My dissertation tells the history of the Electric Power Research Institute (EPRI), the U.S. electric utility industry’s collective technology organization, founded at the onset of the successive “Energy Crises” of the 1970s. The narrative tells a history of EPRI in three registers: the organization, the people, and the ideas. It tracks the internal politics of the industry’s research and development arm through each of its five sectors—nuclear generation, fossil fuel generation, environment and safety, end use, and transmission and distribution. Each sector was buffeted by EPRI’s management history, what one EPRI career project manager dubbed, “Peace, a Civil War, and the Great Depression.” Embedded in each of these sector histories is story of the incremental shift from one regulatory regime, a “natural monopoly,” to an as-of-yet unrealized regime, the “self-regulated network.” When deregulation was imminent in the mid-1990s, utility executives decided that collaboration and competition were at odds. EPRI funding plummeted by half. Instead of making it to the aspired destination at the “self-regulated electricity network,” American power got stuck in an impasse I call, with irony, the “networked grid.” The “networked grid” is a rigid grid with information and communication technology laid on top so as to achieve the illusion of economic efficiency at the cost of reliability, security, sustainability, and physical efficiency.

Thesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2016. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 221-224). / High-Speed Rail (HSR) has been expanding throughout the world, providing various nations with alternative solutions for the infrastructure design of intercity passenger travel. HSR is a capital-intensive infrastructure, in which multiple subsystems are closely integrated. Also, HSR operation lasts for a long period, and its performance indicators are continuously altered by incremental updates. With this background, design and monitoring of lifecycle properties, or "ilities", is an important factor to achieve long-term successful operation. This thesis aims to analyze and evaluate dynamic behaviors of "ilities" and their interactions in HSR operation. After the literature review and the study of industrial trends about HSR "ilities", safety, availability and profitability are chosen as key "ilities" which should be monitored in HSR operation. The Tokaido Shinkansen in Japan, and Amtrak's service in the US Northeast Corridor (NEC) are chosen as cases to study "ilities" trends. In the Tokaido Shinkansen, three "ilities" form a positive feedback loop to make HSR operation successful. The NEC shows high profitability, but it does not perform as well in terms of safety and availability due to several systemic factors. System Dynamics (SD) is applied to visualize interactions of "ilities" and other variables of interest. Qualitative causal loop diagrams (CLD) reveal several feedback loops affecting "ilities". In particular, the integration of train operation and infrastructure / rolling stock management results in the emergence of major feedback loops which cannot easily be captured by other methodologies. Qualitative SD models are converted into quantitative SD models, and numerical simulations are run to further understand the structure of causal loop diagrams. Estimated parameters in the Tokaido and the NEC suggest the different relationships among "ilities" and other variables. Further, sensitivity analyses are conducted to evaluate how different policies affect "ilities" in future HSR operations. / by Tatsuya Doi. / S.M. in Engineering Systems

Thesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (page 84). / This research demonstrates the effectiveness of Systems Theoretic Process Analysis (STPA) and the advantages that result from using this new safety analysis method compared to traditional techniques. To do this, STPA was used to analyze a case study involving Naval Offshore Supply Vessels (OSV) that incorporate software-intensive dynamic positioning in support of target vessel escort operations. The analysis begins by analyzing the OSVs in the context of the Navy's organizational structure and then delves into assessing the functional relationship between OSV system components that can lead to unsafe control and the violation of existing safety constraints. The results of this analysis show that STPA found all of the component failures identified through independently conducted traditional safety analyses of the OSV system. Furthermore, the analysis shows that STPA finds many additional safety issues that were either not identified or inadequately mitigated through the use of Fault Tree Analysis and Failure Modes and Effects Analysis on this system. While showing the benefit of STPA through this case study, other general advantages that STPA has relative to traditional safety analysis techniques are also discussed. First, this thesis discusses how STPA generates results that are completely compliant with the requirements for system hazard analysis set forth in MIL-STD-882E and that STPA more completely satisfies the tasks in MIL-STD-882E than traditional safety analysis techniques. Next, the link between STPA and Causal Analysis using Systems Theory- (CAST), two Systems Theoretic Application and Model Processes (STAMP) tools is discussed to highlight how using STPA for hazard analysis benefits subsequent accident investigations using the CAST framework. / by Blake Ryan Abrecht. / S.M. in Engineering Systems

Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 43-46). / Over the last few decades, although US gross domestic spending on Research and Development (R&D) as a percentage of GDP has risen from around 2.27% in 1981 to 2.74% in 2016, federal funding for R&D has fallen steadily, from 1.19% to o.81% over the same period. These changes reflect a broader shift in the US from a government-driven R&D model to a business-driven model. Towards the goal of identifying the regional economic impacts of federally funded R&D, I first build on previous work to develop a method to obtain federal funding for R&D at granular geographic levels using Natural Language Processing (NLP) methods to automatically classify open data on federal contracts and grants as R&D or non-R&D awards. This method results in a 95% accuracy rate in classifying federal awards, and covers 56% of US federal R&D obligations made in the year 2016. As underreporting issues in the data source are addressed, this method will yield higher coverage rates, thus creating a unique dataset that affords opportunities to study the regional impacts of federally funded R&D. Next, I adapt Hausman, N. (2012). University Innovation, Local Economic Growth, and Entrepreneurship to identify the employment-generation effects of federally funded university R&D and compare impacts of overall R&D funding to the employment-generation arising from R&D funding provided to specific academic disciplines. I find that the employment-generation effects of federally funded computer science R&D are significant and much more pronounced than the corresponding effects of overall federally funded university R&D. / by Shreyas Gadgin Matha. / S.M. in Technology and Policy

Thesis: Ph. D. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 127-137). / This thesis addresses a long-standing question about how to compare energy technologies that emit different types of climate forcers during their life cycles. This problem is challenging because these forcers have dissimilar lifetimes in the atmosphere, ranging from days (black carbon) to decades (methane, CH 4) to centuries or more (carbon dioxide, CO2 ). Efforts to reduce the climate impacts of energy use may involve a tradeoff between these short-and long-lived emissions. Equivalency metrics, which express emissions of one forcer (e.g., CH4 ) in units of another (typically CO2), are widely-used tools for comparing the climate impacts of emissions. These metrics allow climate impacts to be expressed on a single scale, but they require assigning a relative value to short- versus long-lived climate forcing. The equivalency metric approach is used in a large variety of applications, from technology evaluation to emissions trading. These applications almost universally rely on a single metric, developed as a placeholder over twenty-five years ago. This metric, the global warming potential (GWP), compares gases based on their radiative forcing impacts over a fixed time horizon (usually 100 years). The design of the GWP, including critically the time horizon over which emissions are compared, is largely arbitrary, yet it has enormous implications for comparing the climate impacts of energy technologies and other emissions sources. Despite the practical and political importance of equivalency metrics, the scientific literature has not produced a consensus on how to design or choose these metrics. To address this gap in the literature, this thesis develops a new conceptual and quantitative modeling approach to link equivalency metric design to global climate policy goals. This procedure involves (a) formulating a set of goal-inspired equivalency metrics, (b) testing metrics by simulating the results when they are applied in real-world contexts, and (c) selecting metrics based on multiple performance criteria. We highlight two dimensions of metric performance: climate performance (i.e., whether metric-based decisions meet climate policy goals) and energy performance (i.e., whether these decisions support energy use, for example during a technology transition). No metric performs optimally across all criteria, and this approach allows us to quantify these performance tradeoffs. The central result of the thesis is that climate policy goals can be used to inspire equivalency metric design, and these goal-inspired metrics address key shortcomings of the GWP(100). Specifically, under a policy to limit global temperature change to 2°C (where radiative forcing levels stabilize around mid-century), a shorter time horizon is essential. We find that applying the GWP(100) in this policy context can lead to radiative forcing overshoots in excess of two thirds of the remaining budget. One set of goal-inspired metrics addresses this concern by reducing the time horizon over which emissions are compared as a radiative forcing limit is approached (Chapter 2). These metrics increase the impact value placed on short-lived CH4 (relative to long-lived CO2 ) over time. We find that this design reduces the risks of overshooting radiative forcing limits, despite inherent uncertainty in the timeline for reaching these limits (Chapter 3). Relative to other metrics that lead to similar peak radiative forcing outcomes, these goal-inspired metrics allow more energy use early on, which can help enable technology transitions (Chapter 4). Applying these goal-inspired metrics to evaluate natural gas suggests that the mitigation benefits of this high-CH 4-emitting fuel will decrease significantly in the coming years. For example, under a radiative forcing limit consistent with a 2°C temperature change policy, the climate impact of natural gas electricity increases from 50% that of coal to 80% by mid-century (Chapter 2). Similar results apply to transportation fuels with high CH4 (or black carbon) emissions (Chapter 2, Chapter 5). This result draws into question large investments in technologies and long-lived infrastructure with high life cycle CH4 emissions - and provides a quantitative basis for calculating timelines to reduce the CH4 intensity of these technologies or transition to lower-emitting technologies. A bridging strategy, where technologies with high CH4 emissions are followed by those with lower emissions, permits greater overall energy consumption while meeting climate policy targets (Chapter 5). / by Morgan R. Edwards. / Ph. D. in Engineering Systems

