Motivated by global climate change, enhancing innovation systems for energy technologies is seen as one of the largest public policy challenges of the near future. The role of policy in enhancing energy innovation systems takes several forms: public provision of research and develop funding, facilitating the private sector’s capability to develop new technologies, and creating incentives for private actors to adopt innovative and appropriate technologies. This dissertation explores research questions that span this range of policies to develop insights in how energy technology innovation policy can be reformed in the face of climate change. The first chapter of this dissertation explores how decision making to allocate public research and development funding could be improved through the integration of expert technology forecasts. I present a framework to evaluate and optimize the U.S. Department of Energy’s research and development portfolio of applied energy projects, accounting for spillovers from technical complimentary and competition for the same market share. This project integrates one of the largest and most comprehensive sets of expert elicitations on energy technologies (Anadón et al., 2014b) in a benefit evaluation framework. This work entailed developing a new method for probability distribution sampling that accommodates the information that can be provided by expert elicitations. The results of this project show that public research and development in energy storage and solar photovoltaic technologies has the greatest marginal returns to economic surplus, but the methodology developed in this chapter is broadly applicable to other public and private R&D-sponsoring organizations. The second chapter of this dissertation explores how policies to transfer technologies from federally funded research laboratories to commercialization partners, largely private firms, create knowledge spillovers that lead to further innovation. In this chapter, I study the U.S. Department of Energy’s National Laboratories, and provide the first quantitative evidence that technology transfer agreements at the Labs lead to greatly increased rates of innovation spillovers. This chapter also makes a key methodological contribution by introducing a technique to utilize automated text analysis in an empirical matching design that is broadly applicable to other types of social science studies. This work has important implications for how policies should be designed to maximize the social benefits of the $125 billion in annual federal funding allocated to research and development and the extent to which private firms can benefit from technology partnerships with the government. The final chapter of this dissertation explores the effectiveness of international policy to facilitate the deployment of low-emitting energy technologies in developing countries. Together with Joern Huenteler, I examine wind energy deployment in China supported through international climate finance flows under the Kyoto Protocol’s Clean Development Mechanism. Utilizing a project-level financial model of wind energy projects parameterized with high-resolution observations of Chinese wind speeds, we find that the environmental benefits of projects financed under the Clean Development Mechanism are substantially lower than reported, as many Chinese wind projects would have been built without the Mechanism’s support, and thus do not represent additional clean energy generation. Together, the essays in this dissertation suggest several limitations of energy technology innovation policy and areas for reform. Public funds for energy research and development could be made more effective if decision making approaches were better grounded in available technical expertise and developed in framework that captures the important interactions of technologies in a research and development portfolio. The first chapter of this dissertation suggests a politically feasible path towards this type of reform. Policies to “unlock” publicly sponsored inventions from the organizations that develop them have broad impact on private sector innovation. These policies multiply the effect of public research and development funds, but should be strengthened to more rapidly advance the scientific frontier. The second chapter of this dissertation provides some of the first quantitative evidence to support reform in this area. Finally, international policies to facilitate the deployment of climate-friendly technologies in developing countries face serious implementation challenges. The current paradigm of utilizing carbon markets to fund individual projects that would not have otherwise occurred has failed to encourage energy technology deployment in one of the sectors with the greatest experience with such policies. The third chapter of this dissertation suggests that this failure has been largely due to poorly designed procedural rules, but options for reform are available. Mitigation of global climate change will require broad policy response across the full range of scales, sectors, and policy spheres. Undoubtedly, climate mitigation will result in widespread transformation of energy systems. This dissertation focuses on the role of innovation policy in accelerating the transformation of these systems. The range of policies studied in this dissertation can make climate change mitigation more politically feasible and more cost effective by expanding the set of technological choices available to public and private actors faced with incentives and requirements to lower their greenhouse gas emissions to collectively safe levels. / Public Policy

[No abstract submitted] / Science, Faculty of / Physics and Astronomy, Department of / Graduate

abstract: The main objective of this research is to develop reliability assessment methodologies to quantify the effect of various environmental factors on photovoltaic (PV) module performance degradation. The manufacturers of these photovoltaic modules typically provide a warranty level of about 25 years for 20% power degradation from the initial specified power rating. To quantify the reliability of such PV modules, the Accelerated Life Testing (ALT) plays an important role. But there are several obstacles that needs to be tackled to conduct such experiments, since there has not been enough historical field data available. Even if some time-series performance data of maximum output power (Pmax) is available, it may not be useful to develop failure/degradation mode-specific accelerated tests. This is because, to study the specific failure modes, it is essential to use failure mode-specific performance variable (like short circuit current, open circuit voltage or fill factor) that is directly affected by the failure mode, instead of overall power which would be affected by one or more of the performance variables. Hence, to address several of the above-mentioned issues, this research is divided into three phases. The first phase deals with developing models to study climate specific failure modes using failure mode specific parameters instead of power degradation. The limited field data collected after a long time (say 18-21 years), is utilized to model the degradation rate and the developed model is then calibrated to account for several unknown environmental effects using the available qualification testing data. The second phase discusses the cumulative damage modeling method to quantify the effects of various environmental variables on the overall power production of the photovoltaic module. Mainly, this cumulative degradation modeling approach is used to model the power degradation path and quantify the effects of high frequency multiple environmental input data (like temperature, humidity measured every minute or hour) with very sparse response data (power measurements taken quarterly or annually). The third phase deals with optimal planning and inference framework using Iterative-Accelerated Life Testing (I-ALT) methodology. All the proposed methodologies are demonstrated and validated using appropriate case studies. / Dissertation/Thesis / Doctoral Dissertation Industrial Engineering 2020

