As the IEA Warns AI Could Double Data Center Power Demand by 2030, a New Volume Asks What the Energy Transition Can Actually Deliver
The International Energy Agency has been blunt about where grid planning is heading: in its recent analysis of AI and electricity demand, the IEA projects that power consumption from data centers could double by 2030, driven overwhelmingly by AI training and inference workloads layering onto grids that are simultaneously trying to absorb record volumes of wind and solar. Utilities, regulators and climate modellers are now asking the same question from different angles — not just whether there is enough generating capacity on paper, but whether the energy actually invested in building that capacity pays society back fast enough to matter.
That is precisely the gap Net Energy Analysis: The State of the Art, edited by Louis Delannoy and David J. Murphy (Routledge, 2026), is built to close. Net energy analysis, and its central metric, energy return on investment (EROI), measures how much usable energy remains after subtracting everything spent extracting, building, and maintaining the energy system itself. The volume consolidates decades of fragmented EROI methodology — process-based, input-output, and extended exergy approaches — into a single reference, then pushes into genuinely new territory: what net energy metrics can and cannot tell financial analysts pricing energy infrastructure, how EROI feeds into the integrated assessment models climate policymakers rely on, and how the same accounting logic applies to agriculture and societal-level energy use.
Three applications stand out for working researchers. First, climate and integrated-assessment modellers get a dedicated treatment of how net energy constraints should (and currently do not) factor into transition scenarios. Second, energy economists and financial analysts get a direct, two-chapter answer to where EROI is useful for investment decisions and where it is not — a distinction too often blurred in policy debate. Third, planners evaluating a fast, electrification-heavy transition against AI-driven demand growth get a framework for asking whether new capacity is being added fast enough, net of its own energy cost, to keep pace.
For academic and government research libraries building out energy policy, energy economics, or climate modelling collections, this is the first single volume to bring the EROI literature current with 2026's demand picture — a natural companion to existing energy transition and climate policy holdings, and a frequently-cited reference point for graduate research in ecological economics and energy systems.
CLNZ Books ships Net Energy Analysis: The State of the Art worldwide to libraries, research institutes and individual professionals, with secure payment by credit card or PayPal and tracked international courier delivery on every order.
Q&A
What is net energy analysis and why does it matter for the AI power boom?
It measures how much usable energy remains after subtracting the energy spent building and running the energy system itself — the key test of whether capacity can be added fast enough, net of its own cost, to meet AI-driven demand growth.
How is EROI different from the price of electricity?
Price reflects markets and subsidies; EROI measures the physical energy return on the energy invested, giving a more stable long-term signal for comparing fuels and technologies.
Does the book address climate policy modelling directly?
Yes — a dedicated section covers how net energy metrics feed into the integrated assessment models used by climate policymakers.
Is it useful for financial analysts, not just engineers?
Yes — two chapters address specifically what EROI can and cannot tell financial analysts and economists evaluating energy infrastructure.
Where can I buy Net Energy Analysis: The State of the Art?
Directly from CLNZ Books, with worldwide shipping and secure payment by credit card or PayPal.