DISCERN – Distributed Intelligence for Cost-Effective and Reliable Distribution Network Operation
By Carmen Calpe
DISCERN will provide distribution system operators (DSO) with a better understanding of best-practice system solutions for monitoring and control of their Low Voltage and Medium Voltage grids. Up to now, these grids are characterized by non-existent or low observability. With mostly centralized generation, it was historically not necessary to implement systems to monitor and control distribution networks. Due to the changing patterns of electricity production, and greater penetration of decentralized generation on the MV- and LV-level, the electricity distribution systems require new modes of operation, increased levels of monitoring and control and potentially a different architecture to maintain the high quality of power supply.
Based on the recommendations from DISCERN, DSOs will be enabled to implement technical solutions that have been tested and validated in various countries and circumstances. The project aims at giving DSOs the tools to answer complex questions like:
- How much intelligence do the DSOs need in their distribution networks to ensure a cost-effective and reliable operation of the networks?
- What is the most cost-effective solution to implement this intelligence in the network?
- How should the ICT infrastructure be designed to serve the requirements of a DSO?
In order to facilitate the exchange of information and knowledge and provide a consistency, the concept of Leader, Learner and Listener was introduced in the project. This model, also known as 3L, has been used in the project and promoted to stakeholders as a guiding principle to specify, organize and articulate this process.
The 3L methodology has been applied to leverage the commitment of the DSO undertaken through the DISCERN project. A DSO takes one of the roles (Leader, Learner or Listener) in relation to a specific sub-functionality. The role of a Leading DSO is to mentor on a certain sub-functionality. Leading DSOs are characterized by the fact that they have already developed and implemented a solution for the specific smart grid sub-functionality. The DSO is Leading by providing input to other DISCERN partner DSOs who are considering to implement this functionality and also making it available for comparative assessment within DISCERN.
The Learning DSOs are the ones who will implement the technical solution of a sub-functionality within the scope of DISCERN by means of field tests. This means that the DSOs bring their demonstration sites forward by evaluating new solutions through simulations and pilot installations.
Listening DSOs have not yet made any considerations regarding the specific implementation but are keen to take the results from DISCERN into consideration.
In order to keep the exchange of information consistent, the DISCERN project has implemented an approach to represent and exchange smart grid solutions based on the Use Case and SGAM (Smart Grid Architecture Model) methodologies. The latter is a standardized approach to describe system requirements (i.e. IEC 62559); while the former is a framework to represent high level smart grid architectures highlighting key interoperability aspects. Moreover, libraries of Actors, Functions, and Requirements have been developed during the project in order to agree on common terms that should be used in the Use Cases and SGAM models.
To have a better understanding about the necessity of these standardized tools the difficulties for comparing several solutions faced at the beginning of the project have to be considered. At the early stage of the project the proposed smart grid solutions were described in different formats. This made it difficult to: ensure consistency of the descriptions; enable multi-editing of Use Cases and SGAM models; and reuse the Use Case, SGAM models, and libraries in other software tools, such as external repositories.
Given that the tools developed in DISCERN rely on international standards and frameworks, they are well suited to be leveraged in other projects, as well as internally within the companies, with the aim of facilitating sharing of smart grid requirements and architectures. This is particularly useful in the context of large smart grid projects, in which partners from different areas of expertise and different countries need to exchange information on smart grid solutions with each other.
As an important complement to the field test, simulations are being performed during the project to evaluate scalability and replicability of the solutions. The simulation scenarios are also defined based on the development process enabling Leader’s and Learner’s solutions to be evaluated and compared. Dissemination of results is also facilitated by this approach and software tools, making them more accessible and easy to adopt for DSOs and importantly, other stakeholders external to DISCERN.
The DISCERN consortium is composed of five major European DSOs (RWE, Iberdrola, Union Fenosa, Vattenfall and SSE), technology providers (ZIV and ABB), a technical and business consultancy in the field of energy (DNV GL) as well as leading research centers and universities (KTH, OFFIS and CIRCE) under the lead of RWE Deutschland AG. The total DISCERN budget is 7.9 million euros, with 4.8 million euros financing by the European Commission under the Seventh Framework Program (FP7). The investments of the five demonstration projects linked to DISCERN are higher than 100 million euros.
The project started on February 1, 2013 and will last three years (2013 - 2016). For more information on the project results please consult the website www.discern.eu.
The research leading to these results has received funding from the European Union Seventh Framework Program (FP7/2007-2013) under grant agreement no. 308913.
Carmen Calpe holds an MSc degree in industrial engineering with specialization in electricity. She joined the New Technologies Department of RWE in July 2011 and is involved in several European projects dealing with smart grids and new technologies. She is the Project Coordinator of DISCERN project.