Villa, Daniel V.; Schostek, Tyler S.; Bianchi, Carlo B.; MacMillan, Madeline M.; Carvallo, Juan P.
The Multi-scenario extreme weather simulator (MEWS) is a stochastic weather generation tool. The MEWS algorithm uses 50 or more years of National Oceanic and Atmospheric Association (NOAA) daily summaries [1] for maximum and minimum temperature and NOAA climate norms [2] to calculate historical heat wave and cold snap statistics. The algorithm takes these statistics and shifts them according to multiplication factors provided in the Intergovernmental Panel on Climate Change (IPCC) physical basis technical summary [3] for heat waves.
This report provides a design study to produce 100% carbon-free electricity for Sandia NM and Kirtland Air Force Base (KAFB) using concentrating solar power (CSP). Annual electricity requirements for both Sandia and KAFB are presented, along with specific load centers that consume a significant and continuous amount of energy. CSP plant designs of 50 MW and 100 MW are then discussed to meet the needs of Sandia NM and the combined electrical needs of both Sandia NM and KAFB. Probabilistic modeling is performed to evaluate inherent uncertainties in performance and cost parameters on total construction costs and the levelized cost of electricity. Total overnight construction costs are expected to range between ~$300M - $400M for the 50 MW CSP plant and between ~$500M - $800M for the 100 MW plant. Annual operations and maintenance (O&M) costs are estimated together with potential offsets in electrical costs and CO2 emissions. Other considerations such as interconnections, land use and permitting, funding options, and potential agreements and partnerships with Public Service Company of New Mexico (PNM), Western Area Power Administration (WAPA), and other entities are also discussed.
• Shows detailed methodology for applying building energy model fleets to institutional heat wave analysis. • Demonstrates uncertainty in heat wave analysis based on meter data. • Shows how detailed building energy models used for energy retrofit analysis can be used for heat wave analyses. • The proposed methodology is much more extensible than data-driven or low-order energy models to detailed cross analyses between energy efficiency and resilience for future institutional studies. • Cross benefits between resilience analysis and energy retrofit analyses are demonstrated. Heat waves increase electric demand from buildings which can cause power outages. Modeling can help planners quantify the risk of such events. This study shows how Building Energy Modeling (BEM), meter data, and climate projections can estimate heat wave effect on energy consumption and electric peak load. The methodology assumes that a partial representation of BEM for an entire site of buildings is sufficient to represent the entire site. Two linear regression models of the BEM results are produced: 1) Energy use as a function of heat wave heat content and 2) Peak load as a function of maximum daily temperature. The uncertainty conveyed in meter data is applied to these regressions providing slope and intercept 95% confidence intervals. The methodology was applied using 97 detailed BEM, site weather data, 242 building meters, and NEX-DCP30 down-scaled climate data for an entire institution in Albuquerque, New Mexico. A series of heat waves that vary from 2019 weather to a peak increase of 5.9 °C was derived. The results of the study provided institutional planners with information needed for a site that is presently growing very rapidly. The resulting regression models are also useful for resilience analyses involving probabilistic risk assessments.
As climate change and human migration accelerate globally, decision-makers are seeking tools that can deepen their understanding of the complex nexus between climate change and human migration. These tools can help to identify populations under pressure to migrate, and to explore proactive policy options and adaptive measures. Given the complexity of factors influencing migration, this article presents a system dynamics-based model that couples migration decision making and behavior with the interacting dynamics of economy, labor, population, violence, governance, water, food, and disease. The regional model is applied here to the test case of migration within and beyond Mali. The study explores potential systems impacts of a range of proactive policy solutions and shows that improving the effectiveness of governance and increasing foreign aid to urban areas have the highest potential of those investigated to reduce the necessity to migrate in the face of climate change.
Many membrane distillation models have been created to simulate the heat and mass exchange process involved but most of the literature only validates models to a couple of cases with minor configuration changes. Tools are needed that allow tradeoffs between many configurations. The multiconfiguration membrane distillation model handles many configurations. This report introduces membrane distillation, provides theory, and presents the work to verify and validate the model against experimental data from Colorado School of Mines and a lower resolution model created at the National Renewable Energy Laboratory. Though more data analysis and testing are needed, an initial look at the model to experimental comparisons indicates that the model correlates to the data well but that design comparisons are likely to be incorrect across a broad range of configurations. More accurate quantification of heat and mass transfer through computational fluid mechanics is suggested. The model is open source software: https ://github.com/dlvilla/MCMD1
Membrane distillation is a water purification technology which uses a porous hydrophobic membrane. Liquid water cannot penetrate the membrane at operational pressures but vapor flows through the membrane if there is a vapor pressure difference across the membrane. Many configurations for membrane distillation have been investigated over the last several decades. In this modeling effort, two successful direct contact membrane model development using steady-state control volume balances on energy and mass are presented. Verification and validation of the models is applied to the extent necessary to use the models for comparative design purposes. Significant errors between modeling and experimental membrane distillation data are argued to be due to uncertainty in membrane material property measurements. A second effort to model a vacuum membrane distillation system designed by Memsys(r) is still progressing. Two efforts have not yet produced output mass flow comparable to the literature. Even so, much of the framework needed to model the Memsys(r) system is complete. Membrane Distillation Modeling Progress Report Fiscal Year 2016 February 7, 2017 4 REVISION HISTORY Document Number/Revision Date Description SAND2017-0200 November 2016 Official Use Only - Third Party Proprietary SAND2017-1448 February 6, 2017 Approved for Unlimited Release.
Reducing the resource consumption and emissions of large institutions is an important step toward a sustainable future. Sandia National Laboratories' (SNL) Institutional Transformation (IX) project vision is to provide tools that enable planners to make well-informed decisions concerning sustainability, resource conservation, and emissions reduction across multiple sectors. The building sector has been the primary focus so far because it is the largest consumer of resources for SNL. The IX building module allows users to define the evolution of many buildings over time. The module has been created so that it can be generally applied to any set of DOE-2 ( http://doe2.com ) building models that have been altered to include parameters and expressions required by energy conservation measures (ECM). Once building models have been appropriately prepared, they are checked into a Microsoft Access (r) database. Each building can be represented by many models. This enables the capability to keep a continuous record of models in the past, which are replaced with different models as changes occur to the building. In addition to this, the building module has the capability to apply climate scenarios through applying different weather files to each simulation year. Once the database has been configured, a user interface in Microsoft Excel (r) is used to create scenarios with one or more ECMs. The capability to include central utility buildings (CUBs) that service more than one building with chilled water has been developed. A utility has been created that joins multiple building models into a single model. After using the utility, several manual steps are required to complete the process. Once this CUB model has been created, the individual contributions of each building are still tracked through meters. Currently, 120 building models from SNL's New Mexico and California campuses have been created. This includes all buildings at SNL greater than 10,000 sq. ft., representing 80% of the energy consumption at SNL. SNL has been able to leverage this model to estimate energy savings potential of many competing ECMs. The results helped high level decision makers to create energy reduction goals for SNL. These resources also have multiple applications for use of the models as individual buildings. In addition to the building module, a solar module built in Powersim Studio (r) allows planners to evaluate the potential photovoltaic (PV) energy generation potential for flat plate PV, concentrating solar PV, and concentration solar thermal technologies at multiple sites across SNL's New Mexico campus. Development of the IX modeling framework was a unique collaborative effort among planners and engineers in SNL's facilities division; scientists and computer modelers in SNL's research and development division; faculty from Arizona State University; and energy modelers from Bridger and Paxton Consulting Engineers Incorporated.