The Utility Energy Registry (UER) is a database platform that provides streamlined public access to aggregated community-scale utility-reported energy data. The UER is intended to promote and facilitate community-based energy planning and energy use awareness and engagement. On April 19, 2018, the New York State Public Service Commission (PSC) issued the Order Adopting the Utility Energy Registry under regulatory CASE 17-M-0315. The order requires utilities under its regulation to develop and report community energy use data to the UER.

This dataset includes electricity and natural gas usage data reported at the ZIP Code level collected under a data protocol in effect between 2016 and 2021. Other UER datasets include energy use data reported at the city, town, village, and county level. Data collected after 2021 were collected according to a modified protocol. Those data may be found at https://data.ny.gov/Energy-Environment/Utility-Energy-Registry-Monthly-ZIP-Code-Energy-Us/g2x3-izm4.

Data in the UER can be used for several important purposes such as planning community energy programs, developing community greenhouse gas emissions inventories, and relating how certain energy projects and policies may affect a particular community. It is important to note that the data are subject to privacy screening and fields that fail the privacy screen are withheld.

The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and accelerate economic growth. reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit nyserda.ny.gov or follow us on X, Facebook, YouTube, or Instagram.

The Utility Energy Registry (UER) is a database platform that provides streamlined public access to aggregated community-scale energy data. The UER is intended to promote and facilitate community-based energy planning and energy use awareness and engagement. On April 19, 2018, the New York State Public Service Commission (PSC) issued the Order Adopting the Utility Energy Registry under regulatory CASE 17-M-0315. The order requires utilities and CCA administrators under its regulation to develop and report community energy use data to the UER. This dataset includes electricity and natural gas usage data reported at the ZIP Code level. Other UER datasets include energy use data reported at the city, town, village, and county level. Data in the UER can be used for several important purposes such as planning community energy programs, developing community greenhouse gas emissions inventories, and relating how certain energy projects and policies may affect a particular community. It is important to note that the data are subject to privacy screening and fields that fail the privacy screen are withheld. The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit nyserda.ny.gov or follow us on X, Facebook, YouTube, or Instagram.

PLEASE DOWNLOAD THE FULL REPORT UNDER THE ATTACHMENT SECTION IN THE 'ABOUT THIS DATASET' SECTION BELOW. This aggregated and anonymized dataset of single-family residential building asset attributes and observed average annual energy consumption over the 2-year period from August 2017 through July 2019 is available for Monroe County. The dataset includes more than 55,000 properties from the study’s matched residential dataset that had sufficient data for calculation of average annual energy consumption and could not be uniquely identified in the larger dataset of Monroe County residential parcels or Infogroup data. The data were anonymized by removing all property identifying information including address, parcel identifiers, and parcel size. Attributes such as square footage, building age, and assessed value were then grouped such that no groupings contained fewer than three properties in the Monroe County parcel dataset. This dataset with average annual energy consumption for gas, electric, and total consumption can be used by those interested in further analysis and energy modeling. In response to the New York State Department of Public Service (DPS) Order Adopting Accelerated Energy Efficiency targets, issued December, 18, 2018, the New York State Energy Research and Development Authority (NYSERDA) contracted with Stone Environmental, Inc to conduct an Asset Data Matching Pilot in Monroe County to analyze building asset data, utility usage data, and NYSERDA program data for single family residential buildings. The objective of the study was to analyze publicly available data along with two years of utility usage data provided by Rochester Gas and Electric (RG&E) to provide information and data to the market to help reduce customer acquisition costs for adoption of energy efficiency measures and to better understand the ability to use building asset data to determine energy efficiency. See the final report from the analysis under the attachments section. NYSERDA offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and accelerate economic growth. reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit nyserda.ny.gov or follow us on X, Facebook, YouTube, or Instagram.

