Outputs (25)

Life cycle assessment approach for renewable multi-energy system: A comprehensive analysis (2020)
Journal Article

In response to the gradual degradation of natural sources, there is a growing interest in adopting renewable resources for various building energy supply. In this study, a comprehensive life cycle assessment approach is proposed for a renewable multi... Read More about Life cycle assessment approach for renewable multi-energy system: A comprehensive analysis.

Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings (2020)
Journal Article

A genetic algorithm-determined deep feedforward neural network architecture (GA-DFNN) is proposed for both day-ahead hourly and week-ahead daily electricity consumption of a real-world campus building in the United Kingdom. Due to the comprehensive r... Read More about Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings.

Comparative study of machine learning-based multi-objective prediction framework for multiple building energy loads (2020)
Journal Article

Buildings are one of the significant sources of energy consumption and greenhouse gas emission in urban areas all over the world. Lighting control and building integrated photovoltaic (BIPV) are two effective measures in reducing overall primary ener... Read More about Comparative study of machine learning-based multi-objective prediction framework for multiple building energy loads.

Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings (2020)
Journal Article

Accurate forecast of energy consumption is essential in building energy management. Owing to the variation of outdoor weather condition among different seasons, year-round historical weather profile is needed to investigate its feature thoroughly. Da... Read More about Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings.

A novel clustering-enhanced adaptive artificial neural network model for predicting day-ahead building cooling demand (2020)
Journal Article

To accurately predict hourly day-ahead building cooling demand, year-round historical weather profile needs to be evaluated. The daily weather profiles among different time periods result in various features of historical datasets. The different appr... Read More about A novel clustering-enhanced adaptive artificial neural network model for predicting day-ahead building cooling demand.

Two-stage capacity optimization approach of multi-energy system considering its optimal operation (2020)
Journal Article

With the depletion of fossil fuel and climate change, multi-energy systems have attracted widespread attention in buildings. Multi-energy systems, fuelled by renewable energy, including solar and biomass energy, are gaining increasing adoption in com... Read More about Two-stage capacity optimization approach of multi-energy system considering its optimal operation.

3D pattern identification approach for cooling load profiles in different buildings (2020)
Journal Article

© 2020 Elsevier Ltd Building energy conservation has gained increasing concern owing to its large portion of energy consumption and great potential of energy saving. In-depth understanding of representative patterns of daily cooling load profile will... Read More about 3D pattern identification approach for cooling load profiles in different buildings.

Development of an IoT-based big data platform for day-ahead prediction of building heating and cooling demands (2019)
Journal Article

© 2019 Elsevier Ltd The emerging technologies of the Internet of Things (IoT) and big data can be utilised to derive knowledge and support applications for energy-efficient buildings. Effective prediction of heating and cooling demands is fundamental... Read More about Development of an IoT-based big data platform for day-ahead prediction of building heating and cooling demands.

Development of integrated demand and supply side management strategy of multi-energy system for residential building application (2019)
Journal Article

© 2019 Elsevier Ltd The multi-energy system that contains the highly coupled energy supply equipment units can be adopted to simultaneously satisfy the cooling, heating and electrical energy demands. Owing to the complex nature of multiple supplies a... Read More about Development of integrated demand and supply side management strategy of multi-energy system for residential building application.

Development of clustering-based sensor fault detection and diagnosis strategy for chilled water system (2019)
Journal Article

This paper presents a new clustering-based sensor fault detection and diagnosis (SFDD) strategy for chilled water system. For data clustering, k-means algorithm was used and the optimal quantity of clusters was determined by Davis-Bouldin value. With... Read More about Development of clustering-based sensor fault detection and diagnosis strategy for chilled water system.