Grey-box modeling and application for building energy simulations-A critical review
Grey-box modeling, as one of the three fundamental modeling techniques for building
energy models, has many advantages compared with black-box modeling and white-box …
energy models, has many advantages compared with black-box modeling and white-box …
Heating and cooling loads forecasting for residential buildings based on hybrid machine learning applications: A comprehensive review and comparative analysis
A Moradzadeh, B Mohammadi-Ivatloo, M Abapour… - Ieee …, 2021 - ieeexplore.ieee.org
Prediction of building energy consumption plays an important role in energy conservation,
management, and planning. Continuously improving and enhancing the performance of …
management, and planning. Continuously improving and enhancing the performance of …
A novel improved model for building energy consumption prediction based on model integration
R Wang, S Lu, W Feng - Applied Energy, 2020 - Elsevier
Building energy consumption prediction plays an irreplaceable role in energy planning,
management, and conservation. Constantly improving the performance of prediction models …
management, and conservation. Constantly improving the performance of prediction models …
Implementation of a price-driven demand response in a distributed energy system with multi-energy flexibility measures
J Niu, Z Tian, J Zhu, L Yue - Energy Conversion and Management, 2020 - Elsevier
Distributed energy systems are a promising integrated energy technology due to their
energy efficiency and environment benefits. However, the increasing complexity of …
energy efficiency and environment benefits. However, the increasing complexity of …
An artificial intelligence (AI)-driven method for forecasting cooling and heating loads in office buildings by integrating building thermal load characteristics
J Zhao, X Yuan, Y Duan, H Li, D Liu - Journal of Building Engineering, 2023 - Elsevier
Due to the thermal inertia of building envelope and random uncertainty of occupant
behaviors, real-time and accurate forecasting for building cooling and heating loads is not …
behaviors, real-time and accurate forecasting for building cooling and heating loads is not …
An improved decentralized scheme for incentive-based demand response from residential customers
Demand response is becoming increasingly important due to the high penetration of
intermittent and variable renewable energy and electric vehicles in power systems. Real …
intermittent and variable renewable energy and electric vehicles in power systems. Real …
A scalable and distributed algorithm for managing residential demand response programs using alternating direction method of multipliers (ADMM)
For effective engagement of residential demand-side resources and to ensure efficient
operation of distribution networks, we must overcome the challenges of controlling and …
operation of distribution networks, we must overcome the challenges of controlling and …
Similarity-based grouping method for evaluation and optimization of dataset structure in machine-learning based short-term building cooling load prediction without …
Short-term building cooling load prediction plays an import role in the building energy
management. The concept of similar day approach is receiving special attention as an …
management. The concept of similar day approach is receiving special attention as an …
Development of novel PMV-based HVAC control strategies using a mean radiant temperature prediction model by machine learning in Kuwaiti climate
Kuwait is one of the hottest regions globally, where air conditioners (ACs) are indispensable
for indoor thermal environment. However, the AC energy consumption has reached …
for indoor thermal environment. However, the AC energy consumption has reached …
Model-based and data-driven HVAC control strategies for residential demand response
The implementations of residential demand response (DR) based on heating, ventilation,
and air conditioning (HVAC) are inseparable from effective control algorithms for …
and air conditioning (HVAC) are inseparable from effective control algorithms for …