The New York State Energy Research and Development Authority (NYSERDA) hosts a web-based Distributed Energy Resources (DER) integrated data system at https://der.nyserda.ny.gov/. This site provides information on DERs that are funded by and report performance data to NYSERDA. Information is incorporated on more diverse DER technology as it becomes available. Distributed energy resources (DER) are technologies that generate or manage the demand of electricity at different points of the grid, such as at homes and businesses, instead of exclusively at power plants, and includes Combined Heat and Power (CHP) Systems, Anaerobic Digester Gas (ADG)-to-Electricity Systems, Fuel Cell Systems, Energy Storage Systems, and Large Photovoltaic (PV) Solar Electric Systems (larger than 50 kW). Historical databases with hourly readings for each system are updated each night to include data from the previous day. The web interface allows users to view, plot, analyze, and download performance data from one or several different DER sites. Energy storage systems include all operational systems in New York including projects not funded by NYSERDA. Only NYSERDA-funded energy storage systems will have performance data available. The database is intended to provide detailed, accurate performance data that can be used by potential users, developers, and other stakeholders to understand the real-world performance of these technologies. For NYSERDA’s performance-based programs, these data provide the basis for incentive payments to these sites.

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit https://nyserda.ny.gov or follow us on Twitter, Facebook, YouTube, or Instagram.

Overview: Global results from gridfinder model, produced by ESMAP based on joint work with Facebook and others. Uses night-time lights, road networks and existing grid network data to predict the location of transmission and distribution lines globally. Validated in several countries with ~70% accuracy at 1 km. More information: Blog with brief overview: https://blogs.worldbank.org/energy/using-night-lights-map-electrical-gri... Full research paper: https://www.nature.com/articles/s41597-019-0347-4 Visualization: https://gridfinder.org/ The following data are included: grid.gpkg: Vectorized predicted distribution and transmission line network, with existing OpenStreetMap lines tagged in the 'source' column targets.tif: Binary aster showing locations predicted to be connected to distribution grid. lv.tif: Raster of predicted low-voltage infrastructure in kilometres per cell.

Analysis of ‘Statewide Commercial Baseline Study of New York Means of Energy Using Equipment: 2019’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/2333ea0d-9c8d-4da6-98d7-1109197f552d on 12 February 2022.

--- Dataset description provided by original source is as follows ---

The overall objective of the Statewide Commercial Baseline research was to understand the existing commercial building stock in New York State and associated energy use, including the means of energy using equipment. This dataset provides all characteristics that are presented as averages, such as the average square footage of businesses or the average cooling capacity of split systems. All supporting summary statistics are also provided. For more information, see the Final Report at https://www.nyserda.ny.gov/About/Publications/Building-Stock-and-Potential-Studies/Commercial-Statewide-Baseline-Study

NYSERDA offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and accelerate economic growth. reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit nyserda.ny.gov or follow us on Twitter, Facebook, YouTube, or Instagram.

--- Original source retains full ownership of the source dataset ---

The Residential Building Stock Assessment (RBSA) published in 2019 is the first update to the 2015 Residential Statewide Baseline Study (RSBS) of New York State. This New York State Energy Research Development Authority (NYSERDA)-led assessment is a research study designed to inform future New York State energy planning efforts. The overall objective of this study is to understand the current residential building stock, new and existing residential single-family homes, and associated energy use, including saturation of energy consuming equipment by fuel, penetration of energy-efficient equipment, and information on building characteristics and energy management practices. Study results will inform future energy planning, and identify and design potential energy efficiency programs to help homeowners and occupants across the State increase energy efficiency and reduce energy consumption. The study was completed using 456 on-site inspections and 2,419 online and telephone surveys. This dataset represents only the data collected from surveys conducted from September 28, 2018 to December 3, 2018. The on-site inspections are a subset from the online and telephone survey respondents. On-site inspections were conducted between October 10, 2018 and December 15, 2018.

For the data collected from on-site inspections, see the RBSA 2018 on-site dataset at https://data.ny.gov/d/3drn-bhzv.

The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and accelerate economic growth. reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit nyserda.ny.gov or follow us on Twitter, Facebook, YouTube, or Instagram.

