Browsing by Author "Lima, Luana Marangon"
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Item Open Access Analysis of Advocacy Methods for Promoting and Passing State Electric School Bus Policies(2023-04-28) Baad, AlexanderItem Open Access Assessing Industrial Energy Transition in the Textile Sector in Pakistan(2022-04-22) Ul Haq, SomanThis study assesses the industrial captive power generation in Pakistan and its on-going transition to renewable energy. By focusing on the textile sector and conducting an energy survey with detailed interview sessions with energy management teams from a number of large textile companies, we try to answer some of these questions: Why do industries in Pakistan continue to generate captive power even when there is excess generation capacity in the grid, and the government is incentivizing and encouraging the use of grid electricity? What are some factors driving the transition to renewable energy in captive generation? Similarly, what are some barriers for industries to integrate renewable energy in their energy mix? What benefits, in terms of emission reductions and cost savings can be attributed by adding solar PV for these industries? Lastly, we assess the impact of a recently implemented sales taxes on renewable energy equipment on the costs of industrial solar PV projects.Item Open Access Assessing the Water Footprint of Electric Car Batteries – A Dive into the Water-Energy Nexus(2023-04-28) MacDonald, Kathlyn; Thornton, Karen; Allen, Mary Margaret; Katayama, TaroWater has been historically overlooked as a criterion when measuring the environmental impact of a project. This project aims to visualize the water impacts and risks associated with extracting three critical minerals commonly used in electric vehicle (EV) batteries (lithium, cobalt, and nickel) on behalf of Rivian – an EV manufacturing company. As EVs become increasingly popular, the demand for minerals and metals used in their production, such as lithium, cobalt, and nickel, has increased. The mining of these minerals often takes place in water-stressed areas, which can have negative environmental and social impacts. The goal of this project is to assess the water risks associated with mining these minerals and provide recommendations for a more sustainable supply chain. The objectives of this project are to identify potential "hot spots" in the EV supply chain where water risks are most prevalent, evaluate the consumption of water from mining the three minerals, and provide recommendations to create a more sustainable supply chain. We narrowed the supply chain to include an analysis of the mining of three critical EV battery raw materials – lithium, cobalt, and nickel. We researched the specific supply chains of these three minerals and found the geographic location of the top 10 mines by production, with some exceptions. These mines were then overlayed with water scarcity data from WRI’s Aqueduct tool. A dashboard was created to express these findings. In the interest of transparency, we made sure to gather as much water consumption data as possible for the mining processes of lithium, cobalt, and nickel. Though we encountered some limitations during this process, such as differing functional units and definitions of water consumption/use, we did our best to create an informative table displaying our findings. We acknowledge that some of our sources lacked scientific confidence and our sample may not have been fully representative. Potential supply chain hot spots - mines located in areas of high stress extremely high stress, or arid and low water use - were located for each mineral. For cobalt, the potential hot spots included the Murrin Murrin mine in Australia. For lithium, the potential hot spots include Sociedad Quimica y Minera de Chile and Albemarle’s Chile operations. It is also important to note the Greenbush Mine in Australia was located less than 10 miles from a location of high water scarcity and thus, was included in our potential hot spots. For nickel, the potential hot spots include Mount Keith Mine in Australia. The broader ramifications of this work include the potential to promote more sustainable practices within the EV industry. By identifying potential "hot spots" in the supply chain where water stress risks are most present, this project provides a framework for developing a more sustainable supply chain. The recommendations provided in this project can help stakeholders in the EV industry to make more wholistic decisions about the environmental and social impacts of their production practices by including water consumption impacts. This project highlights the need for greater attention to be paid to water scarcity within the EV supply chain. By analyzing the water risks associated with mining critical minerals for EVs and providing recommendations for a more sustainable supply chain, this project seeks to promote more responsible production practices within the EV industry. The findings of this project have the potential to inform future research and policy initiatives aimed at addressing the environmental and social impacts of EV production. Moving forward, there is a need for more comprehensive data on water consumption and direct engagement with upstream suppliers to better understand the potential risks at these locations. Companies in the EV industry should also assess the sustainability of their supply chains on an individual level and explore alternative sources for