HVAC systems
/lab/sbs/
enDesign of an Energy and Water Efficient Hotel
/lab/sbs/UM-design-energy-and-water-efficient-hotel
<span>Design of an Energy and Water Efficient Hotel</span>
<span><span>Anonymous (not verified)</span></span>
<span><time datetime="2015-01-01T00:00:00-07:00" title="Thursday, January 1, 2015 - 00:00">Thu, 01/01/2015 - 00:00</time>
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<a href="/lab/sbs/taxonomy/term/96" hreflang="en">HVAC systems</a>
<a href="/lab/sbs/taxonomy/term/239" hreflang="en">High Performance Buildings</a>
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<img loading="lazy" src="/lab/sbs/sites/default/files/styles/large_image_style/public/article-image/grandbeach.jpg?itok=zn8fFznd" width="1500" height="1001" alt="Grand beach - the prototype of the design hotel">
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<p>Located in Tropical climate, buildings in Miami requires cooling around the year. Space conditioning and domestic hot water systems account for 41% of all energy usage in a hotel. To save the energy for space cooling and domestic hot water heating, we proposed a heat recovery system which pre-heats the city water using the waste heat from space cooling. We also proposed to collect, store and process the rain water for non-portable usage. The system is implemented at the Grand Beach Hotel in Miami Beach, FL. This is a joint project with UCI Engineering.</p>
<h2>Press Release</h2>
<p><a href="http://www.coe.miami.edu/sustainability-research" rel="nofollow">UM COE News "Sustainability Research"</a></p>
<h2><strong>Publications</strong></h2>
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<li>R. J. Miranda, S. Huang, G. A. Barrios, D. Li, W. Zuo 2015. 鈥�<a href="/lab/sbs/node/613/attachment" rel="nofollow">Energy Efficient Design for Hotels in the Tropical Climate Using Modelica.</a>鈥� Proceedings of the 11th International Modelica Conference, pp. 71-78, September 21-23, Versailles, France.</li>
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<p class="text-align-center">Figure SBS lab researcher Rey Miranda is giving a technical tour at the Grand Beach Hotel</p></div>
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Thu, 01 Jan 2015 07:00:00 +0000Anonymous140 at /lab/sbsModel Predictive Control for Chilled Water Plants
/lab/sbs/UM-MPC-chiller-plant
<span>Model Predictive Control for Chilled Water Plants</span>
<span><span>Anonymous (not verified)</span></span>
<span><time datetime="2015-01-01T00:00:00-07:00" title="Thursday, January 1, 2015 - 00:00">Thu, 01/01/2015 - 00:00</time>
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<p>Improving the energy efficiency of chilled water plants is important since they account for about 35% the energy consumed by commercial building cooling equipment in the U.S. Model predictive control is a feasible way to enhance the operational efficiency of the chilled water plants. Our research is to develop a Python-based dynamic optimization platform that can perform continuous optimization for various control settings of chilled water plants. By using the Modelica modeling language, we can quickly model a chilled water plant with any system configurations and dynamically simulate its control behavior.</p>
<h2>Collaborators</h2>
<p> <a href="https://www.lbl.gov/" rel="nofollow">Lawrence Berkeley National Laboratory</a></p>
<h2><strong>Publications</strong>:</h2>
<h4><strong>Journal articles:</strong></h4>
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<li>S. Huang, A. Malara, W. Zuo, M. Sohn 2018. "<a href="/p1de0091ffae/node/186/attachment" rel="nofollow">A Bayesian Network Model for the Optimization of a Chiller Plant鈥檚 Condenser Water Set Point</a>."Journal of Building Performance Simulation, 11(1), pp. 36-47.</li>
<li>S. Huang, W. Zuo, M. Sohn 2018. "<a href="/p1de0091ffae/node/188/attachment" rel="nofollow">A Bayesian Network Model for Predicting Cooling Load of Commercial Buildings</a>." Building Simulation, 11(1), pp. 87-101.</li>
<li>S. Huang, W. Zuo, M. Sohn 2017. "<a href="/p1de0091ffae/node/180/attachment" rel="nofollow">Improved Cooling Tower Control of Legacy Chiller Plants by Optimizing the Condenser Water Set Point</a>." Building and Environment, 111, pp. 33-46.</li>
<li>S. Huang, W. Zuo, M. Sohn 2016. "<a href="/p1de0091ffae/node/194/attachment" rel="nofollow">Amelioration of the Cooling Load Based Chiller Sequencing Control</a>." Applied Energy, 168, pp. 204-215.</li>
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<p><strong>Conference proceedings:</strong></p>
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<li>S. Huang, W. Zuo, M. D. Sohn 2016. 鈥淎 Bayesian Network Model for Predicting the Cooling Load of Educational Facilities.鈥� Proceedings of the ASHRAE and IBPSA-USA SimBuild 2016: Building Performance Modeling Conference, pp. 1-8, August 8-12, Salt Lake City, UT.</li>
<li>S. Huang, M.V. Cavey, R. Sterling, W. Zuo, L. Helsen, A. Giretti, M. Bonvini, Z. O鈥橬eill, M. Wetter, A. Costa, G. Boehme, R. Klein, B. Dong, M. M. Keane 2016. 鈥�<a href="/lab/sbs/node/601/attachment" rel="nofollow">IEA Annex 60 Activity 2.3: Model Use During Operation, Approach and Case Studies.</a>鈥� Proceedings of the 12th REHVA World Congress (CLIMA2016), May 22-25, Aalborg, Denmark.</li>
<li>S. Huang, W. Zuo, M. D. Sohn 2015. 鈥�<a href="/lab/sbs/node/603/attachment" rel="nofollow">A New Method for the Optimal Chiller Sequencing Control.</a>鈥� Proceedings of the 14th Conference of International Building Performance Simulation Association (Building Simulation 2015), pp. 316-323, December 7-9, Hyderabad, India.</li>
<li>A. C. L. Malara, S. Huang, W. Zuo, M. D. Sohn, N. Celik 2015. 鈥�<a href="/lab/sbs/node/611/attachment" rel="nofollow">Optimal Control of Chiller Plants Using Bayesian Network.</a>鈥� Proceedings of the 14th Conference of International Building Performance Simulation Association (Building Simulation 2015), pp. 449-455, December 7-9, Hyderabad, India.</li>
<li>T. Li, G. Shao, W. Zuo, S. Huang 2015. 鈥�<a href="/lab/sbs/node/615/attachment" rel="nofollow">Genetic Algorithm for Building Optimization - State-Of-The-Art Survey.</a>鈥� Proceedings of the 9th International Symposium on Heating, Ventilation and Air Conditioning (ISHVAC) and the 3rd International Conference on Building Energy and Environment (COBEE), pp. 205-210, July 12-15, Tianjin, China.</li>
<li>S. Huang, W. Zuo 2014. 鈥淥ptimization of the Water-Cooled Chiller Plant System Operation.鈥� Proceedings of the 2014 ASHRAE/IBPSA-USA Building Simulation Conference, pp. 300-307, September 10-12, Atlanta, GA.</li>
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Thu, 01 Jan 2015 07:00:00 +0000Anonymous134 at /lab/sbs