Keywords

Electrical energy storage; wind energy; carbon intensity; net energy analysis

18.1 The Need for Storage

The world needs affordable, accessible, sustainable, and low-carbon energy resources [1–3]. Of the renewable resources, solar PV and wind turbines have the highest technical potential to satisfy this need, but these technologies generate electricity from variable, weather-dependent resources [3–7]. Fig. 18.1 provides a compelling visualization of 30 days of superimposed power demand time series data (red) wind energy generation data (blue) and solar insolation data (yellow). Supply correlates poorly with demand. The amount of storage needed for operation of electrical grids incorporating increasing amounts of variable wind resources is a critical yet complicated question. It is complicated for two reasons: (1) the electrical grid, composed of myriad power sources and sinks is conducted as a whole in real-time, and (2) the number of technologies and practices, their varied and evolving characteristics, and their possible implementations under differing and shifting policy landscapes presents a grossly under-determined problem with several solutions.

Technologies and practices positioned to ensure grid-reliability include flexible conventional generation (natural gas combustion turbines and diesel generation sets), flexible renewable generation (curtailment, hydropower, concentrated solar power (CSP) with thermal storage), flexible load (demand-side management), energy storage, and resource sharing (diversity and trans- mission). In the future, when greenhouse gas emissions are constrained, flexible generation will need to be achieved using low-carbon energy supplies.

Studies have made efforts to determine the amount of renewable generation an electrical grid can support by bundling these technologies and practices into an abstract resource: grid flexibility, defined as the percentage of generation and load capable of being readily dispatched or halted [5]. Less flexible grids harbor high percentages of so-called baseload generating plants such as nuclear, coal, and natural gas combined cycle plants. The amount of energy storage capacity required will depend firstly on grid flexibility. It will depend secondly on attributes of the renewable generation. The amount, type, mix, and degree of supply correlation affects how well supply satisfies demand. Today storage on power grids is dominated by pumped hydroelectric storage (PHS). Table 18.1 lists worldwide storage capacity by power and energy. This chapter describes the effect storage has on the energy and carbon intensity of wind generated electricity. First, key storage characteristics are listed. Second, energy return ratio results are presented, and third, carbon intensity calculations and results are presented.

18.2 Key Characteristics for Storage

Energy storage incurs energetic costs and emits carbon to the atmosphere. Direct emissions of carbon are those associated with the round-trip efficiency and operation of the storage device. Indirect emissions are those resulting from the process of mining the materials and manufacturing the storage and flexible generation technologies. The energetic and carbon intensity values for energy storage technologies were obtained from LCA and NEA studies [14–17]. Key characteristics for grid-scale storage are safety, affordability, reliability, longevity, and efficiency. Technologies that satisfy these criteria, in this analysis, include four electrochemical storage technologies: lithium-ion (LiB), sodium sulfur (NaS), traditional lead acid (PbA), vanadium redox flow batteries (VRB); two geological storage technologies; pumped hydroelectric storage (PHS); and compressed air energy storage (CAES).

Key net energy and carbon data are listed in Table 18.2. The energy intensity per unit energy storage capacity, ε_s (kWh_e/kWh_e), depends on the technology’s depth of discharge (D), its total number of charge–discharge cycles (λ), and its cradle-to-gate embodied electrical energy requirement per unit capacity of energy delivered to storage (CTG_e).

Embodied energy accounts for energy expended in mining raw resources, manufacturing the device and delivering the device to point of use. The per cycle carbon intensity (g CO₂eq kW h⁻¹) for storage technologies were calculated by adding capital (GHG_s,cap) and operational greenhouse gas (GHG_s,op) emissions per unit of electrical energy delivered per cycle.

A critical attribute of an energy storage technology is its round-trip efficiency, η. The carbon intensity of the discharged electricity is ≥1/η times the carbon intensity of the input electricity. Using storage increases the carbon intensity of delivered electricity by a factor, χ, as listed in Table 18.2. χ is a carbon intensity multiplier. If storage is 90% efficient, the carbon intensity of the delivered electricity increases by 11%, χ=1.11. Manufacturing storage also incurs its own energetic and carbon costs.

Despite higher energy and carbon intensities when compared to PHS, electrochemical storage technologies present one clear advantage: energy density. Batteries are able to store several hundred times the amount of energy per unit mass and volume than PHS (Fig. 18.2). Additionally, batteries do not require geological features, i.e., steep topography, that PHS requires and therefore can be deployed anywhere including city centers, residences, and commercial buildings (Fig. 18.3).

18.3 Net Energy Analysis of Storing and Curtailing Wind Resources

Curtailing renewable resources results is an immediate and obvious forfeiture of energy. However, flexible grid technologies can also consume significant amounts of energy in their manufacture and operation. These embodied energy costs are not as immediately apparent, but they are an energy sink from a societal perspective.

In this section, I compare the energetic costs of electrical energy storage (EES) to the energetic costs of curtailment. In lieu of storage or other means of grid flexibility, variable resources are curtailed during periods of oversupply or of strong market disincentives [19,20]. Consequently electricity is squandered, capacity factors are reduced, and revenue for turbine owners in certain markets is lost. In Texas, e.g., 1.2%–17.1% of potential wind generation was curtailed on an annual basis between 2007 and 2012, equaling a total of 13 TW h of electrical energy [21]. Worldwide, curtailment rates are projected to increase as wind and solar comprise a larger fraction of the generation mix [5,21]. We ask whether or not storage provides societal net energy gains over curtailment. EES has significant value not quantified or analyzed in this study, including electricity market economics [22], insuring reliable power supplies to critical infrastructure [23], ancillary benefits to power grid operation [8], and application in disaster relief and war zone scenarios.