critical minerals to reduce reliance on high-risk locations.Item Open Access Carbon Free Data Centers Through Solar Photovoltaic Generation, Battery Energy Storage, and Medium Voltage DC Power Distribution(2024-04-26) Biehl, Kevin; Drewyer, HenryUtilities, grid operators, corporates, and other stakeholders are tasked with meeting carbon emission reduction mandates at a time of rising electricity demand. Data centers are a significant driver of load growth, as they are expected to triple as a share of U.S. electricity consumption to 7.5% by 2030. Advances in direct current (DC) circuit breakers and converters enable a medium voltage direct current (MVDC) data center architecture that can take advantage of efficiency gains from DC solar-photovoltaic generation and battery storage. This study quantifies the primary benefits of co-locating these technologies, incorporating efficiency gains along with capital cost savings of MVDC power distribution relative to conventional low voltage alternating current (LVAC) systems. By quantifying these system benefits, this study highlights a cost-efficient path to meet growing data center load, particularly for data centers attempting to demonstrate 24x7 clean energy use.Item Open Access Charging Forward: A Comprehensive Analysis of New York State’s Electric Vehicle and Clean Energy Goals(2024-04-25) Kear, SarahStates throughout the U.S. are implementing electric vehicle (EV)-focused policies to spur EV adoption. EVs are viewed as an environmentally friendly mobility choice for passenger vehicles due to their lack of direct emissions like conventional internal combustion engine vehicles. However, EVs use electricity for power generation and produce upstream emissions. In 2022, New York State enacted legislation stipulating that by 2035, all new vehicles would be zero-emission vehicles. Similarly, the New York Independent System Operator, the organization operating New York's electric grid, has a public goal that 100 percent of electricity is net zero by 2040. Both policy initiatives aim to decrease greenhouse gas emissions but do not provide equal decreases in CO2 emissions throughout the state. This project explores how these policies work together to reduce greenhouse gas emissions in New York State, using county-level analysis to assess emission changes. The findings suggest that under current policies, there will be unequal decreases in emissions, with urban areas in the southeastern part of the state experiencing the greatest decline.Item Open Access Damming Uncertainty: Creating Accurate and Resilient Models for Inflow Forecasting(2022-04-22) Culberson, Benjamin; Vanover, Abi; Xue, KeyangOn the border between Paraguay and southern Brazil lies the Itaipu Binacional Dam, the world’s second largest hydroelectric dam. Both countries contributed to the construction of the dam, which began in 1971. The dam started operation of the first two turbines in 1984, the last turbine started operation in 2007. When it was finally finished, the Itaipu dam possessed twenty turbines with a total of 14,000 MW of installed capacity. Itaipu Binacional holds two of these turbines in reserve in the event of a mechanical issue with one of the other eighteen. With these eighteen turbines, the dam can still produce up to 12,600 MW at any given moment. In a treaty signed in 1973, both Brazil and Paraguay have agreed to equally share the dam’s power output (6,300 MW maximum each). This power allocation is enough to cover 85% of Paraguay’s energy needs and 8% of Brazil’s. Paraguay’s share more than covers their energy needs; terms of the treaty allow them to sell their surplus to Brazil at production cost. As the treaty between the two countries expires in 2023, the negotiations will be intense. Brazil wants to reallocate the power generation from the dam to give it a larger share of the Itaipu energy production, while Paraguay wants to keep the status quo of equal power distribution. Paraguay is also pushing to be able to sell the surplus electricity to third parties at market price. As both countries position themselves for the renegotiation of a future power-sharing agreement, accurate forecasts of future power outputs will become ever more critical. Itaipu Binacional has consistently improved its water inflow forecasting models over the past five decades, and with each improvement, the dam has been able to produce an increasing amount of power. The improvements to these models are so consequential that although the Parana River region, where Itaipu is located, has been under drought conditions for years, the dam currently produces more power than it ever has in its current lifetime. However, properly forecasting inflows into the dam remains challenging and there is still room for improvement. The primary models Itaipu uses to predict these future inflows are deterministic, which means that they predict a single value rather than a range of values. In essence, they do not forecast with uncertainty. Furthermore, these models do not fully capture the non-linear relationship of incremental inflows and other factors that influence hydrological models, such as precipitation. To aid Itaipu Binacional with forecasting future power outputs and to give the engineers there a greater understanding of forecast uncertainty, we constructed an artificial neural network (ANN) to predict future water inflows into the Itaipu water reservoir. This ANN uses repeated iteration to gradually reach an understanding