MORE | Management of Real-time Energy Data - Goals


Green Energy | MORE - Management of Real-time Energy Data
MORE | Management of Real-time Energy Data - Green Energy

Employ AI and Machine Learning techniques to Increase the efficiency of wind turbines and solar parks and to improve the accuracy of forecasting.

Industrial Leadership | MORE - Management of Real-time Energy Data
MORE | Management of Real-time Energy Data - Industrial Leadership

Enable EU stakeholders to offer better renewable energy production facilities, with reduced maintenance costs, and accurate return of investment prediction.

Extreme data analytics | MORE - Management of Real-time Energy Data
MORE | Management of Real-time Energy Data - Extreme data analytics

Create a data analytics platform that will be able to manage extreme loads of sensor streaming data and time series.

Accurate forecasting | MORE - Management of Real-time Energy Data
MORE | Management of Real-time Energy Data - Accurate forecasting

Provide accurate forecasting and prediction through AI algorithms that work over huge volumes of streaming data.

News


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MORE | Management of Real-time Energy Data - Second MORE webinar: Incremental machine learning models for high-frequency big data

With the lowering costs of sensors, high-volume and high-velocity data are increasingly being generated and analyzed, especially in IoT domains like energy and smart homes. Consequently, applications that require accurate short-term forecasts and predictions are also steadily increasing...

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MORE | Management of Real-time Energy Data - Upcoming webinar from MORE: Data-driven soiling detection in PV modules

We present a solution to the problem of estimating the soiling ratio in photo-voltaic (PV) modules, i.e., the ratio of the real power output to the power output that would be produced if solar panels were clean. A key advantage of our method is that it can estimate soiling, without needing to train on labelled data, i.e...

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MORE | Management of Real-time Energy Data - AID4RES workshop supported by MORE

AID4RES23 workshop focuses on challenging and emerging areas in data management, machine learning and artificial intelligence methods and applications that use sensor data and/or big time-series data regarding the RES industry. It is collocated with the ADBIS 2023 conference and will be held on the 4th of September in Barcelona...

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MORE | Management of Real-time Energy Data - Watch the IMLA Colloquium series: Health monitoring challenges in Renewable Energy Sources (RES) sector

Seshu Tirupathi, Giorgos Giannopoulos, Dhaval Patel, Manolis Terrovitis, Dhaval Salwala, and Nikos Raftopoulos shed light on the challenges in the health monitoring of RES installations...

MORE | Management of Real-time Energy Data - Innovations


MORE | Management of Real-time Energy Data - In a nutshell


MORE is a Horizon 2020 project funded under Grant Agreement No. 957345 and will deliver a platform to address the technical challenges in time series and stream management, focusing on the RES industry. Specifically, MORE’s platform will introduce an architecture incorporating edge computing and cloud computing to address responsiveness and the need for sophisticated analytics simultaneously. This architecture will be combined with time series summarization techniques, or as we more accurately term them in MORE, modeling techniques for sensor data. Models are any compressed representations that allow the reconstruction of the original data points of a time series (e.g., a linear function) within a known error-bound (possibly zero). This approach synergizes with the edge computing approach since summarization can be done at the edge, reducing the load in the whole data processing pipeline.



The key objective of MORE is to allow stakeholders in industry sectors with huge volumes of sensor data, especially the RES industry, to: a) scale the management of streaming and historical time series beyond an order of magnitude beyond the state-of-art and b) perform forecasting, prediction, and diagnostics using the entire data available to them with accuracy that outperforms existing approaches.

MORE | Management of Real-time Energy Data - Partners


Athena Innovation Center | MORE - Management of Real-time Energy Data
AAU | MORE - Management of Real-time Energy Data
Inaccess | MORE - Management of Real-time Energy Data
IBM | MORE - Management of Real-time Energy Data
Perception Dynamics | MORE - Management of Real-time Energy Data
ENGIE Laborelec | MORE - Management of Real-time Energy Data
Modelar Data | MORE - Management of Real-time Energy Data

MORE | Management of Real-time Energy Data - Contact