Electric Power Corporation Research Articles

A Financial Analysis and Valuation of Leading Companies in the U.S. Electric Utility Sector

In the post-pandemic era, as societal life demands gradually recover and stabilize, the American public utilities sector has demonstrated positive growth momentum, garnering significant investor attention. This research focuses on four prominent enterprises within the industry, including Southern Company (SO), American Electric Power (AEP), Duke Energy (DUK), and Exelon Corporation (EXC). These entities not only epitomize the developmental trajectories of the electric power industry but also reflect the escalating influence of renewable energy over traditional fossil fuels and the ramifications of heightened environmental standards on corporate operations. Leveraging the 2023 annual reports as foundational data, this study conducts a thorough analysis and valuation of these firms' financial statement indices and price-to-earnings ratios, aiming to offer comprehensive insights and analyses regarding their financial standings and market prospects. The findings indicate that Southern Company exhibits robust market competitiveness and allure, alongside an optimistic outlook for future development, rendering it a viable candidate for sustained attention from investors seeking long-term value investments.

Field demonstration of a 10 MW CO2 capture pilot plant in extended operation using KoSol absorbents for treating off-gas in a coal fired power plant

Efficient CO2 absorbents are crucial for reducing energy use in CO2 capture absorption process. This study evaluates the performance of amine-based CO2 absorbents, KoSol-5 and KoSol-6, developed by the Korea Electric Power Corporation. In a 10 MW pilot plant, KoSol-6 was found to capture more than 90% of the daily CO2 emissions, amounting to over 180 tons per day, from the exhaust gasses of a coal-fired power plant. Its regeneration energy (Qregen) was 2.42 GJ/ton CO2 in the standard absorption process, which is 39.2% less than the monoethanolamine (MEA) system. Implementing advanced techniques like intercooling, lean vapor compression, and thermal vapor recompression further optimized this process. Among these, the thermal vapor recompression mode turned out to be the most efficient and stable. In addition, KoSol-6 showcased excellent thermal and chemical stability, with a consistent Qregen of 2.34 GJ/ton CO2 over a 10,000-hour test. The study provides insights into the potential of KoSol-5 and KoSol-6 for large-scale applications and further developments in CO2 capture technology.

Развитие внутреннего финансового контроля в управлении финансами электроэнергетических корпораций

The article discusses the issue of improving the system of financial control and budgeting at electric power en-terprises. It analyzes the problems of transition from accounting to financial and analytical approach, highlights the difficulties associated with duplication of software and insufficient integration of information systems. The authors present their own approach to constructing a structural and logical budgeting scheme, starting from specifying the development strategy and ending with adjusting operating budgets. The importance of taking into account a variety of factors in the formation of the sales budget, including market trends and the competi-tive environment, is highlighted. Conclusion dwells upon the fact that in order to improve management effi-ciency and achieve strategic goals of the enterprise it is necessary to apply an integrated approach to budget-ing, including detailed diagnostics, strategic planning and operational response to changes in the internal and external environment.

Research on Hierarchical Layer Strategy for Power Material Warehouses---A Case Study of X-Electric Power Corporation

We will raise total factor productivity to make China’s industrial and supply chains more resilient and secure. This paper first provides a hierarchical layer strategy and proposes a hierarchical layout model to minimize operating costs. Warehouse management of electrical materials is a critical link in power supply. This paper analyses the situation of power material warehouse layout, including the models of warehouses layout and the main functions of each warehouse. Then makes a hierarchical layer strategy for power material warehouses on X electric power corporation. Distribution Centre is needed for allocation when the power material companies transport critical production. The flow of materials is draw. Finally, built the hierarchical layer strategy model of power material warehouses, which must consider many influencing factors, such as transportation costs, warehouse maintenance costs, and time penalty costs. This serves as a foundation for research into active distribution of electrical materials.

