02592nas a2200193   4500008004100000245013700041210006900178520187800247653002902125653001202154653003302166653001502199653002202214653001602236100001702252700001902269700002202288856008802310       2017                        eng d00aAutomatic Generation and Simulation of Urban Building Energy Models Based on City Datasets for City-Scale Building Retrofit Analysis0 aAutomatic Generation and Simulation of Urban Building Energy Mod3 a<p>Buildings in cities consume 30% to 70% of total primary energy, and improving building energy efficiency is one of the key strategies towards sustainable urbanization. Urban building energy models (UBEM) can support city managers to evaluate and prioritize energy conservation measures (ECMs) for investment and the design of incentive and rebate programs. This paper presents the retrofit analysis feature of City Building Energy Saver (CityBES) to automatically generate and simulate UBEM using EnergyPlus based on cities’ building datasets and user-selected ECMs. CityBES is a new open web-based tool to support city-scale building energy efficiency strategic plans and programs. The technical details of using CityBES for UBEM generation and simulation are introduced, including the workflow, key assumptions, and major databases. Also presented is a case study that analyzes the potential retrofit energy use and energy cost savings of five individual ECMs and two measure packages for 940 office and retail buildings in six city districts in northeast San Francisco, United States. The results show that: (1) all five measures together can save 23%-38% of site energy per building; (2) replacing lighting with light-emitting diode lamps and adding air economizers to existing heating, ventilation and air-conditioning (HVAC) systems are most cost-effective with an average payback of 2.0 and 4.3 years, respectively; and (3) it is not economical to upgrade HVAC systems or replace windows in San Franciso due to the city’s mild climate and minimal cooling and heating loads. The CityBES retrofit analysis feature does not require users to have deep knowledge of building systems or technologies for the generation and simulation of building energy models, which helps overcome major technical barriers for city managers and their consultants to adopt UBEM.</p>10aBuilding Energy Modeling10aCityBES10aEnergy conservation measures10aenergyplus10aRetrofit Analysis10aUrban Scale1 aChen, Yixing1 aHong, Tianzhen1 aPiette, Mary, Ann  uhttps://simulationresearch.lbl.gov/publications/automatic-generation-and-simulation02261nas a2200241   4500008003900000245011100039210006900150260001200219520144900231653002401680653003201704653002001736653001501756653003101771653001301802100002001815700001901835700002201854700001701876700001701893700002801910856008101938       2015                          d00aAccelerating the energy retrofit of commercial buildings using a database of energy efficiency performance0 aAccelerating the energy retrofit of commercial buildings using a  c07/20153 a<p>Small and medium-sized commercial buildings can be retrofitted to significantly reduce their energy use, however it is a huge challenge as owners usually lack of the expertise and resources to conduct detailed on-site energy audit to identify and evaluate cost-effective energy technologies. This study presents a DEEP (database of energy efficiency performance) that provides a direct resource for quick retrofit analysis of commercial buildings. DEEP, compiled from the results of about ten million EnergyPlus simulations, enables an easy screening of ECMs (energy conservation measures) and retrofit analysis. The simulations utilize prototype models representative of small and mid-size offices and retails in California climates. In the formulation of DEEP, large scale EnergyPlus simulations were conducted on high performance computing clusters to evaluate hundreds of individual and packaged ECMs covering envelope, lighting, heating, ventilation, air-conditioning, plug-loads, and service hot water. The architecture and simulation environment to create DEEP is flexible and can expand to cover additional building types, additional climates, and new ECMs. In this study DEEP is integrated into a web-based retrofit toolkit, the Commercial Building Energy Saver, which provides a platform for energy retrofit decision making by querying DEEP and unearthing recommended ECMs, their estimated energy savings and financial payback.</p>10abuilding simulation10aEnergy conservation measure10aenergy modeling10aenergyplus10aHigh Performance computing10aretrofit1 aLee, Sang, Hoon1 aHong, Tianzhen1 aPiette, Mary, Ann1 aSawaya, Geof1 aChen, Yixing1 aTaylor-Lange, Sarah, C.  uhttps://simulationresearch.lbl.gov/publications/accelerating-energy-retrofit01870nas a2200193   4500008004100000245009500041210006900136260001200205300001200217490000700229520122600236653002801462653002301490653000901513100002201522700002601544700001801570856008801588       2001                        eng d00aAnalysis of an Information Monitoring and Diagnostic System to Improve Building Operations0 aAnalysis of an Information Monitoring and Diagnostic System to I  c10/2001  a783-7920 v333 a<p>This paper discusses a demonstration of a technology to address the problem that buildings do not perform as well as anticipated during design. We partnered with an innovative building operator to evaluate a prototype information monitoring and diagnostic system (IMDS). The IMDS consists of a set of high-quality sensors, data acquisition software and hardware, and data visualization software including a web-based remote access system, that can be used to identify control problems and equipment faults. The information system allowed the operators to make more effective use of the building control system and freeing up time to take care of other tenant needs. They report observing significant improvements in building comfort, potentially improving tenant health and productivity. The reduction in the labor costs to operate the building is about US$ 20,000 per year, which alone could pay for the information system in about 5 years. A control system retrofit based on findings from the information system is expected to reduce energy use by 20% over the next year, worth over US$ 30,000 per year in energy cost savings. The operators are recommending that similar technology be adopted in other buildings.</p>10abuilding control system10abuilding operation10aimds1 aPiette, Mary, Ann1 aKhalsa, Satkartar, T.1 aHaves, Philip  uhttps://simulationresearch.lbl.gov/publications/analysis-information-monitoring-and