Buch, Englisch, 470 Seiten, Format (B × H): 155 mm x 235 mm
6th Energy Informatics Academy Conference, EI.A 2026, Beijing, China, October 14–17, 2026, Proceedings, Part I
Buch, Englisch, 470 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-032-41863-0
Verlag: Springer
The two-volume set LNCS 16981 + 16982 constitutes the proceedings of the 6th Energy Informatics Academy Conference, EI.A 2026, which took place in Beijing, China, during October 14, 2026.
The 41 full papers and 13 Short papers included in the proceedings were carefully reviewed and selected from 77 submissions. They focus on a unique perspective on how digitalization is transforming the technical, economic, and societal dimensions of modern energy systems. They were organized in topical sections as follows:
Part I: Flexibility, Forecasting and Supply in District Heating; Digital Transformation of Buildings into Active Energy Prosumers; HVAC, Thermal Comfort and Building Energy Performance; Trustworthy Data and Language Models for Energy Systems;
Part II: Probabilistic Forecasting and Decision-Making under Uncertainty; Data- and AI-Driven Energy–Climate–Economy Modeling for Mitigation–Adaptation Transitions; Industrial Systems Under Climate and Energy Uncertainty: Adaptation Readiness, Energy Resilience, and Digital Intelligence; Grid Resilience, Energy Storage and Electric Mobility; From Living Labs to Virtual Testbeds: Experimentation and Validation in Energy Informatics.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
Weitere Infos & Material
.- Flexibility, Forecasting and Supply in District Heating.
.- Population-Scale Demand-Side Load Shifting in District Heating: A Certified Aggregation Approach on Smart-Heat-Meter Data.
.- A Portable Governed MLOps Pipeline for Day-Ahead District-Heating Demand Forecasting.
.- Inertia-Aware Cumulative Heat-Demand Forecasting for District-Heated Campus Buildings.
.- Quantifying the Shared Benefits of Decentralized Thermal Energy Storage in District Heating Systems: A Feasibility Study.
.- Economic viability of Air-PVT systems compared to PV.
.- Digital Transformation of Buildings into Active Energy Prosumers.
.- Explainable Reinforcement Learning for Intelligent Battery Management in Residential Microgrids.
.- An Asynchronous Rule-Based Control Architecture for Distributed Battery Energy Arbitrage and Demand Response.
.- Techno-Economic Assessment of Residential PV and Battery Systems in a High-Latitude Electricity Market: A Case Study of Iceland.
.- Identifying Household Responses to Dynamic Pricing Through Behavioral Clustering.
.- Assessing Data Center Integration in Indian Residential Renewable Energy Community.
.- When Market and Grid Signals Disagree: Quantifying Community-Battery Dispatch Alignment in a PV-Rich Low-Voltage Feeder.
.- HVAC, Thermal Comfort and Building Energy Performance.
.- Effect of Air Intake Location on the Heating and Cooling Needs of AHUs: A Case Study from a Danish Educational Building.
.- Assessing Thermal Comfort via CFD for Classrooms in Hot, Humid Climate.
.- Data-Driven Room Occupancy Estimation Using Environmental Sensor Measurements.
.- A Data Driven HVAC System Digital Twin for Assessment of Fan Speed Reduction Under Thermal Comfort and Ventilation Constraints.
.- Dynamic Model Selection for Energy Load Forecasting: A Comparative Study of Bandit, Reinforcement Learning, and Contextual Strategies.
.- Comparative Assessment of EED and pygfunction for Long-Term Brine Temperature Prediction in Ground Source Heat Pump Systems.
.- Data-driven feedforward policy gradient for room temperature control.
.- Forecasting the Total Consumption of an Office Building With Diverse Sensor Data.
.- Trustworthy Data and Language Models for Energy Systems.
.- Leakage-Aware LLM-Assisted Preprocessing for Energy Time Series: A Photovoltaic Imputation Case Study.
.- Do Ontologies Help Large Language Models Answer Building Questions? A Study Across Model Scales and Semantic Representations.
.- Closed-Book Probing of Electricity-Market Role Knowledge in Language Models: The ENTSO-E Harmonised Role Model.
.- A Hybrid Load Synthesizing Model Applied to Distribution Transformer Thermal Degradation.
.- CONFIA: A Modular Framework for Rigorous Energy Forecasting Evaluation.
.- Reliable Natural-Language Interaction with CityGML through Hybrid Retrieval and Spatial Integrity Verification.
.- An AI-Driven Transparency Database for Cross-National Comparison of European Electricity Tariffs.
.- Beyond FedAvg: Aggregation Strategies for Federated Anomaly Detection in Smart Meter Data.
.- Federated Unlearning in Agentic Energy Systems: Security and Governance Implications.
