• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권12호
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• pp.5712-5728
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• 2017

Recently, there are many studies, that considering green wireless cellular networks, have taken the energy consumption of the base station (BS) into consideration. In this work, we first introduce an energy consumption model of multi-mode sharing BS powered by multiple energy sources including renewable energy, local storage and power grid. Then communication load requests of the BS are transformed to energy demand queues, and battery energy level and worst-case delay constraints are considered into the virtual queue to ensure the network QoS when our objective is to minimize the long term electricity cost of BSs. Lyapunov optimization method is applied to work out the optimization objective without knowing the future information of the communication load, real-time electricity market price and renewable energy availability. Finally, linear programming is used, and the corresponding energy efficient scheduling policy is obtained. The performance analysis of our proposed online algorithm based on real-world traces demonstrates that it can greatly reduce one day's electricity cost of individual BS.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 하계학술대회 논문집 A
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• pp.316-318
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• 1994

Photovoltaic is considered to be one of the most promising technologies which can greatly contribute to future energy supply because or a large, secure, essentially inexhaustible and broadly available resource -sunlight. This paper analyzes reduction of synthetic power peak value through weather data and quantity or generation. This explanation and estimations analyses grid connected power system.

• 한국분말재료학회지
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• 제30권6호
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• pp.528-535
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• 2023

Since their initial development in 2012, triboelectric nanogenerators (TENGs) have gained popularity worldwide as a desired option for harnessing energy. The urgent demand for TENGs is attributed to their novel structural design, low cost, and use of large-scale materials. The output performance of a TENG depends on the surface charge density of the friction layers. Several recycled and biowaste materials have been explored as friction layers to enhance the output performance of TENGs. Natural and oceanic biomaterials have also been investigated as alternatives for improving the performance of TENG devices. Moreover, structural innovations have been made in TENGs to develop highly efficient devices. This review summarizes the recent developments in recycling and biowaste materials for TENG devices. The potential of natural and oceanic biowaste materials is also discussed. Finally, future outlooks for the structural developments in TENG devices are presented.

• 한국전기전자재료학회논문지
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• 제37권2호
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• pp.133-140
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• 2024

This study offers a comprehensive evaluation of the role and impact of advanced power semiconductors in solar module systems. Focusing on silicon carbide (SiC) and gallium nitride (GaN) materials, it highlights their superiority over traditional silicon in enhancing system efficiency and reliability. The research underscores the growing industry demand for high-performance semiconductors, driven by global sustainable energy goals. This shift is crucial for overcoming the limitations of conventional solar technology, paving the way for more efficient, economically viable, and environmentally sustainable solar energy solutions. The findings suggest significant potential for these advanced materials in shaping the future of solar power technology.

• 인터넷정보학회논문지
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• 제16권5호
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• pp.29-38
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• 2015

에너지 저장장치(Energy Storage System)은 전력 수요가 적을 때 전력을 저장해 두었다가 수요가 발생하거나 비상시 저장된 전력을 사용함으로 전기 에너지를 저장하여 필요할 때 사용 가능함으로써 에너지 이용 효율 향상, 전력공급 시스템 안정화 및 신재생 에너지 활용도 향상 효과를 가지는 시스템이다. 최근 세계적으로 에너지의 효율적인 소비에 대한 관심이 증대되면서 전력의 안정적인 공급을 원하는 수요자와 전력 수요 평준화를 원하는 공급자의 요구를 충족시켜줄 수 있는 에너지 저장장치의 필요성이 증대되고 있다. 현재 에너지 저장장치를 구성하는 Power Conditioning System(PCS), Battery Management System(BMS), 배터리 셀은 제조사별로 상이한 규격을 가진다. 이로 인해 각 핵심 부품 간 인터페이스가 규격화되어 있지 않아, 에너지 저장장치의 구성 및 운영에 난점으로 작용하고 있다. 본 논문에서는 제조사별로 상이한 특징을 가지는 부품들의 설정과 효율적 운영에 필요한 정보를 수용하여 에너지 저장장치를 구성할 수 있는 XML 기반의 에너지 시스템 전용 프로파일 시스템의 설계와 분석방안을 제안한다. 제조사별 PCS, BMS, 배터리 셀과 그 외의 주변 기기들의 설정 정보 및 운영 정보를 분석하여 프로파일 규격을 정의하고, 에너지 저장장치에 적용할 수 있는 프로파일 어댑터 소프트웨어를 설계 및 구현한다. 프로파일 어댑터를 통해 생성된 프로파일은 설정 프로파일과 운영 프로파일로 구성되며, 추후 확장성을 고려하여 표준 XML의 규격을 따른다. 구현된 프로파일 시스템의 검증은 에너지 저장장치 시스템에 적용되어 기본적인 충 방전 동작을 통해 정상 동작 결과를 제안한다.