of the relationship between exogenous input variables that may influence the rate of incremental inflow into the Itaipu Dam and the incremental inflows themselves. This iterative process relies on trial and error to form these relationships; eventually the ANN model will find an optimal connection between the inputs and the incremental inflows such that the ANN can accurately predict incremental inflows just by looking at the inputs. The final ANN model can outperform a standard autoregressive integrated moving average (ARIMA) time series forecast in many situations and can help the engineers at Itaipu Binacional more comprehensively understand inflow uncertainty to Itaipu. Even in the situations in which the ARIMA model more accurately forecasts incremental inflows, the ANN model still consistently provides more useful information to the user. The ARIMA model forecasts quite conservatively and fails to model the variability of the incremental inflows. Past data shows incremental inflows into Itaipu to be constantly increasing or decreasing, and never stagnant for long. In general, the final ANN model more accurately predicts this variability while the ARIMA generally forecasts a linear trend, a linear trend that does not align with past observed inflows. Thus, the ANN model, when combined with the reasonably accurate models currently used by Itaipu Binacional, provides much more insight than the ARIMA model. For the operators at the dam to optimize power production, they will need as much information as possible about future extreme inflows. For the purposes of providing this kind of information, the ANN model is significantly more useful than the ARIMA model. While the ANN model is unlikely to replace Itaipu Binacional’s current deterministic hydrological models, its ability to assist in the forecast of extreme incremental inflows into the dam means it can provide value to the engineers at Itaipu Binacional.Item Open Access Estimating the Social and Economic Impacts from Renewable Energy Developments in Emerging Energy Markets(2020-04-24) Kaynor, Camille; Simarmata, Monica Raphita; Zhang, JiayiIt is both well-understood and well-documented that household-level energy access introduces numerous social and economic benefits, including financial savings from fuel switching, increased study time for students, and increased ability to conduct income-generating activities within the household. Energy access specifically from renewable sources not only presents benefits due solely to the access to electricity they provide, but their elimination of fossil-based energy sources presents additional environmental, social, economic, and health-related benefits. Using Multi-Tier Framework (MTF) survey data from Myanmar and Nepal, and a statistical technique called “propensity score matching” (PSM), we establish regression models for predicting the social and economic impact from a renewable energy development in both Myanmar and Nepal. Ultimately, this tool provides users with data-backed information regarding optimal placement of renewable energy developments within Nepal and Myanmar to maximize social and/or economic benefits.Item Open Access EXAMINING INDIRECT NETWORK EFFECTS IN THE ELECTRIC VEHICLE MARKET SYSTEM(2023-04-27) Forest, Jade; Jhaveri, Dhruv; Owens, Katherine; Sirison, NannaphatReduction in transportation carbon emissions is a crucial enabler to a net-zero future. As decarbonization efforts increase, many states and the federal government are considering methods to catalyze transportation electrification. This study examines California’s light-duty vehicle (LDV) market's electrification, focusing on capturing EV market behavior that entails: (1) the influence of socioeconomic and demographic variables on the market, (2) the indirect network between electric vehicle (EV) adoption and EV charging infrastructure (EVCS), and (3) adoption and deployment forecast scenarios. The study uses panel data of EV, EVCS, and socioeconomic variables to perform (1) regression analyses and (2) bass diffusion modeling. This study found that median household income and share of owner-occupied housing were most significant to EV adoption and EVCS deployment. The presence of positive bidirectional network effects was verified, with stronger network impacts observed from EVCS than that observed from EVs. The rate of EV and EVCS diffusion until market saturation depends on the current adoption and size of the addressable market.Item Open Access Magic school bus, deploy! Cleaner air and cost savings in North Carolina with electric school buses.(2022-12-16) Fromuth, Jeffrey K.The purpose of this project is to evaluate ways to assist the deployment of electric school buses (ESB) across the state on behalf of the client, the North Carolina Clean Energy Fund (NCCEF). In part one of this report, we simulate vehicle-to-building battery dispatch and discuss resulting savings and economic opportunities from ESB ownership. In part two, we examine potential products NCCEF can employ to expand access to ESBs. This report reviews the strengths and shortcomings of several financing models. Getting more ESBs on the road aligns with NCCEF’s mission to be a market catalyst, ensuring wider access to a proven green product. As shown here, NCCEF is well positioned to enhance some school districts’ purchasing power. We also find that if financing is structured correctly, ESB fuel savings combined with their battery energy storage capabilities, can