SONDER

Service Optimization of Novel Distributed Energy Regions

Info

Project duration: 09/2019 – 03/2023

Funded by: BMVIT and BMDW

Programme: ENERGIE DER ZUKUNFT

Call: ERA-Net SES Joint Call 2018 RegSys

Description

Local and regional energy systems are expected to become important partners for distribution system operators, and significant contributors to energy system stability. There are no control strategies for communities to manage distributed energy resources, help optimizing local efficiency, pool, orchestrate, and command flexibilities in an increasingly digital world, and offer that flexibility on the gas and electricity markets.

Modern trends in massive renewables deployment as well as integration of new types of consumptions such as EVs and datacenters post challenges for existing power distribution systems at local and regional level. Additionally new players such as aggregators are incentivized to maximize usage of the grid – not to optimize or balance it as infrastructure. Therefore, creation of well-integrated and efficient smart energy systems need novel optimization strategies. Together with need owners on the brink of becoming a regional local energy community, we want to develop a scalable, multi-service, and multi-level approach aiding the development of integrated local and regional energy systems that can help efficiently providing, hosting, and utilizing high shares of renewables.

Typically, power peaks can be buffered in local distribution networks, but the unpredictable nature of renewable energy sources, strongly varying processing demands in data centers, unexploited efficiency of gas, electricity, and bio fuels in operating buildings, mobile electric vehicles lead to unknown correlations in time and space. Building on existing knowledge of national and regional projects, we want to investigate the potential of aggregation services for generation, consumption, demand response, and energy storage in a pan-European setting, including data centers, residential and industrial users.

Together with stakeholders in NGOs, industry, and ESCOs, we aim at creating new service concepts for local and regional energy communities to exchange their energy surplus and needs. The services should consider local increase of efficiencies compared to other regions, local optimizations accounting for higher goals of resilience and security of supply, and orchestration or pooling of yet unused flexibilities to ease their potential adoption by market stakeholders.

The enabling technologies are the use of existing consumption models, application of novel AI strategies to optimize local efficiency with the goal to increase the amount of flexibilities by prediction, and active prosumer participation in a cellular, pan-European approach. On top of that, we will look at correlating load profiles of novel actors (such as EVs and datacenters) in order to develop AI based algorithms for optimal placing of these loads in geographical and temporal terms. In other words, our knowledge of grids and power flow enable us to predict optimal conditions for not only grid operation but also its extension and upgrade, with respect to various loads and their characteristics.

We will therefore extract needs from different stakeholders (such as ESCOs, DSOs, datacenter operators, local authorities) not only by direct involvement in scenario interviews but also from dedicated data analysis that may directly point out areas of optimization, combining interests of different stakeholders.

Based on real-life data from several Smart Energy System pilots around Europe (i.e., Austria, Sweden, Switzerland, and Ireland) and by applying AI strategies, we will be able to cross correlate and assess various regional differences and find points of optimization and interaction with respect to characteristics of new types of loads as well as stakeholder needs.

As a result of the project we consider a sensitivity analysis and co-created recommendation system framework that will enable multi-service (e.g. EV charging and datacenter operation, building automation) and multi-level (i.e. local vs. regional) optimization with respect to load characteristics and specific requirements.

This project has been funded by partners of the ERA-Net SES 2018 joint call RegSys (www.eranet-smartenergysystems.eu) – a network of 30 national and regional RTD funding agencies of 23 European countries. As such, this project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 775970.

Austrian Partners

Swedish Partners

Swiss Partners

Swiss National Support