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.

greenhouse emissions graph
Source: Federal Ministry for the Nature, Environment, Nature Conservation, Building and Nuclear Safety, 2015, 
Facts, Trends and Incentives for German Climate Policy

 

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.

 

figure_7

 

2 Replies to “A Framework for Incorporating EROI into Electrical Storage”

  1. I’ve said for a while now that far more research needs to be conducted into energy and emissions intensity valuation of popular storage technologies (overwhelmingly lithium ion these days). This is an outstanding contribution.
    You briefly mention the potential for vehicle-to-grid storage schemes, and I wondered if you had seen this report regarding the undesirability of this approach featuring no less than the chief technology officer of Tesla?
    https://cleantechnica.com/2016/08/22/vehicle-to-grid-used-ev-batteries-grid-storage/

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    1. actinideage, yes, I saw Shahan’s commentary. I’m also skeptical about some of the claims for V2G, but I’m also conscious that there may be business models that might work. I think the problem with these things is the hype, and we tend to push back against the hype more than the technology. FYI, I discussed EV charging in an earlier paper from 2013 –

      At face value, electric vehicles (EV) would seem to have a natural synergy with baseload, which could provide low cost and predictable year-round off-peak power for charging when most vehicles are parked at home, whilst underpinning the load factor for baseload generators in the event of the electrification of the Australian motor car fleet (see chapter 9 [39]). Similarly, in regions that have excess wind power at night, the capability of effectively using excess power to charge vehicles may improve the value of wind energy (see Lund and Kempton [40]).

      The problem with PV-based V2G is that the available supply will be inversely related to the preferred charging regime (i.e., there will be no PV power available for night time charging when the grid has spare capacity, but during the three or four hours centered on solar noon, few motorists will want to ―fill their tank‖ at the peak daytime tariff). Further, as Trainer [17,41] notes, EV batteries are expensive and their longevity is cycle-limited, so vehicle manufacturers will want to optimise their batteries for maximum driving range at lowest cost in order to produce a marketable vehicle, leaving limited spare capacity available for general grid storage. While V2G will offer a valuable niche role such as network support during critical peak demand events, the sort of integrated role envisaged by Delucchi & Jacobson [10], in which a considerable proportion of system energy is cycled through EV batteries on a daily basis, is probably vastly overstated (see [17] and [42]).

      http://www.mdpi.com/2071-1050/5/4/1406

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