This Dataset represents total energy consumption at national level.The Dataset is composed of the following elements:Energy consumption of installations with MAT voltage level (very high voltage);Energy consumption of installations with AT voltage level (high voltage);Energy consumption of installations with MT (medium voltage) voltage level;Energy consumption of installations with BT voltage level (low voltage);Sum of energy consumption of all voltage levels (Total).The data is obtained through information on consumption with network losses by voltage level. At the end of each 15-minute period, the meter stores the total amount of energy during that interval.The update frequency is daily.Use case: This data allows you to monitor national energy consumption, quarter-hourly by voltage level.1. The information made available by E-REDES constitutes an approximation to the values taken from the system and is based on the moment in which it is collected. Given that the connection points, the electricity distribution network, and the consumption and production values themselves are naturally very dynamic, it is safeguarded that the information made available may be subject to subsequent changes and updates, with the exception of any omissions and/or occasional inaccuracies of location that the information may contain.2. In this way, E-REDES is not liable to third parties, namely, partners, service providers, contractors, users and customers, for damages that may arise as a result, direct or indirect, of the use of this Information, in particular when carrying out interventions, calculations and/or estimates, without confirming the accuracy and updating of the data, whereby it is duly noted that the consultation of this information does not affect the duty to promote a direct consultation with E-REDES in order to obtain updated information.The data provided by the E-REDES Open Data Portal is covered by open licenses (CC BY 4.0). There are no restrictions on access, under the commitment that data users cite the publisher. Therefore, we suggest that you cite the Open Data E-REDES Portal as:E-REDES – Distribuição de Eletricidade, “E-REDES Open Data Portal”. Accessed in “Data”. [Online] Available at https://e-redes.opendatasoft.com/pages/homepage/If you share on social media, please add #PortalOpenData_E_REDES

This Dataset represents the best consumption information up to date, presenting a forecast until the end of the year.The Dataset is composed of the following elements:Energy consumption of installations with MAT voltage level (very high voltage);Energy consumption of installations with AT voltage level (high voltage);Energy consumption of installations with MT (medium voltage) voltage level;Energy consumption of installations with BT voltage level (low voltage);Sum of energy consumption of all voltage levels (Total).The data is obtained through the best information on existing consumption until the data, making a forecast until the end of the year based on historical values. At the end of each 15-minute period, the total amount corresponds to the energy during that interval.The update frequency is monthly.Use case: This data allows you to monitor the best information on national energy consumption, quarter-hourly by voltage level during the year in question.1. The information made available by E-REDES constitutes an approximation to the values taken from the system and is based on the moment in which it is collected. Given that the connection points, the electricity distribution network, and the consumption and production values themselves are naturally very dynamic, it is safeguarded that the information made available may be subject to subsequent changes and updates, with the exception of any omissions and/or occasional inaccuracies of location that the information may contain.2. In this way, E-REDES is not liable to third parties, namely, partners, service providers, contractors, users and customers, for damages that may arise as a result, direct or indirect, of the use of this Information, in particular when carrying out interventions, calculations and/or estimates, without confirming the accuracy and updating of the data, whereby it is duly noted that the consultation of this information does not affect the duty to promote a direct consultation with E-REDES in order to obtain updated information.The data provided by the E-REDES Open Data Portal is covered by open licenses (CC BY 4.0). There are no restrictions on access, under the commitment that data users cite the publisher. Therefore, we suggest that you cite the Open Data E-REDES Portal as:E-REDES – Distribuição de Eletricidade, “E-REDES Open Data Portal”. Accessed in “Data”. [Online] Available at https://e-redes.opendatasoft.com/pages/homepage/If you share on social media, please add #PortalOpenData_E_REDES

When do UK Mastodon/Fediverse users (2024) turn their central heating fully off, by month? This informal periodic survey on social media suggests that a substantial fraction of respondents (possibly 20% or more) leave their central heating on year-round, which may lead to unnecessary energy consumption and carbon emissions. Follow on to 2017 to 2022 study:https://www.earth.org.uk/note-on-survey-UK-central-heating-on-off-dates.htmlhttps://datadryad.org/stash/dataset/doi:10.5061/dryad.wstqjq2t6, Monthly informal polls run in 2024 on social media (Mastodon/Fediverse this time) with fixed timing and duration and poll question/answers, aiming to add to the previous study. Â The data from the two studies should be readily combinable., , # EOU UK Central Heating On/Off Date Micro-survey 2024

Analysis Data DOI Secondary data DOI

Follow on to 2017 to 2022 study: Previous analysis Previous data DOI

This is the data from a year's worth of polls on social media asking when is UK home central heating actually off, or when might it come on 'accidentally' on a chilly evening well away from the heating season?