Distribution System Operator (DSO) Functions in South Korea—Part I: Development, Practical Obstacles, and Future Work

This paper presents our initial research findings on distribution system operator (DSO) functions in South Korea. The project team includes the Korean Electric Power Corporation, which is the only public utility company in South Korea. The planned development is based on a real distribution network and real‐world environments. The project encompasses DSO–transmission system operator coordination and management of real‐time distribution network congestion; this paper focuses on the latter aspect. For real‐time congestion management, algorithms that handle all steps from database analysis to data export, including data preprocessing, topological configuration, power flow calculation, sensitivity analysis, and derivation of solutions to congestion, are developed. The distribution system equipment database of Korean Electric Power Corporation is used to develop a network congestion management system. When examining the database, many gaps between the theoretical and practical environments were found which are introduced in this paper. A practical distribution network database for South Korea is developed to narrow these gaps and to implement practical congestion management techniques. The remaining problems are introduced as future works.

Future scenarios of digital technology-driven energy consumption in South Korea

This study explored potential future scenarios of digital technology-driven energy consumption in South Korea. A Battelle Scenario Inputs to Corporate Strategies analysis was conducted to derive the future scenarios. This study identified four key factors and the specific order among factors that will drive future energy consumption: energy mix, energy network, energy trading market, and changes in the industrial structure. A total of 13 scenarios were derived, and the three most likely scenarios were identified. In the first scenario, energy efficiency centered around Korea Electric Power Corporation. The second scenario involved a transition to a digitally powered society. Finally, an energy-centered, hyper-connected society was predicted for the third scenario.

Structured stochastic models based on multi-source heterogeneous data for predicting internal electricity load of non-residential buildings

Electricity load patterns in buildings are increasingly diverse and inherently present building-by-building and temporal variations. This study develops structured stochastic models to capture individual and temporal variations in non-residential building groups (e.g., education, office, culture, and retail buildings). Hourly electricity load data of non-residential buildings, categorized by building use, are sourced from two open datasets (Ministry of Land, Infrastructure and Transport and Korea Electric Power Corporation). First, heterogeneous public datasets are processed and utilized to provide both detailed building information and high-resolution electricity load data. Second, a structured set of four stochastic models are formulated using linear regression and multivariate normal distribution models. Model 1 utilizes the beta distribution to derive daily average electricity load per unit area for each building use. Model 2 utilizes the burr distribution to determine the daily variation of electricity load from the daily average. Models 3 and 4 utilize a multivariate normal distribution to represent the hourly average electricity load profile and its time variation, respectively. The coefficient of variation of the root mean square error (CVRMSE) for the structured probabilistic models ranges from 5.2 % to 14.8 % regarding five key load characterization variables. CVRMSEs for near-peak load, near-base load, rise time, high-load duration, and fall time are 8.5–13.9, 9.5–14.7, 7.3–14.8, 6.4–13.9, and 5.2–11.4 %, respectively. The validation results demonstrate that the proposed probabilistic models capture actual variations in measurements. Structured statistical models improve prediction performance by distinctly reflecting individual and temporal variations in electricity loads.

Role of employee recruitment and selection on performance of Ethiopian electric power corporation, Mekelle Branch

Purpose: This study aimed to assess the impact of recruitment and selection on organizational performance. It was to find out the recruitment and selection policy or practice, the impact of recruitment and selection process, the challenges associated with the recruitment and selection practice and ways to help improve human resource planning and development. Research Methodology: The study obtained information from twenty (20) respondents from staff of the Ethiopian Electric Power Corporation in the Mekelle branch using a questionnaire. The collected data were statistically analyzed using SPSS, and the chi-square test was used to interpret the hypotheses. Results: The results indicated that the advertising of job vacancies to the general public, use of employment agents, TV, newspapers, and employee referrals is mostly the mode for recruiting potential employees, and that the method used in the recruiting and selection process was very effective. Moreover, it helped improve employee performance, and the selection and recruitment process was also characterized by many challenges. Limitations: The major limitations of this study are time constraint, crisis of COVID 19, and inappropriate fulfillment of the questionnaire by respondents. Contribution: This study suggests that potential employees should be treated fairly in the recruitment and selection processes. Moreover, employees must be constantly appraised to ensure that they improve their performance.