Taiwan EC: EP: MFG: FB: Other Food data was reported at 1,204,131.309 kWh th in 2017. This records an increase from the previous number of 1,148,753.773 kWh th for 2016. Taiwan EC: EP: MFG: FB: Other Food data is updated yearly, averaging 678,146.676 kWh th from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 1,204,131.309 kWh th in 2017 and a record low of 418,792.534 kWh th in 1998. Taiwan EC: EP: MFG: FB: Other Food data remains active status in CEIC and is reported by Taiwan Power Company. The data is categorized under Global Database’s Taiwan – Table TW.RB007: Energy Consumption: Electricity: By Industry: Taiwan Power Company (Annual).

Taiwan EC: EP: MFG: FB: Sugar data was reported at 71,884.865 kWh th in 2017. This records a decrease from the previous number of 74,090.894 kWh th for 2016. Taiwan EC: EP: MFG: FB: Sugar data is updated yearly, averaging 72,457.519 kWh th from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 78,038.039 kWh th in 2011 and a record low of 65,245.988 kWh th in 2009. Taiwan EC: EP: MFG: FB: Sugar data remains active status in CEIC and is reported by Taiwan Power Company. The data is categorized under Global Database’s Taiwan – Table TW.RB007: Energy Consumption: Electricity: By Industry: Taiwan Power Company (Annual).

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Subject:

Facebook recently introduced a new bidding system called "average bidding"(test group) alongside the existing "maximum bidding"(control group) system. These bidding systems determine which ads get displayed to users based on how much advertisers are willing to pay.

With "maximum bidding," advertisers specify the maximum amount they are willing to pay for each impression. For example, an advertiser might say, "I'm willing to pay a maximum of $10 for each impression."

With "average bidding," advertisers specify an average amount they are willing to pay for impressions. For instance, they might say, "On average, I'm willing to pay $6 for each impression."

Here's the key point: In this dataset, we've gathered the results of these two bidding strategies over the last 40 days to see which one is more effective at getting their ads displayed to the target audience.

Business Challenge: Unleashing the Power of Facebook Advertising

As a forward-thinking company poised to make waves in the realm of Facebook advertising, we're on a mission to unearth the most advantageous approach for our brand. Our burning questions:

1. Maximize Clicks and Purchases: Which strategy will propel us toward our goal of skyrocketing clicks and driving purchases?
2. Battle of Titans: Is there a discernible and statistically significant difference between the two bidding options?

Enter the AB Test: Today, we embark on a journey of data-driven discovery, where the clash of titans—Average Bidding versus Maximum Bidding—will be meticulously dissected and evaluated. We're on a quest for insights that will define our Facebook advertising strategy's future, using data as our compass and innovation as our weapon.

The outcome of this AB Test will not just answer our questions but will be the harbinger of a glorious era in our Facebook advertising endeavors. Stay tuned for a transformation that will leave a mark on the digital advertising landscape.

Features:

• Impression: Number of impressions per ad.
• Click: Numbers of clicks per ad.
• Purchase: The number of products purchased after the click.
• Earnings: Earning after purchase.

Taiwan EC: EP: MFG: FB: Slaughtering data was reported at 219,433.613 kWh th in 2017. This records an increase from the previous number of 214,430.082 kWh th for 2016. Taiwan EC: EP: MFG: FB: Slaughtering data is updated yearly, averaging 160,273.986 kWh th from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 219,433.613 kWh th in 2017 and a record low of 103,431.688 kWh th in 1999. Taiwan EC: EP: MFG: FB: Slaughtering data remains active status in CEIC and is reported by Taiwan Power Company. The data is categorized under Global Database’s Taiwan – Table TW.RB007: Energy Consumption: Electricity: By Industry: Taiwan Power Company (Annual).

Taiwan EC: EP: MFG: FB: Dairy Product data was reported at 203,598.335 kWh th in 2017. This records a decrease from the previous number of 205,163.566 kWh th for 2016. Taiwan EC: EP: MFG: FB: Dairy Product data is updated yearly, averaging 194,987.014 kWh th from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 210,080.362 kWh th in 2013 and a record low of 149,512.293 kWh th in 1998. Taiwan EC: EP: MFG: FB: Dairy Product data remains active status in CEIC and is reported by Taiwan Power Company. The data is categorized under Global Database’s Taiwan – Table TW.RB007: Energy Consumption: Electricity: By Industry: Taiwan Power Company (Annual).

