All Outputs (26)

An integrated passive and active retrofitting approach toward minimum whole-life carbon footprint (2023)
Journal Article
Luo, X. J. (2023). An integrated passive and active retrofitting approach toward minimum whole-life carbon footprint. Energy and Buildings, 295, Article 113337. https://doi.org/10.1016/j.enbuild.2023.113337

The state-of-the-art retrofitting strategies generally use either passive or active measures to reduce carbon emissions during its operating stage. The coordination among a range of passive and active energy devices is not considered while the concep... Read More about An integrated passive and active retrofitting approach toward minimum whole-life carbon footprint.

Network effects and store-of-value features in the cryptocurrency market (2023)
Journal Article
Bakhtiar, T., Luo, X., & Adelopo, I. (2023). Network effects and store-of-value features in the cryptocurrency market. Technology in Society, 74, Article 102320. https://doi.org/10.1016/j.techsoc.2023.102320

It is important to determine the network effects and store-of-value feature of cryptocurrencies due to the argument that it could be considered as a new ‘asset class’. Current studies on cryptocurrencies' network effects mainly focused on using Metca... Read More about Network effects and store-of-value features in the cryptocurrency market.

A hybrid multiple sensor fault detection, diagnosis and reconstruction algorithm for chiller plants (2023)
Journal Article
Fong, K. F., Lee, C. K., Leung, M. K. H., Sun, Y. J., Zhu, G., Baek, S. H., …Leung, H. S. Y. (2023). A hybrid multiple sensor fault detection, diagnosis and reconstruction algorithm for chiller plants. Journal of Building Performance Simulation, 16(5), 588-608. https://doi.org/10.1080/19401493.2023.2189303

In a chiller plant, primary or critical sensors are used to control the system operation while secondary sensors are installed to monitor the performance/health of individual equipment. Current sensor fault detection and diagnosis (SFDD) approaches a... Read More about A hybrid multiple sensor fault detection, diagnosis and reconstruction algorithm for chiller plants.

Retrofitting existing office buildings towards life-cycle net-zero energy and carbon (2022)
Journal Article
Luo, X. (2022). Retrofitting existing office buildings towards life-cycle net-zero energy and carbon. Sustainable Cities and Society, 83, Article 103956. https://doi.org/10.1016/j.scs.2022.103956

Background Energy devices for achieving net-zero operating energy and carbon generally entails additional embodied energy and carbon during the production and disposal stages. For a building to be considered as truly life-cycle net-zero, the energy... Read More about Retrofitting existing office buildings towards life-cycle net-zero energy and carbon.

Life cycle optimisation of building retrofitting considering climate change effects (2022)
Journal Article
Luo, X. J., & Oyedele, L. O. (2022). Life cycle optimisation of building retrofitting considering climate change effects. Energy and Buildings, 258, 111830. https://doi.org/10.1016/j.enbuild.2022.111830

Novelty: Climate change has significant impacts on building energy performance. A novel life cycle optimisation strategy is developed for determining optimal retrofitting solutions for office buildings with climate change effects taken into considera... Read More about Life cycle optimisation of building retrofitting considering climate change effects.

A self-adaptive deep learning model for building electricity load prediction with moving horizon (2022)
Journal Article
Luo, X., & Oyedele, L. (2022). A self-adaptive deep learning model for building electricity load prediction with moving horizon. Machine Learning with Applications, 7, Article 100257. https://doi.org/10.1016/j.mlwa.2022.100257

A self-adaptive deep learning model powered by ranking selection-based particle swarm optimisation (RSPSO) is developed to predict electricity load in buildings with moving horizons. The main features of the load prediction model include its self-ada... Read More about A self-adaptive deep learning model for building electricity load prediction with moving horizon.

Integrated life-cycle optimisation and supply-side management for building retrofitting (2021)
Journal Article
Luo, X., & Oyedele, L. O. (2022). Integrated life-cycle optimisation and supply-side management for building retrofitting. Renewable and Sustainable Energy Reviews, 154, Article 111827. https://doi.org/10.1016/j.rser.2021.111827

Building retrofitting is a powerful approach to enhance building energy performance. The net-zero ambition urges the need to renovate building energy system in view of the life-cycle optimal, to address climate and environmental challenges. Existing... Read More about Integrated life-cycle optimisation and supply-side management for building retrofitting.

Assessment and optimisation of life cycle environment, economy and energy for building retrofitting (2021)
Journal Article
Luo, X. J., & Oyedele, L. O. (2021). Assessment and optimisation of life cycle environment, economy and energy for building retrofitting. Energy for Sustainable Development, 65, 77-100. https://doi.org/10.1016/j.esd.2021.10.002

Building retrofitting plays a vital role in realising net-zero carbon ambition. Conventional retrofitting solutions are generally based upon decreasing operating energy usage or corresponding costs. However, many of these would increase the embodied... Read More about Assessment and optimisation of life cycle environment, economy and energy for building retrofitting.

Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm (2021)
Journal Article
Luo, X., & Oyedele, L. O. (2021). Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm. Advanced Engineering Informatics, 50, Article 101357. https://doi.org/10.1016/j.aei.2021.101357

The real-world building can be regarded as a comprehensive energy engineering system; its actual energy consumption depends on complex affecting factors, including various weather data and time signature. Accurate energy consumption forecasting and e... Read More about Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm.

A data-driven life-cycle optimisation approach for building retrofitting: A comprehensive assessment on economy, energy and environment (2021)
Journal Article
Luo, X. J., & Oyedele, L. O. (2021). A data-driven life-cycle optimisation approach for building retrofitting: A comprehensive assessment on economy, energy and environment. Journal of Building Engineering, 43, Article 102934. https://doi.org/10.1016/j.jobe.2021.102934

A novel data-driven life-cycle optimisation approach is proposed for building retrofitting. The innovation points include big-data information, integrated retrofitting design, and life-cycle optimisation through a comprehensive assessment of the econ... Read More about A data-driven life-cycle optimisation approach for building retrofitting: A comprehensive assessment on economy, energy and environment.

Life cycle assessment approach for renewable multi-energy system: A comprehensive analysis (2020)
Journal Article
Luo, X., Oyedele, L. O., Owolabi, H. A., Bilal, M., Ajayi, A. O., & Akinade, O. O. (2020). Life cycle assessment approach for renewable multi-energy system: A comprehensive analysis. Energy Conversion and Management, 224, Article 113354. https://doi.org/10.1016/j.enconman.2020.113354

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
Luo, X. J., Oyedele, L. O., Ajayi, A. O., Akinade, O. O., Delgado, J. M. D., Owolabi, H. A., & Ahmed, A. (2020). Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings. Energy and AI, 2, Article 100015. https://doi.org/10.1016/j.egyai.2020.100015

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
Luo, X. J., Oyedele, L. O., Ajayi, A. O., & Akinade, O. O. (2020). Comparative study of machine learning-based multi-objective prediction framework for multiple building energy loads. Sustainable Cities and Society, 61, Article 102283. https://doi.org/10.1016/j.scs.2020.102283

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
Luo, X. J., Oyedele, L. O., Ajayi, A. O., Akinade, O. O., Owolabi, H. A., & Ahmed, A. (2020). Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings. Renewable and Sustainable Energy Reviews, 131, Article 109980. https://doi.org/10.1016/j.rser.2020.109980

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
Luo, X. J. (2020). A novel clustering-enhanced adaptive artificial neural network model for predicting day-ahead building cooling demand. Journal of Building Engineering, 32, Article 101504. https://doi.org/10.1016/j.jobe.2020.101504

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
Luo, X. J., Oyedele, L. O., Akinade, O. O., & Ajayi, A. O. (2020). Two-stage capacity optimization approach of multi-energy system considering its optimal operation. Energy and AI, 1, Article 100005. https://doi.org/10.1016/j.egyai.2020.100005

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
Luo, X. J., Oyedele, L. O., Akinade, O., & Ajayi, A. O. (2020). 3D pattern identification approach for cooling load profiles in different buildings. Journal of Building Engineering, 31, Article 101339. https://doi.org/10.1016/j.jobe.2020.101339

© 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
Luo, X. J., Oyedele, L. O., Ajayi, A. O., Monyei, C. G., Akinade, O. O., & Akanbi, L. A. (2019). Development of an IoT-based big data platform for day-ahead prediction of building heating and cooling demands. Advanced Engineering Informatics, 41, Article 100926. https://doi.org/10.1016/j.aei.2019.100926

© 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.

Benchmarks for energy access: Policy vagueness and incoherence as barriers to sustainable electrification of the global south (2019)
Journal Article
Monyei, C. G., Oyedele, L. O., Akinade, O. O., Ajayi, A. O., & Luo, X. J. (2019). Benchmarks for energy access: Policy vagueness and incoherence as barriers to sustainable electrification of the global south. Energy Research and Social Science, 54, 113-116. https://doi.org/10.1016/j.erss.2019.04.005

© 2019 The unavailability of tangible policy benchmarks continues to mitigate against sustainable electrification in the global south. Furthermore, incoherent policy benchmarks as to what should constitute clean energy allow for varying interpretatio... Read More about Benchmarks for energy access: Policy vagueness and incoherence as barriers to sustainable electrification of the global south.

Development of integrated demand and supply side management strategy of multi-energy system for residential building application (2019)
Journal Article
Luo, X. J., & Fong, K. F. (2019). Development of integrated demand and supply side management strategy of multi-energy system for residential building application. Applied Energy, 242, 570-587. https://doi.org/10.1016/j.apenergy.2019.03.149

© 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.