Energy transition frameworks

Achieving climate-neutral Europe, long-term sustainability objectives require the transformation of core societal systems, which can be understood by transition dynamics, as presented in EEA (2019), where four systemic change perspectives are defined. The socio-ecological perspective explains ecology and earth system transformations through social sciences. The socio-economic perspective explains how economic activity affects and how social processes modify it. The socio-technical perspective has insights from evolutionary economics, innovation studies, and institutional theory. Action-oriented perspectives give insights into different roles of actors (individuals, communities, or other groups) in systemic change by enhancing other systemic approaches, for example, increasingly in socio-technical research.

This research focus is on the socio-technical perspective, in which the characteristics of transitions are defined in EEA (2017) as follows:

1. “Transitions are co-evolutionary processes that require multiple changes in socio-technical systems. Transitions involve both the development of technical innovations and their use in societal application domains. This

‘use’ includes adoption by consumers (markets and integration into user

practices) and broader processes of societal embedding, which may require changes in regulations, markets, infrastructures and cultural discourses.

2. Transitions are multi-actor processes, entailing interactions between businesses, different types of users, scientific communities, policymakers, social movements and special interest groups.

3. Transitions are radical shifts from one system to another. The term ‘radical’

refers to the scope of change, not to its speed. Radical innovations may be sudden and lead to creative destruction, but they can also be slow, proceeding in a step-wise fashion.

4. Transitions are often long-term processes (40-50 years). While breakthroughs may be relatively fast (e.g. 10 years), the preceding innovation journeys through which new socio-technical systems gradually emerge usually take much longer (20-30 years).”

The socio-technical transitions in the energy and power systems are discussed in Adil & Ko (2016), EEA (2019), Jacobsson & Bergek (2011), Smith et al. (2005), and G. Verbong & Geels (2007, 2010). In sustainable transition, the end-customers’

behaviour plays a central role, which is analysed, for example, in Claudy et al.

(2013), by discussing the attitude-behavioural gap for renewable energy systems.

This thesis is limited to the socio-technical transition in electricity distribution grids with an action-oriented perspective, meaning that network functional level UCs are considered. However, the business level UCs and techno-economic examinations are excluded. However, in addition to the socio-technical evolution of power grids, the socio-economic perspective is essential (EEA, 2019). Bigerna et al. (2016) reviewed the socio-economic features of Smart Grids development.

Van Den Bergh et al. (2011) presents the theoretical frameworks for sustainability transitions, which are 1) the innovation systems approach to transitions, 2) the MLP and the SNM frameworks, 3) transition management (TM), and 4) evolutionary-economic views and multi-agent modelling of transitions. In this research, the MLP approach was the most suitable for the socio-technical analysis of power system evolution because of the key concepts in which it is applicable:

“Multiple (competing) technologies, structural change, multiple levels (niche, regime, landscape), multiple phases, coevolution, networks, transformation, reconfiguration, technological substitution, de-alignment and re-alignment”, and its policy view: “Align technologies and user practices. Strategic niche management (SNM) – reflexive management of real-world experiments” (Van Den Bergh et al., 2011).

Geels (2002, 2011) presents the MLP framework describing technology transition to sustainability that combines technology trajectories, technology regimes, and new combinations that result in paths and trajectories. Technological transitions are processes occurring over long time periods in socio-technical systems involving technologies, actors or user practices, regulation, industrial networks, infrastructure, and symbolic meaning or culture. The MLP illustrates the transition through three analytical levels: niches, regimes, and landscape. The existing socio-technical system refers to the regime level characterised by dominant rules, institutions, and technologies. Innovations and pilots emerge at the niche (micro) level, trying to enter the regime level. The landscape-level stimulates and puts pressure on the regime and niche levels covering environmental and demographic trends, political ideologies or macro-politics, societal values or cultural patterns, and macroeconomic patterns. The changes in the landscape happen because of exogenous factors, such as wars, economic crises, natural disasters, and political upheaval. The regime and niche levels are influenced by the landscape (macro) level. The policy is needed to destabilise the established regimes to promote radical niches towards the regime (Kern, 2012).

Figure 10 presents the MLP analysis tool that deals with the complexity and resistance in transition. The radical innovations emerge in niches where the eager actors promote technology and social innovations. The innovations, which can diverge from the current regime practices, can be boosted in the niches influenced by the markets and regulation that usually requires landscape developments that would open the “windows of opportunity” at the regime level. (Geels, 2002)

Figure 10. Multi-Level Perspective. Adapted from Geels (2002).

This thesis is interested in the MLP framework (Geels, 2004) and the idea of the multi-regime and multi-system interactions (Papachristos et al., 2013) in studying the socio-technical transition of power systems. Particularly the emergence of niches, niche-regime interactions (Diaz et al., 2013), the window of opportunity

(Berkhout et al., 2010), the acceleration of innovations (Markard et al., 2020), and the development pathways (Berkhout et al., 2010) are of interest.

By reflecting the MLP framework for the power grid’s transition towards Smart Grids, niches can be new concepts like the ADNs or microgrids. The current power system presents the regime level. The SNM extends the MLP by taking the socio-technical regime as a research subject with a particular technology like the Smart Grids. SNM supports the socio-technical experiments where the different stakeholders are encouraged to collaborate and exchange information, knowledge, and experiences. The SNM aims to build a shared understanding behind a product or concept with the stakeholders and actors whose coordinated actions are necessary to shift the related technologies and practices. The goal of the SNM is to achieve an interactive learning process that would facilitate the emergence of new technology. Consequently, new, more sustainable systems, operational practices, and services might emerge based on new experiences and ideas through open socio-technical research and learning processes through the experiments, improving societal embedding and the uptake of new technologies.

Summarising previous information, the movement evolution towards Smart Grids is a socio-technical transition through the technologies and new concepts in the niche level, trying to enter the regime level influenced by the landscape level.

Figure 11 presents an exemplary case where equipment like photovoltaics (PV) and battery energy storage systems (BESS) or concepts like microgrids, virtual power plants (VPPs), or DR are functioning simultaneously in niches. Successful management of the niche experiments is needed to obtain these new systems and concepts in the implementation of the Smart Grids and further to new practices at the regime level. The major contributing factor influencing the landscape level is the environmental trend which puts development pressure on the niche and regime levels. As a result, significant changes occur in the electricity distribution networks because of the interconnection of various DER, and new concepts like different microgrids emerge for active network management.

Figure 11. Niches for the Smart Grids technologies in the MLP.