Graph and download economic data for Manufacturing Sector: Energy Costs (MPU9900641) from 1987 to 2023 about cost, energy, sector, manufacturing, and USA.

Industrial electricity prices including electricity tax reached ***** cents per kilowatt-hour in Germany, as of March 2025. Figures fluctuated during the specified timeline. The largest share of industrial electricity costs was due to energy procurement, network charges and distribution.

China Energy Consumption: Industry: Manufacturing data was reported at 3,070.860 SCE Ton mn in 2022. This records an increase from the previous number of 2,930.650 SCE Ton mn for 2021. China Energy Consumption: Industry: Manufacturing data is updated yearly, averaging 1,364.079 SCE Ton mn from Dec 1985 (Median) to 2022, with 37 observations. The data reached an all-time high of 3,070.860 SCE Ton mn in 2022 and a record low of 434.600 SCE Ton mn in 1985. China Energy Consumption: Industry: Manufacturing data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under Global Database’s China – Table CN.RBB: Energy Consumption.

United States - Manufacturing Sector: Cost of Energy was 86.27500 Bil. of Current $ in January of 2023, according to the United States Federal Reserve. Historically, United States - Manufacturing Sector: Cost of Energy reached a record high of 144.80500 in January of 2008 and a record low of 59.18000 in January of 1998. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Manufacturing Sector: Cost of Energy - last updated from the United States Federal Reserve on November of 2025.

Electricity prices for industries in the United States increased over the past few years, peaking in summer 2022. Industrial electricity prices amounted to **** U.S. cents per kilowatt-hour in May 2024, up from **** U.S. dollar cents per kilowatt-hour the previous month. The average retail electricity price for industrial consumers in the United States stood at **** U.S. dollar cents per kilowatt-hour in 2023.

Graph and download economic data for Wood Products: Energy Costs (MPU5000641) from 1987 to 2023 about cost, wood, energy, durable goods, production, goods, manufacturing, and USA.

Content

This company produces several types of coils, steel plates, and iron plates. The information on electricity consumption is held in a cloud-based system. The information on energy consumption of the industry is stored on the website of the Korea Electric Power Corporation (pccs.kepco.go.kr), and the perspectives on daily, monthly, and annual data are calculated and shown.

Attribute Information:

Date Continuous-time data taken on the first of the month Usage_kWh Industry Energy Consumption Continuous kWh Lagging Current reactive power Continuous kVarh Leading Current reactive power Continuous kVarh CO2 Continuous ppm NSM Number of Seconds from midnight Continuous S Week status Categorical (Weekend (0) or a Weekday(1)) Day of week Categorical Sunday, Monday : Saturday Load Type Categorical Light Load, Medium Load, Maximum Load

Acknowledgements

This dataset is sourced from the UCI Machine Learning Repository Relevant Papers:

1. Sathishkumar V E, Changsun Shin, Youngyun Cho, “Efficient energy consumption prediction model for a data analytic-enabled industry building in a smart city†, Building Research & Information, Vol. 49. no. 1, pp. 127-143, 2021.
2. Sathishkumar V E, Myeongbae Lee, Jonghyun Lim, Yubin Kim, Changsun Shin, Jangwoo Park, Yongyun Cho, “An Energy Consumption Prediction Model for Smart Factory using Data Mining Algorithms†KIPS Transactions on Software and Data Engineering, Vol. 9, no. 5, pp. 153-160, 2020. Transactions on Software and Data Engineering, Vol. 9, no. 5, pp. 153-160, 2020.
3. Sathishkumar V E, Jonghyun Lim, Myeongbae Lee, Yongyun Cho, Jangwoo Park, Changsun Shin, and Yongyun Cho, “Industry Energy Consumption Prediction Using Data Mining Techniques†, International Journal of Energy Information and Communications, Vol. 11, no. 1, pp. 7-14, 2020.

Inspiration

Which times of the year is the most energy consumed? What patterns can we identify in energy usage?

Graph and download economic data for Paper Products: Energy Costs (MPU5650641) from 1987 to 2023 about cost, paper, nondurable goods, energy, production, goods, manufacturing, and USA.

Graph and download economic data for Petroleum and Coal Products: Energy Costs (MPU5750641) from 1987 to 2023 about coal, petroleum, cost, nondurable goods, energy, production, goods, manufacturing, and USA.

Graph and download economic data for Computer and Electronic Products: Energy Costs (MPU5250641) from 1987 to 2023 about cost, computers, electronics, energy, durable goods, production, goods, manufacturing, and USA.

Dataset Description Title: Electricity Market Dataset for Long-Term Forecasting (2018–2024)

Overview: This dataset provides a comprehensive collection of electricity market data, focusing on long-term forecasting and strategic planning in the energy sector. The data is derived from real-world electricity market records and policy reports from Germany, specifically the Frankfurt region, a major European energy hub. It includes hourly observations spanning from January 1, 2018, to December 31, 2024, covering key economic, environmental, and operational factors that influence electricity market dynamics. This dataset is ideal for predictive modeling tasks such as electricity price forecasting, renewable energy integration planning, and market risk assessment.

