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U.S. Energy Information Administration

The U.S. Energy Information Administration (EIA) is a principal agency of the U.S. Federal Statistical System responsible for collecting, analyzing, and disseminating energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment. EIA programs cover data on coal, petroleum, natural gas, electric,  renewable and nuclear energy.

所有数据集:  A C D E G I N R U W
  • A
    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 11 十二月, 2018
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      World Electricity access database Hundreds of millions of people have gained access to modern energy over the last two decades, especially in China and India. Rapid economic development in several developing countries, increasing urbanisation and ongoing energy access programmes have been important factors in this achievement. The IEA Access to Energy database provides a snapshot of progress made toward meeting the ultimate goal of universal access. Note: For indicator population without access, value 1 represent <1 except Botswana, Guatemala countries
  • C
  • D
    • 十一月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 14 十一月, 2018
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      The Drilling Productivity Report uses recent data on the total number of drilling rigs in operation along with estimates of drilling productivity and estimated changes in production from existing oil and natural gas wells to provide estimated changes in Oil and Natural gas production for seven key regions: Bakken, Eagle Ford, Haynesville, Marcellus, Niobrara, Permian and Utica
  • E
    • 二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 11 六月, 2018
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      EIA's Annual Energy Outlook provides modeled projections of domestic energy markets through 2050, and it includes cases with different assumptions regarding macroeconomic growth, world oil prices, technological progress, and energy policies. Strong domestic production coupled with relatively flat energy demand allow the United States to become a net energy exporter over the projection period in most cases. In the Reference case, natural gas consumption grows the most on an absolute basis, and non-hydroelectric renewables grow the most on a percentage basis.The AEO is developed using the National Energy Modeling System (NEMS), an integrated model that captures interactions of economic changes and energy supply, demand, and prices.Energy market projections are subject to much uncertainty, as many of the events that shape energy markets and future developments in technologies, demographics, and resources cannot be foreseen with certainty.
    • 十一月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 27 十一月, 2018
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    • 十一月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 21 十一月, 2018
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      Energy & Environment Statistics of Louisiana
    • 十一月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 28 十一月, 2018
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      The yearly data is the sum of the monthly data for all indicators. Energy consumption data by different sector are developed from a group of energy-related surveys, typically called "supply surveys," conducted by the U.S. Energy Information Administration (EIA). Supply surveys are directed to suppliers and marketers of specific energy sources. They measure the quantities of specific energy sources produced, or the quantities supplied to the market, or both. The data obtained from EIA's supply surveys are integrated to yield the summary consumption statistics.
    • 一月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 09 二月, 2018
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      Energy-related carbon dioxide (CO2) emissions vary significantly across states, whether considered on an absolute or per capita basis. Total state CO2 emissions include those from direct fuel use across all sectors, including residential, commercial, industrial, and transportation, as well as primary fuels consumed for electric generation. The overall size of a state, as well as the available fuels, types of businesses, climate, and population density, play a role in determining the level of both total and per capita emissions. Additionally, each state’s energy system reflects circumstances specific to that state. For example, some states have abundant hydroelectric supplies, while others contain abundant coal resources. This paper presents a basic analysis of the factors that contribute to a state’s CO2 profile. This analysis neither attempts to assess the effect of state policies on absolute emissions levels or on changes over time, nor does it intend to imply that certain policies would be appropriate for a particular state. The term energy-related CO2 emissions includes emissions released at the location where fossil fuels are consumed. Therefore, to the extent that fuels are used in one state to generate electricity that is consumed in another state, emissions are attributed to the former rather than the latter. Analysis attributing emissions to the consumption of electricity, rather than the production of electricity, would yield different results. For feed-stock application, carbon stored in products such as plastics are subtracted from reported emissions for the states where they are produced.
    • 十一月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 26 十一月, 2018
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      Estimates of Annual Fossil-Fuel CO2 Emitted for Each State in the U.S.A. and the District of Columbia for Each Year from 1960 through 2001. Consumption data for coal, petroleum, and natural gas are multiplied by their respective thermal conversion factors, which are in units of heat energy per unit of fuel consumed (i.e., per cubic foot, barrel, or ton), to calculate the amount of heat energy derived from fuel combustion. Results are expressed in terms of heat energy obtained from each fuel type. These energy consumption data were multiplied by their respective carbon dioxide emission factors, which are called carbon content coefficients by the U.S. Environmental Protection Agency (EPA). These factors quantify the mass of oxidized carbon per unit of energy released from a fuel. In the U.S.A., they are typically expressed in units of teragrams of carbon (Tg-C = 10^12 grams of carbon) per quadrillion British thermal units (quadrillion Btu = 10^15 Btu, or "quad"), and are highest for coal and lowest for natural gas. Our results are given in teragrams of carbon emitted. To convert to carbon dioxide, multiply by 44/12 (= 3.67).
