Thermal, Lighting and IAQ Control System for Energy Saving and Comfort Management
The present work proposes a simulation and control framework for home and building automation, focusing on heating, ventilating, and air conditioning processes. Control systems based on different advanced control architectures and different control policies are simulated and compared, highlighting c...
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description | The present work proposes a simulation and control framework for home and building automation, focusing on heating, ventilating, and air conditioning processes. Control systems based on different advanced control architectures and different control policies are simulated and compared, highlighting control performances, and energy-saving results in terms of CO2 emissions reduction. Heat, lighting, and natural ventilation phenomena were modelized through first-principles and empirical equations, obtaining a reliable and flexible simulation framework. Energy-consuming and green energy-supplying renewable sources were integrated into the framework, e.g., heat pumps, artificial lights, fresh air flow, and natural illuminance. Different control schemes are proposed, based on proportional–integral–derivative advanced control architectures and discrete event dynamic systems-based supervisors; different control specifications are included, resulting in a multi-mode control system. The specifications refer to energy savings and comfort management, while minimizing overall costs. Comfort specifications include thermal comfort, lighting comfort, and a good level of indoor air quality. Simulations on different scenarios considering various control schemes and specifications show the reliability and soundness of the simulation and control framework. The simulated control and energy performances show the potential of the proposed approach, which can provide energy-saving results greater or equal to 6 [%] (in each season) and 19 [%] (in one year) with respect to more standard approaches. |
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Control systems based on different advanced control architectures and different control policies are simulated and compared, highlighting control performances, and energy-saving results in terms of CO2 emissions reduction. Heat, lighting, and natural ventilation phenomena were modelized through first-principles and empirical equations, obtaining a reliable and flexible simulation framework. Energy-consuming and green energy-supplying renewable sources were integrated into the framework, e.g., heat pumps, artificial lights, fresh air flow, and natural illuminance. Different control schemes are proposed, based on proportional–integral–derivative advanced control architectures and discrete event dynamic systems-based supervisors; different control specifications are included, resulting in a multi-mode control system. The specifications refer to energy savings and comfort management, while minimizing overall costs. Comfort specifications include thermal comfort, lighting comfort, and a good level of indoor air quality. Simulations on different scenarios considering various control schemes and specifications show the reliability and soundness of the simulation and control framework. The simulated control and energy performances show the potential of the proposed approach, which can provide energy-saving results greater or equal to 6 [%] (in each season) and 19 [%] (in one year) with respect to more standard approaches.</description><identifier>ISSN: 2227-9717</identifier><identifier>EISSN: 2227-9717</identifier><identifier>DOI: 10.3390/pr11010222</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Air conditioning ; Air flow ; Air quality ; Automation ; Building automation ; Building management systems ; Carbon dioxide ; Clean energy ; Control algorithms ; Control systems ; Controllers ; Cost control ; Deep learning ; Design ; Discrete event systems ; Dynamical systems ; Emissions ; Empirical equations ; Energy ; Energy conservation ; Energy consumption ; Energy efficiency ; Energy management ; Energy policy ; First principles ; Fuzzy logic ; Green buildings ; Heat pumps ; Humidity ; HVAC ; Illuminance ; Indoor air pollution ; Indoor air quality ; Lighting ; Multimode control ; Optimization techniques ; Proportional integral derivative ; Simulation ; Smart houses ; Software ; Specifications ; Supervisors ; Thermal comfort</subject><ispartof>Processes, 2023-01, Vol.11 (1), p.222</ispartof><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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The simulated control and energy performances show the potential of the proposed approach, which can provide energy-saving results greater or equal to 6 [%] (in each season) and 19 [%] (in one year) with respect to more standard approaches.