ECD-UY, detailed household electricity consumption dataset of Uruguay

The combination of ongoing urban expansion and electrification of uses challenges the power grid. In such a context, information regarding customers’ consumption is vital to assess the expected load at strategic nodes over time, and to guide power system planning strategies. Comprehensive household consumption databases are widely available today thanks to the roll-out of smart meters, while the consumption of tertiary premises is seldom shared mainly due to privacy concerns. To fill this gap, the French main distribution system operator, Enedis, commissioned Mines Paris to derive load profiles of industrial and tertiary sectors for its prospective tools. The ELMAS dataset is an open dataset of 18 electricity load profiles derived from hourly consumption time series collected continuously over one year from a total of 55,730 customers. These customers are divided into 424 fields of activity, and three levels of capacity subscription. A clustering approach is employed to gather activities sharing similar temporal patterns, before averaging the associated time series to ensure anonymity.

Section: Methodsmentioning

confidence: 99%

Section: Background and Summarymentioning

confidence: 99%

ELMAS: a one-year dataset of hourly electrical load profiles from 424 French industrial and tertiary sectors

Bellinguer,

Girard,

Bocquet

et al. 2023

“…High-resolution, wastewater sector-specific national 17 and continental 18 tariff datasets exist for Europe, but we are unaware of comparable datasets elsewhere. Instead, there are several localized (e.g., city or county-level 19 ) electricity and natural gas tariff datasets that focus on specific markets (e.g., residential 20 ) or provide energy charges in terms of average unit cost 21 . We seek to close this gap by providing a central repository of utility-published electricity and natural gas tariffs for the U.S. wastewater sector that explicitly accounts for underlying variability in charges as a function of time, location, and quantity of energy consumed.…”

Section: Background and Summarymentioning

confidence: 99%

Electricity and natural gas tariffs at United States wastewater treatment plants

Chapin,

Bolorinos,

Mauter

2024

Wastewater treatment plants (WWTPs) are large electricity and natural gas consumers with untapped potential to recover carbon-neutral biogas and provide energy services for the grid. Techno-economic analysis of emerging energy recovery and management technologies is critical to understanding their commercial viability, but quantifying their energy cost savings potential is stymied by a lack of well curated, nationally representative electricity and natural gas tariff data. We present a dataset of electricity tariffs for the 100 largest WWTPs in the Clean Watershed Needs Survey (CWNS) and natural gas tariffs for the 54 of 100 WWTPs with on-site cogeneration. We manually collected tariffs from each utility’s website and implemented data checks to ensure their validity. The dataset includes facility metadata, electricity tariffs, and natural gas tariffs (where cogeneration is present). Tariffs are current as of November 2021. We provide code for technical validation along with a sample simulation.

“…Note that data missing is mainly caused by data gaps larger than one day. The completeness criterion states that a complete day has at least 95% of the expected records 24 . Statistical results indicate that more than 99% of the days have more than 91 records, i.e.…”

Section: Technical Validationmentioning

confidence: 99%

EWELD: A Large-Scale Industrial and Commercial Load Dataset in Extreme Weather Events

Liu,

Bai

et al. 2023

Load forecasting is crucial for the economic and secure operation of power systems. Extreme weather events, such as extreme heat and typhoons, can lead to more significant fluctuations in power consumption, making load forecasting more difficult. At present, due to the lack of relevant public data, the research on load forecasting under extreme weather events is still blank, so it is necessary to release a large-scale load dataset containing extreme weather events. The dataset includes electricity consumption data of industrial and commercial users under extreme weather events such as typhoons and extreme heat, which are collected at 15-minute intervals. The data is collected over six years from smart meters installed at the power entry points of users in southern China. The dataset consists of electricity consumption data from 386 industrial and commercial users in 17 industries, with more than 50 million records. During the recording period, extreme weather events such as typhoons and extreme heat are marked to form a total of 5,741 event records.