These were informal polls conducted by the author in 2024 on social media (Mastodon/Fediverse for this dataset) with fixed timing and duration and poll question/answers, aiming to add to the previous study. The data from the two studies should be readily combinable.

The poll duration was shortened from the previous apparent Twitter def...

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.

Here are a few use cases for this project:

Use Case 1: Retail Marketing Analytics "contAInt" can be used to analyze in-store display photos automatically, identifying and categorizing advertisements, promotional material, and various featured products. This data could be utilized to improve store layout, display effectiveness, and marketing strategies.

Use Case 2: Social Media Ad Performance Tracking The model can be employed to process large quantities of social media images containing ads featuring various beauty products. By identifying relevant features such as text, products, and logos, "contAInt" enables advertisers to monitor and optimize their ad campaigns more efficiently.

Use Case 3: Appliance and Product Recognition in Lifestyle Media "contAInt" can be used to analyze images from lifestyle magazines, blogs, and other media by identifying appliances, beauty products, and other objects. This information can provide insights into current trends and popular products, helping businesses and marketers stay up-to-date with consumer preferences.

Use Case 4: Visual Product Recommendation By recognizing various products in user-uploaded images, "contAInt" could be integrated into an e-commerce platform to provide product recommendations based on objects identified in the image. This targeted approach could improve the shopping experience by offering personalized suggestions.

Use Case 5: Smart Home Appliance Management This computer vision model can be implemented in a smart home system to identify different appliances (refrigerator, washing machine, oven) and their respective states (on/off, in use, etc.). It can then generate notifications, provide energy-saving recommendations, or integrate with other smart devices for efficient home management.

Success.ai’s Energy Consumption Data for Middle-east Energy Professionals offers a comprehensive dataset tailored for businesses and organizations seeking to connect with leaders and decision-makers in the energy sector. Covering roles such as energy consultants, project managers, engineers, and executives, this dataset provides verified work emails, phone numbers, and detailed decision-maker profiles.

With access to over 700 million verified global profiles, Success.ai ensures your outreach, research, and collaboration strategies are powered by accurate, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution empowers you to navigate the dynamic and fast-evolving energy landscape in the Middle-east.

Why Choose Success.ai’s Energy Consumption Data?

1. Verified Contact Data for Precision Targeting

   • Access verified work emails, phone numbers, and LinkedIn profiles of energy sector professionals across the Middle-east.
   • AI-driven validation ensures 99% accuracy, improving engagement rates and minimizing errors in outreach.

2. Comprehensive Coverage Across the Middle-east

   • Includes professionals from key energy-producing countries such as Saudi Arabia, UAE, Qatar, Oman, Kuwait, and Bahrain.
   • Gain insights into regional energy trends, consumption patterns, and emerging technologies.

3. Continuously Updated Datasets

   • Real-time updates capture changes in roles, organizational structures, and market developments.
   • Stay aligned with industry trends to identify opportunities and remain competitive in the energy sector.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

• 700M+ Verified Global Profiles: Connect with energy professionals and decision-makers across the Middle-east.
• Verified Contact Details: Gain work emails, phone numbers, and LinkedIn profiles for precise targeting.
• Decision-maker Profiles: Access profiles of executives, consultants, and project managers responsible for energy initiatives and consumption strategies.
• Industry Insights: Understand energy consumption trends, market challenges, and emerging technologies in the Middle-east.

Key Features of the Dataset:

1. Comprehensive Energy Professional Profiles

   • Identify and connect with professionals overseeing energy projects, regulatory compliance, and operational efficiency in the energy sector.
   • Target decision-makers involved in renewable energy, oil and gas, and energy infrastructure projects.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by industry focus (renewables, oil and gas, utilities), geographic location, or job function.
   • Tailor campaigns to align with specific energy needs, such as efficiency improvements, technology adoption, or sustainability goals.