Comparative Analysis of Estimated and Actual Power Self-Sufficiency Rates in Energy-Sharing Communities with Solar Power Systems

Amid the ongoing climate crisis, the international community is enacting policies to promote low-carbon energy-sharing communities. The primary objective of such communities is to enhance community-level energy self-sufficiency. Accurate energy self-sufficiency assessments are paramount in planning energy-efficient architectural designs, urban landscapes, and communal environments. In this study, the energy self-sufficiency rate of an energy-sharing community was estimated at the design stage and compared with the actual energy self-sufficiency rate calculated based on data collected over the following year (April 2022 to March 2023). The outcomes reveal that the estimated energy self-sufficiency rate is 171%, whereas the realized rate is 133%, underscoring the disparity between the projections and outcomes. An analysis of the seasonal variations in these discrepancies elucidated a correlation between the differences in the insolation levels between standard typical meteorological year (TMY) data that are conventionally used for energy generation projections and the actual meteorological conditions. Moreover, a notable incongruity surface exists between the monthly average electricity consumption of a standard four-person household, as stipulated by the Korean Electric Power Corporation (KEPCO) at 273 kWh, and the empirical power consumption at 430 kWh, resulting in a variance of approximately 157 kWh. This study illuminates the complex relationship between variables affecting energy self-sufficiency in energy-sharing communities. It serves as a crucial step towards informed decision making and precision in sustainable urban energy solutions.

The Republic of Korea experience of «Smart-Grid» implementing in the post-war recovery of Ukrainian energy system

The aim of the article. The article is devoted to the investigation of the South Korean experience of the «Smart-Grids» implementation in the post-war recovery of the domestic energy system and modernization of the existing power grids in Ukraine. Analysis results. Analyzed the main provisions of «Smart Grids» in the Law of Ukraine «On Energy Efficiency», which are defined as highly intelligent power grids, which functioning due to the ICT use on the basis of the smart meters, allowing independently and efficiently distribution and to manage the power grid. Emphasized the adopted by Ukrainian Government Concept for the implementation of Smart Grids in Ukraine until 2035, the main task of which is to promote the development of national energy system strategy with the creation of a highly intelligent power grid based on the Information and Communications Technologies. It has been proven that the Republic of Korea is one of the first countries where practically implemented a project of the «Smart Grid» introduction and distribution on South-Korea's Jeju-do island, which combines the concept of «Smart City» and «Smart Factory» based on the use of renewable energy sources. Grid technology is one aspect of a general trend towards smart technologies and a large market for Korean export. Smart-Grid technologies include electrical supply grids that use demand response, connectivity and renewable energy sources which increases the energy efficiency of manufacturing entities and households. Due to the high spread of the Internet of Things all around the world the transition to «Smart-Grid» is an imperative of increasing «Smart City» and «Smart Factory» concept in the sustainable development of a State, which includes the use of wearable technologies. That is why, collecting the large amount of data requires a high speed of the internet networks, like 5G. Conclusions and directions for further research. The issue of the actualizing of bilateral collaboration in the field of «Smart Grid» between Ukraine and the Republic of Korea is extremely important for both countries, because for the successful implementation of «Smart Grid» in the existing domestic realities it is necessary to involve practical South-Korean experience and for Korean business partners – Ukraine is a potential foreign market for technological items export, which requires «Smart Grid» industry. Since the time when «Miracle on the Han River» start, the main goal of the South-Korean Government was to find stable sources of energy supply and to cover electricity demand for heavy-industry manufacturing corporations and households from the sources of cheap energy supply. To achieve such goals was established Government-owned entity «Korea Electric Power Corporation» (KEPCO) and the developing of power industry was based on the large-scale centralized power systems, main aim of which was to reduce the cost of energy for long-term South-Korean economy boost

Impact of Global Fuel Price Volatility on the Korean Electric Sector: Market Risk Estimation and Electricity Rate Cap

