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Renewable Energy

FLEXERGY - Energy flexibility through synergies of big data, novel technologies and innovative markets

The purpose of the project is to maximise synergies in big data, novel technologies and innovative market design for higher degrees of flexibility in energy systems. 

Project manager at MDH

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The transition towards a highly renewable energy system will require enhancing flexibility of energy systems to accommodate more intermittent renewable energies such as solar and wind, and also to meet the growing need of capacity. This synergy proposal contributes to the improvement of flexibility by maximizing the synergies in big data, novel technologies and innovative market design. This project will involve both energy suppliers and end-users in an effective way, with sufficient transparency and mutual understanding for the needs and supply, and driving forces of various stakeholders.

The project brings together a set of key business partners to be key enablers for the successful development to enhance flexibility in the energy markets. It involves utility companies (Mälarenergi, Eskilstuna Energi och Miljö) with businesses in district heating, electricity production and distribution that are highly complex interconnected, together with end-users (Castellum, Hemsö, Aroseken and Rocklunda Fastigheter) representing an extensive number of interests as they own various types of buildings. The synergy proposal also includes technology providers like Northvolt and Amazon Web Services as key partners in the development of smarter solutions for cities, energy systems and buildings. It involves local and regional governments (cities and regions) as they are responsible for the development on various levels and in different domains in the society.

Three most important areas have been identified, namely Subprojects (SPs) motivated by integrating technologies, data and tools, and market. All three subprojects bring together research and development efforts in following key enabling areas to achieve the overall target of the synergy proposal:

SP1: Innovative solutions for the provision of flexibility: To identify new needs and development of technologies for flexibility in combination with development of novel energy system solutions and to create analytical tools to better understand impact of technologies at energy system level;
SP2: Flexibility markets and business concepts: To understand the needs and driving forces of different stakeholders, and to explore novel business models such as efficient combinations of price mechanisms, behavioral triggers, to enhance the willingness to participate in flexibility markets.
SP3: Data mining and deep-learning techniques for improved flexibility: To explore possibilities to merge various data sources, big data, to efficiently predict energy demand more efficient and accurate (spatial, temporal) and to build novel tools for short and long-term forecasting of load demand considering the dependencies of local and regional socio-economic development.

Besides the individual contributions of each sub-project, the project as a whole will also create multiple synergies for the development of these enabling domains coupled on city, regional and national levels.

Project objectives

All the following three subprojects bring together R&D efforts in the key enabling areas in order to reach the overall target of the synergy of the FLEXERGY:
  • Innovative solutions for the provision of flexibility (SP1): To identify new needs and development of technologies for flexibility in combination with development of novel energy system solutions and to create analytical tools to better understand the impact of technologies at the energy system level;
  • Flexibility markets and business concepts (SP2): To understand the needs and driving forces of different stakeholders, and to explore novel business models such as efficient combinations of price mechanisms, and behavioral triggers, to enhance the willingness to participate in flexibility markets;
  • Data mining and deep-learning techniques for improved flexibility (SP3): To explore possibilities to merge various data sources, and big data, to efficiently predict energy demand more efficiently and accurately (spatial, temporal) and to build novel tools for short and long-term forecasting of load demand considering the dependencies of local and regional socio-economic development.

 

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