3. Regional and Sector-specific Insights

   • Leverage data on energy trends, regulatory frameworks, and consumption patterns in the Middle-east.
   • Refine marketing and outreach strategies to align with regional priorities and opportunities.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Lead Generation

   • Promote energy solutions, technology innovations, or consultancy services to energy professionals in the Middle-east.
   • Use verified contact data for multi-channel outreach, including email, phone, and social media campaigns.

2. Partnership Development and Collaboration

   • Build relationships with energy companies, utilities, and regulatory agencies seeking strategic alliances or innovative solutions.
   • Foster collaborations that drive efficiency, sustainability, or renewable energy adoption.

3. Market Research and Competitive Analysis

   • Analyze energy consumption trends, technological advancements, and regulatory changes across the Middle-east.
   • Benchmark against competitors to identify market gaps and high-demand solutions.

4. Recruitment and Talent Acquisition

   • Target HR professionals and hiring managers recruiting for roles in energy management, engineering, or project leadership.
   • Provide workforce optimization platforms or training solutions tailored to the energy sector.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality energy consumption data at competitive prices, ensuring strong ROI for your outreach, marketing, and business development efforts.

2. Seamless Integration

   • Integrate verified energy data into CRM systems, analytics tools, or marketing platforms via APIs or downloadable formats, streamlining workflows and enhancing productivity.

3. Data Accuracy with AI Validation

   • Trust in 99%...

When do UK Twitter users (2017 to 2022) turn their central heating fully off, by month? This informal periodic survey on social media suggests that a substantial fraction of respondents (up to 10%) leave their central heating on year-round, which may lead to unnecessary energy consumption and carbon emissions.

A heat network is a centrally produced heat distribution system that serves a large number of users (public or private tertiary buildings, condominiums, social housing, etc.). One of the major assets of the heat networks is to mobilise renewable energy present in the territory, which is difficult to distribute otherwise. Data at IRIS on consumption and delivery points on the Francisian networks allow an understanding of the degree of operation of the current networks and gives an overview of the areas in which connections would benefit from multiplication.

In order to measure the impact of its Open Data, Ores is interested in being kept informed of reuses that will be made of the data made available. Report name: Consumption of DSO customers, by type of customer Level of aggregation: The dataset contains information aggregated by Energy (Electricity/Gas), Geographic Area, and DSO Client Type (Federal Protected, Protected Regional, Other(Supplier X)) Year of consumption: Year concerned Scope: Reporting of all access points with a connection that was contractually active on the last day of the quarter of consumption concerned. Energy: electricity Frequency: Quarterly (made available annually) End date of the dataset: undefined Date of availability of the dataset: 30/10/N+1 Injection/sampling: Sampling (Consumption) Consumption : The amount of energy consumed (natural gas or electricity) measured by a device in an indoor installation. Electricity or natural gas may be collected and/or or injected into the distribution network through an access point. Sampling is the purchase of electricity and / or gas natural to the distribution network. Injection is the surplus energy produced by the user of the network who is not consumed for his own use, but who is re-injected into the distribution network. Geographical area: "The geographical areas correspond to the territories of the former inter-municipal before amalgamation. These are territorial subdivisions of ORES Assets comprising certain partners (affiliated municipalities and intermunicipal authorities) associated funding) by geographical area. The link below lists the municipalities affiliated to each sector." https://www.oresassets.be/en/territories-d-activities-and-sectors Locality: A locality is a territorial entity of indeterminate size or not, usually inhabited. A municipality usually corresponding to a city with villages surrounding areas, to several villages or to an important village surrounded by hamlets. The locality is the name given to these communal subdivisions. Number of access points: The point in the distribution system where electricity or gas is taken; or injected and identified by a single NAE. EAN: European Article Numbering. Unique identification code of an access point (point of supply). This code shall be communicated to the customer concerned by the DSO. Consumption (MWh): "Value calculated from the consumption related to the volume of energy withdrawn, then reduced to calendar year / calendar month. These approximate consumptions are calculated monthly. MWh: Megawatt-hour symbol, unit of measurement of energy, which corresponds to the power of one megawatt active for one hour. " Type of customer: "To to help people whose financial or social situation is precarious; The legislature provided for the grant of protection status. Thus, any client – or cohabitant or child living under the same roof – which meets the criteria defined by the Federal (protected customer federal) or by the Walloon Region (regional protected client) benefits from the protected customer status and protective measures, including the tariff social. Category "Other (Supplier X)": In certain situations provided for by regional legislation, ORES supplies temporarily unprotected customers. This is the case, for example, if we do not Let's not manage to place a budget meter at an unprotected customer in the 40-day deadline imposed. As soon as the meter is placed, the customer "returns" at his commercial supplier. All consumption taken during this period shall be invoiced at the maximum rate approved by the CREG." Translation into German: Name of the Berichts: Verbrauch der Kunden of VNB nach Kundentyp Aggregierungslevel: Der Datensatz enthält Informationen, die nach Energieträger (Elektrizität/Gas), geografischem Gebiet und Kundentyp des VNB (geschützter Kunde auf föderaler Ebene, geschützter Kunde auf regionaler Ebene, sonstiger Kunde (Kunde mit unbekanntem Energieversorger)) aggregiert werden. Verbrauchsjahr: Betroffenes Jahr Umfang: Reporting sämtlicher Zugriffsstellen mit einer Verbindung, die am letzten betreffenden Verbrauchsquartals vertraglich aktiv war. Energy: Elektrizität Häufigkeit: Quartalsweise Einspeisung / Abnahme: Abnahme (Verbrauch) Verbrauch: verbrauchte Menge einer Energie (Erdgas bzw. Elektrizität), die von einem Messgerät in einer Innenanlage aufgezeichnet wird. Elektrizität oder Erdgas kann von einer Zugriffsstelle vom Verteilernetz abgenommen und / oder darin eingespeist werden. Die Abnahme entspricht dem Ankauf von Elektrizität und / oder Erdgas auf dem Verteilernetz. Die Einspeisung entspricht dem Überschuss an Energy, den der Verteilernetznutzer zwar selbst erzeugt, jedoch nicht zu seinem Eigenzweck verbraucht, sondern ins Verteilernetz einspeist. Geografisches Geb...

