Decision support methodologies and day-ahead optimization for smart building energy management in a dynamic pricing scenario

Pallante, A.; Adacher, Ludovica; Botticelli, M.; Pizzuti, Stefano; Comodi, Gabriele; Monteriù, Andrea

doi:10.1016/j.enbuild.2020.109963

Cited by 16 publications

(7 citation statements)

References 14 publications

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“…2 The workflow of HVACDSS Structure and design of technology for information systems: the overall structure of the HVACDSS system is depicted in Figure 2, where both the user interface and analytical components and the data gathering modules are represented. The HVACDSS receives and saves all the information gathered by the capture modules in a semantic data store [28].…”

Section: Architecture Of the Hvacdssmentioning

confidence: 99%

Modeling, Implementing and Evaluation a Decision Support System Used for Choosing the Best HVAC System in The Buildings, Case Study in Iraq

Ahmed,

Ali Salah

2024

JOIV : Int. J. Inform. Visualization

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The life cycle cost of a building is affected by the heating, ventilation, and air conditioning (HVAC) system chosen by the Life Cycle Costs (LCC). Quality, constructability, appearance of the structure's interior and exterior, HVAC size and weight, and LCC are some of the criteria influencing the choice. Methods: To monitor a project's progress based on energy savings, standard measures such as cost variance (CV) and schedule variation have used an idea when tracking the performance of intelligent buildings. Also, as described in the article, this research compared the decision-making limits of Building Information Modelling (BIM) and (MCDM). Analysis: The conventional approach cannot reveal information regarding divergence from the expected level of performance. Based on the outcomes of the construction cost variables, the key finding was the observation of 12 efficient elements. Finding and Novelty: According to the R, a building's most valuable features are its (Energy Saving Features, Warranties, Budget, Protect Your Unit, SEER Ratings, and Home Square Footage). The findings of Actual value (AV) and planned value (PV) were significantly different, as noted by the Multi-Criteria Decision Maker (MCDM). The new method also makes it possible to track project costs and timetables more accurately. The paper will characterize the HVAC Decision Support System's architecture (HVACDSS). Also, a case study of action modeling is provided, and the preliminary findings are addressed. Six criteria characteristics are used by the HVACDSS technique by an analysis of building construction conducted using the WEKA mining tool (decision tree).

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Section: Architecture Of the Hvacdssmentioning

confidence: 99%

Modeling, Implementing and Evaluation a Decision Support System Used for Choosing the Best HVAC System in The Buildings, Case Study in Iraq

Ahmed,

Ali Salah

2024

JOIV : Int. J. Inform. Visualization

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“…Building-related anthropogenic activities harm the environment due to the high energy and resources consumed in buildings [3]. For instance, the building energy consumed in regions such as the European Union, United States, Hong Kong, Saudi Arabia, and Africa accounts for 40%, 20%, 90%, 73%, and 56%, respectively [4][5][6][7][8]. Consequently, the building stock in https://doi.org/10.1007/s42452-022-05262-y these same regions is responsible for 36%, 40%, 60%, 33%, and 32% CO 2 emissions, respectively.…”

Section: Introductionmentioning

confidence: 99%

Benefits of adopting smart building technologies in building construction of developing countries: review of literature

Ejidike

Mewomo

2023

SN Appl. Sci.

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Smart building technology has received a broad audience due to digitalisation and benefits in the construction industry. With global interest, the construction of smart buildings has become a new trend in development. Many studies identified a significant interest in the smart building technology application more than in conventional buildings. However, in developing countries, construction professionals have paid little attention to the adoption of smart building technology. Therefore, this paper aims to identify the benefits that are attached to the adoption of smart building technology (SBT) in the construction industry. The study is based on a systematic review of published articles in peer-reviewed journals and conferences. A total of 55 papers comprising conferences and journal articles retrieved from Scopus database were utilised for the study. The study's findings revealed efficient energy consumption, cost-effective building maintenance and operation, job creation, health care management, real-time monitoring, safety and security, among others, as benefits of smart building technologies (SBTs). For smart building technology to thrive in emerging economies, a comprehensive understanding of its benefits is highly imperative. This will not only promote construction professionals' knowledge of its concept but also enhance its successful adoption in these regions. Thus, the paper provides some insights into the benefit of smart building technology in developing countries while suggesting the formation of a synergic structure between the research community and practitioners in the construction sector. Article highlight Smart building promotes sustainability in the construction industry. Productivity, collaboration and security increase smart building adoption. Rigorous studies on smart building benefits are limited in developing countries.

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“…Considering the intermittency of renewable energy and the continuously shifting user demands, implementing day-ahead scheduling in microgrids is paramount to efficiently manage energy supply and storage. Pallante et al [4] conducted a study on day-ahead scheduling for a real office building equipped with a heating system, fan coil power supply network, and lighting network. MATLAB/Simulink was employed to create a physical model of the building.…”

Section: Introductionmentioning

confidence: 99%

Day-ahead optimal scheduling of micro gas turbine-based microgrid considering electricity and heating energy

Zhang,

Assadi

2023

IOP Conf. Ser.: Mater. Sci. Eng.

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Microgrids are considered as the crucial element in the integration of various distributed energy resources in buildings. They are capable of operating in both grid-connected and islanded mode and have shown immense potential in absorbing renewable energy. However, the widespread implementation of intermittent renewable energy sources, coupled with variable electricity pricing, has significantly increased the operation uncertainty of microgrids. This paper presents an analysis of the operation strategies of an integrated energy system that includes a micro gas turbine, a ground source heat pump, PV panels with the aim of meeting the heating and electricity demands of a commercial building. To facilitate this endeavor, a neural network model for micro gas turbines was developed with a focus on fast computation time and high accuracy in capturing off-design performance. Furthermore, mathematical models for ground source heat pump, PV panel were developed and validated using the Modelica language. Dymola optimization package was utilized to derive the day-ahead scheduling followed by one-hour intervals for the system, with the purpose of minimizing the electricity and heating costs associated with the system. The results demonstrate that the total costs could be reduced by approximately 51% during the analyzed period, indicating a promising avenue for cost savings in the system’s operation.

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Decision support methodologies and day-ahead optimization for smart building energy management in a dynamic pricing scenario

Cited by 16 publications

References 14 publications

Modeling, Implementing and Evaluation a Decision Support System Used for Choosing the Best HVAC System in The Buildings, Case Study in Iraq

Modeling, Implementing and Evaluation a Decision Support System Used for Choosing the Best HVAC System in The Buildings, Case Study in Iraq

Benefits of adopting smart building technologies in building construction of developing countries: review of literature

Day-ahead optimal scheduling of micro gas turbine-based microgrid considering electricity and heating energy

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