  • G
    • 十一月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 01 十二月, 2018
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      Source: https://www.eia.gov/dnav/pet/pet_stoc_gp_a_EPLLB0I_SKN_mbbl_a.htm https://www.eia.gov/dnav/ng/ng_stor_sum_dcu_nus_m.htm
  • I
    • 十一月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 06 十二月, 2018
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    • 七月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 17 九月, 2018
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      IEO2018 focuses on macroeconomic uncertainty by conducting sensitivity analyses in three IEO regions: China, India, and Africa. These are projected to be three of the fastest growing and most populous regions in the IEO2018 Reference case, and there is significant uncertainty regarding their future economic growth.
  • N
  • R
  • U
    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十二月, 2018
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    • 四月 2017
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 11 四月, 2017
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      EIA has expanded the Monthly Energy Review (MER) to include annual data as far back as 1949 for those data tables that are found in both the Annual Energy Review (AER) and the MER. In the list of tables below, grayed-out table numbers now go to MER tables that contain 1949-2012 (and later) data series.
    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十二月, 2018
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    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十二月, 2018
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    • 十月 2017
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 27 十月, 2017
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    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 06 十二月, 2018
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      Data updates are released on Thursday and Sunday.
    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十二月, 2018
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    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十二月, 2018
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      U.S. Petroleum Balance Sheet
    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 07 十二月, 2018
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    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十二月, 2018
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    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十二月, 2018
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    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十二月, 2018
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    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 14 十二月, 2018
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    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十二月, 2018
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    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十二月, 2018
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    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十二月, 2018
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    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十二月, 2018
      选择数据集
    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十二月, 2018
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    • 十月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 十月, 2018
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    • 十一月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 03 十二月, 2018
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    • 十一月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 26 十一月, 2018
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      Note: * Indicator "Electric Price" source link:http://www.eia.gov/electricity/data/browser/#/topic/7?agg=2 * Value for "Spark Spread" has been calculated from "Electric Price" and "Average Cost of Natural Gas"   Formula: Spark Spread = (Electricity Price-((100*Average Cost of Natural Gas)/293.29722222222))
    • 十一月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 27 十一月, 2018
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    • 六月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 02 七月, 2018
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    • 九月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 09 十月, 2018
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      The taxes and other fees on retail gasoline and diesel fuel, in cents per gallon, as of August 1, 2018     This list includes rates of general application (including, but not limited to, excise taxes, environmental taxes, special taxes, and inspection fees), exclusive of county and local taxes. Rates are also exclusive of any state taxes based on gross or net receipts. The information included in this document is for general informational purposes only and should not be construed as legal, tax, or other advice. Contact the appropriate state agencies for official information or guidance about motor fuel taxes and fees. State rates in effect as of January 1, 2018. Sources: State and Territorial statutes and government agencies.
    • 十一月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 18 十二月, 2018
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      1). U.S. Gross Output: Gross output is the value of gross domestic product (GDP) plus the value of intermediate inputs used to produce GDP 2). Implicit Price Deflator: The gross domestic product implicit price deflator is used to convert nominal dollars to chained (2009) dollars.
    • 十一月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 04 十二月, 2018
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      The monthly survey Form EIA-860M, ‘Monthly Update to Annual Electric Generator Report’ supplements the annual survey form EIA-860 data with monthly information that monitors the current status of existing and proposed generating units at electric power plants with 1 megawatt or greater of combined nameplate capacity. EIA estimates the current and near-term unit inventory of electric power generating capacity by integrating the information on these surveys along with ongoing EIA research of new units. However, creating this monthly estimate sometimes requires the use of data submitted on the annual EIA-860 before it has been fully verified by EIA. For this reason, reported capacities are EIA’s preliminary estimates of capacity for that month. Estimates will be corrected without specific acknowledgement or explanation in subsequent month’s inventory.   Starting with March 2017 data, Preliminary Monthly Electric Generator Inventory includes a comprehensive list of generators which retired since 2002. The list can be found on the ‘Retired’ tab of the datafile.   Capacities reported in this preliminary inventory are best estimates of current generating capacity, but are not meant to be capacity commitments by the associated facilities.
