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An Empirical Comparison of a Calibrated White-box versus multiple LSTM Black-box Building Energy Models
Building energy simulation plays a critical role in establishing the impact of new energy
conservation measures (ECMs) in buildings, in recent years it has become a go-to tool when …
conservation measures (ECMs) in buildings, in recent years it has become a go-to tool when …
An advanced fractional order method for temperature control
Temperature control in buildings has been a highly studied area of research and interest
since it affects the comfort of occupants. Commonly, temperature systems like centralized air …
since it affects the comfort of occupants. Commonly, temperature systems like centralized air …
Energy Management in Buildings: Lessons Learnt for Modeling and Advanced Control Design
This paper presents a comparative analysis of different modeling and control techniques that
can be used to tackle the energy efficiency and management problems in buildings. Multiple …
can be used to tackle the energy efficiency and management problems in buildings. Multiple …
Multi-Physics and Artificial Intelligence Models for Digital Twin Implementations of Residential Electric Loads
Heating, ventilation, and air-conditioning (HVAC) and electric water heating (EWH)
represent residential loads. Simulating these appliances for electric load forecasting …
represent residential loads. Simulating these appliances for electric load forecasting …
Dynamic modeling of smart buildings energy consumption: A cyber-physical fusion approach
Energy consumption modeling constitutes an imperative step towards improving energy
efficiency of smart buildings. In this context, conventional static modeling methods are not …
efficiency of smart buildings. In this context, conventional static modeling methods are not …
Cluster-based Energy Load Profiling on Residential Smart Buildings
Percentage of population living in cities is expected to reach 60% by 2030, accounting for
60%-80% of world annual energy needs and making the impact of energy efficient solutions …
60%-80% of world annual energy needs and making the impact of energy efficient solutions …
Machine Learning Techniques for Prediction of Electricity Consumption in Buildings
G Blaszczyk - 2022 - norma.ncirl.ie
Energy use in buildings is responsible for 40% of total global energy consumption. With this
in mind, it is imperative to focus on application of that energy to the most efficient use. This …
in mind, it is imperative to focus on application of that energy to the most efficient use. This …
Capability evaluation of deep learning for time-series prediction in medical packaging production
V Frossard - 2020 - repositum.tuwien.at
With the increasing production volatility in the power grids due to renewable energy sources,
an exact and individualized energy demand forecast of industrial customers is becoming …
an exact and individualized energy demand forecast of industrial customers is becoming …