Thermal comfort and building energy consumption implications - A review

The importance of landscape and heritage recording and documentation with optical remote sensing sensors is well recognized at international level. The continuous development of new sensors, data capture methodologies and multi-resolution 3D representations, contributes significantly to the digital 3D documentation, mapping, conservation and representation of landscapes and heritages and to the growth of research in this field. This article reviews the actual optical 3D measurement sensors and 3D modeling techniques, with their limitations and potentialities, requirements and specifications. Examples of 3D surveying and modeling of heritage sites and objects are also shown throughout the paper.

https://www.mdpi.com/2072-4292/3/6/1104/pdf

Heritage Recording and 3D Modeling with Photogrammetry and 3D Scanning

To mitigate the impact of climate change and global warming, the use of renewable energies is increasing day by day significantly. A considerable amount of electricity is generated from renewable energy sources since the last decade. Among the potential renewable energies, photovoltaic (PV) has experienced enormous growth in electricity generation. A large number of PV systems have been installed in on-grid and off-grid systems in the last few years. The number of PV systems will increase rapidly in the future due to the policies of the government and international organizations, and the advantages of PV technology. However, the variability of PV power generation creates different negative impacts on the electric grid system, such as the stability, reliability, and planning of the operation, aside from the economic benefits. Therefore, accurate forecasting of PV power generation is significantly important to stabilize and secure grid operation and promote large-scale PV power integration. A good number of research has been conducted to forecast PV power generation in different perspectives. This paper made a comprehensive and systematic review of the direct forecasting of PV power generation. The importance of the correlation of the input-output data and the preprocessing of model input data are discussed. This review covers the performance analysis of several PV power forecasting models based on different classifications. The critical analysis of recent works, including statistical and machine-learning models based on historical data, is also presented. Moreover, the strengths and weaknesses of the different forecasting models, including hybrid models, and performance matrices in evaluating the forecasting model, are considered in this research. In addition, the potential benefits of model optimization are also discussed.

Forecasting of photovoltaic power generation and model optimization: A review

Introducing a new hobby for other people may inspire them to join with you. Reading, as one of mutual hobby, is considered as the very easy hobby to do. But, many people are not interested in this hobby. Why? Boring is the reason of why. However, this feel actually can deal with the book and time of you reading. Yeah, one that we will refer to break the boredom in reading is choosing the myth of the paperless office as the reading material.

The Myth of the Paperless Office

Urban building energy modeling – A review of a nascent field

https://architecture.mit.edu/sites/architecture.mit.edu/files/attachments/lecture/large%20scale%20integration%20of%20photovoltaics.pdf

Large scale integration of photovoltaics in cities

Combining system dynamics model, GIS and 3D visualization in sustainability assessment of urban residential development

Combining GIS-based statistical and engineering urban heat consumption models: Towards a new framework for multi-scale policy support

One dimensional convolutional neural network architectures for wind prediction

An urban energy management tool was developed, which is able to predict the heating energy demand of urban districts and analyze strategies for improving building standards. Building models of different Levels of Detail are investigated and analyzed according to their suitability for forecasting energy demand. Based on the specific 3D city model, an input file is generated, which can be read by the building simulation model. Special focus is put on a method for modeling the heating energy demand of the buildings with the fewest input parameters possible, but one which will give reliable forecast results. A simple transmission heat loss method and an energy-balance method were tested. In both cases, there was a good correlation between the measured and calculated annual values for a case study area of over 700 buildings in Ostfildern, Germany. The results also show that a 3D city model (with low geometrical detail) can be used for energy demand forecasting on an urban scale.

https://architecture.mit.edu/sites/architecture.mit.edu/files/attachments/lecture/ASHRAE%20paper-1.pdf

Volker Coors

Papers

Large scale integration of photovoltaics in cities

Combining system dynamics model, GIS and 3D visualization in sustainability assessment of urban residential development

Combining GIS-based statistical and engineering urban heat consumption models: Towards a new framework for multi-scale policy support

One dimensional convolutional neural network architectures for wind prediction

3D City modeling for urban scale heating energy demand forecasting