    • 六月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 05 七月, 2018
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      The State Energy Data System (SEDS) is the U.S. Energy Information Administration's (EIA) source for comprehensive State energy statistics. Included are estimates of energy production, consumption, prices, and expenditures broken down by energy source and sector. Production and consumption estimates begin with the year 1960 while price and expenditure estimates begin with 1970.
    • 十月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 08 十一月, 2018
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      Indicator Details are as Below:Advanced Meters – This file, compiled from data collected on both Forms EIA-861 and EIA-861S, contains information on Automated Meter Readings (AMR) and Advanced Metering Infrastructure (AMI). (Formerly File 8)Balancing Authority – This file, contains the list of Balancing Authorities and the states they operate in, for the EIA-861 and EIA-861S. (Formerly File 1_cao)Demand Response (2013 forward) – This file, compiled from data collected on Form EIA-861 only, contains the number of customers enrolled, energy savings, potential and actual peak savings, and associated costs.Distribution Systems (2013 forward) – This file, compiled from data collected on Form EIA-861 only, contains the number of distribution circuits and circuits with voltage optimization.Dynamic Pricing (2013 forward) – This file, compiled from data collected on Form EIA-861 only, contains the number of customers enrolled in various programs, i.e. time of use, real time, variable peak and critical peak pricing, and critical peak rebate programs.Energy Efficiency (2013 forward) – This file, compiled from data collected on Form EIA-861 only, contains incremental and life cycle data on energy savings, peak demand savings, weighted average life, and associated costs.Mergers (2007 forward) – This file, compiled from data collected on Form EIA-861 only, contains information on mergers and acquisitions. (Formerly File 7)Net Metering (2007 forward) – This file, compiled from data collected on Form EIA-861 only, contains number of customers and displaced energy, by sector and state. For 2010 forward, it contains capacity, customer count, and energy sold back (an optional question on the survey) by sector and state and by technology type, i.e. photovoltaic, wind, and/or other.Non Net Metering Distributed – This file, compiled from data collected on Form EIA-861 only, contains information on utility or customer-owned distributed generators such as the number, capacity, and technology type of generators. Capacities by photovoltaic and storage generation types were added in 2010, fuel cells were added in 2016. Starting in 2016, this data is now collected at the sector level. (Formerly Distributed Generation, Formerly File 6)Operational Data – This file, compiled from data collected on Form EIA-861 only, contains aggregate operational data for the source and disposition of energy and revenue information from each electric utility in the country, including power marketers and federal power marketing administrations. (Formerly File 1)Reliability (2013 forward) – This file, compiled from data collected on Form EIA-861 only, contains SAIDI and SAIFI data.Sales to Ultimate Customers – This file, compiled from data collected on the Form EIA-861 and an estimate from Form EIA-861S for data by customer sector, contains information on retail revenue, sales, and customer counts by state, balancing authority, and class of service (including the transportation sector which was added in 2003) for each electric distribution utility or energy service provider. (Formerly File 2)Sales to Ultimate Customers, Customer Sited – This file, compiled from data collected on the Form EIA-923 only, contains information on retail revenue, sales, and customer counts by state and balancing authority. This includes retail sales from any units located at a customer site.Utility Data (2007 forward) – This file, compiled from data collected on Form EIA-861 only, contains information on the types of activities each utility engages in, the NERC regions of operation, whether the utility generates power, whether it operates alternative-fueled vehicles, and, beginning in 2010, the ISO or RTO region in which the entity conducts operations. (Formerly File 1_a)Demand-Side Management (discontinued after 2012) – This file, compiled from data collected on both Form EIA-861 and, for time-based rate programs, Form EIA-861S, contains information on electric utility demand-side management programs, including energy efficiency and load management effects and expenditures. Beginning in 2007, it also contains the number of customers in time-based rate programs. (Formerly File 3)Green Pricing (discontinued after 2012) – This file, compiled from data collected on Form EIA-861 only, contains number of customers, sales, and revenue, by sector and state. (Formerly File 5)  
  • W
    • 十二月 2018
      来源: U.S. Energy Information Administration
      上传者: Knoema
      访问日期: 17 十二月, 2018
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      Correlation defined as linear relationship between two variables. Correlation coefficient (r) is used to measure linear association between two variables and its range varies between -1 to +1. There are two types of correlation namely positive and negative. r=+1 represents perfect positive correlation whereas r=-1 represents perfect negative correlation. Positive correlation tells both indicators are moving in same direction for e.g. If prices of crude oil and Natural gas are positively correlated and there is an increase in price of crude oil then price of Natural gas will also increase. On the other hand negative correlation between the same indicators, if there is increase in price of one will decrease the price of others.