This Dataset represents the origin of the energy that is injected into the Distribution network.The Dataset is composed of the following elements:PRE - Production originating from producers under a special regime specifications by production technology.The data is obtained through production information from producers with guaranteed tariff (PRE) by technology. At the end of each 15-minute period, the meter stores the total amount of energy during that interval.The update frequency is daily.Use case: This data allows monitoring of energy injected (PRE) into the distribution network in a given period, by production technology and allows the comparison of similar periods.1. The information made available by E-REDES constitutes an approximation to the values taken from the system and is based on the moment in which it is collected. Given that the connection points, the electricity distribution network, and the consumption and production values themselves are naturally very dynamic, it is safeguarded that the information made available may be subject to subsequent changes and updates, with the exception of any omissions and/or occasional inaccuracies of location that the information may contain.2. In this way, E-REDES is not liable to third parties, namely, partners, service providers, contractors, users and customers, for damages that may arise as a result, direct or indirect, of the use of this Information, in particular when carrying out interventions, calculations and/or estimates, without confirming the accuracy and updating of the data, whereby it is duly noted that the consultation of this information does not affect the duty to promote a direct consultation with E-REDES in order to obtain updated information.The data provided by the E-REDES Open Data Portal is covered by open licenses (CC BY 4.0). There are no restrictions on access, under the commitment that data users cite the publisher. Therefore, we suggest that you cite the Open Data E-REDES Portal as:E-REDES – Distribuição de Eletricidade, “E-REDES Open Data Portal”. Accessed in “Data”. [Online] Available at https://e-redes.opendatasoft.com/pages/homepage/If you share on social media, please add #PortalOpenData_E_REDES

