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Encored provides the full stack services to customers from small scale households to large scale owners of renewable assets, using our core technologies of AI analytics engines, real-time data platform, and energy IoT.
AI Analytics Engines
Disaggregation
Disaggregates the total load into each home appliances by
NILM (Non-Intrusive Load Monitoring) technology
NILM (Non-Intrusive Load Monitoring) technology
Forecasting
Forecasts power generation and energy consumption
by day ahead and intraday
by day ahead and intraday
Judgement
Detects and judges abnormal status and faults on
condition of renewable assets and energy usage patterns
condition of renewable assets and energy usage patterns
Optimization
Optimizes Load-SolarPV-ESS consolidated system
to minimize cost and maximize profit
to minimize cost and maximize profit
Our Publications
- K Park, J Jeong, H Kim (2020). Missing-insensitive Short-term Load Forecasting Leveraging Autoencoder and LSTM. ICLR Climate Change AI
- C Shin, E Lee, J Han, J Yim, W Rhee, H Lee (2019). The ENERTALK Dataset, 15 Hz Electricity Consumption Data from 22 Houses in Korea. Scientific data, 6(1), pp.1-13.
- E Lee, K Lee, H Lee, E Kim, W Rhee (2019). Defining Virtual Control Group to Improve Customer Baseline Load Calculation of Residential Demand Response. Applied Energy, 250, pp.946-958.
- S Ryu, H Choi, H Lee, H Kim (2019). Convolutional Autoencoder based Feature Extraction and Clustering for Customer Load Analysis. IEEE Transactions on Power Systems.
- C Shin, S Joo, J Yim, H Lee, T Moon, W Rhee (2019). Subtask Gated Networks for Non-Intrusive Load Monitoring. Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 33, pp.1150-1157.
- M Kim, K Kim, H Choi, S Lee, H Kim (2019). Practical Operation Strategies for Energy Storage System under Uncertainty. Energies, 12(6), p.1098.
- C Shin, S Rho, H Lee, W Rhee (2019). Data Requirements for Applying Machine Learning to Energy Disaggregation. Energies, 12(9) p.1696.
- S Ryu, H Choi, H Lee, H Kim, V Wong (2018). Residential Load Profile Clustering via Deep Convolutional Autoencoder. 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), pp.1-6.
- K Lee, H Lee, H Lee, Y Yoon, E Lee, W Rhee (2018). Assuring Explainability on Demand Response Targeting via Credit Scoring. Energy, 161, pp.670-679.
- J Han, E Lee, H Cho, Y Yoon, H Lee, W Rhee (2018). Improving the Energy Saving Process with High-Resolution Data: A Case Study in a University Building. Sensors, 18(5), p.1606.
Energy IoT
- Power management : Provides fundamental management services such as usage and billing check, progressive billing stage check, etc.
- Occupancy : Energy usage information through sensor data gives information for occupancy.
- Living patterns : Check schedules through sensor data of waking up, eating, and absent timings.
- Confirmation of use of household appliances : Confirmation of use of certain appliances
- Abnormal situation notification : Real-time notification to the guardian in case of detection of the abnormal usage pattern (e.g. if there is no movement for 12 hours)
Real-Time Data Platform
Artificial Intelligence powered
Integrated Distributed Energy Resources Management System
Renewable
Asset
Management
Microgrid
Management
Minimize O&M cost and generation loss
with unmanned monitoring
Maximize profit
and achieve the best efficiency
Renewable
Asset
Management
Minimize O&M cost and generation loss
with unmanned monitoring
Microgrid
Management
Maximize profit
and achieve the best efficiency
About Us
We are US based company doing Energy AI located in San Jose, California and was established in 2013. Encored is a startup funded by George Soros and SoftBank, leading next-generation technology. We are offering innovative solutions in the energy industry by using AI and Big-Data algorithms. Our mission is to develop a purpose-driven connection from people to energy data by creating a network between DERs and consumers.
Investors
Partners & Customers
Recognitions & Certificates
CIO APPLICATIONS
CIO APPLICATIONS
International Accreditation Forum
: 클라우드 기반 실시간 전력 서브미터
산업통상자원부
산업통상자원부
한국디자인진흥원
산업통상자원부
국가산업융합지원센터
한국인터넷전문가협회
지능형전력망 법제도, 정책지원 및 기술개발
산업통상자원부
서울형 R&D 지원사업 과제 우수성과 : 기술혁신 및 경제 발전 기여
서울특별시
산업 융합의 활성화 및 보급확산
산업통상자원부장관
지능형 전력망 산업 진흥을 통한 국가사회발전 기여
산업통상자원부
스마트 시티 SOC-ICT 우수기업
국토교통위원회
중소벤처기업부
이전
다음
Team
As a group of energy experts, mathematicians, statisticians, psychologists, designers and computer scientists, and project planners with more than 10 years of experience in each field, we provide IT-based energy technology to enhance the customer's business competitiveness and services. We have 33 members in Korea office, with more 20+ in U.S. and Japan.
Kyoungil Shin
CTO
Former Senior Manager in Nexon
BS in Mathematics
Dr Jin Lee
CMO (US)
Former General Manager and CTO in GE Healthcare IT
PhD in Mechanical Engineering
Dr Seonjeong Lee
Head of Algorithms
PhD in Mathematics
BS in Mathematics
Dr Jaeryun Yim
Senior Data scientist
PhD in Computational Science
BS in Mathematics
Contact Us
If you’d like to hear more about how Encored could help you, please get in touch with us at esolution@encoredtech.com, or you can fill in the form below for the request of further materials, such as case study, white paper, demo video, etc.
We will reach out within 48 hours.
BROCHURE DOWNLOAD
Encored
Head Quarter
3031 Tisch Way, 110 PlazaWest
San Jose, CA
United States, 95128
Encored Technologies
R&D Center · Asian-Pacific Sales
13F, 327 Bongeunsa-ro
Gangnam-gu, Seoul
South Korea, 06103
ENCORED JAPAN
Joint Venture with SoftBank
27F, Shiodome Sumitomo Bldg. 1-9-2
Higashi-Shimbashi, Minato-ku, Tokyo
Japan, 105-0004