Taiwan EC: EP: MFG: FB: Seasoning data was reported at 162,198.882 kWh th in 2017. This records a decrease from the previous number of 179,709.047 kWh th for 2016. Taiwan EC: EP: MFG: FB: Seasoning data is updated yearly, averaging 198,393.351 kWh th from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 289,051.990 kWh th in 1998 and a record low of 162,198.882 kWh th in 2017. Taiwan EC: EP: MFG: FB: Seasoning data remains active status in CEIC and is reported by Taiwan Power Company. The data is categorized under Global Database’s Taiwan – Table TW.RB007: Energy Consumption: Electricity: By Industry: Taiwan Power Company (Annual).

Energy storage is critical to New York’s clean energy future. As renewable power sources like wind and solar provide a larger portion of New York’s electricity, storage will allow clean energy to be available when and where it is most needed. NYSERDA’s retail and bulk storage incentive programs are directed at achieving New York’s 3,000 MW by 2030 energy storage goal and 1,500 MW by 2025 energy storage target, codified in the Climate Leadership and Community Preservation Act. In December 2018, the New York Public Service Commission (PSC) issued a landmark energy storage order establishing the 3,000 MW by 2030 goal and authorizing the incentive programs. Details on the incentive structure and design are available at https://www.nyserda.ny.gov/energystorage. Retail and Bulk Energy Storage Incentive Programs Reported by NYSERDA: Beginning 2019 dataset includes data points for projects completed and approved in the pipeline (not yet installed) in NYSERDA’s Incentive Programs beginning April 2019.The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit nyserda.ny.gov or follow us on X, Facebook, YouTube, or Instagram.

The Average Residential Retail Kerosene Prices dataset provides New York residents and businesses with objective information on average residential retail kerosene pricing in New York State and by region beginning September 4, 2000. Pricing data is obtained via surveys conducted by New York State Energy Research and Development Authority (NYSERDA) staff on a weekly basis during heating season (September to March) and bi-weekly during the rest of the year. All prices are listed in dollars per gallon.

The Average Home Heating Oil Prices dataset, Average Residential Retail Kerosene Prices dataset, and Average Residential Retail Propane Prices dataset are collectively referred to as the Heating Fuel Prices dataset.

For current and historical residential retail price data, regional comparisons, and fuel type comparisons, please visit the Kerosene Prices Dashboard: https://www.nyserda.ny.gov/researchers-and-policymakers/energy-prices/kerosene/average-kerosene-prices

The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit https://nyserda.ny.gov or follow us on X, Facebook, YouTube, or Instagram.

To request placement in this database, or to update your company’s information, please visit NYSERDA’s Supply Chain Database webpage at https://www.nyserda.ny.gov/All-Programs/Offshore-Wind/Focus-Areas/Supply-Chain-Economic-Development/Supply-Chain-Database to submit a request form.How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit https://nyserda.ny.gov or follow us on Twitter, Facebook, YouTube, or Instagram.

Annual air trends report in the form of an interactive web application. The report features a suite of visualization tools that allow the user to: -Learn about air pollution and how it can affect our health and environment. -Compare key air emissions to gross domestic product, vehicle miles traveled, population, and energy consumption back to 1970. -Take a closer look at how the number of days with unhealthy air has dropped since 2000 in 35 major US cities. -Explore how air quality and emissions have changed through time and space for each of the common air pollutants. -Check out air trends where you live. Users will also be able to share this content across social media, with one-click access to Facebook, Twitter, Pinterest, and other major social media sites.