This paper investigates the challenges that the Korean electric sector has encountered in 2022 under a regulated framework different from market-based approaches. The Ukraine-Russia war caused chaotic circumstances in every aspect of the global economy, and the energy market was not an exception. Every nation has been struggling in 2022 to secure its energy needs due to the supply chain disruptions associated with the geopolitical issues, as well as to minimize the economic impact. As electricity is a derivative product from fuels, it has serious vulnerability to fuel price volatility, unless the nation is self-sufficient in energy supply with 100% renewable energy sources or equivalent alternatives. When an electric market is deregulated with open market competition, the market cost of goods is simply passed through to end customers. However, it may not be the same case for a regulated utility that is subject to the rules set by public agencies. Korea Electric Power Corporation (KEPCO), a Korean public utility, has made every effort to stay away from bankruptcy due to its deficit of KRW 3 trillion (U$ 24 billion) in 2022. The main reason for the deficit is the regulated electric rate cap that KEPCO must charge to retail customers for the wholesale power purchased at market rates from the Korea Power Exchange. The price disparity may be explained by the year-on-year change in October: the rate cap is up 22% as opposed to the wholesale market price spike of 89%. This paper analyzes price diversions or volatilities of eight comparable asset classes, from a DJIA stock to the Korean electricity prices, in a historical context (January 2018-August 2022), and applies current fuel market parameters to estimate the value-at-risk, or price change, in Korea electricity prices to understand the estimated divergence between the two prices.

Optimal grid expansion under future electricity demand for groundwater irrigation in Ethiopia

Ethiopia is a lower-income country with an agrarian based, fast-growing economy that is susceptible to climate change impacts. As the nation continues to develop, domestic electricity consumption and electricity export opportunities will increase alongside a growing electricity demand for groundwater irrigation to mitigate the effects of drought. There are upcoming mega-dams– the Grand Ethiopian Renaissance Dam, Genale Dawa III, and Koysha – that will triple the electricity generation capacity. However, the central electricity grid is not sufficient to efficiently utilize this new capacity. We model future grid expansion scenarios by building a regional-scale linear optimal power flow model based on a transshipment representation of power flow that guides cost-optimal generation operations and transmission expansion, while satisfying competing electricity demand for domestic electricity consumption, groundwater irrigation, and international electricity export.We first evaluate cost-optimal generation and transmission expansion for a baseline case, with an estimate of current Ethiopian electricity demand. We then consider five potential future demand scenarios. These demand scenarios include estimates of both present and future domestic electricity demand, multiple levels of productive electricity demand for groundwater irrigation, and demand for international exports. Compared to the baseline, seasonal capacity factors for generators in the five model scenarios increased when collocated with an increase in electricity demand except for the generators that already operated at maximum capacity. All scenarios with higher domestic regional demand than the baseline surpass the transmission expansion planned by the Ethiopian Electric Power Corporation, independent of changes in irrigation and export demand. Our analysis suggests that the current expansion plan is not sufficient to meet future demand. Our research contributes to the literature by creating an optimal power flow model that can be applied in data-poor environments to model endogenous electricity infrastructure decisions under different scenarios of internal and external demand.

Missing data imputation using an iterative denoising autoencoder (IDAE) for dissolved gas analysis

• A data imputation method is proposed to address transformers with multiple missing DGA data. • An iterative imputation method is demonstrated, based on a denoising autoencoder. • Features are extracted from both gas trend and composition ratios for better imputation. • The proposed method is validated using a vast amount of field data. With the expansion of the energy market, safe and stable operation of the electrical power system has become an important issue. In an effort to achieve this goal, much research has been conducted on diagnosis approaches suitable for core components of the electrical power system. Transformers are one such core component. Most of the research on transformers has focused on developing a diagnosis model; less effort has been devoted to the data, in spite of the fact that such models require data of sufficient quantity and quality, which is not usually readily available for transformers. Thus, in this paper, we propose a way to fully exploit the valuable transformer data, using a data imputation approach called the iterative denoising autoencoder (IDAE) method. The proposed method imputes missing values of dissolved gas analysis (DGA) data, which is frequently lost, for various reasons. IDAE can help diagnose the health state of transformers accurately by estimating the missing values of DGA data. The proposed method is verified in this research through three comparative studies that examine field data provided by an electric power corporation. Specific studies provide: (1) a comparison with conventional methods on imputation performance for a single gas, (2) examination of imputation performance between multiple missing values, and (3) documentation of diagnosis accuracy before and after imputation. The results of the case studies show that the proposed method is effective for imputation of the missing DGA data.