This Dataset represents the total energy produced nationally.It is composed of the following elements:DGM (Market Generation Diagram) referring to the energy production of producers that are on the market - Information provided by REN; PRE (Special Regime Production) referring to the energy production of producers under special regime; Sum of DGM and PRE production (Total).The data is obtained through total production on the market and producers under special regime. At the end of each 15-minute period, the meter stores the total amount of energy during that interval.The update frequency is daily.Use case: This data allows us to monitor the evolution of energy produced at a national level. 1. The information made available by E-REDES constitutes an approximation to the values taken from the system and is based on the moment in which it is collected. Given that the connection points, the electricity distribution network, and the consumption and production values themselves are naturally very dynamic, it is safeguarded that the information made available may be subject to subsequent changes and updates, with the exception of any omissions and/or occasional inaccuracies of location that the information may contain.2. In this way, E-REDES is not liable to third parties, namely, partners, service providers, contractors, users and customers, for damages that may arise as a result, direct or indirect, of the use of this Information, in particular when carrying out interventions, calculations and/or estimates, without confirming the accuracy and updating of the data, whereby it is duly noted that the consultation of this information does not affect the duty to promote a direct consultation with E-REDES in order to obtain updated information. The data provided by the E-REDES Open Data Portal is covered by open licenses (CC BY 4.0). There are no restrictions on access, under the commitment that data users cite the publisher. Therefore, we suggest that you cite the Open Data E-REDES Portal as:E-REDES – Distribuição de Eletricidade, “E-REDES Open Data Portal”. Accessed in “Data”. [Online] Available at https://e-redes.opendatasoft.com/pages/homepage/If you share on social media, please add #PortalOpenData_E_REDES

In order to measure the impact of its Open Data, Ores is interested in being kept informed of reuses that will be made of the data made available. Report name: Number protected customers at the Social Provider, by category and type of protection Level of aggregation: dell’Accademia dei Lincei (1610-1630)’, S. Brevaglieri, L. Guerrini, F. Solinas, dataset contains information aggregated by Energy (Electricity/Gas), Geographical area, Location, Protection category, type of protection and CPAs Year of consumption: Year concerned Scope: Reporting of all access points with a connection that was contractually active 31 December of the year of consumption. Energy: electricity Frequency: Annual End date of the dataset: undefined Date of availability of the dataset: 30/10/N+1 Injection/sampling: Sampling Consumption : The amount of energy consumed (natural gas or electricity) measured by a device in an indoor installation. Electricity or natural gas may be collected and/or or injected into the distribution network through an access point. Sampling is the purchase of electricity and / or gas natural to the distribution network. Injection is the surplus energy produced by the user of the network who is not consumed for his own use, but who is re-injected into the distribution network. Geographical area: "The geographical areas correspond to the territories of the former inter-municipal before amalgamation. These are territorial subdivisions of ORES Assets comprising certain partners (affiliated municipalities and intermunicipal authorities) associated funding) by geographical area. The link below lists the municipalities affiliated to each sector." https://www.oresassets.be/en/territories-d-activities-and-sectors Locality: A locality is a territorial entity of indeterminate size or not, usually inhabited. A municipality usually corresponding to a city with villages surrounding areas, to several villages or to an important village surrounded by hamlets. The locality is the name given to these communal subdivisions. Number of access points: The point in the distribution system where electricity or gas is taken; or injected and identified by a single NAE. EAN: European Article Numbering. Unique identification code of an access point (point of supply). This code shall be communicated to the customer concerned by the DSO. Category/type of protection: - Federal: Income Federal social integration: Certificate conferring entitlement to the Social Tariff Federal legislation for people with a SocTar social integration income: Certificate sent by the FPS Economy Entitlement to the Federal Social Tariff SocTar BIM: Certificate sent by the FPS Economy opening the right to the Federal Social Tariff for Beneficiaries of a Enhanced intervention Protected Virgin Black: Certificate of Entitlement to the Federal Social Tariff for Individuals Disabled Protected Pensions : Certificate of Entitlement to the Federal Social Tariff for Individuals Retirees – Regional: Customer in debt mediation: Certificate sent by the CPAS opening the right to the Tariff regional social for people in debt mediation Client in collective settlement of debts: Certificate sent by the CPAS opening the right to the Regional Social Tariff for persons in collective settlement of Protected Debt Guidance CPAS: Certificate sent by the CPAS opening the right to the Social Tariff regional for people in educational guidance of a financial nature Protected client cyclical: Certificate of Entitlement to the Regional Social Tariff for persons in temporary financial difficulties CPAS: CPAS to which is attached to the customer Translation into German: Name of the Berichts: Anzahl der Kunden, die beim Social Provider geschützt sind, nach Kategorie und Schutzes Aggregierungslevel: Der Datensatz enthält Informationen, die nach Energieträger (Elektrizität/Gas), geografischem Gebiet, Ort, Schutzkategorie, Zündschutzart und CPAS Verbrauchsjahr: Betroffenes Jahr Umfang: Reporting sämtlicher Zugriffsstellen mit einer Verbindung, die am 31. Dezember 's betreffenden Verbrauchsjahrs vertraglich aktiv war. Energy: Elektrizität Häufigkeit: Jährlich Geografisches Gebiet: die geografischen Bereiche entsprechen den Gebieten der ehemaligen Interkommunalen vor der Fusion. Es handelt sich um territorial Untergliederungen von ORES Assets, die manche Gesellschafter (angeschlossene Gemeinden und Finanzierungsinterkommunalen) nach geografischem Gebiet umfassen. Über folgenden Link gelangen Sie zur List der Gemeinden mit Zuweisung zum geografischen Bereich." https://www.oresassets.be/en/territories-d-activities-and-sectors Ort: Ein Ort ist Einheit von bestimmter oder unbestimmter Fläche, die generell bewohnt ist. Eine Gemeinde entspricht im Allgemeinen e...

