Search

The use of renewable energy sources to achieve carbon neutrality is increasing. However, the uncertainty and volatility of renewable resources are causing problems in power systems. Flexible and low-carbon resources such as Energy Storage Systems (ESSs) are essential for solving the problems of power systems and achieving greenhouse gas reduction goals. However, ESSs are not being installed because of Korea's fuel-based electricity market. To address this issue, this paper presents a method for determining the optimal investment timing of Battery Energy Storage Systems (BESSs) using the Least Squares Monte Carlo (LSMC) method. A case study is conducted considering the System Marginal Price (SMP) and Capacity Payment (CP), which are electricity rates in Korea. Revenue is calculated through the arbitrage of a 10 MW/40 MWh lithium-ion BESS, and linear programming optimization is performed for ESS scheduling to maximize revenue. The ESS revenue with uncertainty is modeled as a stochastic process using Geometric Brownian Motion (GBM), and the optimal time to invest in an ESS is determined using an LSMC simulation considering investment costs. The proposed method can be used as a decision-making tool for ESS investors to provide information on facility investments in arbitrage situations. [ABSTRACT FROM AUTHOR]

As the penetration of renewable energy sources into a power system increases, the significance of precise short-term forecasts for wind power generation becomes paramount. However, the erratic and non-periodic nature of wind poses challenges in accurately predicting the output. This paper presents a comprehensive investigation into forecasting wind power generation for the following day, using three machine learning models: long short-term memory (LSTM), convolutional neural network-bidirectional LSTM (CNN-biLSTM), and light gradient boosting machine (LGBM). In addition, this paper proposes a method to improve the prediction performance of LGBM by separating data according to the distribution of features, and training and testing each separated dataset with a distinct model. This study includes a comparative analysis of the performance of the proposed models in predicting wind turbine output, offering valuable insights into their respective efficiencies. The results of this investigation were analyzed for two geographically distinct wind farms (Korea and the UK). The findings of this study are expected to facilitate the selection of efficient prediction models within the forecast accuracy auxiliary service market and assist grid operators in ensuring reliable power supply for the grid. [ABSTRACT FROM AUTHOR]

Recently, the proportion of renewable energy (RE) sources in a power system has been increasing worldwide to reduce carbon emissions. To effectively accommodate renewable energy, there is a growing need to develop integrated planning strategies for both renewable energy sources and transmission lines in a power system, taking into account the location-specific characteristics of renewable energy. Economically viable and rapid system expansion plans are required to resolve the problem of delayed integration of renewable energy into existing power system, which arises due to inadequate transmission facilities. To address these problems, this paper presents an integrated economic evaluation method that considers the inherently uncertain output characteristics of renewable energy, contingent on location, the costs associated with installing transmission lines, and environmental benefits. The case study is conducted using a modified power system in Korea. In the case study, it is assumed that by integrating solar power generators in a low-demand area and wind power generators in a high-demand area, wind power plants have higher construction costs than solar power generators. However, the transmission costs for wind power plants are lower than those for solar power generators due to the regional characteristics of the power grid in the installation areas because renewable energy in high-demand areas typically requires less additional power infrastructure than in low-demand areas. The results of this study show that the net benefit for the wind power plant is estimated at USD 225.4 M, while the solar power plant yields a net benefit of USD 22.9 M in the example system. These results demonstrate the effectiveness of the proposed method, underscoring its potential to mitigate the challenges faced in the practical implementation of renewable energy projects. [ABSTRACT FROM AUTHOR]

In South Korea, Renewable Energy Sources (RES) have been increasing with the application of energy policies, such as Feed in Tariff (FIT) and the Renewable Portfolio Standard (RPS). However, a rapid increase in RES supply leads to an uncertain power supply due to the intermittent output of RES. A representative example is the curtailment of Wind Turbines (WT), which frequently occurs in Jeju Island, South Korea. The proportion of RES power on Jeju Island is 67%, and there are cases where WT is curtailed among the operable sections to maintain the balance of power supply and demand. This paper applies Power-to-Gas (P2G) technology to hydrogenate, store, and utilize unused power to solve this problem. In this paper, Aewol-eup in Jeju Island is selected as a target site for case study. An Integrated Energy System (IES) for various energy operations is designed to control RES output. This paper proposes the optimal facility configuration and finally drives the optimal design and operation solution of IES by analyzing the objective functions and focusing on the Independent Power Producer (IPP) perspective. [ABSTRACT FROM AUTHOR]

