 구성된 변전자동화시스템이 적용된 변전소를 의미한다. 한전은 2013 년 이후로 신설되는 154kV 변전소를 디지털변전소로 구축하고 있으며, 기설변전소도 디지털화를 통해 디지털변전소로 변모하고 있다. 이렇게 변전소에 IEC 61850 기반의 변전자동화시스템이 확대 도입됨에 따라 통신 설정과 성능을 검증하는 시험이 반드시 필요하다. 이에 전력연구원은 세계 최고수준의 IEC 61850 기반 디지털변전 시험기술을 확보하였으며, 본 보고서를 통해 연구원이 보유하고 있는 시험기술과 현장에 적용한 사례를 소개하고자 한다.

한국전력공사 전력연구원에서는 2018 년 고창 전력시험센터에서 최초 화재 발생 이후, ESS 시스템의 화재 발생 원인에 대한 분석 및 실증시험을 수행하였으며, 이를 통해 현장에서 화재 발생을 최소화할 수 있는 다양한 설비개선안을 도출하였다. 도출된 설비개선안을 통하여 기술지원 요청 부서에서는 전국의 모든 현장 적용을 시행하고 있으며, 이를 통하여 한전이 보유한 모든 ESS 설비는 2021 년 내재 가동될 예정이다.

우리나라 서해안 및 동해안지역에는 대규모 발전단지가 집중되어 운영 중이며 이 발전단지들의 발전력을 송전하고 있는 765kV 송전선로 2 회선 고장이 발생하는 경우 송전선로의 용량부족으로 인해서 수 GW 규모의 발전력을 불시에 탈락시키도록 보호체계(SPS, Special Protection System)가 운영 중이다. 이 SPS 가 동작하여 대규모 공급능력이 불시에 상실되면 급격한 주파수 하락이 발생하게 되어 저주파수계전기(Under Frequency Relay, UFR)가 동작할 수 있기 때문에 SPS 탈락 발전기의 출력을 상시에 감소시키는 제약비발전(Constraint off)을 시행하고 있다. 이 제약비발전으로 인해 매년 수천억원의 제약비용이 발생하고 있기 때문에 제약을 완화시키기 위한 방안으로 배터리 에너지저장장치(BESS)를 적용하는 사업이 추진되고 있다. 이는 "발전제약완화 에너지저장장치(이하 발전제약완화용 ESS) 사업"으로 불리며 전국 19 개 변전소에 총 1.4GW(2C-Rate)의 에너지저장장치가 설치되는 국내 최대규모의 BESS 사업이다. 향후 송전망 확충에 의해서 발전제약이 해소되는 경우 주파수 조정용, 재생에너지 변동성 완화용 등의 다목적 ESS 로 활용될 계획이다. 본 보고서에서는 발전제약완화 ESS 사업의 기술적 효과를 실효치 기반의 시뮬레이션(PSS/E v33.3)을 통해서 검토하였다.

지상변압기는 수용가에 직접적으로 전력을 공급하는 역할을 수행하며 저압 선로의 고장으로부터 계통을 보호하기 위한 보호장치를 구비한다. 본 기술지원은 지상변압기의 STP 미동작에 따른 화재원인을 분석하고 적정동작범위를 제안한다.

한전에서 운영중인 사우디라빅발전소에서 저압터빈 블레이드가 파손되었다. 블레이드의 경우 터빈의 핵심부품으로서 증기를 활용하여 발전기를 회전시켜 전기를 생산하는데 필수 부품이다. 반복적인 사고발생을 예방하기 위해 조직분석, 운전신호 분석등을 활용하여 원인을 규명하였고, 대책을 제시하였다.

관형지지물은 단일 강관 기둥 형태의 송전탑으로 강관은 상하 여러 개의 프레임으로 분할되어 플랜지부에서 볼트로 체결된다. 신설 송전선로 관형지지물 플랜지 연결부에서 가압전 조립 볼트 절손이 발견됨에 따라 강관도괴방지 대책 수립을 위한 손상원인분석 기술지원을 수행하였다. 본 건에 대해 파손면·균열 분석 기술을 통해 제작과정 상의 문제가 있었음을 확인하였다.

