AISOP creates an international consortium of highly qualified partners comprising need owners, scientific partners, technology providers, and demo sites.
Our research partners bring competence in advanced analytics, power systems modelling, grid optimisation, grid anomaly detection and grid situational awareness. Our technology partners provide systems and tools for grid monitoring, market platforms, and digital twins of energy systems.
When competence and technology are combined with the operational experience and test fields of the DSO partners, AISOP has the components it needs to develop advanced AI-based tools for operational planning that will support electricity network decarbonisation.
AISOP’s multi-disciplinary approach for collaborative innovation is lead by our research partners and integrates research domains in a number of fields including power system modelling, smart grid technologies, data science and AI, edge intelligence, digital twin, local energy markets and practical implementation in the field.
The Lucerne University of Applied Sciences and Arts conducts practically oriented research and development with practice partners such as regional and national companies, non-profit organisations, communities and cantons as well as federal offices and EU institutions.
HSLU provides competence in AI, edge and federated analytics, local energy markets, and power systems modelling.
The HSLU team has experience in application of edge analytics and distributed intelligence in modern power systems. The participation of the team in other relevant research and industry related projects in Switzerland and abroad guarantee the successful project management and development of the proposed tasks.
HSLU leads various projects relating to detection and forecasting network issues using data from sensors in distribution networks. The project KnowlEDGE (2020 - 2022) investigates a distributed analysis strategy to secure value from smart meter data in multiple locations, in particular targeting DSO use cases, investigating the feasibility of conducting analysis of data at the grid edge. HSLU has other ongoing Innosuisse-funded projects relating to identification and forecasting of anomalies in distribution networks and in DER (e.g. HelioHealth 2020 - 2022), and in the exploitation of local markets for improved penetration and management of renewable energy in distribution networks (eNet 2020, 2021).
ZEDO eV is the Center for Consulting Systems in Technology, based in Dortmund. ZEDO makes its know-how in the field of advisory systems available to its partners and interested parties from business, administration and science. For more than 25 years, ZEDO has been used for research, development and knowledge transfer in the field of information and knowledge processing in technical systems.
ZEDO is organized as an association with legal capacity in accordance with its statutes. ZEDO has concluded a cooperation agreement with the TU Dortmund. According to the cooperation agreement with the TU Dortmund, a university lecturer from the TU Dortmund is the chairman of the board of ZEDO.
ZEDO will use their expertise, to develop ML based models to identify grid anomalies due to demand-side patterns in order to enhance the grid situational awareness. Together with Logarithmo and the delivered data from the DSO WWN, the data flow processes from the DPP Logarithmo will be used to test and validate the developed methods on the demonstration side at WWN with the underlying DPT architecture. ASEW has the opportunity to disseminate the AISOP project ideas and results in form of e.g. working groups on a regular basis in order to gain practice-relevant feedback at a very early stage.
The Research Centre for Energy Networks of ETH Zurich (Forschungsstelle Energienetze - FEN) was established in June 2011 to contribute to addressing the energy challenges of today and the future towards a more sustainable energy system with a special focus on energy networks by means of independent, credible, applied and interdisciplinary research.
Within AISOP, ETH-FEN conducts optimization and develops machine learning methods to power system operation and energy markets, power system modelling, power system stability and protection.
They have competence in applications of optimization and machine learning methods to power system operation and energy markets, power system modelling, power system stability and protection. Researchers have industrial experience in leading and coordinating national and international projects as well as experience in the form of consulting, leading and performing industrial and academic research.
The ETHZ team at FEN brings expertise from a number of previous projects. They were part of a project funded by SFOE, ISCHESS, to study the integration strategies required for increasing the penetration level of distributed stochastic generation in the Swiss electrical supply system and quantify the costs, risks and opportunities of each strategy. Furthermore, FEN is involved in the SWEET PATHFNDR project, which studies data-driven methods applied to electric distribution grid infra-structure planning and operation. The solution methods and the foundation of data analytics framework will be used in this project, in the design phase of time-variant price signals to steer the customer/prosumer behaviour.
AISOP’s technology partners lead the consortium towards to possible and practical, making ideas a reality. The AISOP project enables disparate technologies and technology partners to come together to create innovative and coherent solutions for the distribution system.
Depsys SA works with Distribution System Operators (DSOs) in a variety of ways to help them gain greater insight, understanding and control of their grids.
Depsys empowers grid managers to evolve their operations using data insights gained from Depsys digital technology.
