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Interoperable tools for an efficient management and effective planning of the electricity grid

Periodic Reporting for period 1 - INTERPRETER (Interoperable tools for an efficient management and effective planning of the electricity grid)

Reporting period: 2019-10-01 to 2021-03-31

The project brings together 9 entities from 6 European countries in order to develop the INTERPRETER platform, which is a modular grid management solution that provides data services based on an integrated grid modelling tool. The solution targets grid operators who want to improve management of their distribution grid, where observability is still low, despite smart meter data. INTERPRETER provides a data lake, unifying diverse data formats, together with tool which creates a grid model from available data. This grid model enables advanced monitoring, O&M, planning, and flexibility services. A total of 10 services are being developed, being 5 devoted to grid operation and maintenance: Non-technical losses detection, Ancillary services for DSO based on voltage balance and congestion, DSO/TSO interaction for ancillary services extension, Predictive maintenance strategies for grid assets, Grid control optimisation and self-Healing. The other 5 services cover grid planning issues, such as Optimal reactive power compensation, Planned phase balancing, Nodal capacity allocation, Dispersed storage units location optimization and finally, Environmental and economic assessment based on LCA/LCC techniques. As a result, cost reductions are expected for grid operators (CAPEX and OPEX), due to improved O&M (less interruptions and losses), Optimized Planning and Theft detection. Added value is obtained from flexibility services, taking into account challenges and opportunities from Distributed generation and Dispersed storage. In summary, proposed solutions are conceived to support the profound change which is under way, in order to reach a sustainable energy supply based on distributed and renewable sources.
In the first half of the project, the main focus of the activities was the development of the grid modelling tool and the platform architecture. In a first step, a review of AMIs and other sensors created a solid basis for data availability considerations. In addition, the definition of use cases for all INTERPRETER tools helped to define data requirements, which are relevant for the grid model (required level of model detail). Also, a data collection protocol has been developed, which helped to identify data-availability at the pilot sites and data privacy issues. As a result, 3 data-availability scenarios have been defined, to create a common basis for the development of the grid modelling tool and the validation process. Taking into account all this, a set of algorithms have been developed, which estimate missing information on different levels (from finding minor mistakes to creating a grid layout), to finally obtain a complete grid model. Currently, all algorithms are integrated in a grid modelling tool. Resulting grid models are converted into CIM format, which has been defined ensuring compatibility with the Common Grid Model Exchange Specification (CGMES) requirements (IEC specifications TS 61970-600-1 and 61970-600-2).
Apart from the grid modelling tool, the development of the 10 grid management tools has been started. In a first step, identification of existing and future issues affecting grid management helped revising objectives of the INTERPRETER tools. In a second step, definition of formal use cases for all tools helped to define data requirements (input and output). Regarding the INTERPRETER platform, specific data spaces and adaptors are being developed to integrate multiple data sources and platforms from pilot sites and support data ingestion for software applications.
The main innovation within the first half of the project is related with the grid modelling tool and data availability scenarios. A scientific paper has been published by CERTH in the Journal Energies (“An Efficient Backward/Forward Sweep Algorithm for Power Flow Analysis through a Novel Tree-Like Structure for Unbalanced Distribution Networks”). This power flow algorithm will enable the grid modelling tool to handle unbalanced distribution networks, entirely based on Python programming, which is compatible with the open-source software Pandapower. Another step beyond the state of the art is the integration of the algorithms which will allow an automated, massive generation of functional grid models. The finalization of this development step is foreseen for the second half of the project.
Most of the innovations are expected to be achieved in the second reporting period, including all grid management tools and the INTERPRETER platform, aligned with main objectives of the project: (1) To complete the existing information that grid operators have about their networks with a tool able to generate new grid models from different available sources, (2) To increase the efficiency of the grid management – including both operation and maintenance – through a set of innovative, interoperable and modular software applications making use of the new grid models (3) To improve the sustainability and to reduce the costs in the electricity grid design and planning through a set of innovative, interoperable and modular software applications making use the new grid models (4) To ensure the smooth and flexible integration of INTERPRETER tools into the existing systems of the grid operators through an open source platform (FUSE) as the core part of a complete hybrid multi-cloud solution and (5) To test and validate INTERPRETER solutions using a set of representative use cases defined in collaboration with 2 different European DSOs from Spain and Belgium.
Even though, one publication has been achieved for one planning tool: “Optimizing nodal capacity allocation using risk assessment of element failure rate” published in IEEE CPE-POWERENG2020 by R&D NESTER. Further publications are expected which will show innovations within the other tools and the INTERPRETER platform.
CUERVA DSO
SysLab DTU