해외 발전사업의 기술 경쟁력 우위 선점을 위해서는 발전시스템에 대한 최적설계기술 및 발전소 운영 기간 중 최소 비용으로 높은 신뢰도의 설비 관리, 최적 성능 유지를 할 수 있는 O&M 관리 기술이 필요하다. 전력연구원은 해외발전사업 전주기 기술지원을 위한 연구개발을 수행하고 있다.

한전에서 운영중인 요르단 알카트라나발전소에서 발전기 고정자권선 전계완화 절연물의 손상되었다. Overlap 부위의 정비를 수행한 결과를 분석하였고, 손상원인을 규명하여 불시정지로 인한 손실을 최소화하기 위한 단기대책과 장기적인 대책을 제시하였다.

As the big data analysis technologies has been developed worldwide, the importance of asset management for electric power facilities based data analysis is increasing. It is essential to secure quality of data that will determine the performance of the RISK evaluation algorithm for asset management. To improve reliability of asset management, asset data must be preprocessed. In particular, the process of cleaning dirty data is required, and it is also urgent to develop an algorithm to reduce time and improve accuracy for data treatment. In this paper, the result of the development of an automatic cleaning algorithm specialized in overhead transmission asset data is presented. A data cleaning algorithm was developed to enable data clean by analyzing quality and overall pattern of raw data.

The fundamental element to be kept for big data analysis, artificial intelligence technologies and asset management system is a data quality, which could directly affect the entire system reliability. For this reason, the momentum of data cleaning works is recently increased and data cleaning methods have been investigating around the world. In the field of electric power, however, asset data cleaning methods have not been fully determined therefore, automatic cleaning algorithm of asset data for transmission cables has been studied in this paper. Cleaning algorithm is composed of missing data treatment and outlier data one. Rule-based and expert opinion based cleaning methods are converged and utilized for these dirty data.

With the social atmosphere of respect for human life and the increasing interest in safety of field workers, research and development is underway in various ways to transform direct live method into indirect live method in the field of distribution. As part of this measure, it was necessary to convert electric pole and complex facilities work from machining power distribution to indirect live operation, and install a straight connecting sleeve that connects cut wires for by-pass method, but it failed to meet the tensile strength standard when constructing a sleeve constructed by direct method. In this paper, the design factors were derived based on the case of overseas similar sleeves and the tensile strength evaluation of each variable was performed, based on the analysis of these test results, the method for securing tensile strength of straight-line access sleeves for indirect running was presented.

The government has proposed a mission to enhance intelligent power networks, decrease coal-fired generation, expand distributed energy resources, and promote energy prosumer into the distribution network in Korea. Installation cost of facility expansion to guaranteed interconnection with small distributed energy resources increases dramatically on KEPCO's distribution sector. And it is hard to withdraw in time. In addition, there are explicit research is required to meet the reliability on grid corresponding to the increase of distributed power. Infrastructure support for accommodating energy prosumer is also needed. Therefore, KEPCO is pushing transition to DSO by expanding distribution management scope and changing its roles. In addition, KEPCO is proactively preparing for integrated operation between distribution network and existing distributed power which is accommodated passively. KEPCO is also trying to accept multiple network users, e.g. building platforms, to manage a data and promote new markets. In the long term, transition to DSO will achieve saving investment costs for accommodating distributed sources and maintaining stable electrical quality. And it will be possible to create new business model using the platform to secure revenue.