description: (Link to Metadata) The Renewable Energy Atlas of Vermont and this dataset were created to assist town energy committees, the Clean Energy Development Fund and other funders, educators, planners, policy-makers, and businesses in making informed decisions about the planning and implementation of renewable energy in their communities - decisions that ultimately lead to successful projects, greater energy security, a cleaner and healthier environment, and a better quality of life across the state. Energy flows through nature into social systems as life support. Human societies depended on renewable, solar powered energy for fuel, shelter, tools, and other items for most of our history. Today, when we flip on a light switch, turn an ignition or a water faucet, or eat a hamburger, we engage complex energy extraction systems that largely rely on non-renewable energy to power our lives. About 90% of Vermont's total energy consumption is currently generated from non-renewable energy sources. This dependency puts Vermont at considerable risk, as the peaking of world oil production, global financial instability, climate change, and other factors impact the state.; abstract: (Link to Metadata) The Renewable Energy Atlas of Vermont and this dataset were created to assist town energy committees, the Clean Energy Development Fund and other funders, educators, planners, policy-makers, and businesses in making informed decisions about the planning and implementation of renewable energy in their communities - decisions that ultimately lead to successful projects, greater energy security, a cleaner and healthier environment, and a better quality of life across the state. Energy flows through nature into social systems as life support. Human societies depended on renewable, solar powered energy for fuel, shelter, tools, and other items for most of our history. Today, when we flip on a light switch, turn an ignition or a water faucet, or eat a hamburger, we engage complex energy extraction systems that largely rely on non-renewable energy to power our lives. About 90% of Vermont's total energy consumption is currently generated from non-renewable energy sources. This dependency puts Vermont at considerable risk, as the peaking of world oil production, global financial instability, climate change, and other factors impact the state.

description: (Link to Metadata) The Renewable Energy Atlas of Vermont and this dataset were created to assist town energy committees, the Clean Energy Development Fund and other funders, educators, planners, policy-makers, and businesses in making informed decisions about the planning and implementation of renewable energy in their communities - decisions that ultimately lead to successful projects, greater energy security, a cleaner and healthier environment, and a better quality of life across the state. Energy flows through nature into social systems as life support. Human societies depended on renewable, solar powered energy for fuel, shelter, tools, and other items for most of our history. Today, when we flip on a light switch, turn an ignition or a water faucet, or eat a hamburger, we engage complex energy extraction systems that largely rely on non-renewable energy to power our lives. About 90% of Vermont's total energy consumption is currently generated from non-renewable energy sources. This dependency puts Vermont at considerable risk, as the peaking of world oil production, global financial instability, climate change, and other factors impact the state.; abstract: (Link to Metadata) The Renewable Energy Atlas of Vermont and this dataset were created to assist town energy committees, the Clean Energy Development Fund and other funders, educators, planners, policy-makers, and businesses in making informed decisions about the planning and implementation of renewable energy in their communities - decisions that ultimately lead to successful projects, greater energy security, a cleaner and healthier environment, and a better quality of life across the state. Energy flows through nature into social systems as life support. Human societies depended on renewable, solar powered energy for fuel, shelter, tools, and other items for most of our history. Today, when we flip on a light switch, turn an ignition or a water faucet, or eat a hamburger, we engage complex energy extraction systems that largely rely on non-renewable energy to power our lives. About 90% of Vermont's total energy consumption is currently generated from non-renewable energy sources. This dependency puts Vermont at considerable risk, as the peaking of world oil production, global financial instability, climate change, and other factors impact the state.