</description><subject>Air conditioning</subject><subject>Air flow</subject><subject>Air quality</subject><subject>Automation</subject><subject>Building automation</subject><subject>Building management systems</subject><subject>Carbon dioxide</subject><subject>Clean energy</subject><subject>Control algorithms</subject><subject>Control systems</subject><subject>Controllers</subject><subject>Cost control</subject><subject>Deep learning</subject><subject>Design</subject><subject>Discrete event systems</subject><subject>Dynamical systems</subject><subject>Emissions</subject><subject>Empirical equations</subject><subject>Energy</subject><subject>Energy conservation</subject><subject>Energy consumption</subject><subject>Energy efficiency</subject><subject>Energy management</subject><subject>Energy policy</subject><subject>First principles</subject><subject>Fuzzy logic</subject><subject>Green buildings</subject><subject>Heat pumps</subject><subject>Humidity</subject><subject>HVAC</subject><subject>Illuminance</subject><subject>Indoor air pollution</subject><subject>Indoor air quality</subject><subject>Lighting</subject><subject>Multimode control</subject><subject>Optimization techniques</subject><subject>Proportional integral derivative</subject><subject>Simulation</subject><subject>Smart houses</subject><subject>Software</subject><subject>Specifications</subject><subject>Supervisors</subject><subject>Thermal comfort</subject><issn>2227-9717</issn><issn>2227-9717</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNpNkF9LwzAUxYMoOOZe_AQB38Rq_jRN8zjKnIOKjM3nkrRp19EmNcmEfnsrU_Q-nHvh_rjncgC4xeiRUoGeBocxwogQcgFmk_JIcMwv_83XYOH9EU0lME1ZMgPb_UG7XnYPMG-bQ2hNA6Wp4Ga5hZk1wdkO7kYfdA9r6-DKaNeMcCc_f8HM9tMiwFdpZKN7bcINuKpl5_Xip8_B-_Nqn71E-dt6ky3zqCSChSimTAjNVIxrlNRIKM2o4opzKafHKoRiTkoWqzShVAtFKGEUJ5inVVyWimk6B3fnu4OzHyftQ3G0J2cmy4LwhJOEU8wn6v5Mlc5673RdDK7tpRsLjIrv1Iq_1OgXze5c3Q</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Zanoli, Silvia Maria</creator><creator>Pepe, Crescenzo</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>COVID</scope><scope>D1I</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>KB.</scope><scope>LK8</scope><scope>M7P</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><orcidid>https://orcid.org/0000-0002-0007-1648</orcidid><orcidid>https://orcid.org/0000-0003-1917-1064</orcidid></search><sort><creationdate>20230101</creationdate><title>Thermal, Lighting and IAQ Control System for Energy Saving and Comfort Management</title><author>Zanoli, Silvia Maria ; Pepe, Crescenzo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c295t-43599e5b41f06f09be53b7b77aa856d00472c54b8633e9b2325316178d4ccb5e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Air conditioning</topic><topic>Air flow</topic><topic>Air quality</topic><topic>Automation</topic><topic>Building automation</topic><topic>Building management systems</topic><topic>Carbon dioxide</topic><topic>Clean energy</topic><topic>Control algorithms</topic><topic>Control systems</topic><topic>Controllers</topic><topic>Cost control</topic><topic>Deep learning</topic><topic>Design</topic><topic>Discrete event systems</topic><topic>Dynamical systems</topic><topic>Emissions</topic><topic>Empirical equations</topic><topic>Energy</topic><topic>Energy conservation</topic><topic>Energy consumption</topic><topic>Energy efficiency</topic><topic>Energy management</topic><topic>Energy policy</topic><topic>First principles</topic><topic>Fuzzy logic</topic><topic>Green buildings</topic><topic>Heat pumps</topic><topic>Humidity</topic><topic>HVAC</topic><topic>Illuminance</topic><topic>Indoor air pollution</topic><topic>Indoor air quality</topic><topic>Lighting</topic><topic>Multimode control</topic><topic>Optimization techniques</topic><topic>Proportional integral derivative</topic><topic>Simulation</topic><topic>Smart houses</topic><topic>Software</topic><topic>Specifications</topic><topic>Supervisors</topic><topic>Thermal comfort</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zanoli, Silvia Maria</creatorcontrib><creatorcontrib>Pepe, Crescenzo</creatorcontrib><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>Materials Science Database</collection><collection>ProQuest Biological Science Collection</collection><collection>Biological Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Processes</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zanoli, Silvia Maria</au><au>Pepe, Crescenzo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Thermal, Lighting and IAQ Control System for Energy Saving and Comfort Management</atitle><jtitle>Processes</jtitle><date>2023-01-01</date><risdate>2023</risdate><volume>11</volume><issue>1</issue><spage>222</spage><pages>222-</pages><issn>2227-9717</issn><eissn>2227-9717</eissn><abstract>The present work proposes a simulation and control framework for home and building automation, focusing on heating, ventilating, and air conditioning processes. 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subjects | Air conditioning Air flow Air quality Automation Building automation Building management systems Carbon dioxide Clean energy Control algorithms Control systems Controllers Cost control Deep learning Design Discrete event systems Dynamical systems Emissions Empirical equations Energy Energy conservation Energy consumption Energy efficiency Energy management Energy policy First principles Fuzzy logic Green buildings Heat pumps Humidity HVAC Illuminance Indoor air pollution Indoor air quality Lighting Multimode control Optimization techniques Proportional integral derivative Simulation Smart houses Software Specifications Supervisors Thermal comfort |
title | Thermal, Lighting and IAQ Control System for Energy Saving and Comfort Management |
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