This study intends to shed light on the environmental impacts of energy decisions in South Korea by analyzing the correlation between energy consumption patterns and environmental indicators such as carbon dioxide emissions. In 2021, global CO2 emissions increased by 6%—to the highest ever level of 36.3 billion tons—according to the International Energy Agency (IEA). This increase in CO2 emissions is a big problem for all countries around the world. The aim of this article is an analyze the impact of fossil fuels, renewable energy, and nuclear energy on South Korea's environment based on the STIRPAT (stochastic impact by regression on population, affluence, and technology) model. Exploring the intricate nexus between economic and energy indicators and environmental outcomes, this study employs the STIRPAT model to analyze the influence of GDP, population dynamics, fossil fuels, renewable energy, and nuclear energy on South Korea's environment. The yearly data from 1972 to 2021 are analyzed in this paper using an autoregressive distributed lag (ARDL) model. The reliability of this study is also examined by employing FMOLS (fully modified ordinary least squares) and CCR (canonical cointegrating regression) estimators. This study confirms the findings of previous research by showing that the rising South Korea GDP and population can lead to higher CO2 emissions and that a strategy switching to renewable energy can cut down on CO2 emissions in Korea, as it exhibits a coefficient of −0.085 *. The robustness results of FMOLS and CCR's findings support baseline ARDL findings. [ABSTRACT FROM AUTHOR]

An SMR (small modular reactor) is expected to be able to operate flexibly in conjunction with a high renewable energy penetration grid as a result of improved safety and easy power control compared to large nuclear power plants. SMRs, such as South Korea's System-integrated Modular Advanced ReacTor (SMART), are designed to use canned motors (CMs) for their reactor coolant pumps (RCPs) to enhance their safety. CMs passively enhance the reactor's safety by preventing the leakage of radioactive reactor coolant. However, with motor sizes designed to be as small as possible, and the increased air gap of CMs between the stator and rotor, the starting torque may be insufficiently low compared to that of similar-sized induction motors (IMs). Thus, CMs may require variable frequency drives (VFDs) to start. This paper compares the torque characteristics of CMs with those of IMs for SMART's RCPs. ETAP is then used to perform a motor-starting analysis for CMs activated with and without VFDs. The results are presented and analyzed to find out if VFDs can deal with the CM starting torque issue. [ABSTRACT FROM AUTHOR]

This paper proposes a wind power probabilistic model (WPPM) using the reflection method and multi-kernel function kernel density estimation (KDE). With the increasing penetration of renewable energy sources (RESs) into power systems, several probabilistic approaches have been introduced to assess the impact of RESs on the power system. A probabilistic approach requires a wind power scenario (WPS), and the WPS is generated from the WPPM. Previously, WPPM was generated using a parametric density estimation, and it had limitations in reflecting the characteristics of wind power data (WPD) due to a boundary bias problem. The paper proposes a WPPM generated using the KDE, which is a non-parametric method. Additionally, the paper proposes a reflection method correcting for the boundary bias problem caused by the double-bounded characteristic of the WPD and the multi-kernel function KDE minimizing the effect of tied values. Six bandwidth selectors are used to calculate the bandwidth for the KDE, and one is selected by analyzing the correlation between the normalized WPD and the calculated bandwidth. The results were validated by generating WPPMs with WPDs in six regions of the Republic of Korea, and it was confirmed that the accuracy and goodness-of-fit are improved when the proposed method is used. [ABSTRACT FROM AUTHOR]

The energy industry has been trying to reduce the use of fossil fuels that emit carbon and to proliferate renewable energy as a way to respond to climate change. The attempts to reduce carbon emissions resulting from the process of generating the electric and thermal energy needed by a building were bolstered with the introduction of the concept of nZEB (nearly zero-energy building). In line with such initiatives, the South Korean government made it mandatory for new buildings to have an nZEB certificate as a way to promote the supply of renewable energy. The criteria for Energy Independence Rate, which is one of the nZEB certification criteria in South Korea, is to maintain the share of renewable energy as at least 20% of the primary energy sources for the building. For a new building in South Korea to have an nZEB certificate, it is required to establish an energy plan that would allow the building to meet the Energy Independence requirement. This optimally reflects the cost of installation for renewable energy facilities and the cost of purchasing energy from external sources, such as the national grid or district heating companies. In South Korea, the base retail rate of energy is calculated based on the peak demand per hour over the year, rather than the contracted energy. This has produced difficulties in standardizing the process with a mathematical model; in addition, there have not been many preceding studies that could be used as a reference. In this regard, this paper analyzed a modeling strategy for developing a realistic yet optimized energy plan in consideration of the unique conditions of the retail energy rates of South Korea, and analyzed the impact of the rates based on peak demands upon the total energy plan. In this study, our research team analyzed the electric billing system, conducted a case study, and analyzed the impact of the billing system that is based on the peak demand upon the optimal cost. By utilizing the restrictions for reaching the 20% Energy Independence goal, this paper calculated the proper energy supply facility capacity for renewable energy. Then, the cases in which the maximum demand modeling was used and the cases without one were compared to confirm the cost benefits observable when the suggested model is added or implemented. [ABSTRACT FROM AUTHOR]