Encouragement of DER from Korean government with several policies boosts DER installation in power system. When the penetration of DER in the grid is getting high, loss of generation with break-away of DER by abnormal grid conditions should be considered, because loss of high generation causes abnormal low frequency and additional operations of protection system. Therefore, KEPCO where is Korean power utility is preparing improvement in regulations for DERs connected to the grid to support abnormal grid conditions such as low and high frequencies or voltages. This is called 'Ride Through' because the requirement is for DER to maintain grid connection during required periods when abnormal grid conditions occur. However, it is not easy to have a test for ride through capability in reality because emulation of abnormal grid conditions is not possible in real power system in operation. Also, it is not easy to have a study on grid effect when ride through capability fails with the same reason. PHILs (Power Hardware In the Loop System) makes it possible to analyze power system and hardware performance at once. Therefore, this paper introduces PHILs test methods and presents verification of ride through capability especially for low voltage grid conditions.

High penetration of renewable energy generators causes unnecessary investment for power system facilities. Especially with Korean government policies such as Renewable Energy 3020 and Inter-connection support Responsibility of KEPCO for 1 MW DERs, the applications of DER interconnection in distribution system have been increasing. To save the investment, smart control functions for DERs are required and the test bed for the inverters which have not been prepared are necessary to insure DER inter-connection stability. For this, test bed for advanced functions of a smart inverter has been constructed and the tests for necessary functions have been implemented. In this paper, the test bed and environment as well as specifications are introduced and the test results for the validation of the functions are analyzed.

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.

This paper presents the root cause failure analysis of the circulating water pump in the 560 MW thermal power plant. A fractured austenitic stainless-steel shaft operated for 24 years was examined. Fracture morphology was investigated by micro and macro-fractographic analysis. The metallurgical analyses including chemical analysis, metallography and hardness testing were performed. The analysis reveals that the pump shaft was fractured due to the reverse bending load with combination of rotating bending load. Corrective actions for plant operator was recommended based on the analysis.

Recently, additive manufacturing (AM) technology such as powder bed fusion (PBF) and directed energy deposition (DED) are actively attempted as consumers' needs for parts with complex shapes and expensive materials. In the present work, the effect of processing parameters on the mechanical properties of 316L stainless steel coupons fabricated by PBF and DED AM technology was investigated. Three major mechanical tests, including tension, impact, and fatigue, were performed on coupons extracted from the standard components at angles of 0, 45, 90 degrees for the build layers, and compared with those of investment casting and commercial wrought products. Austenitic 316L stainless steel additively manufactured have been well known to be generally stronger but highly vulnerable to impact and lack in elongation compared to casting and wrought materials. The process-induced pore density has been proved the most critical factor in determining the mechanical properties of AM-built metal parts. Therefore, it was strongly recommended to reduce those lack of fusion defects as much as possible by carefully control the energy density of the laser. For example, under the high energy density conditions, PBF-built parts showed 46% higher tensile strength but more than 75% lower impact strength than the wrought products. However, by optimizing the energy density of the laser of the metal AM system, it has been confirmed that it is possible to manufacture metal parts that can satisfy both strength and ductility, and thus it is expected to be actively applied in the field of electric power section soon.

As an electrochemical water electrolysis for green hydrogen production, both polymer electrolyte membrane (PEM) and alkaline electrolyte are being developed extensively in various countries. The PEM electrolyzer with high current density (above 2 A/cm²) has the advantage of being able to design a simple structure. Also, it is known that it has high response to electrical output fluctuations. However, the cost problem of major components is the most important issue that a PEM electrolyzer must overcome. Instantly, there are platinum group metal (PGM)-based electrocatalysts, fluorine-based polyfluoro sulfuric acid (PFSA) membrane, Ti felt (porous transport layer, PTL) and so on. Another challenging issue is productivity. A securing outstanding productivity brings price benefits of the electrolytic cells. From this point of view, we conducted basic studies on manufacturing electrode and membrane electrode assembly (MEA) for PEM electrolyzer production.

Environmental change due to construction of large offshore wind farm has been a debate for a long time in Korea. There are various data acquired on hydrodynamics around this area before and during construction of offshore wind farm but no data during operation could be made due to delayed schedule. In this study, environmental change such as bathymetry change and scouring was forecasted using MIKE, numerical hydrodynamics model, and its results were validated using the observation data before and during construction.

