A Framework for Incorporating EROI into Electrical Storage
The fundamental problem with a transition to renewable energy is that modern society has been structured around demand-based power flows. Any quantity of power is available at any time – the only limit is the circuit breaker in your mains connection. But the major scalable and affordable renewable power sources are wind and solar PV, both of which are intermittent. We could add biomass, but the degree to which biomass and biofuels can be scaled is limited and anyway, their use is contested. Until now, intermittency has been manageable because the variability generated by the modest proportion of RE is readily accommodated with the legacy infrastructure. Regions with a high penetration of VRE, including Denmark and South Australia, have access to virtual batteries in the form of interconnectors to larger grids. The question is – how do we deal with intermittency as legacy infrastructure is retired and wind and solar have to take on a greater role?
The solution is of course storage, but what sort of storage, how much, and what are the biophysical limits of storage. EROI is really about exploring the biophysical limits of storage rather than business models and markets. It may be economic to install a Tesla Powerwall based on feed-in and retail tariffs, but tariff-induced economics may not reflect the value of storage at a societal level.
In recent years, there have been important contributions to applying EROI to storage, however, there remains uncertainty as to how to apply these metrics to practical systems to derive useful or predictive information. I propose a methodology that assesses the EROI of the variable renewable energy and storage as a system, relative to the quantity of conventional generation capacity that is displaced.
A justification for focusing on substitution of capacity is the German Energiewende. Between the starting point of the EEG in 2003 and 2014, total installed power generation capacity grew by 51%, although total annual generation was virtually unchanged. The emission intensity for electricity declined from 610 to 559 grams CO2/kWh over the period. Unlike historical energy transitions, such as wood to coal or coal to oil, we simply haven’t seen the substitution of legacy infrastructure and productivity gains.
In a new paper in BioPhysical Economics and Resource Quality I explore these issues, with the aim of introducing a framework for further exploration. The most important outcome is the shape and behaviour of the embodied energy and marginal embodied energy curves. The first units of storage and VRE are the least energetically expensive. Using a simulation for the Texas ERCOT grid, I find that it is 4 to 41 times more energetically expensive to displace a gigawatt of generation capacity at near 100% RE than at low penetration RE. Geographic and technology diversity improve these numbers. Unlike conventional generation, which has access to essentially unlimited ‘stored sunlight‘ or nucleosynthesis in the form of fuels, VRE is handicapped by the energetic demands of surplus VRE and storage.