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

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.

随着可再生能源发电渗透率持续提升，电力系统的转动惯量不断降低。为维持系统频率稳定，电网调度机构一直在研发创新性的频率响应产品。英国新近推出的增强型频率响应（Enhanced Frequency Response, EFR）便是典型代表，其针对具备储能能力的资产设定了更高的技术要求与定制化规范。本团队曾在《IEEE Transactions on Industrial Informatics》发表学术论文，提出了针对工业加热负载——沥青储罐——群体的EFR容量估算方法，并设计了去中心化控制方案以使其具备提供EFR服务的能力。研究采用英国实际频率数据与实际储罐参数开展案例验证，结果表明：沥青储罐在提供Type 1型EFR服务时可输出高质量响应，但在针对死区更窄的Type 2型EFR服务时表现欠佳。沥青储罐在高、低频率场景下均表现优异，且随着储罐总规模显著提升，或是在电力系统转动惯量更高的月份，其性能会进一步优化。

本论文配套数据集共计包含6个Excel文件，各文件详细说明如下：
1. "Evaluation results and figures _ Case 1.xlsx"：收录本文案例1的数值计算结果，展示基准工况下（采用2016年11月16日——该日为2016年频率最高日——作为评估基准）沥青储罐提供EFR服务的性能表现。该文件包含3个工作表，分别对应论文中图10、图11与图12的原始数据。其中"Fig. 10"工作表包含"实际响应"、"输送包络上限"与"输送包络下限"数据；"Fig. 11"工作表包含当日各结算时段的"服务性能指标（Service Performance Measure, SPM）"与"可用系数（Availability Factor, AF）"数据；"Fig. 12"工作表包含"实际爬坡速率"、"爬坡速率上限"与"爬坡速率下限"数据。
2. "Evaluation results and figures _ Case 2.xlsx"：收录本文案例2的数值计算结果，展示时延相关分析结果。该文件仅含1个工作表，对应论文中图13的原始数据。"Fig. 13"工作表包含"相关性"与对应的"时延（s）"数据。
3. "Evaluation results and figures _ Case 3.xlsx"：收录本文案例3的数值计算结果，展示不同类型EFR服务下的分析结果。该文件包含2个工作表，对应论文中图14的原始数据。其中"Fig. 14(a)"工作表包含当日各结算时段下两类EFR服务的"服务性能指标（SPM）"数据；"Fig. 14(b)"工作表包含当日各结算时段下两类EFR服务的"可用系数（AF）"数据。
4. "Evaluation results and figures _ Case 5.xlsx"：收录本文案例5的数值计算结果，展示不同沥青储罐群体规模下的分析结果。该文件包含2个工作表，对应论文中图15的原始数据。其中"Fig. 15(a)"工作表包含当日各结算时段下不同群体规模对应的"平均服务性能指标（Average SPM）"数据；"Fig. 15(b)"工作表包含当日各结算时段下不同群体规模对应的"可用系数（AF）"数据。
5. "Evaluation results and figures _ Case 6.xlsx"：收录本文案例6的数值计算结果，展示月度级别评估结果。该文件包含5个工作表，对应论文中图16至图20的原始数据。其中"Fig. 16"工作表包含Type 1型EFR服务在整个1月的各结算时段的"SPM"与"AF"数据；"Fig. 17"工作表包含Type 2型EFR服务在整个1月的各结算时段的"SPM"与"AF"数据；"Fig. 18"工作表包含Type 1型EFR服务在整个7月的各结算时段的"SPM"与"AF"数据；"Fig. 19"工作表包含Type 2型EFR服务在整个7月的各结算时段的"SPM"与"AF"数据；"Fig. 20"工作表包含不同群体规模下Type 1型EFR服务在整个7月的各结算时段的"SPM"与"AF"数据。
6. "Baseline Estimation _ Fig 5.xlsx"：收录论文中图5对应的原始数值数据，该内容围绕200台沥青储罐群体的月度基线负荷计算展开。该文件仅含1个工作表，其中按秒级粒度提供了全月储罐的"聚合负荷（MW）"数据，以及该月估算得到的"基线负荷（MW）"数据。