[ESS] 문헌조사

기업

http://www.omnisystem.co.kr/platform/platform_01.php

옴니시스템(주)

LG엔솔, 공장 증설·차세대 전지에 10조 쏜다 : 네이버 뉴스 (naver.com)

LG엔솔, 공장 증설·차세대 전지에 10조 쏜다

 

 

Institution

에너지기술연구원

https://www.kier.re.kr/board?menuId=MENU00805 

ESS연구실-재생에너지연구소-연구부서

하나금융연구소

http://www.hanaif.re.kr/boardDetail.do?hmpeSeqNo=33893 

하나금융경영연구소

KISTEP

전력피크+대응을+위한+ESS+실증연구사업.pdf

2.24MB

 

 

 

한국에너지공과대학교 (Korea Institute of Energy Technology, KENTECH)

https://kentech.ac.kr/eng/512/subview.do

Institute for Energy AI

Promoting Five specialized energy fields

Global agenda of 2050 carbon neutrality and current paradigm shifts in the global energy industry has calld for integrated efforts to address the climate change with stricter world-wide environmental regulations, creating new global economic order. Eco-friendly market pursuits are dominantly on the rise and global energy players try to position themselves to serve the increased needs of the environment-focused energy markets.

 

Towards the goal of global theme of zero carbon era, KENTECH creates five specialized energy tracks to be a good global citizen who aim to make contribution to developing core enerygy technology and cultivating energy engineers and professionals to address the humanity's challenges posed by the climate change. KENTECH's five specialized reseaerch fields will also help the nation build and the technology foundation for national competitiveness and sustainable growthin the global energy marketplace. 

 

Five specialized energy institutes

Field	Objective
1. Energy AI	Development of innovative AI/computer advanced technology applicable to the energy field.	- Machine learning - Deep reinforcement learning - Natural language processing - Computer vision - Data analytics - HCI  - CPS
2. Energy materials and Devices	Research on the source technology and industrial application technology of future energy materials and devices.
3. Environmental and Climate Technology	A study on new materials/process/convergence technology to deal with climate change caused by greenhouse gas emissions
4. Grid Modernization	A study on the next generation grid design, operation, and control technology in the era of carbon neutrality.
5. Hydrogen Energy	Eco-friendly hydrogen energy system without emission of GHG is a promising future energy system

Machine learning	Self-supervised learning, transfer learning, meta learning, generative and discriminative modeling, graph neural networks, representation learning, and explainable AI
Deep reinforcement learning	Multi-agent reinforcement learning, hierarchical reinforcement learning, policy gradient methods, planning and learning, efficient and stable training, scalability, imitation learning, applications to optimal control systems (Energy Systems)
Coputer vision, NLP	Pre-training, transformer, word embedding, time-series analysis, super resolution, image enhancement, feature extraction, and pose estimation
Data analytics	Recommender systems, text mining, graph mining, social network analysis, and visualization
HCI, Mobile Computing	Activity modeling and recognition, sensing (acoustic, RF), UI/UX, AR/VR, emotional and mental wellbeing, localization, tracking, wearable computing, human mobility, and gesture recognition
CPS	IoT, cyber security (system, network), energy-efficient protocols, digital twin, real-time systems, distributed systems, and applications

 

Cafe

https://cafe.naver.com/fnkey/82056

안녕하세요 ESS 산업 연구 중인 박사과정 학생 인사드립니다

 

BOOK

https://book.naver.com/bookdb/book_detail.nhn?bid=17730302 

ESS 사업 아는 만큼 성공한다

Report / Paper

KEEI

http://www.keei.re.kr/keei/download/KIP1416.pdf

https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE10481793 

ESS 잔존수명 추정 모델 경량화 연구

https://www.koreascience.or.kr/article/JAKO202031837625668.page

Lightweight Model for Energy Storage System Remaining Useful Lifetime Estimation -The Journal of Korea Institute of Informat

https://www.fpn119.co.kr/125493

[집중조명] ESS 화재안전대책 연구 보고서 입수, 내용 보니…

스마트그리드+시대의+에너지+저장기술+동향+분석.pdf

0.80MB

 

 

34-2_101-109.pdf

1.13MB

 

http://ksme.or.kr/Newsletter/202001/data/2.%ED%85%8C%EB%A7%88%EA%B8%B0%ED%9A%8D.pdf

https://www.sciencedirect.com/science/article/abs/pii/S0263876221003312

Machine learning on sustainable energy: A review and outlook on renewable energy systems, catalysis, smart grid and energy stora

 

https://reader.elsevier.com/reader/sd/pii/S2352152X18305255?token=5632ADF97A788F281D038AA74ADD71856E554E7B4D7F24E5E1CF57C9161E2C936190537767907E97AB0CC203D6CD9CC3&originRegion=us-east-1&originCreation=20211219042839 

Battery energy storage system modeling: A combined comprehensive approach

 

https://reader.elsevier.com/reader/sd/pii/S2589004220311330?token=23D5DCEA69DCF259E58E92F02EA6140FCB2287AC4EC1365F3A3FE815F8C05AD63842702560B034F9BD273720C1C16B82&originRegion=us-east-1&originCreation=20211219042513 

Machine learning toward advanced energy storage devices and systems

 

https://www.sciencedirect.com/science/article/abs/pii/S0360132321010465

A novel LCSA-Machine learning based optimization model for sustainable building design-A case study of energy storage systems

 

https://www.sciencedirect.com/science/article/abs/pii/S0378778821000645

A simplified method of generating sequential meteorological parameters for uncertainty-based energy system design

https://www.sciencedirect.com/science/article/pii/S2352484720312464

Review of energy storage services, applications, limitations, and benefits

 

 

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