The results shown here were originally presented in Ref. [24], which presents a theoretical framework for quantifying how storage affects net energy ratios. This framework accommodates any type of generation or storage technology. Using Life Cycle Assessment (LCA) data for generation and storage technologies, we calculate which storage and generation technologies result in a net energy gain over curtailment. We present our data and results in terms of EROI: the amount of electrical energy returned per unit of electrical energy invested. A complete derivation of the methods and detailed results can be found in Ref. [24]. Fig. 18.4 shows calculated grid EROI values, EROI_grid, for PV (top) and wind resources (bottom) used with storage technologies (colored lines) as a function of φ. The solid black line bisecting the plots indicates the EROI value due to curtailment, spanning a range from original resource EROI to zero. The green region to the right of this line indicates combinations of EROI, ESOIe, and φ in which storage yields better energy returns than curtailment, EROI_grid>EROI_curt. To the left, in blue, EROI_grid<EROI_curt, storage implementation is more energetically costly than simply curtailing the resource. Several interesting results emerge from Fig. 18.4. First, storage technologies with low ESOIe values, like PbA and ZnBr, reduce the grid EROI down much more severely than technologies with high ESOIe values, like PHS, CAES, and Li-Ion. Second, battery technologies paired with wind yield grid EROI values far below EROI values from curtailment alone for reasonable values of φ. However, these grid EROI values are greater than the average US power grid values ~20. Ideally storage technologies that support generation resources should not diminish energy return ratios below curtailment energy return ratios for reasonable values of φ. This means that geologic storage technologies, not contemporary battery technologies, are much more favorable for storing electricity generated from wind power.

Curtailment of wind resources during times of excess generation is a viable form of grid flexibility. Curtailment rates of up to 30% yield carbon and energy intensities that are lower than respective pairings with electrochemical storage technologies. While curtailment appears to be an immediate waste of a resource, the life-cycle energy costs of storage are greater than curtailment at reasonable rates below about 30%. Avoiding curtailment may not lead to the most environmentally sound decisions. Curtailment is not the only option, nor is it ideal. Useful applications for excess electricity occur beyond the power grid. Excess electricity could be used for thermal storage, producing heat or ice for later use. Additionally, electricity could be used to pump or desalinate water, smelt metal ores, or manufacture goods. The energy is “stored,” i.e., embodied elsewhere in the economy.

18.4 The Carbon Footprint of Storing Wind Energy

Energy storage emits carbon to the atmosphere. Direct emissions of carbon are those associated with the round-trip efficiency and operation of the storage device. Indirect emissions are those resulting from the process of mining the materials and manufacturing the storage and flexible generation technologies. The carbon intensity values for energy storage technologies were obtained from LCA and NEA studies [14–17]. Carbon intensity values for the average US power grid emissions and subgrid emissions were obtained from Ref. [25] (Table 18.3).

The per cycle carbon intensity (g CO₂eq kW h⁻¹) for storage technologies were calculated by adding capital and operational greenhouse gas (GHG) emissions.

${\mathrm{GHG}}_s={\mathrm{GHG}}_{s,cap}/(\lambda D)+{\mathrm{GHG}}_{(1s,op)}$ (18.1)

(18.1)

The storage technology’s depth of discharge, D, modulates per cycle capital (GHG_s,cap) emissions from storage meaning that a shallow depth of discharge requires larger batteries (with associated manufacturing costs) to provide equivalent storage capacities. Values used in these calculations can be found in Table 18.2.

The life-cycle carbon intensity of electricity delivered to the power grid from generation resources via energy storage technologies was calculated by summing per cycle storage carbon intensities with lifecycle generation carbon intensities.

${\mathrm{GHG}}_g={\mathrm{GHG}}_s+{\mathrm{GHG}}_r/\eta$ (18.2)

(18.2)

Fig. 18.5 shows carbon intensity values in terms of kg CO_2eq per electrical energy delivered to the power grid from various wind storage technology pathways. For reference, the average carbon intensity values for the US power grid (518 kg MW h⁻¹ is shown. Additionally, carbon intensity values direct wind and grid–storage pairings are shown. All wind storage pairings emit less carbon than the US power grid average. The best performing storage technologies are PHS, VRB, and Li-Ion. The worst performing technologies are PbA and CAES, which emits carbon via natural gas combustion upon discharge.

18.5 Conclusions

Energy storage promises many benefits for electrical power grids and societal energy use in general. Our analysis shows how to calculate and compare their energy and carbon footprints. In conclusion the analyses presented in this chapter reveal the following insights:

Energy storage and curtailment can provide the flexibility the power grid will require as the fraction of intermittent wind resource supply increases. This chapter shows the benefits of using systems-level energy intensity and carbon intensity analysis to compare performance of flexible options for wind [29]. Policy makers and consumers that consider the effects of deploying storage with wind can better identify environmentally sound solutions.