D-JRA1.3 Methods for Test Upscaling and Domain Extension
Creators: name: Heussen, Kai
name: Schwarz, Jan Sören
name: Cortés, Andrés
name: Feng, Zhiwang
name: Nikoletatos, John
name: Pham, Ming Cong
name: Tran, Quoc Tuan
name: Adrinanesis, Panagiotis
name: Kamsamrong, Jirapa
Publisher: name: The ERIGrid 2.0 Consortium
Year: 2023
Subjects: Domain Extension
Scaling
Scale-up
Scale-out
Test Planning
Deliverable
European Union (EU)
H2020
Project
ERIGrid 2.0
GA 870620

description: This document presents a conceptual clarification and a number of methods for test upscaling and domain extension and the challenges associated with it. Benchmarks developed in the ERIGrid 2.0 project have been used as practical examples to interested users and practitioners for adopting these methods for their research in Research Infrastructures.

The motivation behind this work originates from researchers active in the energy domain attempting to upscale a given test or extend the number of domains represented in their experiment. Typically, a reference model or laboratory setup could be used for a simple experiment but it has its limitations when translating results to the scale of real systems, especially large systems. The challenge here is how to utilise and adapt a given reference setup for delivering results applicable to larger systems and also how to extend the experiment to other domains, especially for tests involving Cyber-Physical Energy System. A typical approach could be to rely on in-house experience for applying appropriate scaling methods, such as replicating some components which might affect the system, leading to significant system change in system behaviour.Since the terminology for upscaling itself can be interpreted differently, which could lead to confusion among researchers.

This research activity first outlines the terminology used for upscaling and domain extension. Scalability and replicability are essential characteristics considered for rolling out any given technology to a given market. While scalability refers to the capability of a system to modify its scale to accommodate an increase in volume, replicability refers to which extent an exact copy of the system can be created. To refine the technical interpretation of scalability, the terms scaling up and scaling out are defined in this work which could help create a common understanding among researchers. By scaling a testbed, the physical scale of the system can be reduced, whilst maintaining the integrity and realistic representation of the larger real system. When scaling out the number of individual components being investigated are increased, thereby enhancing the capability of the testbed. Domain extension means to address also interdependencies of use cases operating across multiple domains throughout a system.To support the design and assessment of scaling and domain extension tests, a set of analytical methods is identified. The methods are summarised and their connection to the above listed scaling concepts is explained.

Two sets of case studies are presented for scaling and domain extension in practice by using two benchmarks; an electrical network and a multi-energy network. The first case study illustrates four examples of scaling up and scaling out in a power system. This case study can realistically represent the current challenges for high Distributed Energy Resource penetration at the Low Voltage systems and also highlight the importance of scaling in the power system analysis. The second case study focuses on domain expansion and scaling up in multi-energy systems. A result of the second case study is that it can be used to identify appropriate testing needs for physical laboratories to prepare the field roll-out of the intended design.