Scheduled energy interruptions aggregated by postal code.1. The information made available by E-REDES constitutes an approximation to the values taken from the system and is based on the moment in which it is collected. Given that the connection points, the electricity distribution network, and the consumption and production values themselves are naturally very dynamic, it is safeguarded that the information made available may be subject to subsequent changes and updates, with the exception of any omissions and/or occasional inaccuracies of location that the information may contain.2. In this way, E-REDES is not liable to third parties, namely, partners, service providers, contractors, users and customers, for damages that may arise as a result, direct or indirect, of the use of this Information, in particular when carrying out interventions, calculations and/or estimates, without confirming the accuracy and updating of the data, whereby it is duly noted that the consultation of this information does not affect the duty to promote a direct consultation with E-REDES in order to obtain updated information.The data provided by the E-REDES Open Data Portal is covered by open licenses (CC BY 4.0). There are no restrictions on access, under the commitment that data users cite the publisher. Therefore, we suggest that you cite the Open Data E-REDES Portal as:E-REDES – Distribuição de Eletricidade, “E-REDES Open Data Portal”. Accessed in “Data”. [Online] Available at https://e-redes.opendatasoft.com/pages/homepage/If you share on social media, please add #PortalOpenData_E_REDES

description: (Link to Metadata) The Renewable Energy Atlas of Vermont and this dataset were created to assist town energy committees, the Clean Energy Development Fund and other funders, educators, planners, policy-makers, and businesses in making informed decisions about the planning and implementation of renewable energy in their communities - decisions that ultimately lead to successful projects, greater energy security, a cleaner and healthier environment, and a better quality of life across the state. Energy flows through nature into social systems as life support. Human societies depended on renewable, solar powered energy for fuel, shelter, tools, and other items for most of our history. Today, when we flip on a light switch, turn an ignition or a water faucet, or eat a hamburger, we engage complex energy extraction systems that largely rely on non-renewable energy to power our lives. About 90% of Vermont's total energy consumption is currently generated from non-renewable energy sources. This dependency puts Vermont at considerable risk, as the peaking of world oil production, global financial instability, climate change, and other factors impact the state.; abstract: (Link to Metadata) The Renewable Energy Atlas of Vermont and this dataset were created to assist town energy committees, the Clean Energy Development Fund and other funders, educators, planners, policy-makers, and businesses in making informed decisions about the planning and implementation of renewable energy in their communities - decisions that ultimately lead to successful projects, greater energy security, a cleaner and healthier environment, and a better quality of life across the state. Energy flows through nature into social systems as life support. Human societies depended on renewable, solar powered energy for fuel, shelter, tools, and other items for most of our history. Today, when we flip on a light switch, turn an ignition or a water faucet, or eat a hamburger, we engage complex energy extraction systems that largely rely on non-renewable energy to power our lives. About 90% of Vermont's total energy consumption is currently generated from non-renewable energy sources. This dependency puts Vermont at considerable risk, as the peaking of world oil production, global financial instability, climate change, and other factors impact the state.

Monthly consumption by district, municipality, parish and voltage level; history since Nov-2020.Consumptions (active energy) that were billed since Nov-2020. The year/month refers to the period of consumption (not the time of billing).For General Data Protection Regulation (GDPR) reasons, some consumptions may appear aggregated in a category identified as "OUTROS District Name", which includes all consumption in the District that, for the reasons mentioned, cannot be made available in the respective Parish/Municipality.1. The information made available by E-REDES constitutes an approximation to the values taken from the system and is based on the moment in which it is collected. Given that the connection points, the electricity distribution network, and the consumption and production values themselves are naturally very dynamic, it is safeguarded that the information made available may be subject to subsequent changes and updates, with the exception of any omissions and/or occasional inaccuracies of location that the information may contain.2. In this way, E-REDES is not liable to third parties, namely, partners, service providers, contractors, users and customers, for damages that may arise as a result, direct or indirect, of the use of this Information, in particular when carrying out interventions, calculations and/or estimates, without confirming the accuracy and updating of the data, whereby it is duly noted that the consultation of this information does not affect the duty to promote a direct consultation with E-REDES in order to obtain updated information.The data provided by the E-REDES Open Data Portal is covered by open licenses (CC BY 4.0). There are no restrictions on access, under the commitment that data users cite the publisher. Therefore, we suggest that you cite the Open Data E-REDES Portal as:E-REDES – Distribuição de Eletricidade, “E-REDES Open Data Portal”. Accessed in “Data”. [Online] Available at https://e-redes.opendatasoft.com/pages/homepage/If you share on social media, please add #PortalOpenData_E_REDES