Features Description Feature Name Description Type Timestamp The timestamp for each hourly observation. Datetime Historical_Electricity_Prices Hourly historical electricity prices in the Frankfurt market. Continuous (Float) Projected_Electricity_Prices Forecasted electricity prices (short, medium, long term). Continuous (Float) Inflation_Rates Hourly inflation rate trends impacting energy markets. Continuous (Float) GDP_Growth_Rate Hourly GDP growth rate trends for Germany. Continuous (Float) Energy_Market_Demand Hourly electricity demand across all sectors. Continuous (Float) Renewable_Investment_Costs Investment costs (capital and operational) for renewable energy projects. Continuous (Float) Fossil_Fuel_Costs Costs for fossil fuels like coal, oil, and natural gas. Continuous (Float) Electricity_Export_Prices Prices for electricity exports from Germany to neighboring regions. Continuous (Float) Market_Elasticity Sensitivity of electricity demand to price changes. Continuous (Float) Energy_Production_By_Solar Hourly solar energy production. Continuous (Float) Energy_Production_By_Wind Hourly wind energy production. Continuous (Float) Energy_Production_By_Coal Hourly coal-based energy production. Continuous (Float) Energy_Storage_Capacity Available storage capacity (e.g., batteries, pumped hydro). Continuous (Float) GHG_Emissions Hourly greenhouse gas emissions from energy production. Continuous (Float) Renewable_Penetration_Rate Percentage of renewable energy in total energy production. Continuous (Float) Regulatory_Policies Categorical representation of regulatory impact on electricity markets (e.g., Low, Medium, High). Categorical Energy_Access_Data Categorization of energy accessibility (Urban or Rural). Categorical LCOE Levelized Cost of Energy by source. Continuous (Float) ROI Return on investment for energy projects. Continuous (Float) Net_Present_Value Net present value of proposed energy projects. Continuous (Float) Population_Growth Population growth rate trends impacting energy demand. Continuous (Float) Optimal_Energy_Mix Suggested optimal mix of renewable, non-renewable, and nuclear energy. Continuous (Float) Electricity_Price_Forecast Predicted electricity prices based on various factors. Continuous (Float) Project_Risk_Analysis Categorical analysis of project risks (Low, Medium, High). Categorical Investment_Feasibility Indicator of the feasibility of energy investments. Continuous (Float) Use Cases Electricity Price Forecasting: Utilize historical and projected price trends to predict future electricity prices. Project Risk Classification: Categorize projects into risk levels for better decision-making. Optimal Energy Mix Analysis: Analyze the balance between renewable, non-renewable, and nuclear energy sources. Policy Impact Assessment: Study the effect of regulatory and market policies on energy planning. Long-Term Strategic Planning: Provide insights into investment feasibility, GHG emission reduction, and energy market dynamics. Acknowledgment This dataset is based on publicly available records and market data specific to the Frankfurt region, Germany. The dataset is designed for research and educational purposes in energy informatics, computational intelligence, and long-term forecasting.

China Energy Consumption: Industry: Mfg: Paper Making data was reported at 44.620 SCE Ton mn in 2022. This records an increase from the previous number of 42.040 SCE Ton mn for 2021. China Energy Consumption: Industry: Mfg: Paper Making data is updated yearly, averaging 36.124 SCE Ton mn from Dec 1985 (Median) to 2022, with 37 observations. The data reached an all-time high of 46.866 SCE Ton mn in 2009 and a record low of 12.950 SCE Ton mn in 1985. China Energy Consumption: Industry: Mfg: Paper Making data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Energy Sector – Table CN.RBB: Energy Consumption.

Facility-level industrial combustion energy use is calculated from greenhouse gas emissions data reported by large emitters (>25,000 metric tons CO2e per year) under the U.S. EPA's Greenhouse Gas Reporting Program (GHGRP, https://www.epa.gov/ghgreporting). The calculation applies EPA default emissions factors to reported fuel use by fuel type. Additional facility information is included with calculated combustion energy values, such as industry type (six-digit NAICS code), location (lat, long, zip code, county, and state), combustion unit type, and combustion unit name. Further identification of combustion energy use is provided by calculating energy end use (e.g., conventional boiler use, co-generation/CHP use, process heating, other facility support) by manufacturing NAICS code. Manufacturing facilities are matched by their NAICS code and reported fuel type with the proportion of combustion fuel energy for each end use category identified in the 2010 Energy Information Administration Manufacturing Energy Consumption Survey (MECS, http://www.eia.gov/consumption/manufacturing/data/2010/). MECS data are adjusted to account for data that were withheld or whose end use was unspecified following the procedure described in Fox, Don B., Daniel Sutter, and Jefferson W. Tester. 2011. The Thermal Spectrum of Low-Temperature Energy Use in the United States, NY: Cornell Energy Institute.

Industrial consumers of electricity in the United States paid an average of 8.15 U.S. dollar cents per kilowatt-hour in 2024. This was an increase compared to the previous year, when prices peaked at 8.3 U.S. dollar cents per kilowatt-hour. Prices are forecast to increase further to 8.32 U.S. dollar cents per kilowatt-hour by the end of 2025.

United States Total Energy Consumption data was reported at 93.691 BTU qn in 2023. This records a decrease from the previous number of 94.812 BTU qn for 2022. United States Total Energy Consumption data is updated yearly, averaging 92.977 BTU qn from Dec 1980 (Median) to 2023, with 44 observations. The data reached an all-time high of 98.965 BTU qn in 2007 and a record low of 70.489 BTU qn in 1983. United States Total Energy Consumption data remains active status in CEIC and is reported by U.S. Energy Information Administration. The data is categorized under Global Database’s United States – Table US.EIA.IES: Energy Production and Consumption: Annual.

Graph and download economic data for Furniture and Related Products: Energy Costs (MPU5400641) from 1987 to 2023 about cost, furniture, energy, durable goods, production, goods, manufacturing, and USA.