• KEPCO Journal on Electric Power and Energy
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• 제2권3호
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• pp.391-395
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• 2016

최근 몇 년간, 전력 소비의 급격한 증가로 인하여 전력 수급의 불안이 전 세계적으로 발생하였다. 또한 전력 예측의 불확실성 및 전력 발전량이 급격히 증가하게 되었다. 이러한 문제를 해결하기 위한 방안으로 전력망과 IT 기술을 결합한 스마트 그리드기술은 각광을 받고 있다. 스마트 그리드는 전력 최대 부하율을 낮추며 효율적인 전력 사용을 유도한다. 이를 위하여 스마트 그리드 시스템은 다양한 요금 정책, 수요반응 기술, 스마트 전자 기기들을 활용한다. 특히 전력 사용을 효율적으로 스케줄링 해주는 수요반응 기술은 스마트 그리드의 핵심 기술이다. 본 논문에서는 수요 반응 기술을 위한 그리디 기법을 제안한다. 제안하는 그리디 기법은 전력 요금의 최소화뿐만 아니라, 사용자의 편의성을 고려하며 시스템 정전을 방지하는 것을 목표로 한다.

• 전기학회논문지
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• 제67권8호
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• pp.1009-1018
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• 2018

As the generation of renewable energy increases rapidly, the stability of the grid due to its intermittency becomes a problem. The most appropriate way to solve this problem is to combine and operate the renewable generators with the ESS(Energy Storage System). However, since the revenues of operating the ESS are less than the investment cost, many countries are implementing various incentive policies for encouraging investment of the ESS. In this paper we estimated optimal capacity of the ESS to maximize profits of renewable energy generation businesses under the incentive policy of Korea and analyzed the impact of the incentive policy on the future electric power system of Jeju island. The simulation results show that the incentive policy has significantly improved the profitability of the renewable energy businesses generation business. But the volatility of the net demand has increased as the energy stored in the ESS is discharged intensively at the time of the incentive application.

• 한국태양에너지학회 논문집
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• 제28권6호
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• pp.87-92
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• 2008

Buildings are responsible for approximately 50% of current carbon dioxide emissions. Energy planning at a town and city scale needs a strategic approach, supported by strong planning policies. The purpose of this study was to investigate the urban scale grid-connected photovoltaic(PV) system for urban residential and commercial sector applications. The integration of PV technology into roof of houses is an approach that is being championed in Germany, Japan and United states etc. In the Korea, PV roofing systems already are given the large number of houses which are projected to be built by 2012. However unlike germany and Japan, urban scale grid-connected PV system is not yet installed. The solar city which is installed building-integrated photovoltaic system is available to use of renewable energy sources such as solar to meet demand, instead of fossil fuels, with the goal of realizing an ecologically oriented energy supply.

• 한국인공지능학회지
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• 제12권1호
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• pp.17-24
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• 2024

This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1516-1529
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• 2016

While global manufacturing is becoming more competitive due to variety of customer demand, increase in production cost and uncertainty in resource availability, the future ability of manufacturing industries depends upon the implementation of Smart Factory. With the convergence of new information and communication technology, Smart Factory enables manufacturers to respond quickly to customer demand and minimize resource usage while maximizing productivity performance. This paper presents the development of a big data analytics platform architecture for Smart Factory. As this platform represents a conceptual software structure needed to implement data-driven decision-making mechanism in shop floors, it enables the creation and use of diagnosis, prediction and optimization models through the use of data analytics and big data. The completion of implementing the platform will help manufacturers: 1) acquire an advanced technology towards manufacturing intelligence, 2) implement a cost-effective analytics environment through the use of standardized data interfaces and open-source solutions, 3) obtain a technical reference for time-efficiently implementing an analytics modeling environment, and 4) eventually improve productivity performance in manufacturing systems. This paper also presents a technical architecture for big data infrastructure, which we are implementing, and a case study to demonstrate energy-predictive analytics in a machine tool system.