Authors’ have designed and simulated a hybrid AC-DC micro-grid for a geographical area of Bangladesh, Payra (22.1493° N, 90.1352° E) aiming to the economical electricity supply. The design was held using a popular simulation software, “Homer Pro”. In the micro-grid, solar photovoltaic panel, wind turbine, and Natural gas generator were used as sources and 100 household’s AC load, and 30 Electric vehicle’s DC load as consumers. Solar Global Horizontal Irradiance, wind speed, hourly annual load demand were the corresponding input parameters. In order to utilize the generated power, the load demand has been simulated differently by increasing and decreasing it to some extent, such as 10%, 5% and 2.5% more and less respectively. Finally, there arise 7 datasets including the original and the 6 varied load scenarios. The dataset has total 8761 instance of data where, each set has 14 data samples. Data file contents: Data 1:: Payra_Original_load.csv: Contains raw output data corresponds to the original load demand of Payra, collected from the micro-grid simulation. This file has 8762 set of data where, each set having 14 data samples from the simulation output. Data arrangement is described below: Column 1: Date and time of data recording in the format of DD-MM-YY [hh]:[mm]. Time is in 24-hour format. Column 2: Output power data of the flat plate photovoltaic panel in the "kW" unit. Column 3: Output power data of the Northern Power NPS 60-24 wind turbine in the "kW" unit. Column 4: Output power data of the Autosize Genset Natural gas generator in the "kW" unit. Column 5: Output power data of the Autosize Genset Natural gas generator Fuel consumption in the "m-3" unit. Power values have a maximum of seven decimal places. Column 6: Data for the total electrical load served in the "kW" unit. Column 7: Data for percentage penetration of renewable energy sources. Column 8: Output power data of the Excess Electricity Production in the "kW" unit. Column 9: Output power data of the total renewable energy sources in the "kW" unit. Column 10: Output power data of the Inverter used in the model in the "kW" unit. Column 11: Output power data of the Rectifier, used in the model in the "kW" unit. Column 12: Output power data of the CELLCUBE® FB 20-130 Battery charge in the "kW" unit. Column 13: Output power data of the CELLCUBE® FB 20-130 Battery discharge in the "kW" unit. Column 14: Data for percentage state of charge of the CELLCUBE® FB 20-130 Battery.

Data 2:: Payra_10%more_load.csv, Data 3:: Payra_10%less_load.csv, Data 4:: Payra_5%more_load.csv, Data 5:: Payra_5%less_load.csv, Data 6:: Payra_2.5%more_load.csv, and Data 7:: Payra_2.5%less_load.csv :: Contains raw output data that corresponds to the (10% more, 10% less, 5% more, 5%less, 2.5% more, 2.5% less load demand respectively) of Payra, collected from the micro-grid simulation, having the same shape and data arrangement as before.

The Regional Greenhouse Gas Initiative (RGGI) is a multi-state cap-and-trade mechanism where polluters of greenhouse gas emissions must either reduce emissions or purchase emissions allowances. New York State allocates funds received from selling allowances to the New York State Energy Research and Development Authority (NYSERDA) to manage programs aimed at reducing fossil fuel consumption. The New York State RGGI Auction Proceeds dataset provides the results from each allowance auction including the allowance clearing price, the total number of allowances sold by the State, and the value earned by the State from selling allowances.

The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit https://nyserda.ny.gov or follow us on X, Facebook, YouTube, or Instagram.

Gasoline retail prices weekly average by region dataset provides the weekly average retail gasoline prices for New York State and sixteen New York metropolitan regions in U.S. dollars per gallon. Data is a weekly average from October 2007 through current. Some metropolitan regions begin in 2017.

Average daily retail gasoline prices are collected from the American Automobile Association (AAA) Daily Fuel Gauge Report. The AAA Daily Fuel Gauge Report prices are averaged to produce a weekly average retail price for New York State and each metropolitan region.

The New York State metropolitan regions in the dataset are Albany (Albany-Schenectady-Troy), Batavia, Binghamton, Buffalo (Buffalo-Niagara Falls), Dutchess (Dutchess-Putnam), Elmira, Glens Falls, Ithaca, Kingston, Nassau (Nassau-Suffolk), New York City, Rochester, Syracuse, Utica (Utica-Rome), Watertown (Watertown-Fort Drum), and White Plains.

The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit https://nyserda.ny.gov or follow us on Twitter, Facebook, YouTube, or Instagram.