Teitl: Enhanced Frequency Response From Industrial Heating Loads for Electric Power Systems (Great Britain and Bitumen Tanks as examples)

Dyfyniad
Zhou Y, Cheng M, Wu J (2018). Enhanced Frequency Response From Industrial Heating Loads for Electric Power Systems (Great Britain and Bitumen Tanks as examples). Cardiff University. http://doi.org/10.17035/d.2018.0064005779


Hawliau Mynediad: Gall data fod ar gael yn rhad ac am ddim yn amodol ar briodoli
Dull Mynediad: I anfon cais i gael y data hwn, ebostiwch opendata@caerdydd.ac.uk

Crewyr y Set Ddata o Brifysgol Caerdydd

Manylion y Set Ddata
Cyhoeddwr: Cardiff University
Dyddiad (y flwyddyn) pryd y daeth y data ar gael i'r cyhoedd: 2018
Fformat y data: .xlsx
Meddalwedd ofynnol: Microsoft EXCEL
Amcangyfrif o gyfanswm maint storio'r set ddata: Llai nag 1 gigabeit
Nifer y ffeiliau yn y set ddata: 6
DOI: 10.17035/d.2018.0064005779

Disgrifiad

Increasing penetration of renewable generation results in lower inertia of electric power systems. To maintain the system frequency, system operators have been designing innovative frequency response products. Enhanced Frequency Response (EFR) newly introduced in the UK is an example with higher technical requirements and customized specifications for assets with energy storage capability. We published a paper on IEEE Transactions on Industrial Informatics, proposing a method to estimate the EFR capacity of a population of industrial heating loads, bitumen tanks. A decentralized control scheme was also devised to enable them to deliver EFR. Case study was conducted using real UK frequency data and practical tank parameters. Results showed that bitumen tanks delivered high-quality service when providing service-1-type EFR, but underperformed for service-2-type EFR with much narrower deadband. Bitumen tanks performed well in both high and low frequency scenarios, and had better performance with significantly larger numbers of tanks or in months with higher power system inertia.

The dataset regarding this paper includes 6 EXCEL files in total. The detailed description for them are presented as follows:

1. “Evaluation results and figures _ Case 1.xlsx” provides the numerical results of Case 1 of the paper, showing the performance of bitumen tanks to provide EFR service in the base case settings (the day with the highest frequency in 2016, 16 Nov 2016, used for evaluation). It contains three sheets, providing the data behind Fig. 10, Fig. 11 and Fig. 12 of the paper respectively. In the “Fig. 10” sheet, the “Actual Response” is provided along with “Upper Limits of Delivery Envelope” and “Lower Limits of Delivery Envelopes”. In the “Fig. 11” sheet, the “SPM” (Service Performance Measure) and “AF” (Availability Factor) are provided for the settlement periods over the day. In the “Fig. 12” sheet, the “Actual Ramp Rate” is provided along with “Upper Limits of Ramp Rate” and “Lower Limits of Ramp Rate”.

2. “Evaluation results and figures _ Case 2.xlsx” provides the numerical results of Case 2 of the paper, showing the results of time delay. It contains only one sheet, providing the data behind Fig. 13 of the paper. In the “Fig. 13” sheet, the “Correlation” is provided along with the corresponding “Lag (s)”.

3. “Evaluation results and figures _ Case 3.xlsx” provides the numerical results of Case 3 of the paper, showing the results given different types of EFR service. It contains two sheets, providing the data behind Fig. 14 of the paper. In the “Fig. 14(a)” sheet, the “SPM” (Service Performance Measure) for the settlement periods over the day is provided for both types of EFR. In the “Fig. 14(b)” sheet, the “AF” (Availability Factor) for the settlement periods over the day is provided for both types of EFR.

4. “Evaluation results and figures _ Case 5.xlsx” provides the numerical results of Case 5 of the paper, showing the results with various population sizes of bitumen tanks. It contains two sheets, providing the data behind Fig. 15 of the paper. In the “Fig. 15(a)” sheet, the “Average SPM” (Service Performance Measure) for the settlement periods over the day is provided for various population sizes. In the “Fig. 15(b)” sheet, the “AF” (Availability Factor) for the settlement periods over the day is provided for various population sizes.

5. “Evaluation results and figures _ Case 6.xlsx” provides the numerical results of Case 6 of the paper, showing the month-level evaluation results. It contains five sheets, providing the data behind Fig. 16 through Fig. 20 of the paper. In the “Fig. 16” sheet, the “SPM” (Service Performance Measure) and “AF” (Availability Factor) for the settlement periods over the whole January is provided for service-1-type EFR. In the “Fig. 17” sheet, the “SPM” (Service Performance Measure) and “AF” (Availability Factor) for the settlement periods over the whole January is provided for service-2-type EFR. In the “Fig. 18” sheet, the “SPM” (Service Performance Measure) and “AF” (Availability Factor) for the settlement periods over the whole July is provided for service-1-type EFR. In the “Fig. 19” sheet, the “SPM” (Service Performance Measure) and “AF” (Availability Factor) for the settlement periods over the whole July is provided for service-2-type EFR. In the “Fig. 20” sheet, the “SPM” (Service Performance Measure) and “AF” (Availability Factor) for the settlement periods over the whole July is provided for various population sizes.

6. “Baseline Estimation _ Fig 5.xlsx” provides the numerical data behind Fig. 5 of the paper, which is about the baseline load calculation for the tank population (200 tanks) over one-month basis. It contains only one sheet, in which the “Aggregated Load (MW)” of the tanks is provided for the whole month on a second-by-second basis, and the “Baseline load (MW)” estimated for the month is provided.

Research results based upon these data are published at http://doi.org/10.1109/TII.2018.2879907


Allweddeiriau

Decentralized control, Frequency response, Industrial heating load

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Diweddarwyd y tro diwethaf ar 2019-07-01 am 11:48