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Solar photovoltaic (PV) has the potential to make an important contribution to global sustainability, however, the misalignment between solar production and residential demand presents challenges for widespread PV adoption. Combining PV and storage is one way that this challenge can be overcome. In this work, we use one year of smart meter data from 369 consumers in three different US regions and calculate their economic benefits from both PV and coupled PV-battery systems. We consider a range of different electricity pricing schemes from the consumer regions, including both Feed-In-Tariff (FIT) and Net-Energy-Metering (NEM) policies. Significantly, our work uses real demand data, real PV generation data and optimizes each individual consumer’s battery operation to minimize their electricity bill. Furthermore, we study the effect of batteries on consumer self-sufficiency, which is important because increasing self-sufficiency is a primary motivating factor behind battery adoption. We find that PV is profitable for the majority of consumers with most current pricing scenarios but PV-battery systems are always less profitable. However, batteries can provide very significant increases in self-sufficiency and we find that a majority of consumers can exceed 70% self-sufficiency with a 20 kW h battery and a PV system that produces the equivalent of their consumption. This is compared to an average self-sufficiency of 35% with PV only. Finally, recognizing that a number of factors could lead to profitable batteries in future, we study the sensitivity of battery profitability to future electricity prices in a FIT scenario, also accounting for future decreases in PV and battery costs. We find that if PV-battery systems are to become better investments than PV-only for the majority of consumers, retail electricity prices above $0.40/kW h and FIT rates below $0.05/kW h are a likely requirement. [ABSTRACT FROM AUTHOR]

Energy storage can help integrate local renewable generation, however the best deployment level for storage remains an open question. Using a data-driven approach, this paper simulates 15-min electricity consumption for households and groups them into local communities of neighbors using real locations and the road network in Cambridge, MA. We then simulate PV for these households and use this framework to study battery economics in a high PV adoption, high electricity cost scenario, in order to demonstrate significant storage adoption. We compare the results of storage adoption at the level of individual households to storage adoption on the community level using the aggregated community demands. Under the simulated conditions, we find that the optimum storage at the community level was 65% of that at the level of individual households and each kWh of community battery installed was 64–94% more effective at reducing exports from the community to the wider network. Therefore, given the current increasing rates of residential battery deployment, our research highlights the need for energy policy to develop market mechanisms which facilitate the deployment of community storage. [ABSTRACT FROM AUTHOR]

The global effort to decarbonise electricity systems has led to widespread deployments of variable renewable energy generation technologies, which in turn has boosted research and development interest in bulk Electrical Energy Storage (EES). However despite large increases in research funding, many electricity markets with increasingly large proportions of variable renewable generation have seen little actual bulk EES deployment. While this can be partly attributed to the need for technological developments, it is also due to the challenge of fairly rewarding storage operators for the range of services that storage provides to the wider network, especially in markets that have undergone significant restructuring and liberalisation. Pumped Hydroelectric Energy Storage (PHES) is the overwhelmingly established bulk EES technology (with a global installed capacity around 130 GW) and has been an integral part of many markets since the 1960s. This review provides an historical overview of the development of PHES in several significant electrical markets and compares a number of mechanisms that can reward PHES in different international market frameworks. As well as providing up-to-date information about PHES, a primary motivation for this work is to provide an overview about the types of rewards available to bulk EES for the wider storage community including investors, technology developers and policy-makers. Observing that bulk EES projects seem to be unattractive investments for the private sector, the paper also includes a brief discussion in terms of public sector investment. [ABSTRACT FROM AUTHOR]

The majority of articles on Adiabatic Compressed Air Energy Storage (A-CAES) so far have focussed on the use of indirect-contact heat exchangers and a thermal fluid in which to store the compression heat. While packed beds have been suggested, a detailed analysis of A-CAES with packed beds is lacking in the available literature. This paper presents such an analysis. We develop a numerical model of an A-CAES system with packed beds and validate it against analytical solutions. Our results suggest that an efficiency in excess of 70% should be achievable, which is higher than many of the previous estimates for A-CAES systems using indirect-contact heat exchangers. We carry out an exergy analysis for a single charge–storage–discharge cycle to see where the main losses are likely to transpire and we find that the main losses occur in the compressors and expanders (accounting for nearly 20% of the work input) rather than in the packed beds. The system is then simulated for continuous cycling and it is found that the build-up of leftover heat from previous cycles in the packed beds results in higher steady state temperature profiles of the packed beds. This leads to a small reduction (<0.5%) in efficiency for continuous operation. [ABSTRACT FROM AUTHOR]

This paper explores whether negative electricity prices can change the rationale that efficient energy storage devices are more economical for arbitrage in electricity markets. An established model algorithm to determine the maximum available arbitrage revenue and optimum schedule of electrical energy storage (EES) operation is used to simulate storage with a time-series of electricity prices which includes some negative prices. Our results suggest that at any likely frequency of negative electricity prices, inefficient EES is not encouraged, and can only be encouraged for EES devices with very low energy capacity to power ratios. [ABSTRACT FROM AUTHOR]