By providing unparalleled intelligence, insight, and control, Depsys enables grid managers to simply and successfully manage their operational transition and to guarantee sustainable electricity for future generations.
Depsys’ core platform ‘GridEye’ combines hardware and software components to produce and process high-precision, real-time data. GridEye helps to monitor, operate, analyse, control and automate any power distribution grid.
AISOP includes the collection and processing of heterogenous data (filtering, clustering, edge analysis, federation etc.) that is available through deployed conventional and new grid measurements that include technology provided by Depsys (e.g., dPMUs, IEDs). Depsys technology also supports the ability to improve understanding of the presence of intermittent faults, and the impact of these through scenario planning and risk analysis.
Depsys experience includes the REeL demo, in the framework of SCCER-FURIES, where they worked closely with Romande Energie in the deployment and analysis of distribution sensors, Era-Net project DigriFlex, which develops and validates forecasting and optimal control algorithms for optimal and secure low voltage grid operation, and Grid Data Digger, a Depsys Innosuisse project for development of machine learning algorithms on a big data platform to use GridEye measurement data for distribution grid operation decision making.
Hive Power is a technology provider of a platform fully open to existing and new energy actors. The goal of Hive Power is to create energy sharing communities where all participants are guaranteed to benefit from the participation.
Hive Power’s provides the FLEXO community manager, an AI-powered energy flexibility orchestrator for managing and optimising Energy Communities.
The AISOP decision support system will be connected with innovation in local energy markets through the HIVE platform, allowing insights from data to be translated into data-driven temporal and spatial identification of dynamic prices signals (e.g., time-variant feed-in-tariffs and retail prices) to steer customer/prosumer behaviour. In this way, the impacts and integration of local trading can be explored in relation to operational planning. The technology-agnostic nature of the HIVE platform allows for interdependencies and synergies between sectors. The framework aims to ensure the stakeholder adoption by addressing the needs of the involved need-owners including the grid operators, customers, and prosumers. ML-based decision-support tools will identify time-variant/dynamic price signals while accounting for the boundary conditions imposed by the local energy markets, allowing techno-economic simulations on the Hive Platform.
Hive Power will bring expertise from PARITY (H2020), where they are developing new business models for local flexibility markets and ODIS (SFOE) where they are developing a multi-level flexibility orchestrator to match the needs of DSOs and the TSO.
logarithmo is B2B software partner for the development and provision of data-driven services for the energy sector and manufacturing industries.
Logarithmo provides their resilient data flow platform for digital process twin to link data silos and IT security classifications, enabling a flexible access to the data for use cases.
The digital process twin developed within AISOP will guarantee that the practical aspects relevant to data acquisition, transmission, storage and access are appropriately addressed while developing the decision-support tools. The provided platform components by logarithmo have been applied for data-driven use- cases for numerous European TSOs, Siemens, CORESO, TSCNET, and innogy.
AISOP’s utility partners provide access to data and user feedback, helping to ensure that AISOP delivers functional solutions that are relevant and useable by electricity system operators. As need owners, they will provide the project consortium access to their pilot sites and stakeholder networks, and will actively participate in the design of the on-site or virtual demonstration projects.
ASEW is the efficiency network for municipal utilities in Germany. They provide support for energy suppliers in relation to energy efficiency and renewable energy. ASEW provides training, energy products for utilities, runs workshops, provides consulting services, and conducts research.
As the largest energy efficiency network for municipal utilities in Germany, ASEW will use its existing working groups to discuss in detail project results regarding their applicability and scalability in practice. The feedback will be used to expand the list of requirements defined by the AISOP need owners.
Romande Energie is a Swiss energy production, distribution and marketing company , also active in energy services. Romande Energie has in excess of 300’000 customers and its portfolio of generating assets includes hydropower, PV, and biomass.
Romande Energie provides data collected at two sites (Rolle: smart meter, PMU intelligent grid sensor data for analysis of LV network faults; Chapelle-sur-Moudon: LV and MV network, including two utility-scale BESS, and an energy community).
Westfalen-Weser Netz is a German municipal network operator with around 740,000 customers. They manage the regional distribution networks for electricity, gas and water, and have a renewable energy penetration of more than 49%.
(DE) provides static and dynamic data and will support the practical implementation of the digital process twin. In addition to the scientifically developed methodology and algorithms for the identification of network anomalies (demand and supply), WWN’s focus is on twin implementation.
AISOP combines data access and ingestion, decision-support, dynamic tariffs, and digital platform integration for improved distribution grid situational awareness.