Buch, Englisch, 426 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 II
Buch, Englisch, 426 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-032-41866-1
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 Daten / Datenbanken Data Mining
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
Weitere Infos & Material
.- Probabilistic Forecasting and Decision-Making under Uncertainty.
.- Uncertainty Aware Hybrid Inflow Forecasting with Probabilistic Dynamic HBV Parameters.
.- Calibrated Two-Stage Probabilistic Forecasting for the Nordic mFRR Energy Activation Market.
.- Dynamic Tariff Design for Demand-Side Flexibility: A Regime-Switching Approach to Consumption Forecasting in Distribution Grids.
.- Energy storage selection with Racing.
.- Technical Indicators for Load Pattern Recognition: An Automated Feature Engineering Framework.
.- Data- and AI-Driven Energy–Climate–Economy Modeling for Mitigation–Adaptation Transitions.
.- Approximately 70% of the footprint of utility-scale photovoltaics in China is aligned with biodiversity conservation.
.- When EVs Charge Matters - Steering Charging into India’s Midday Solar Surplus.
.- Towards Responsible and Sustainable Growth of AI Using a Decoupling Approach.
.- Industrial Systems Under Climate and Energy Uncertainty: Adaptation Readiness, Energy Resilience, and Digital Intelligence.
.- Hybrid Modelling of an Industrial Malt Drying Kiln.
.- A Proof-of-Concept Framework for Energy Pathway Assessment of Diverse Pyrolysis Feedstocks.
.- STREAM: An Objective-Driven and Uncertainty-Aware Framework for Industrial Energy Data Acquisition.
.- Energy-Oriented Resource Dispatching under Industrial Data Constraints: A Simulation-Based Evaluation in Foundry Production.
.- Data-Driven Fault Detection and Energy Optimization in Supermarket Refrigeration: A Multi-Site Pilot Study.
.- TIMES Compatible Physics-Based Surrogate Industrial Modelling for the Refinery and Petrochemical Sector.
.- Climate-Informed Process Safety (CIPS): A Framework for Integrating Climate Intelligence into Industrial Risk Management.
.- Grid Resilience, Energy Storage and Electric Mobility.
.- Action-Masked Proximal Policy Optimization for Critical-Load Restoration in Distribution Grids with Grid-Forming Storage.
.- PLEXOS Based Contingency Analysis of the Jeju Island Power System.
.- Operating-Condition Boundaries for the Selection of New and Second-Life Batteries in Stationary Energy Storage.
.- The more Effective Energy Shift Algorithm (mEfES).
.- Reinforcement Learning vs. MILP: Benchmarking a User-centered optimization agent for emissions-aware V2G Energy Arbitrage.
.- From Living Labs to Virtual Testbeds: Experimentation and Validation in Energy Informatics.
.- Traceable Data-Quality Assurance for Building IoT Digital Threads.
.- CityGML-Based Scene Graphs for Spatially Grounded Sensor-Aware Building Digital Twins.
.- Congestion control for actively steered power flows in the Energy Packet Grid.
.- Cloud-Native Orchestration of Agent-Based Simulations for Energy Systems Research.
.- From Models to Meaning in Practice - Demonstrating Reflexive Modelling Through a Nordic Volt-Var Optimization Study.
.- Developing a Validation Framework for Virtual Home Energy Labelling: Insights from Stakeholder Interviews and a Literature Review.
