Energy Informatics 4th Energy Informatics Academy Conference, EI.A 2024, Kuta, Bali, Indonesia, October 23–25, 2024, Proceedings, Part I
Produktdetaljer
The two-volume set LNCS 15271 and 15272 constitutes the proceedings of the 4th Energy Informatics Academy Conference, EI.A 2024, held in Kuta, Bali, Indonesia, during October 23–25, 2024.
The 40 full papers and 8 short papers included in these proceedings were carefully reviewed and selected from 64 submissions. They are categorized under the topical sections as follows:
Part I: IoT Edge Computing, and Software Innovations in Energy, Big Data Analytics and Cybersecurity in Energy, Digital Twin Technology and Energy Simulations, Energy data and consumer behaviors, and Digitalization of District Heating and Cooling Systems.
Part II: Smart Buildings and Energy Communities, Energy Pricing, Trading, and Market Dynamics, Demand Flexibility and Energy Conservation Strategies, Optimization of Energy Systems and Renewable Integration and Energy System Resilience and Reliability.
Chapter “Automation Level Taxonomy for Time Series Forecasting Services: Guideline for Real-World Smart Grid Applications” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
IoT Edge Computing, and Software Innovations in Energy.- Scheduling Electric Currents in Converter-Dominated Power Grids with Time Slotted Energy Packets.- Symbiosis A Web Based Decision Support Tool for Achieving Symbiosis in Industrial Parks.- A Cost Effective Edge Computing Gateway for Smart Buildings.- Leveraging Internet of Things Network Metadata for Cost Effective Automatic Smart Building Visualization.- Process to Market A Web based Evaluation Tool for Electricity Market Participation.- IoT Based Smart Air Ventilation and Energy Management System.- Big Data Analytics and Cybersecurity in Energy.- Leveraging Open Data for Energy Source Selection in Bi Valent Industrial Processes.- Legal overview of latest developments in the Energy Sector regarding data protection and cybersecurity.- Energy Data Collection Protocol A Case Study on the ADRENALIN Project.- DataPro A Standardized Data Understanding and Processing Procedure A Case Study of an Eco-driving Project.- Detection of Municipal Heat Plan Documents Using Semantic Recognition Methods.- Digital Twin Technology and Energy Simulations.- Challenges in Transitioning from Co-Simulation to Practical Application A Case Study on Economic Emission Dispatch in a Greenhouse Compartment.- Multi Agent Based Simulation for Investigating Centralized Charging Strategies and their Impact on Electric Vehicle Home Charging Ecosystem.- Leveraging Digital Twins for Sustainable District Heating A Study on Waste Heat from Power to X Plants.- Hardware in the Loop Based Validation of Distribution System Control Applications with Grid Operators Customer and Market Participants.- Geospatial Semantic Enriched Digital Twin with Logical Reasoning Rules for Managing Control Loops.- Data Driven Digital Twin for Foundry Production Process Facilitating Best Practice Operations Investigation and Impact Analysis.- Energy data and consumer behaviors.- Automation level taxonomy for time series forecasting services Guideline for real world smart grid applications.- Enhanced Consumer Segmentation through Load Profile Analysis Using Auto encoder and K shape Cluster.- Occupants experiencing energy poverty Where are they in energy datasets and Time Use Surveys.- Extracting Daily Aggregate Load Profiles from Monthly Consumption.- Digitalization of District Heating and Cooling Systems.- Digitalization of District Heating Transforming Heat Networks for a Sustainable Future.- Fault detection in district heating substations overview of real life faults in residential heating installations.- Multi agent based modeling for investigating excess heat utilization from electrolyzer production to district heating network.
Chapter “Automation Level Taxonomy for Time Series Forecasting Services: Guideline for Real-World Smart Grid Applications” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.