A two-step process for increasing the leaching efficiency of yttrium and neodymium from coal fly ash were investigated at solid loadings of 5.0 g ash ~1,000 g ash/l of 1.0 N~10.0 N H₂SO₄, temperature ranging from 30℃ to 90℃, ultrasonic leaching time of 1~10 hours, and ultrasonic power of 25~200 W. The yttrium and neodymium from coal fly ash were effectively leached into ion phases by step change of the first conventional dissolution at room temperature and then the second heating process with the aid of ultrasonic wave, and maximum leaching efficiency of yttrium and neodymium obtained were 66 % and 63 %, respectively. The activation energies for the leaching reaction of yttrium and neodymium at second heating process dependent on leaching time and temperature were derived to be 41.540 kJmol^-1 and 507.92 kJmol^-1, respectively. The optimum conditions for the maximum leaching of yttrium and neodymium were found to be the solid loading of 250 g ash/l of H₂SO₄, solvent concentration of 2.0 N H₂SO₄, and second step process of temperatures of 30℃ for 3 hours and then 90℃ for 4 hours with ultrasonic intensity of 100 W.

In general, SOFCs mainly use Ni-YSZ cermet, a mixture of Ni and YSZ, as an anode material, which is stable in a high-temperature reducing atmosphere. However, when SOFCs have operated at a high temperature for a long time, the structural change of Ni occurs and it results in the problem of reducing durability and efficiency. Accordingly, a development of a new anode material that can replace existing nickel and exhibits similar performance is in progress. In this study, SrTiO₃, which is a perovskite-based mixed conductor and one of the candidate materials, was used. In order to increase the electrical conduction properties, Y_0.08Sr_0.92Fe_0.3Ti_0.7O₃, doped with 0.08 mol of Y³⁺ in Sr-site and 0.03 mol of transition metal Fe³⁺ in Ti-site, was synthesized and its chemical diffusion coefficient and reaction constant were measured. Its electrical conductivity changes were also observed while changing the oxygen partial pressure at a constant temperature. The performance as a candidate electrode material was verified by predicting the defect area through the electrical conductivity pattern according to the oxygen partial pressure.

In this study, monodispersive silica nanoparticles with double mesoporous shells were synthesized, and the pore size of synthetic mesoporous silica nanoparticles was controlled. Cetyltrimethylammonium chloride (CTAC), N, N-dimethylbenzene, and decane were used as soft template and induced to form outer mesoporous shell. The resultant double mesoporous silica nanoparticles were consisted of two layers of shells having different pore sizes, and it has been confirmed that outer shells with larger pores (Mean pore size > 2.5 nm) are formed directly on the surface of the smaller pore sized shell (Mean pore size < 2.5 nm). It was confirmed that the regulation of the molar ratio of pore expansion agents plays a key role in determining the pore size of double mesoporous shells.

In terms of distribution planning, accurate electric load prediction is one of the most important factors. The future load prediction has manually been performed by calculating the maximum electric load considering loads transfer/switching and multiplying it with the load increase rate. In here, the risk of human error is inherent and thus an automated maximum electric load forecasting system is required. Although there are many existing methods and techniques to predict future electric loads, such as regression analysis, many of them have limitations in reflecting the nonlinear characteristics of the electric load and the complexity due to Photovoltaics (PVs), Electric Vehicles (EVs), and etc. This study, therefore, proposes a method of predicting future electric loads on distribution lines by using Machine Learning (ML) method that can reflect the characteristics of these nonlinearities. In addition, predictive models were developed based on actual data collected at KEPCO's existing distribution lines and the adequacy of developed models was verified as well. Also, as the distribution planning has a direct bearing on the investment, and amount of investment has a direct bearing on the maximum electric load, various baseline such as maximum, lowest, median value that can assesses the adequacy and accuracy of proposed ML based electric load prediction methods were suggested.

EPRI 의 설립배경과 현황, 최근 R&D 연구 동향인 Low Carbon Resource Initiative (LCRI)와 Electrification 에 대하여 소개하고, 멤버십 혜택을 통해 EPRI 활용을 극대화할 수 있는 방안을 제시한다.