A Preference Analysis for a Peer-to-Peer (P2P) Electricity Trading Platform in South Korea

The Korean government is committed to advance the country’s energy transition to greener energy by increasing the share of renewable electricity to 20 percent by 2030 and to 30–35 percent by 2040. Achieving these goals will necessitate flexibility in energy markets as well as innovative business models and technological solutions. Peer-to-peer (P2P) electricity trading platforms (ETPs) are rapidly gaining traction, as they enable the integration of distributed energy sources into power systems. This study explores whether South Koreans are willing to participate in a hypothetical P2P ETP, which allows prosumers (who both consume and produce electricity) to trade electricity surpluses with their neighbours or with KEPCO (Korea Electric Power Corporation). We employ a choice experiment (CE) to examine respondent heterogeneous preferences and their willingness to pay (WTP) for a hypothetical P2P ETP in South Korea. Our findings indicate that two-thirds of total respondents in our CE are in favour of a P2P ETP if available. Cost savings and security play an essential role in respondent preferences for a P2P ETP business model. Respondents also prefer to trade renewable electricity with KEPCO rather than with other individuals. Per our statistical estimations, respondent WTP for a P2P ETP was estimated at USD 55.68/per month. Our analysis strongly recommends increasing consumer awareness of P2P ETPs to spur adoption. Energy trading platforms that are anchored in secure block chain technology can generate cost savings as well as support the country’s policy tilt toward green energy.

신재생발전 지역 관제를 위한 신재생 발전출력 예측 기술

This paper introduces the Local Renewable Management System(LRMS) developed by Korea Electric Power Corporation and describes the Renewable Energy Forecasting System, which is one of the main module in LRMS. The Renewable Energy Forecasting System forecasts the generation output by using meteorological data from the Korea Meteorological Administration, electrical data acquired from SCADA and DAS which are KEPCO

도시 가로수 관리 품셈 개선에 관한 연구†

This study aims to provide basic data for high-quality street tree management by setting reasonable management items and appropriate unit prices by reviewing the adequacy of current street tree management. Currently, street tree management items, except for street tree pruning, use general landscape tree quantity per unit for the street tree management quantity per unit. KEPCO (Korea Electric Power Corporation) applied pruning items from standard electric production infrastructure and carried out the activities at an average unit price of 51% lower for heavy pruning and 39% lower for light pruning than the standard estimate. This was judged to be a level that could not maintain or increase the quality of street tree management. It was determined that an appropriate standard unit price for street tree management was necessary. To improve the quantity per unit for the proper management of street trees, it was necessary to review costs in the field. However, due to the absence of data on actual construction costs in the domestic landscape field, detailed items of the US RSMeans Building Construction Cost Data (RSMeans) were reviewed, and the actual construction costs were calculated by applying personal domestic expenses. As a result, the standard of the estimated unit showed a good ratio of 107% for heavy pruning of street tree pruning compared to the actual construction cost, but light pruning was underestimated with a 59% ratio. Shrub pruning was 82%, weeding was 92%, tree fertilization was 87%, and windbreak wall installation was 91% under-engineered. In addition, it was also confirmed that the watering by sprinkler trucks and chemical spraying were over-designed compared to the actual construction cost at the rates of 118% and 124%, respectively. Due to the specificity of the street trees, the increase in personal expenses and the input cost of equipment, such as road safety controls, were judged to be the main cause of the underestimation of items. Therefore, it is necessary to add items related to street trees and general landscape trees to the landscape maintenance items of the standard of the estimated unit.