with the intensification of market competition and the complexity of consumer behavior, enterprises are faced with the challenge of how to accurately identify potential customers and improve user conversion rate. This paper aims to study the application of machine learning in consumer behavior prediction and precision marketing. Four models, namely support vector machine (SVM), extreme gradient boosting (XGBoost), categorical boosting (CatBoost), and backpropagation artificial neural network (BPANN), are mainly used to predict consumers’ purchase intention, and the performance of these models in different scenarios is verified through experiments. The results show that CatBoost and XGBoost have the best prediction results when dealing with complex features and large-scale data, F1 scores are 0.93 and 0.92 respectively, and CatBoost’s ROC AUC reaches the highest value of 0.985. while SVM has an advantage in accuracy rate, but slightly underperformance when dealing with large-scale data. Through feature importance analysis, we identify the significant impact of page views, residence time and other features on purchasing behavior. Based on the model prediction results, this paper proposes the specific application of optimization marketing strategies such as recommendation system, dynamic pricing and personalized advertising. Future research could improve the predictive power of the model by introducing more kinds of unstructured data, such as consumer reviews, images, videos, and social media data. In addition, the use of deep learning models, such as Transformers or Self-Attention Mechanisms, can better capture complex patterns in long time series data.

Number of Network Connection Requests completed, by municipality; Semiannual.This dataset contains information about new network connections, power increases, public lighting connections, network modifications, self-consumption connections, among others.1. The information made available by E-REDES constitutes an approximation to the values taken from the system and is based on the moment in which it is collected. Given that the connection points, the electricity distribution network, and the consumption and production values themselves are naturally very dynamic, it is safeguarded that the information made available may be subject to subsequent changes and updates, with the exception of any omissions and/or occasional inaccuracies of location that the information may contain.2. In this way, E-REDES is not liable to third parties, namely, partners, service providers, contractors, users and customers, for damages that may arise as a result, direct or indirect, of the use of this Information, in particular when carrying out interventions, calculations and/or estimates, without confirming the accuracy and updating of the data, whereby it is duly noted that the consultation of this information does not affect the duty to promote a direct consultation with E-REDES in order to obtain updated information.The data provided by the E-REDES Open Data Portal is covered by open licenses (CC BY 4.0). There are no restrictions on access, under the commitment that data users cite the publisher. Therefore, we suggest that you cite the Open Data E-REDES Portal as:E-REDES – Distribuição de Eletricidade, “E-REDES Open Data Portal”. Accessed in “Data”. [Online] Available at https://e-redes.opendatasoft.com/pages/homepage/If you share on social media, please add #PortalOpenData_E_REDES

Active energy interruptions by postal code.1. The information made available by E-REDES constitutes an approximation to the values taken from the system and is based on the moment in which it is collected. Given that the connection points, the electricity distribution network, and the consumption and production values themselves are naturally very dynamic, it is safeguarded that the information made available may be subject to subsequent changes and updates, with the exception of any omissions and/or occasional inaccuracies of location that the information may contain.2. In this way, E-REDES is not liable to third parties, namely, partners, service providers, contractors, users and customers, for damages that may arise as a result, direct or indirect, of the use of this Information, in particular when carrying out interventions, calculations and/or estimates, without confirming the accuracy and updating of the data, whereby it is duly noted that the consultation of this information does not affect the duty to promote a direct consultation with E-REDES in order to obtain updated information.The data provided by the E-REDES Open Data Portal is covered by open licenses (CC BY 4.0). There are no restrictions on access, under the commitment that data users cite the publisher. Therefore, we suggest that you cite the Open Data E-REDES Portal as:E-REDES – Distribuição de Eletricidade, “E-REDES Open Data Portal”. Accessed in “Data”. [Online] Available at https://e-redes.opendatasoft.com/pages/homepage/If you share on social media, please add #PortalOpenData_E_REDES