Dataset to accompany paper: "Can battery deployment avoid network reinforcement in an unbundled electricity system? A Great Britain case study"
Description
This dataset accompanies manuscript entitled "Can battery deployment avoid network reinforcement in an unbundled electricity system? A Great Britain case study". The research is in the context of a recognised need for flexible resources on Great Britain (GB)'s electricity system, as greater penetrations of less flexible or inflexible generation are deployed to aid system decarbonisation. The work explores research questions: "Will deployment of battery energy storage, engaged in wholesale trading, reduce peak flows across Great Britain’s electrical networks, and thus reduce or defer the need for network reinforcement? Or, conversely, might deployment of batteries add to maximum network flows and reinforcement needs?" The data are arranged in folders which follow the structure of the manuscript. All folders and subfolders contain "read_me" text files with more information about data themselves, their sources and their interpretation. All data were sourced from open sources or were created as part of the research. Folder 1 has data for auction prices of frequency regulation and response services procured by the Electricity System Operator during 2022, which show a decline in prices in the later part of the year. In these circumstances, alternative activities were becoming more attractive for battery owners. Folder 2 contains timeseries data for wholesale trading and Balancing Mechanism activity during 2022 of around 20 commercial batteries active in GB's Balancing Mechanism. These datasets illustrate increasing interest in wholesale trading during the year. Folder 3 contains data relating to a battery simulation model created for this research, and its outputs. The model simulates a battery agent, engaged in wholesale trades (i.e. arbitrage), and intent on accruing maximum overall net revenues. It contains the day-ahead spot market price data used in this work (during selected periods during 2022), model outputs for the most lucrative battery simulations, including timeseries of simulated charging and discharging activity. These timeseries are later used together with other data to assess the effect of battery activity on distribution and transmission network congestion. Folder 4 has data for the distribution network case study. It contains data relating to the topology and thermal limits of the networks studied, timeseries of demands and distributed wind generator outputs, used to calculate aggregated flows on 33kV networks, and then the effect of simulated battery activity on these flows. Folder 5 accompanies the transmission network study. It contains timeseries data of wind generation availability and curtailment, in Scotland, which are viewed together with simulated battery activity to determine batteries' likely effect on transmission congestion. Folder 6 contains timeseries of GB system demand, and of embedded solar and wind generation from the ESO, which the manuscript's Discussion section refers to.
Files
Institutions
- University of Strathclyde
Categories
Funders
- Northern Powergrid plc