The connection of high penetrations of renewable generation such as wind to distribution networks requires new active management techniques. Curtailing distributed generation during periods of network congestion allows for a higher penetration of distributed wind to connect, however, it reduces the potential revenue from these wind turbines. Energy storage can be used to alleviate this and the store can also be used to carry out other tasks such as trading on an electricity spot market, a mode of operation known as arbitrage. The combination of available revenue streams is crucial in the financial viability of energy storage. This study presents a heuristic algorithm for the optimisation of revenue generated by an energy storage unit working with two revenue streams: generation‐curtailment reduction and arbitrage. The algorithm is used to demonstrate the ability of storage to generate revenue and to reduce generation curtailment for two case study networks. Studies carried out include a single wind farm and multiple wind farms connected under a 'last‐in‐first‐out' principle of access. The results clearly show that storage using both operating modes increases revenue over either mode individually. Moreover, energy storage is shown to be effective at reducing curtailment while increasing the utilisation of circuits linking the distribution and transmission networks. Finally, renewable subsidies are considered as a potential third revenue stream. It is interesting to note that under current market agreements such subsidies have the potential to perversely encourage the installation of inefficient storage technologies, because of increased losses facilitating greater "utilisation" of renewable generation. [ABSTRACT FROM AUTHOR]

Energy storage is a key solution to supply renewable electricity on demand and in particular batteries are becoming attractive for consumers who install PV panels. In order to minimize their electricity bill and keep the grid stable, batteries can combine applications. The daily match between PV supply and the electricity load profile is often considered as a determinant for the attractiveness of residential PV-coupled battery systems, however, the previous literature has so far mainly focused on the annual energy balance. In this paper, we analyze the techno-economic impact of adding a battery system to a new PV system that would otherwise be installed on its own, for different residential electricity load profiles in Geneva (Switzerland) and Austin (U.S.) using lithium-ion batteries performing various consumer applications, namely PV self-consumption, demand load-shifting, avoidance of PV curtailment, and demand peak shaving, individually and jointly. We employ clustering of the household's load profile (with 15-minute resolution) for households with low, medium, and high annual electricity consumption in the two locations using a 1:1:1 sizing ratio. Our results show that with this simple sizing rule-of-thumb, the shape of the load profile has a small impact on the net present value of batteries. Overall, our analysis suggests that the effect of the load profile is small and differs across locations, whereas the combination of applications significantly increases profitability while marginally decreasing the share of self-consumption. Moreover, without the combination of applications, batteries are far from being economically viable. [ABSTRACT FROM AUTHOR]

Medium and long-duration energy storage systems are expected to play a critical role in the transition towards electrical grids powered by renewable energy sources. ACAES is a promising solution, capable of handling power and energy ratings over hundreds of MW and MWh, respectively. One challenge with ACAES is achieving the required highly efficient operation in the compressor over the range of conditions encountered in the system as the pressure in the air store changes. In this paper, an application-oriented axial-flow compressor is designed, aiming towards efficient operation throughout the operation range, whilst also associating the performance prediction to a practical compressor geometry. A two-step design methodology based on inviscid, axisymmetric flow conditions has been implemented, leading to the flowtrack, blade-row geometries and the compressor performance map. The compressor model is integrated into an ACAES model, including two compression spools, two expansion stages with preheat, a constant volume high pressure storage operating between 5.5 and 7.7 MPa and two separate Thermal Energy Storage units. While the existing ACAES literature either ignores the transient off-design operation or uses generic numerical correlations (which are not associated to a particular geometry), the key novelty of this paper is the application of a detailed design method for turbomachinery to ACAES. The results indicate that the designed compressor requires 33 stages over the two spools, and is able to operate efficiently over the storage pressure range, showing that if the application-oriented design procedure is applied to the compressor, it does not stop ACAES reaching 70% round-trip efficiency, outputting 35MW for approximately 15 h. Importantly, the specific ACAES requirement of conserving heat at higher temperatures has been fulfilled by decreasing the number of intercoolers. Finally, it is recommended that a similar level of scrutiny is applied to the other components (i.e. expanders, heat exchangers and TES units), keeping in mind the unique set of operational requirements of ACAES. This work is an important step towards removing the common misconception that off-the-shelf components can be easily be used in typical ACAES designs. • ACAES imposes unique conditions on its components, aiming system reversibility. • The compressors must run efficiently and keep the airflow temperature high. • This paper develops an axial-flow compressor geometry and performance map for ACAES. • The compressor is integrated into an ACAES model, operating within 5.5 and 7.7 MPa. • The ACAES system results indicate the system reaches 70% RTE after stabilisation. [ABSTRACT FROM AUTHOR]

• The regional impacts of storage operation on CO 2 emissions are studied. • A new method of determining regional emissions factors was developed. • Emissions factors found using linear regression and a power flow model. • Large differences in emissions across storage operating scenarios and regions. • Differences in Great Britain can be equivalent to fitting coal power with CCS. While energy storage is key to increasing the penetration of variable renewables, the near-term effects of storage on greenhouse gas emissions are uncertain. Several studies have shown that storage operation can increase emissions even if the storage has 100% turnaround efficiency. Furthermore, previous studies have relied on national-level data and given very little attention to the impacts of storage on emissions at local scales. This is an important omission, as carbon intensities can vary very significantly at sub-national scales. We introduce a novel approach to calculating regional marginal emissions factors, based on a validated power system model and regression analysis. The techniques are used to investigate the impacts of storage operation on CO 2 emissions in Great Britain in 2019, under a range of operating scenarios. It is found that there are significant regional differences in storage emissions factors, with storage tending to increase emissions when used for wind balancing in areas with little wind curtailment. In contrast, the greatest emissions reductions are achieved when charging storage with otherwise-curtailed renewables and discharging to reduce peak demands in areas consuming high volumes of fossil fuel power. Over all regions and operating modes studied, the difference between the highest reduction in emissions and the highest increase in emissions is considerable, at 741 gCO 2 per kWh discharged. We conclude that power system regulators should pay increased attention to the impact of storage operation on system CO 2 emissions. [ABSTRACT FROM AUTHOR]