Systems

Energy systems are not simply technical objects with well-defined components. They are sociotechnical configurations in which physical infrastructure, regulatory frameworks, economic actors, and everyday practices are mutually constituted. Systems thinking draws on traditions from engineering, ecology, and social science, and provides tools for analysing how change in one part of the system propagates, where leverage points exist, and why interventions sometimes produce unintended consequences.¹⁾

A widely used framing in transition research defines socio-technical systems as the linkages between elements necessary to fulfil societal functions.²⁾ Under this view, energy provision is not accomplished by technology alone, but by complex webs of actors, technologies, and institutions that co-evolve and become aligned over extended periods of time.³⁾ From the supply side, this includes generation and distribution infrastructure; from the demand side, it encompasses consumer practices, building stock, and industrial processes. Both are shaped by regulatory norms, market rules, and cultural expectations that become embedded in the system over time.

This co-evolutionary stability has a dual character. On one hand, it enables reliable energy provision at scale. On the other, it creates path dependency and lock-in: existing technologies, regulations, and actor relationships reinforce each other, making radical change difficult even when the need for it is clear.⁴⁾ The multi-level perspective (MLP) — a widely used heuristic in transition studies — conceptualises this through three analytical levels: the landscape (broad macro-level forces), the regime (the dominant rules, practices, and technologies of an established system), and the niche (where radical innovations develop, initially sheltered from full market exposure). Transitions occur when destabilisation at the regime level aligns with niche innovations gaining sufficient momentum.

A layered functional reading of the energy system complements the socio-technical framing. Rather than treating the energy system as a single integrated whole, it distinguishes between a resource layer (fossil fuels, wind, solar, nuclear), a production layer (centralised generation, transformation, and industrial processes), a logistics layer (transmission, distribution, storage, and imports/exports), and an end-use layer (people, industry, transport/mobility, and ICT and other services). Cutting across all of these are supporting capacities — research, innovation, and education — and supporting infrastructures, particularly transport and information and communication technologies. This layered view makes visible how interventions at one layer propagate across others and where systemic dependencies concentrate.

The integration of digital communication and control technologies into energy infrastructure introduces a further analytical lens: the cyber-physical system (CPS). A CPS combines physical processes with embedded computation, networking, and real-time control, allowing systems to monitor, respond to, and influence their own operation. The smart grid has been characterised in this way — as a system of cyber-physical systems that must work together to exchange data and perform predictably.⁵⁾

The U.S. National Institute of Standards and Technology (NIST) has developed a smart grid conceptual model identifying seven functional domains — bulk generation, transmission, distribution, markets, operations, service provider, and customer — and the interfaces among them across which interoperable, secure data exchange must take place.⁶⁾ This architectural framing emphasises that smart grid modernisation is not simply a technology upgrade problem, but a system-of-systems design challenge, requiring coordinated standards, security by design, and new operating relationships between actors across domains.

From a CPS perspective, the distinguishing feature of the smart grid is the addition of two-way communication alongside two-way power flow. Intelligent sensors, automated controls, advanced metering infrastructure, and distributed energy resources all participate in real-time coordination between physical processes and digital systems. This introduces both new operational capabilities — demand flexibility, distributed generation integration, improved outage response — and new vulnerabilities, as expanded connectivity increases the attack surface for cyber threats. Cybersecurity thus becomes a systemic property of the energy infrastructure, not a bolt-on technical concern.

A third framing shifts from the structure of the existing system to the dynamics of its transformation. The technological innovation systems (TIS) approach, developed in the sustainability transitions literature, analyses how new energy technologies emerge, gain traction, and eventually challenge incumbent systems.⁷⁾ A TIS comprises the technologies, actors, and institutions organised around a particular innovation, and its performance can be analysed through seven system functions: knowledge development and diffusion, entrepreneurial experimentation, influence on the direction of search, market formation, legitimation, resource mobilisation, and development of positive externalities.⁸⁾

Where the TIS approach focuses on the emergence of specific innovations, the concept of an innovation ecosystem describes the broader interdependent network of actors — entrepreneurs, technology providers, research organisations, financiers, regulators, and users — whose co-ordinated activity enables commercialisation and scaling. In energy transitions, these two concepts address different questions: the TIS framework asks what systemic conditions are needed for a new technology to develop; the ecosystem framing asks what relational and organisational structures allow an innovation to move from niche to market at scale.

Both framings complement the MLP by attending to the supply side of transitions — the actors and mechanisms that produce the niche innovations that can, under the right conditions, challenge incumbent regimes. For smart grid transitions specifically, research has highlighted how ICT firms entering the electricity sector constitute potential catalysts for sectoral change, bringing new capabilities, business models, and institutional expectations that do not fit comfortably within traditional utility-centred systems.⁹⁾

• Socio-technical system: A configuration of actors, technologies, and institutions co-evolved to fulfil a societal function such as energy provision.
• Regime: The dominant rules, norms, and practices stabilising an established socio-technical system; resistant to radical change.
• Niche: A protected space in which radical innovations develop outside the full competitive and regulatory pressures of the regime.
• Cyber-physical system (CPS): A system integrating physical processes with computation, networking, and real-time control.
• Technological innovation system (TIS): The actors, institutions, and technologies organised around a specific technology, assessed through system functions.
• Lock-in: The self-reinforcing interdependencies between technologies, actors, and institutions that make system change difficult.

The socio-technical framing and the CPS framing address the same physical infrastructure from different starting points: the former asks how social and technical elements have co-evolved and what this means for change; the latter asks how physical and digital elements must be designed to function reliably together. In practice, smart grid transitions require both: the engineering architecture must be designed for interoperability and security, while the institutional and market architecture must also evolve to accommodate new actors, responsibilities, and co-ordination demands.

The TIS and innovation ecosystem concepts similarly address overlapping territory. An innovation ecosystem is in one sense a particular configuration of a technological innovation system at a given moment in a given geography. The distinction carries analytical weight because ecosystem framing tends to emphasise co-ordination, interdependence, and orchestration logic — asking who connects whom and who sets the terms of collaboration — while TIS framing tends to emphasise functional performance — asking what activities the system is or is not carrying out.

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Erlinghagen, S., & Markard, J. (2012). Smart grids and the transformation of the electricity sector: ICT firms as potential catalysts for sectoral change. Energy Policy, 51, 895–906.

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Geels, F. W., Sovacool, B. K., Schwanen, T., & Sorrell, S. (2017). The socio-technical dynamics of low-carbon transitions. Joule, 1(3), 463–479.

Markard, J., Raven, R., & Truffer, B. (2012). Sustainability transitions: An emerging field of research and its prospects. Research Policy, 41(6), 955–967.

Meadows, D. H. (2008). Thinking in systems: A primer. Chelsea Green Publishing.

NARUC (2021). Understanding Cybersecurity for the Smart Grid. National Association of Regulatory Utility Commissioners.

NIST (2021). Framework and Roadmap for Smart Grid Interoperability Standards, Release 4.0. National Institute of Standards and Technology.