A comparative evaluation on the case for the implementation of building integrated photovoltaic/thermal (BIPV/T) air based systems on a typical mid-rise commercial building in Canadian cities

Hasan, Javeriya; Fung, Alan S.; Horvat, Miljana

doi:10.1016/j.jobe.2021.103325

Cited by 7 publications

(2 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The International Energy Agency (IEA) reported that solar energy accounted for 45% of the total renewable energy sources in 2016 (a 50% increase compared to 2015) [10]. However, even though PV power is the most widely used renewable energy source in residential, commercial, and industrial fields [11][12][13][14][15], PV power output is typically intermittent owing to its dependence on various environmental factors, such as solar irradiance, PV module surface temperature, and sky conditions, which result in unstable power production. Therefore, accurate forecasting of PV power output based on this is essential for managing an hourly electricity balance in grid-connected BIPV (Building-Integrated Photovoltaic) systems [16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach for Day-Ahead Hourly Building-Integrated Photovoltaic Power Prediction by Using Feature Engineering and Simple Weather Forecasting Service

Jeong,

Lee,

Chae

2023

Energies

View full text Add to dashboard Cite

Although the accuracy of short-term prediction of building-integrated photovoltaics is essential to making an optimal decision on the management of the generated electricity, the weather forecasting service in many countries provides insufficient features for improving the prediction accuracy of the photovoltaics power output. This study suggests a machine learning model incorporated with feature engineering to improve the prediction performance of day-ahead hourly power outputs using a simple weather forecast service. A new synthetic feature, the modified sky condition, is derived to infer onsite sky condition and solar irradiation, which is not supported by the typical weather forecasting services. It evaluated the prediction performance with different training and hyper-parameter conditions for 60 days. By using the derived modified sky condition, the model outperformed other predictor configurations in most daily sky conditions; particularly, the accuracy improved by more than 50% on overcast days compared to when it used the original weather forecasting service data. The result demonstrates the feasibility and ability of the model to enable more efficient energy management of building-integrated photovoltaic power output in buildings without an onsite weather station, thus contributing toward the optimized dispatch of the integrated electricity energy storage system and other distributed energy resources.

show abstract

Section: Introductionmentioning

confidence: 99%

A Novel Approach for Day-Ahead Hourly Building-Integrated Photovoltaic Power Prediction by Using Feature Engineering and Simple Weather Forecasting Service

Jeong,

Lee,

Chae

2023

Energies

View full text Add to dashboard Cite

show abstract

“…On-site energy generation systems from renewable sources may include photovoltaic and photovoltaic/thermal systems [116], wind turbines [117], solar collectors [118], as well as organic Rankine cycles [114,119] (mainly used for waste-heat recovery at the moment [120]).…”

mentioning

confidence: 99%

A Critical Perspective on Current Research Trends in Building Operation: Pressing Challenges and Promising Opportunities

Saloux,

Zhang,

Candanedo

2023

Buildings

View full text Add to dashboard Cite

Despite the development of increasingly efficient technologies and the ever-growing amount of available data from Building Automation Systems (BAS) and connected devices, buildings are still far from reaching their performance potential due to inadequate controls and suboptimal operation sequences. Advanced control methods such as model-based controls or model-based predictive controls (MPC) are widely acknowledged as effective solutions for improving building operation. Although they have been well-investigated in the past, their widespread adoption has yet to be reached. Based on our experience in this field, this paper aims to provide a broader perspective on research trends on advanced controls in the built environment to researchers and practitioners, as well as to newcomers in the field. Pressing challenges are explored, such as inefficient local controls (which must be addressed in priority) and data availability and quality (not as good as expected, despite the advent of the digital era). Other major hurdles that slow down the large-scale adoption of advanced controls include communication issues with BAS and lack of guidelines and standards tailored for controls. To encourage their uptake, cost-effective solutions and successful case studies are required, which need to be further supported by better training and engagement between the industry and research communities. This paper also discusses promising opportunities: while building modelling is already playing a critical role, data-driven methods and data analytics are becoming a popular option to improve buildings controls. High-performance local and supervisory controls have emerged as promising solutions. Energy flexibility appears instrumental in achieving decarbonization targets in the built environment.

show abstract

Techno-economic evaluation of a hybrid photovoltaic system with hot/cold water storage for poly-generation in a residential building

et al. 2023

View full text Add to dashboard Cite

A comparative evaluation on the case for the implementation of building integrated photovoltaic/thermal (BIPV/T) air based systems on a typical mid-rise commercial building in Canadian cities

Cited by 7 publications

References 25 publications

A Novel Approach for Day-Ahead Hourly Building-Integrated Photovoltaic Power Prediction by Using Feature Engineering and Simple Weather Forecasting Service

A Novel Approach for Day-Ahead Hourly Building-Integrated Photovoltaic Power Prediction by Using Feature Engineering and Simple Weather Forecasting Service

A Critical Perspective on Current Research Trends in Building Operation: Pressing Challenges and Promising Opportunities

Techno-economic evaluation of a hybrid photovoltaic system with hot/cold water storage for poly-generation in a residential building

Contact Info

Product

Resources

About