John P. Barton

Energy storage and its use with intermittent renewable energy

A simple probabilistic method has been developed to predict the ability of energy storage to increase the penetration of intermittent embedded renewable generation (ERG) on weak electricity grids and to enhance the value of the electricity generated by time-shifting delivery to the network. This paper focuses on the connection of wind generators at locations where the level of ERG would be limited by the voltage rise. Short-term storage, covering less than 1 h, offers only a small increase in the amount of electricity that can be absorbed by the network. Storage over periods of up to one day delivers greater energy benefits, but is significantly more expensive. Different feasible electricity storage technologies are compared for their operational suitability over different time scales. The value of storage in relation to power rating and energy capacity has been investigated so as to facilitate appropriate sizing.

Modelling of the Performance of a Building-Mounted Ducted Wind Turbine

This paper presents computational fluid dynamics (CFD) modelling of the performance of a building-mounted ducted wind turbine. A resistive volume within the duct is used to represent a cross-flow turbine and different diffuser geometries have been investigated. A comparison is made between the power performance ratio of such a building-mounted ducted wind turbine rotor predicted by CFD calculations and those predicted on the basis of one-dimensional (1D) theory. Good agreement is seen between the two approaches for a freestanding duct but deviations are seen for the building-mounted case for the calculated power performance ratio apparently due to asymmetry in the flow profile entering the duct and the flow geometry around the combination of building and duct.

Energy storage and its use with wind power

A simple probabilistic method has been developed to predict the ability of energy storage to accommodate the intermittency of wind-powered generation. This method can estimate the fraction of time the store is empty or full, the amount of wind energy that must curtailed and the amount of electrical demand left unsatisfied by wind power alone. The method can be applied to stand-alone systems or to weak electricity grids where the level of wind powered generation would be limited by network constraints. A wide range of time scales from seconds to months can be accommodated. The method is briefly outlined, and illustrated by example.

Short-run impact of electricity storage on CO2 emissions in power systems with high penetrations of wind power: A case-study of Ireland:

This article studies the impact on CO2 emissions of electrical storage systems in power systems with high penetrations of wind generation. Using the Irish All-Island power system as a case-study, data on the observed dispatch of each large generator for the years 2008 to 2012 was used to estimate a marginal emissions factor of 0.547 kgCO2/kWh. Selected storage operation scenarios were used to estimate storage emissions factors – the carbon emissions impact associated with each unit of storage energy used. The results show that carbon emissions increase in the short-run for all storage technologies when consistently operated in ‘peak shaving and trough filling’ modes, and indicate that this should also be true for the GB and US power systems. Carbon emissions increase when storage is operated in ‘wind balancing’ mode, but reduce when storage is operated to reduce wind power curtailment, as in this case wind power operates on the margin. For power systems where wind is curtailed to maintain system stability, the results show that energy storage technologies that provide synthetic inertia achieve considerably greater carbon reductions. The results highlight a tension for policy makers and investors in storage, as scenarios based on the operation of storage for economic gains increase emissions, while those that decrease emissions are unlikely to be economically favourable. While some scenarios indicate storage increases emissions in the short-run, these should be considered alongside long-run assessments, which indicate that energy storage is essential to the secure operation of a fossil fuel-free grid.

Time-step analysis of the DECC 2050 calculator pathways

An hour-by-hour time-step analysis is presented of United Kingdom electricity grid balancing in low-carbon energy pathways from the DECC 2050 Calculator. The detailed modelling uses the future energy scenario assessment (FESA) tool, which uses real weather data and real electricity demand data from year 2001 to model future supply and demand profiles, suitably adjusted to reflect technology uptakes. The paper describes the linking of the DECC 2050 Calculator with FESA and many of the detailed considerations within the modelling. The calculation of net demand (total demand less intermittent renewables and inflexible portions of other electricity generation) reveals the magnitude and duration of peaks and troughs throughout the year and this allows quantification of required peaking plant, energy storage, demand response or a combination of these. The results indicate that the grid balancing challenge is much greater than is apparent from the DECC 2050 Calculator, with significant excess power from renewables and less flexible generators needing to be exported or curtailed, and, at other times of the year, a significant amount of additional conventional generation being required. FESA also indicates significantly lower capacity factors for despatchable generators than indicated in the DECC 2050 Calculator. The results underline the value of energy storage and flexible demand, particularly in the high-renewables pathways, but also that much of that storage and flexibility needs to be available for days or even weeks rather than hours.