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Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 69-74). / This thesis explores the evolution of the electric power sector in New England under the expansion of transmission capacity and under policy with increasing Clean Energy Standards (CES). I use EleMod, a Capacity Expansion Planning model, to compare (1) the reference case of current transmission assets, (2) increasing transmission interface capacities within New England, (3) increasing interconnection capacities with Canada, and (4) both capacity expansions. Transmission expansion allows electricity trade between states and enables them to take advantage of localized, intermittent resources like wind power. Increasing the interconnection capacity with Canada allows the system to optimally allocate the available hydropower energy for imports in the hours of highest net demand. Both transmission expansions together make even stronger use of their contributions. For the capacity expansion model, I choose a set of generation technologies available in New England, and supply cost and operational data from public domain sources. My contributions to EleMod include: (1) the representation of transmission interfaces for New England; (2) the addition of an CES policy standard forcing generation shares from a subset of CES-eligible resources; (3) the modeling of an external hydro reservoir resource in Canada that can be used to supply the load in New England based on cross-border interconnection constraints and the total available energy per year; and (4) the detailed state-level representation of the New England power sector with generation technologies, installed capacities, transmission interface capacities, and CES targets. Policy scenarios increase CES from an average of 25% in 2018 in the base scenario to 95% in 2050 in the decarbonization scenario. Through all policy scenarios, combined-cycle gas plants (GasCC) with carbon capture and storage (CCS) technology dominate the capacity expansions. Increases in transmission capacity lead to higher shares of wind in generation, especially when both transmission and interconnection are expanded. Natural gas, in the form of GasCC with and without CCS, takes shares of the generation mix of up to 85% by 2050. Thus, I also assess the role of pipeline capacities into New England. Because other natural gas uses like residential heating demand have priority over generators, gas-fired power plants cannot expect to meet all their demand during critical periods of shortage in the winter. However, this issue is part of a larger integrated resource planning process. Both transmission and interconnection expansion reduce total system costs by an annual 3.95% and 4.29%, respectively. Because transmission costs are not included in the model, I separately assess the costs and benefits of both transmission expansion scenarios. Transmission expansions from Maine to Massachusetts of 2,000 MW and interconnection expansions to Canada of 3,000 MW and 4,500 MW from Maine and Vermont, respectively, allow for optimal allocation of flows across lines in over 90% of the hours. For interconnection, the calculation estimates costs to be about 1% higher than the benefits, and for transmission within the region the benefits exceed the costs by about 40%. / by Christoph Tries. / S.M. in Technology and Policy

Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2018 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 51-55). / This thesis studies the food safety supply and demand in China with the focus on the producing entities and the end consumers. The first chapter concerns different farmers' organizational models and their implications for food safety issues. We conducted three research trips to China and interviewed key personnel from 25 agricultural cooperatives and one agricultural enterprise about the way they organize production activities with farmers. Our findings show that agricultural cooperatives employ a mix of models to mobilize farmers that exert different levels of direct controls over the production activities. We concluded that the choice of model is likely to be based on the difficulty of cultivating certain types of crops. Also, the motivation of agricultural cooperatives in obtaining quality certifications varies based on their position in the value chain: cooperatives that sell directly to end consumers are more motivated to obtain quality certifications than cooperatives selling to downstream processors or distributors. In the case of agricultural enterprise who employs large area of land employ, the contracting farming model is usually adopted. Despite low cost in acquiring land and labor for production, the enterprise has to compromise with a lower level of control over the production activities in the contract farming model. The second chapter studies consumers' response towards different food safety transparency information with respect to different demographic and socio-economical characteristics. The findings suggest that consumers are most likely to respond to seeing organic certificates and the use of organic ingredients in processed products with higher level of purchase intention and a higher willingness to pay. We also found out that respondents who are either male or have children are more likely to respond to food safety information than the other demographic groups.. / by Wenjia Wang. / S.M. in Technology and Policy / S.M.inTechnologyandPolicy Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2018 / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 67-70). / Declining soil health is a major problem in India, affecting nearly 120 million hectares of land constituting 37% of the total geographic area. Soil degradation poses a significant threat to India's food security, due to its negative impact on long-term crop yields, which are crucial for feeding a burgeoning population. Imbalanced fertilizer use, a negative consequence of the Green Revolution, is one of the primary causes of soil degradation and adversely impacts the environment, human health, and farm profitability. The problem can be addressed by adopting the principles of site-specific nutrient management (SSNM), which call for judicious use of fertilizer based on frequent soil testing. However, inadequate soil testing capacity and lack of access to information act as barriers to its adoption. / This project aims to facilitate adoption of SSNM by developing a point-of-use soil testing and nutrient management system, made up of two key components 1) an affordable, point-of-use sensor that enables on-farm soil testing and 2) a recommendation engine that provides actionable fertilizer advice through mobile phones. This thesis presents the design of the fertilizer recommendation engine, by answering the following research question: "How to implement actionable fertilizer recommendations, in order to maximize adoption by resource-constrained farmers?" In doing so, it represents the second phase of the project, building on the actionability framework laid by done by fellow researcher, Soumya Braganza. This thesis mainly focuses on the issues involved in the implementation of the recommendation engine, through a "user centered approach" adopting diverse methods such as stakeholder interviews and conjoint analysis. / In order to answer the question of customization, data from the conjoint study was analyzed, revealing the influence of farmers' behavioral factors on actionability. In order to realize the level of customization required, a Bayesian algorithm was proposed to generate recommendations suited to a farmer's behavior. Thereafter, lessons from field studies were consolidated into system requirements for the fertilizer recommendation engine, and methods were proposed to address them. Lastly, a layered architecture is presented to implement the desired features of the recommendation engine in an integrated manner. / Funded by MIT-Tata Center / by Nikhil Mallareddy. / S.M. in Technology and Policy / S.M.inTechnologyandPolicy Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society

Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2019 / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 108-111). / Cost-reflective electricity tariffs hold the key to enabling a wider adoption of distributed energy resources. Standard residential electricity tariffs have a flat monthly charge and a static volumetric energy charge that do not provide the correct economic signals to customers and do not reflect the costs of maintaining and operating the grid. Besides subsidies or specific supports to certain technologies, there are currently limited economic incentives for customers to invest in numerous technology options, like home batteries and AC controls, that could collectively and in response to efficient price signals: reduce system peak load, reduce greenhouse gas emission, provide greater system reliability, and reduce system costs. This thesis qualitatively explores the cost drivers of the electricity system and their implications for residential tariff design, as well as the economic inefficiencies and cross subsides that are present under the current volumetric rate tariff. / In addition, we quantitatively assess the impacts of different electricity tariffs on consumers and on distributed energy resource adoption. Based on hourly electricity meter data for 54,412 users in the Chicago area, the EIA 2016 residential energy survey, and the Commonwealth Edison's (ComEd's) costs of service reports, this thesis creates a full picture of residential energy consumption and costs. A regression-based Electric Load Decomposition (ELD) model was developed to predict hourly load profiles for each user's air-conditioning usage, electric heating usage and electric hot water heating usage. In addition, the MIT Demand Response and Distributed Resource Economics (DRE) model was used to evaluate the impacts of different electricity tariffs on customer bill changes, adoption of distributed energy resources, and reduction of CO₂ emissions. / In this work, we design twelve revenue-neutral tariffs which recover the same total amount of revenues as ComEd's default volumetric tariff. We then compare these tariffs to the current utility volumetric tariff for all 54,412 residential electricity accounts, and we assess the impacts of flat volumetric charges, Time of Use Pricing, Critical Peak Pricing, Coincident Peak Capacity Charges, Real Time Pricing, and Carbon Pricing on customer bills and other metrics of interest. In addition, we also model the adoption of several distributed energy resources in response to these different tariff scenarios in order to understand their economic viability. This work identifies the main tariff features that have meaningful impact on electricity bills, energy usage and CO₂ emissions. Recovering network costs through a tariff that relies on a large capacity charge creates substantial bill changes compared to the default flat tariff. / Alternatively, a tariff that has a combination of a flat volumetric rate and a real-time price creates minimal bill impacts. Additionally, we find that most of the tariffs tested in this work incentivize the adoption of smart thermostats for air conditioning and for electric hot water heater. However, in the case of electric space heating, none of the tariffs produced significant incentives to load shift by preheating the building, therefore smart thermostats for electric space heating were rarely adopted. The value created by residential batteries and solar panels are never enough to offset their high (unsubsidized) upfront costs. Furthermore, we find that tariffs that rely on large capacity charges to recover significant portions of network costs, also create favorable prices during the winter that allow electric heat pumps to have lower annual operational costs than natural gas furnaces. / Finally, we find that although precooling or preheating of a building (to avoid high price periods) lowers the electricity costs associated to space conditioning, they also result in increased energy consumption and increased carbon dioxide emissions. On the other hand, the scheduling and operating of smart electric hot water heaters can reduce emissions. / Funding from Alfred P. Sloan Foundation / by Nelson Lee. / S.M. in Technology and Policy / S.M.inTechnologyandPolicy Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society