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Today, advanced energy storage technologies, particularly electrochemical batteries, represent an increasingly economic option for supporting the integration of renewable energy resources and providing the grid with greater operational flexibility. Crucially though, the large-scale deployment of these assets, and the development of successful business models to support them is heavily reliant on policy, regulation and market design. In this paper, we present a comprehensive review of the array of federal, ISO/RTO and state-level rules and regulations shaping today's energy storage deployment across the United States. We highlight the fragmented and heterogeneous nature of existing market participation models available for advanced energy storage across restructured power markets and emphasize the need for design changes to power markets at all timescales to allow for the more efficient integration of energy storage. We also reflect on how well FERC's recent Order 841 does in terms of providing a framework for the establishment of more fit-for-purpose market participation models for storage, something that will be key for today's evolving power sector as it becomes more dependent on intermittent renewable resources.

There are a large number of accounts about rapidly declining costs of batteries with potentially transformative effects, but these accounts often are not based on detailed design and technical information. Using a method ideally suited for that purpose, we find that when experts are free to assume any battery pack design, a majority of the cost estimates are consistent with the ranges reported in the literature, although the range is notably large. However, we also find that 55% of relevant experts’ component-level cost projections are inconsistent with their total pack-level projections, and 55% of relevant experts’ elicited cost projections are inconsistent with the cost projections generated by putting their design- and process-level assumptions into our process-based cost model (PBCM). These results suggest a need for better understanding of the technical assumptions driving popular consensus regarding future costs. Approaches focusing on technological details first, followed by non-aggregated and systemic cost estimates while keeping the experts aware of any discrepancies, should they arise, may result in more accurate forecasts.

We develop three novel enhanced mixed integer-linear representations of the power limit of the battery and its efficiency as a function of the charge and discharge power and the state of charge of the battery, which can be directly implemented in large-scale power systems models and solved with commercial optimization solvers. Using these battery representations, we conduct a techno-economic analysis of the performance of a 10 MWh lithium-ion battery system testing the effect of a 5-min vs. a 60-min price signal on profits using real time prices from a selected node in the MISO electricity market. Results show that models of lithium-ion batteries where the power limits and efficiency are held constant overestimate profits by 10% compared to those obtained from an enhanced representation that more closely matches the real behavior of the battery. When the battery system is exposed to a 5-min price signal, the energy arbitrage profitability improves by 60% compared to that from hourly price exposure. These results indicate that a more accurate representation of li-ion batteries as well as the market rules that govern the frequency of electricity prices can play a major role on the estimation of the value of battery technologies for power grid applications.

We investigate six different lithium-ion battery modeling approaches to highlight the importance of accurately representing batteries in decision tools. Advanced mixed-integer-linear battery models account for efficiencies as a function of the discharge power, power-limits as a function of the state-of-charge, along with degradation, which are usually not accounted for in power systems models. The revenue potential from offshore wind paired with battery systems is then examined using the more advanced representation where degradation is the sum of the capacity fades resulting from calendar- and cycle-aging. The impacts of variability of offshore wind output along with energy- and capacity-market prices are evaluated using publicly available data from 2010 to 2013 using NYISO as a test case. For 2013, results highlight that without accurate battery representations, models can overestimate battery revenues by up to 35%, resulting primarily from degradation-tied costs. Advanced dispatch algorithms that account for calendar- and cycle-aging of the battery can help operate the battery more efficiently. Locating the battery onshore yields higher revenues and with wider useable SOC windows, it is possible to monetize higher arbitrage opportunities, which can compensate for any additional degradation-tied costs. The added value of a MWh of energy storage varies from $2 to $4.5 per MWh of wind energy, which leads to a breakeven cost range of $50–115 per kWh for the battery systems. As such, energy- and capacity-market revenues were found to be insufficient in recovering the investment costs of current battery systems for the applications considered in this analysis.