Republic of Korea has unique geographical characteristics similar to those of an island, resulting in an isolated power system. For this reason, securing sufficient operating reserves for the system's stability and reliability in the face of the intermittency of increasing variable renewable energy (VRE) is paramount, and this will pave the way to achieving the nation's decarbonization target and carbon neutrality. However, the current reserve-operation method in Republic of Korea does not take into account energy-system conditions, such as the intermittency of the VRE. Therefore, this paper presents an analysis of the impact of changes in reserve-operation methods on the electricity market in the future Republic of Korean power system, with the increased levels of VRE that are currently envisioned. Specifically, three reserve-operation methods, including Korea's current reserve-power-operation standards, were applied to the two power-system plans announced by the Korean government to analyze the annual generator operation and costs. The analysis results show that securing reserves proportional to the VRE would exert negative effects, such as increased power-generation costs and the curtailment of nuclear and VRE generation. These results can contribute to the estimation of operational reserves needed for high levels of VRE and to the design of new the Korean reserve market, to be introduced in 2025. [ABSTRACT FROM AUTHOR]

As environmental pollution deteriorates, the acceleration of decarbonization worldwide is underway. Several countries, including Korea, are incorporating new and renewable energy into existing systems, and various methods of decarbonization are being researched. With changes in the control environment, the expansion of the system linkage of new and renewable energy can cause system instability problems. This paper introduces an operation plan that uses the fast response characteristics of energy storage system(s) (ESS) to improve stability and review system stability as a result of the expansion of new and renewable energy on Jeju Island. Frequency stability was ensured through an analysis of frequency response characteristics in the event of a system accident, and an efficient ESS operation plan was simulated by changing the ESS parameters. Through this simulation, stable ESS operation and hunting in the frequency recovery process were minimized through cooperation between the existing and new ESS via a wide dead-band range and speed adjustment rate correction, and the lowest frequency was improved. [ABSTRACT FROM AUTHOR]

Not only the driving for offshore wind energy capacity of 12 GW by Korea's Renewable Energy 2030 plan but also the need for the rejuvenation of existing world-class shipbuilders' infrastructures is drawing much attention to offshore wind energy in Korea, especially to the diverse substructures. Considering the deep-sea environment in the East Sea, this paper presents detailed modeling and analysis of spar-type substructure for a 5 MW floating offshore wind turbine (FOWT). This process uses a fully coupled integrated load analysis, which was carried out using FAST, a widely used integrated load analysis software developed by NREL, coupled with an in-house hydrodynamic code (UOU code). The environmental design loads were calculated from data recorded over three years at the Ulsan Marine buoy point according to the ABS and DNVGL standards. The total 12 maximum cases from DLC 6.1 were selected to evaluate the structural integrity of the spar-type substructure under the three co-directional conditions (45°, 135°, and 315°) of wind and wave. A three-dimensional (3D) structural finite element (FE) model incorporating the wind turbine tower and floating structure bolted joint connection was constructed in FEGate (pre/post-structural analysis module based on MSC NASTRAN for ship and offshore structures). The FEM analysis applied the external loads such as the structural loads due to the inertial acceleration, buoyancy, and gravity, and the environmental loads due to the wind, wave, and current. The three-dimensional FE analysis results from the MSC Nastran software showed that the designed spar-type substructure had enough strength to endure the extreme limitation in the East Sea based on the von Mises criteria. The current process of this study would be applicable to the other substructures such as the submersible type. [ABSTRACT FROM AUTHOR]

With the technical growth and the reduction of deployment cost for distributed energy resources (DERs), such as solar photovoltaic (PV), energy trading has been recently encouraged to energy consumers, which can sell energy from their own energy storage system (ESS). Meanwhile, due to the unprecedented rise of greenhouse gas (GHG) emissions, some countries (e.g., Republic of Korea and India) have mandated using a renewable energy certificate (REC) in energy trading markets. In this paper, we propose an energy broker model to boost energy trading between the existing power grid and energy consumers. In particular, to maximize the profits of energy consumers and the energy provider, the proposed energy broker is in charge of deciding the optimal demand and dynamic price of energy in an REC-based energy trading market. In this solution, the smart agents (e.g., IoT intelligent devices) of consumers exchange energy trading associated information, including the amount of energy generation, price and REC. For deciding the optimal demand and dynamic pricing, we formulate convex optimization problems using dual decomposition. Through a numerical simulation analysis, we compare the performance of the proposed dynamic pricing strategy with the conventional pricing strategies. Results show that the proposed dynamic pricing and demand control strategies can encourage energy trading by allowing RECs trading of the conventional power grid. [ABSTRACT FROM AUTHOR]