Best economical hybrid energy solution: Model development and case study of a WDS in Portugal

Energy Policy ◽  
2011 ◽  
Vol 39 (6) ◽  
pp. 3361-3369 ◽  
Author(s):  
F.V. Gonçalves ◽  
L.H. Costa ◽  
H.M. Ramos
Keyword(s):  
Model Development ◽  
Solution Model ◽  
Energy Solution ◽  
Hybrid Energy

scholarly journals Predictive Maintenance in Building Facilities: A Machine Learning-Based Approach

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1044
Author(s):  
Yassine Bouabdallaoui ◽  
Zoubeir Lafhaj ◽  
Pascal Yim ◽  
Laure Ducoulombier ◽  
Belkacem Bennadji
Keyword(s):  
Machine Learning ◽  
Model Development ◽  
Predictive Maintenance ◽  
Data Availability ◽  
Machine Learning Techniques ◽  
Automation System ◽  
Building Maintenance ◽  
Collection Data ◽  
Iot Devices

The operation and maintenance of buildings has seen several advances in recent years. Multiple information and communication technology (ICT) solutions have been introduced to better manage building maintenance. However, maintenance practices in buildings remain less efficient and lead to significant energy waste. In this paper, a predictive maintenance framework based on machine learning techniques is proposed. This framework aims to provide guidelines to implement predictive maintenance for building installations. The framework is organised into five steps: data collection, data processing, model development, fault notification and model improvement. A sport facility was selected as a case study in this work to demonstrate the framework. Data were collected from different heating ventilation and air conditioning (HVAC) installations using Internet of Things (IoT) devices and a building automation system (BAS). Then, a deep learning model was used to predict failures. The case study showed the potential of this framework to predict failures. However, multiple obstacles and barriers were observed related to data availability and feedback collection. The overall results of this paper can help to provide guidelines for scientists and practitioners to implement predictive maintenance approaches in buildings.

scholarly journals History, Colonialism, and Archival Methods in Socio-Hydrological Scholarship: A Case Study of the Boerasirie Conservancy in British Guiana

World ◽  
2020 ◽  
Vol 1 (3) ◽  
pp. 205-215
Author(s):  
Joshua Mullenite
Keyword(s):  
Environmental History ◽  
Cross Section ◽  
Science And Technology Studies ◽  
Model Development ◽  
Human Geography ◽  
Hydrological Models ◽  
British Guiana ◽  
Current Role

In this article, I review a cross-section of research in socio-hydrology from across disciplines in order to better understand the current role of historical-archival analysis in the development of socio-hydrological scholarship. I argue that despite its widespread use in environmental history, science and technology studies, anthropology, and human geography, archival methods are currently underutilized in socio-hydrological scholarship more broadly, particularly in the development of socio-hydrological models. Drawing on archival research conducted in relation to the socio-hydrology of coastal Guyana, I demonstrate the ways in which such scholarship can be readily incorporated into model development.

Effect of Manufacturing Variability on Turbine Engine Performance: A Probabilistic Study

2013 ◽  
Author(s):  
Michael Gorelik ◽  
Jacob Obayomi ◽  
Jack Slovisky ◽  
Dan Frias ◽  
Howie Swanson ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Model Development ◽  
Engine Performance ◽  
Performance Model ◽  
Probabilistic Methods ◽  
System Level ◽  
Turbine Engine ◽  
Probabilistic Study ◽  
Blade Geometry

While turbine engine Original Equipment Manufacturers (OEMs) accumulated significant experience in the application of probabilistic methods (PM) and uncertainty quantification (UQ) methods to specific technical disciplines and engine components, experience with system-level PM applications has been limited. To demonstrate the feasibility and benefits of an integrated PM-based system, a numerical case study has been developed around the Honeywell turbine engine application. The case study uses experimental observations of engine performance such as horsepower and fuel flow from a population of engines. Due to manufacturing variability, there are unit-to-unit and supplier-to-supplier variations in compressor blade geometry. Blade inspection data are available for the characterization of these geometric variations, and CFD analysis can be linked to the engine performance model, so that the effect of blade geometry variation on system-level performance characteristics can be quantified. Other elements of the case study included the use of engine performance and blade geometry data to perform Bayesian updating of the model inputs, such as efficiency adders and turbine tip clearances. A probabilistic engine performance model was developed, system-level sensitivity analysis performed, and the predicted distribution of engine performance metrics was calibrated against the observed distributions. This paper describes the model development approach and key simulation results. The benefits of using PM and UQ methods in the system-level framework are discussed. This case study was developed under Defense Advanced Research Projects Agency (DARPA) funding which is gratefully acknowledged.

scholarly journals Feasibility and techno-economic analysis of stand-alone and grid-connected PV/Wind/Diesel/Batt hybrid energy system: A case study

2021 ◽  
Vol 37 ◽  
pp. 100673
Author(s):  
Barun K. Das ◽  
Majed A. Alotaibi ◽  
Pronob Das ◽  
M.S. Islam ◽  
Sajal K. Das ◽  
...  
Keyword(s):  
Economic Analysis ◽  
Energy System ◽  
Hybrid Energy System ◽  
Hybrid Energy ◽  
System A

Design of a University-Based Venture Gestation Program (UVGP)

2016 ◽  
Vol 24 (01) ◽  
pp. 1-35 ◽  
Author(s):  
Hoe Chin Goi ◽  
Jiro Kokuryo
Keyword(s):  
Design Science ◽  
Business Plan ◽  
Design Principles ◽  
Solution Model ◽  
Dynamic Capability ◽  
Comparative Case Study ◽  
Competency Development ◽  
Entrepreneurial Bricolage ◽  
Science Methodology

Design science methodology was used to develop and test a University-based Venture Gestation Program (UVGP), the model built after identifying key problems and reactions to them in student based gestation ventures. The model relied on a three-year longitudinal comparative case study of a successful and an unsuccessful student venture team. The teams came from the same university and were winners of business plan contests in 2012 and 2013. Although the teams were very similar to begin with, analyses revealed that different responses to three shared problems were key determinants of venture gestation success, and failure. Based on these observations, three design principles, termed tenure, competence compatibility and entrepreneurial bricolage, were adapted to derive a solution model, the Venture Gestation Model (VGM), with the aim of improving chances of venture success. To develop the model, the study drew on dynamic capability theory, and subsequently yielded the UVGP which provided concrete tools (prescriptions) toward gestation venture success. As a means of testing the designed solution, an evaluation of the program was conducted by observing the gestation venture of the 2014 winner of the annual contest. Findings show that gestation success depends more on the effectiveness of the program in increasing awareness of internal problems than on reactions to external changes. However, the prescription on competency development requires revision to overcome inadequacy issues.

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