비가시권 송전선로 점검드론 시스템 개발

In this paper, we proposed a Beyond Visual Line Of Sight(BVLOS) drone system for inspection of transmission lines. As drone technology advances, drones are replacing dangerous tasks in the electric power industry. According to this trend, Korea Electric Power Corporation has developed the automatic inspection drone system for transmission lines. This system targeted inspection of transmission lines in the visible area. Since the transmission line is mainly located in mountainous area, the drone frequently enter the invisible area. In order to inspect multiple transmission lines with the existing system, frequent movement for drone takeoff and a lot of preparation time are required. To overcome this problem, we upgraded the existing system to inspect BVLOS transmission lines. For BVLOS flight, laws and regulations must be observed. Therefore, essential functions were derived from laws and regulations, and these functions were developed to be suitable for inspection of transmission lines. Finally, our system was verified through special flight approval from the Ministry of Land, Infrastructure and Transport. Through the new transmission line inspection drone system, the multiple transmission lines can be efficiently inspected at once.

Smart managed charging (V1G) field demonstration in KEPCO

Korea Electric Power Corporation (KEPCO) has been leading a project on electric vehicle - power grid Integration (VGI) for smart managed charging (V1G) and bidirectional power transfer (V2G) system development and demonstration as a fast-demand response resource. KEPCO has developed VGI management system(“kVGI”) for V1G and V2G control. To use EV batteries as a useful flexibility resource through V1G, we developed a battery state of charge (SoC) reading device and estimation model for conventional EVs. Also, we developed and installed 100 EV supply equipment (EVSE) for V1G demonstration. In this article, we present some early results of V1G fielddemonstration of more than 100 EVs.

데이터 기반 지상용 변압기의 잔여수명과 고장확률(PoF) 도출방안 연구

In Korea, as power facilities are aging like overseas nations, maintenance and replacement costs of power facilities are expected to increase rapidly. In order to operate power facilities with a limited budget efficiently, it is necessary to introduce Asset Management System (AMS) in maintenance of the power facility in line with the global trend. To this end, it is essential for power companies to predict the remaining lifetime of power facilities and develop Probability of Failure (PoF) in their own way depending on the type and operating conditions of power facilities. Existing studies only calculated the statistical life expectancy of the power facility, but in this study, both of the statistical life expectancy and the condition remaining lifetime are presented in order to assess the PoF of power facility, in which the statistical life expectancy is calculated by using Weibull distributions. In this study, we present the criteria for determining the condition remaining lifetime using Health Index, inspection and diagnosis data of the pad mounted transformer operated by Korea Electric Power Corporation (KEPCO) in the field. In addition, the final remaining lifetime of the pad mounted transformer was derived through the folding function and was converted into PoF using Hazard rate distribution based on the apparent age. PoF derived in this study is expected to be used in the risk matrix of the AMS and useful in establishing the systematic maintenance plan of the pad mounted transformer.

Optimization of ESS Scheduling for Cost Reduction in Commercial and Industry Customers in Korea

Various attempts have been made to reduce carbon emissions in the energy sector as part of global net zero emissions trends. Among them, interest in the use of energy storage systems (ESSs) for energy efficiency is growing. Utilities intend to improve the efficiency of investment and operating costs by reducing the maximum peak and leveling the load. Many ESS-scheduling optimization techniques have been studied to reduce the peak demand, balance the load, or reduce the cost corresponding to these two purposes from the customer’s point of view. In this paper, a method for cost minimization that simultaneously considers both the peak demand and load balancing is proposed, and the results and analysis of a case study in Korea Electric Power Corporation (KEPCO), Korea are presented. Through these results, we show that there is a priority among the objective functions of the ESS schedule, that demand charge is more important than energy charge, and that the ESS schedule problem for customers to reduce costs is also beneficial to power system operation by the utility’s rate policy.