provide returns that sustain and broaden NCCEF investments.Item Open Access Project Resiliency: Overcoming Barriers for Repeatable Microgrids in the United States(2021-04-27) Leon-Hinton, Reed; Nadeem, Hassan; Amjad, ZukhrufThe recent blackouts in Texas and California caused by extreme weather events, such as snowstorms and wildfires, have revealed the growing burden on the national transmission system. Grid outages cost the US about $28 to $33 billion annually, with this expense growing as climate change leads to increasingly severe weather events across the globe. Microgrids, which are localized grids that can isolate from the main power grid during an outage, are key to strengthening grid resiliency, mitigating grid disturbances, and allowing faster recovery. They also accelerate the integration of distributed and renewable energy resources on the grid. This project analyzes the key barriers that hinder repeatable microgrid deployment which would enable economies of scale and thus provide cost-effective energy solutions to small scale manufacturing customers in the US. Additionally, the financial analysis and energy modeling undertaken in this study find that the participation of microgrids in energy markets is vital to deployment on a national scale. This can be achieved through uniform state-level regulation, streamlined interconnection processes, and “microgrid ready” facility infrastructure. Lastly, the risk assessment and mitigation provide a roadmap to public-private financing mechanisms for microgrid deployment.Item Open Access Reforming Solar Net Metering(2021-04-26) Ghadiri, Franco; Krishnan, Akshay; Li, RuoshuiOne of the important policies aimed at diversifying the energy resource mix, stimulating local economic growth, and encouraging private investment in solar energy is Net Energy Metering (NEM). Under current NEM policies, participating customers generating electricity to serve their load can receive a financial credit for any surplus energy that they feed back to their utility’s grid. Unfortunately, several studies have shown that NEM policies are regressive onto low-income, disadvantaged communities as the revenue loss for utilities causes them to raise electricity rates in order to recover their costs. To quantify how NEM schema can potentially change the grid power flow and lead to variance in grid congestion, Locational Marginal Price, and utility’s avoided cost, we conducted an optimal power flow analysis in a synthetic IEEE 30-bus grid under 192 scenarios for three States (CA, FL, & MA). We used NREL’s System Advisor Model (SAM) to create synthetic data of our transmission grid using both the electricity load of a combination of residential and commercial buildings within our 30-bus system, and the behind-the-meter solar PV production generated using PVWatts & PySAM tools. We evaluated NEM policies by performing a cost-benefit analysis from the perspective of the NEM customers, non-NEM customers and the utilities, to demonstrate how NEM policies result in a net cost. We proposed several recommendations that can be incorporated into future NEM tariffs that will make them more equitable for the non-NEM ratepayers.Item Open Access The Electric Vehicle Transition: An Analysis of the EV Value Chain and Market Entry Strategies for an Energy Client(2020-04-24) Adams, Tucker; Davenport, Emily; Vitha, JayThe increasing adoption of Electric Vehicles (EVs) will change the landscape of several industries including transportation, technology, and electric power. EVs will impact the business plans and strategies of energy providers as they continue to provide energy to customers. An energy client is trying to capture the additional value that EVs are going to bring to the energy sector. This study analyzes and categorizes the current state of the EV market, both in Texas and nationally, organizes the current projections made from large industry reports, assesses the value chain of EVs and provides recommendations for an energy client about how to best proceed with a new strategy that incorporates EVs to make the firm successful in this quickly changing industry.Item Open Access The Impact of Electric Vehicle Adoption in North Carolina(2019-04-24) Chen, Shiwen; Jiang, Yi; Shen, Yangdi; Singh, NikhitaThe U.S total annual sales of Battery Electric Vehicles (EVs) and Plug-in EVs increased from 16 thousand in 2011 to 190 thousand in 2017; that is 12 times in size over 6 years (Fitzgerald). Consequently, the demand for electricity has increased rapidly, which creates new challenges and opportunities for the electricity generation system and the power grid. This project assesses the impacts of different scenarios of penetration of EVs in the Duke Energy Carolinas/Duke Energy Progress (DEC/DEP) region in 2030. Specifically, the project simulates the real-time EVs operation in 2030 and provides economic, environmental and social insights. First this project will characterize scenarios of EV penetration in the region that take EV growth and charging patterns into consideration. Then the additional demand caused by each scenario will be generated by a custom model built for this project. Lastly this project will utilize Aurora, an electric modeling, forecasting, and analysis tool, to simulate the impact of the additional demand on the DEC/DEP system in 2030. The results of this project underline the relationship between the economic and environmental impact of electric vehicles and the DEC/DEP fuel mix.