Heating control schemes for energy management in buildings

Paris, Benjamin; Eynard, Julien; Grieu, Stéphane; Talbert, Thierry; Polit, Monique

doi:10.1016/j.enbuild.2010.05.027

Cited by 84 publications

(32 citation statements)

References 25 publications

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“…Clearly, these parameters have a direct and indirect influence on the building energy demands. Q hc , necessary to maintain the indoor air at the desired set point temperatures, is calculated according through a proportional integral (PI) controller (widely adopted in buildings for heating and cooling systems control [42]). The indoor air temperature can be controlled to a fixed set point or free to float in an allowed interval avoiding the activation of the ideal heating and cooling system.…”

Section: Q Radmentioning

confidence: 99%

Code-to-Code Validation and Application of a Dynamic Simulation Tool for the Building Energy Performance Analysis

Buonomano

2016

Energies

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Abstract:In this paper details about the results of a code-to-code validation procedure of an in-house developed building simulation model, called DETECt, are reported. The tool was developed for research purposes in order to carry out dynamic building energy performance and parametric analyses by taking into account new building envelope integrated technologies, novel construction materials and innovative energy saving strategies. The reliability and accuracy of DETECt was appropriately tested by means of the standard BESTEST validation procedure. In the paper, details of this validation process are accurately described. A good agreement between the obtained results and all the reference data of the BESTEST qualification cases is achieved. In particular, the obtained results vs. standard BESTEST output are always within the provided ranges of confidence. In addition, several test cases output obtained by DETECt (e.g., dynamic profiles of indoor air and building surfaces temperature and heat fluxes and spatial trends of temperature across walls) are provided.

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Section: Q Radmentioning

confidence: 99%

Code-to-Code Validation and Application of a Dynamic Simulation Tool for the Building Energy Performance Analysis

Buonomano

2016

Energies

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“…Several previous works have indicated that model-based controllers can result in energy savings from about 20-50% without compromising comfort [2][3][4][5][6]. However, a typically high level of complexity means that implementation at most common sites are prevented along with a widespread utilization.…”

Section: Introductionmentioning

confidence: 98%

Energy efficient climate control in office buildings without giving up implementability

2015

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h i g h l i g h t sThe principle of model-based controller for indoor climate control was adopted. A simplified version was presented and evaluated through experiments. A typical office working day was re-created in a test facility. Experiments were conducted for two weather seasons and two types of office rooms. Energy usage was reduced at the same time as the indoor climate was improved. Keywords:Office buildings Indoor climate control Implementability Air-based heating and cooling Energy efficiency Model-based controller a b s t r a c tThe adaptation between a building and its automation system can potentially be increased by model-based controllers with an integrated control model and information about indoor climate disturbances. The associated energy savings potential is large but a widespread utilization is typically prevented by high complexities. From that point of view, a trade-off technology that combines implementability with an overall higher performance than the system of current practice would be a better option at most sites. This work presents an experimental evaluation of an alternative controller that follows the same principle as model-based, but has gone through a large number of simplification measures for a reduced overall complexity and a limited function. The controller was evaluated for indoor climate control by automating the ventilation flow rate during a typical office working day that was re-created in a laboratory environment. Experiments were conducted in two different office sites, as well as during two weather seasons of Swedish summer and winter. From the investigation, it was concluded that despite of the reduced complexity, the investigated controller could save between 12% and 19% of indicated energy compared to a system of common practice at the same time as the quality of indoor climate was maintained.

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“…The majority of energy consumed in buildings is for the Heating, Ventilating, and Air Conditioning (HVAC), particularly when there are differences between indoor and outdoor temperatures. Energy consumption accounts for about 60% of all delivered energy consumed in buildings [39]. There is an urgent need to extensively investigate adaptive and optimized control models on the HVAC systems for SFM [15].…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated Proactive Control Model for Energy Efficiency Processes in Facilities Management: Applying Dynamic Exponential Smoothing Optimization

2017

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Sustainable facilities management (SFM) opens the door of opportunity for companies to evaluate the quality of resources and environment management at their facilities. It enables the principles of sustainable development. There is still inefficiency in quantitative research of integrating environmental factors, particularly multi-source data, to monitor and control complicated systems in buildings. The objective of this research is to develop an effective method to dynamically optimize energy efficiency in SFM plans and strategies. The research question is: can the integrated proactive method reduce energy consumption with dynamically adjustable controls? This paper proposes a coordinated proactive control method using dynamic time-series prediction (PCM-DTSP) for SFM, which optimizes system controls by integrating the prediction results and monitored environmental-data. The results show that, after optimization, the temperature fluctuations are reduced to 33.3%. The average temperature and maximum temperature are reduced by 8% and 13.1%, respectively. The instantaneous power consumption was reduced by 0.17 KW per hour for each cooling system unit. The PCM-DTSP method can significantly optimize energy efficiency, which paves the way for long-term comprehensive energy management. The contribution of the research lies in its optimized control of energy consumption, temperature stabilization, and improvement of environmental comfort solutions, which can be generalized to various types of buildings.

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Heating control schemes for energy management in buildings

Cited by 84 publications

References 25 publications

Code-to-Code Validation and Application of a Dynamic Simulation Tool for the Building Energy Performance Analysis

Code-to-Code Validation and Application of a Dynamic Simulation Tool for the Building Energy Performance Analysis

Energy efficient climate control in office buildings without giving up implementability

Integrated Proactive Control Model for Energy Efficiency Processes in Facilities Management: Applying Dynamic Exponential Smoothing Optimization

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