3 ENERGY TRANSITION
5.4 Development procedure utilising living laboratories
Piloting or field tests are crucial in Smart Grid deployment to test innovations in a real-life context with potential end-users. A living lab methodology based on co-creation focuses on the active and collaborative development of an artefact (product, interface, service, IoT solution) for the stakeholders, including users.
Technical, societal, and economic challenges and benefits can be evaluated through a real-life environment. This thesis defines living labs following the definitions in Evans, P., Schuurman, D., Stahlbrost, A. and Vervoort (2017):
A living lab is a multi-stakeholder organisation established to develop a co-creation platform for developing innovations that adhere to the open and user innovations and leverage real-life experiments with the stakeholders’ benefit objectives.
In this context, living labs are the key platforms, the potential niches entering the regime level. Piloting in living labs gives real-life feedback and validates a developed concept or product before mass production, business applications, and sales. The stakeholders’ co-creation within living labs has a socio-technical participatory aspect. For example, the field tests in a living lab encourage users to propose improvements for the technology being tested compared to a traditional field test, which aims to gather user feedback (Spohrer & Freund, 2012). The field tests can differ according to the phases of the living lab process, but generally, a field test can be defined (Coorevits et al., 2018):
“A field test is a user study in which the interactions of test users with an innovation in the context of use are tested and evaluated.”
The living lab process phases can be defined as 1) co-creation, 2) exploration, 3) experimentation phase, and 4) evaluation (Vicini et al., 2012). These process phases can be extended, producing eight working steps (Steen & van Bueren, 2017). The exploration phase can be described by implementing a concept to a solution. The experimentation phase can be described from concept to prototype putting the designed solution to the test in a real-life context to the greatest extent possible. The users face the solution for the first time. The evaluation phase is characterised by mature innovations focusing on market entry aspects. (Coorevits et al., 2018)
The development of a product needs research platforms and testbeds in its RDI phases; in product design, engineering, and prototyping. The real-life experiments and testing are traditionally at the end of the development process when the innovation has already reached a certain maturity level. The product features and settings are already close to actual usage. Interactions between the system, the user, and the environment can be diverse. If the scope needs to be changed, it can lead to high development costs or even a technological valley of death. Therefore, the real-life dynamics could be replicated in the early phases of the living lab project by simulations (usability lab, technology) or technology development.
(Coorevits et al., 2018)
Hence, testing goes through the exploration, experimentation, and evaluation phases. The exploration phase can include trials in the laboratory. The experimentation phase can benefit from the SNM approach in the implementation of the innovation and its testing. The evaluation phase includes the final tests and customer validation, targeting for launching the solution.
Organising field tests in the early stages of innovation is challenging (Marez &
Verleye, 2004). The degree of realism (physical location, test users, tasks, participants motivations) describes the test proximity to the actual use and context relevant to the assessment and aspects of use that are important enough to be present in the assessed configuration or evaluated setup (Coorevits & Jacobs, 2017). The components influencing the interactions with a system, should be considered in the simulation set-up development are 1) temporal, 2) physical, 3) technical/information, 4) social, and 5) task contexts (Coorevits et al., 2018).
HIL platforms combined with the models of living lab dynamics (such as co-simulation) can offer a means for early-stage learning in SNM. Integrating the actions of users in the power systems’ technical simulations is essential for future scenario development and testing. This approach presents the socio-technical dynamics. For this reason, Publication II introduces a framework and a method to model the evolution of customers within the socio-technical dynamics of the electricity distribution networks.
The evaluation of appropriate simulations and testing methods, by accuracy and fidelity (Figure 24, p. 56), is essential when developing a living lab environment.
Real-time simulation is of interest in technology development, but the HIL methods must be better known to various stakeholders, the potential collaborative partners in living labs (K. Sirviö, Kauhaniemi, Laaksonen, et al., 2020). As HIL technologies accelerate RDI, they enable new ideas to get faster in the piloting stage. Additionally, the measurements coming from living laboratories combine
with the real-time simulations to provide safe product development testing in the laboratory in various scenarios flexibly.
Figure 29 presents an outline for using HIL methods together with a living laboratory. The development of Digital twins is essential for evaluating the power system and control models. This research utilised one-year measurement data from the Sundom Smart Grid to evaluate the power system modelled.
Figure 29. Real-time development and testing methods utilising living laboratories. Adapted from (K. Sirviö, Kauhaniemi, Laaksonen, et al., 2020).
In addition, Coorevits et al. (2018) define four types of field tests in living labs, characterised by their phase and degree of realism: concept (for example, proxy tests), mock-up (a scale or a full-size model of a design or a device), pilot, and go to markets to guide setting up field tests in the living lab process stages. The early-stage field tests are small-scale and closed. They need a higher degree of guidance, and they are qualitative. The later-stage field tests are large-scale and open, with limited to no guidance, and they are primarily quantitative.
Figure 30 presents the key elements of piloting within a living lab framework.
Naturally, legislation and other regulations constantly influence the background in piloting and living labs. The figure intends to show the development stages (1-4), and basically, the actions by authorities and governments affect in all stages.
The key elements are users, devices, intelligent networks, network operations, business applications, and exports, briefly introduced in the following description.
Besides considering the interactions between the users and devices, and their testing, intelligent networks must be assessed when planning a pilot in a living lab environment. The challenges of intelligent networks are grid modernisation (AI,
Internet of Things, IoT), open architecture solutions, computing power increase, appropriate balance between security and investments. IoT development in the energy application domain is essential and identified (Brynskov et al., 2019) in security/cybersecurity, privacy, safety, and interoperability.
Network operations are the value creation procedures for the stakeholders with the appropriate methods. The Smart Grid operations include methods for the reliable, flexible, and efficient power flow and enable operations in the markets, with the ADNM scheme solutions (Figure 18, p. 43). By understanding the operations maturity, the windows of opportunity can be easier to notice. The maturity levels of the operations are described in Hui (2014) as reactive, informed, managed, automated, and predictive, defining the utility’s ability and capacity to manage the data influx. Business applications can be solutions for ASs, DER, home area networks (HAN), advanced metering infrastructure (AMI), advanced utility control and management systems, smart EVs charging infrastructure. The exports of the Smart Grids technologies relate to the know-how, devices, and solutions.
Figure 30. Key elements of piloting in living labs.