Improved energy management of chiller system with AI-based regression

Article Construction & Building Technology

Short-term cooling and heating loads forecasting of building district energy system based on data-driven models

Hanfei Yu et al.

Summary: Accurate forecasting of cooling and heating loads is critical for optimizing energy usage and planning in building district energy systems. This study develops a framework and evaluates multiple data-driven models for load prediction. The results show improved accuracy and interpretability when an attention mechanism is introduced.

ENERGY AND BUILDINGS (2023)

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Article Construction & Building Technology

A novel Transformer-based network forecasting method for building cooling loads

Long Li et al.

Summary: Accurate building cooling load forecasting technology is crucial for cooling equipment management and scheduling optimization. This paper proposes a building load prediction model based on a transformer network to improve the accuracy of building load prediction. Compared with other methods, the proposed model achieves the best prediction accuracy and stability.

ENERGY AND BUILDINGS (2023)

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Review Energy & Fuels

Building energy simulation and its application for building performance optimization: A review of methods, tools, and case studies

Yiqun Pan et al.

Summary: As one of the most important technologies for carbon-mitigation in the building sector, building performance simulation (BPS) has played an increasingly important role with the support of building energy modelling (BEM) technology. This paper reviews the application of BEM at different scales and stages, providing insights into its objectives, frameworks, modelling methods, and applicability. The paper also discusses future research opportunities and recommendations for integrating BEM with other technologies.

ADVANCES IN APPLIED ENERGY (2023)

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Article Construction & Building Technology

Investigation of different cooling tower fan control strategies using COP of actual chillers and calibrated models of actual cooling towers and fans

Gang Wang et al.

Summary: This paper reexamines the fan control strategies for cooling towers and finds that the optimal fan speed is significantly affected by the chiller load. It recommends a simplified optimal speed control method by resetting the setpoint.

ENERGY AND BUILDINGS (2022)

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Article Computer Science, Artificial Intelligence

Multicondition operation fault detection for chillers based on global density-weighted support vector data description

Kuiliang Chen et al.

Summary: This study proposes a method based on global density-weighted support vector data description (GDW-SVDD) to detect chiller faults, which can effectively improve fault detection accuracy and reduce false alarm rate. Experimental results show that compared to conventional methods and other methods, this approach has significant advantages in fault detection accuracy.

APPLIED SOFT COMPUTING (2021)

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Article Computer Science, Artificial Intelligence

A data-driven approach to simultaneous fault detection and diagnosis in data centers

Sahar Asgari et al.

Summary: A rapid and accurate FDD strategy for data center cooling systems is proposed, which uses data-driven fault classifiers to predict multiple simultaneous faults, and the effect of adding Gaussian white noise to training data is discussed, showing high accuracy even in low noise environments.

APPLIED SOFT COMPUTING (2021)

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Article Biochemistry & Molecular Biology