The increasing integration of renewable generation presents power systems with economic and reliability challenges, mostly due to renewables' volatility, which cannot be effectively addressed with business-as-usual practices. Fortunately, this is concurrent with rising levels of Distributed Energy Resources (DERs), including photovoltaics, microgeneration and flexible loads like HVAC loads and electric vehicles. DERs are capable of attractive time-shiftable behavior and of transacting reactive power and reserves in addition to real power. If DER capacity is optimally allocated among these three products, distribution network and economic benefits can be realized and renewable-related challenges can be mitigated, enabling increased renewable integration safety limits. In order to achieve optimal DER scheduling, this thesis proposes the formulation of a spatiotemporal marginal-cost based distribution power market and develops and implements tractable clearing algorithms. First, we formulate a centralized market clearing algorithm whose result is the optimal DER real power, reactive power and reserves schedules and the optimal nodal marginal costs. Our market formulation develops for the first time detailed and realistic models of the salient distribution network variable costs (transformer degradation, voltage sensitive loads) together with distribution network constraints (voltage bound constraints, that reflect distribution network congestion and AC load flow), and intertemporal DER dynamics and capabilities. However, the centralized algorithm does not scale, motivating the use of distributed algorithms. We propose two distributed algorithms: • A fully distributed algorithm that relies on massively parallel DER and distribution line specific sub-problem solutions, iteratively coordinated by nodal price estimates which promote and eventually enforce nodal balances. Upon convergence, nodal balances hold and optimal marginal costs are discovered. We further existing practices by using local penalty updates and stopping criteria that significantly reduce communication requirements. • A novel, partially distributed formulation in which DERs self-schedule in parallel based on centrally calculated price estimates, resulting from a load flow calculation. Nodal balances hold during all iterations. Finally, we are, to the best of our knowledge, the first to study voltage-constrained distribution market instances cleared with distributed methods. We decrease the deviation of marginal costs from their optimal values using first order optimality conditions and use voltage barrier functions for speedier convergence. / 2020-03-31T00:00:00Z

In this dissertation, a meso-scale computational model, using the smoothed particle hydrodynamics (SPH) numerical method, is used to simulate the deposition process at the electrolyte/anode interface of a lithium metal battery. The SPH model simulates the physics at this interface by solving the governing equations for diffusion, migration, and potential distribution in a binary electrolyte and near a reactive, moving interface and dendrite surfaces. The model is implemented in the LAMMPs code base and includes the ability to model charge/discharge cycles. Using the SPH model, the effect of various structures in the electrolyte on mass transport and dendrite growth are investigated. The first goal is to understand the effects of local transport through battery separators on dendrite growth by explicitly representing commercial battery separator structures taken from SEM images. Using SPH, the geometrical parameters of the separator are characterized based on their effect on mass transport and dendrite growth. The findings from the simulations suggest that the tortuosity of the separator is a key property affecting transport. Additionally, despite the characterization of battery separators using bulk properties, the heterogeneity of the separators lead to vastly different local transport outcomes. Building upon these insights and in collaboration with experimental groups, the effect of the structure of novel coatings and electrolytes on the mass transport to the anode and subsequent dendrite morphology are investigated. The computational studies demonstrate the mechanisms by which these novel techniques improve the performance of lithium metal batteries such as reducing the pore size in carbon nanomembranes reduces dendrite length and increases deposition density; ionic liquid crystal supramolecular assemblies oriented perpendicular to the anode increase the uniformity of Li+ deposition at the anode; the effects of homogeneity of ionic conductivity of protective coatings on the anode to enable uniform Li+ deposition. Additionally, the model is used to explore how the local conditions in the electrolyte change during battery cycling. During standard charging, the Li+ concentrations at the anode create reaction rate limited conditions that lead to more uniform Li+ deposition. However, during “fast” charging, the local Li+ concentrations rapidly decrease leading to mass transport limited conditions which result in dendrite growth and lower battery performance.

No description available.

Elemental aluminum is highly reactive with water but is normally coated with a layer of aluminum-oxide, which prevents any interaction between the aluminum and the water. A process was recently developed that removes the aluminum-oxide layer and enables the aluminum-water reaction to occur and produce heat and hydrogen. The resulting fuel is a promising technology in reducing the logistical burden of fueling remote locations, due to its high energy density and ability to generate large volumes of hydrogen. However, there are significant challenges in dispensing the solid fuel that must be overcome before the fuel could be used in field applications. One avenue to address this problem is to transform the solid aluminum fuel into a slurry by mixing ground aluminum fuel particles and mineral oil. The objective of this work is to improve and characterize the aluminum slurry fuel and demonstrate an application for the technology. First, experiments were conducted to improve the rheological properties of the aluminum slurry and characterize the impact of slurry parameters on reaction behavior. A study was conducted to identify the optimal pumping composition of aluminum-mineral oil slurry. Reducing the aluminum particle size and the addition of 2% bentonite and 1% fumed silica to the slurry were found to have the greatest reduction in viscosity and settling of the aluminum slurry. Another study examined the impact of particle size, temperature, and water turbulence on the reaction time and hydrogen release of the aluminum slurry. Analysis suggests that the reaction rate of the slurry is limited by the mobility of the aluminum in the mineral oil. The data from the reaction experimentation can be found in the supplemental materials. Second, a prototype cooking system was developed to demonstrate an application for the aluminum slurry and to use the heat from the aluminum-water reaction. The system displayed the ability to dispense aluminum slurry in a controlled manner, maintain a flame using generated low-pressure hydrogen, and heat a body of water using the aluminum-water reaction.

Chromium poisoning of the air electrode remains a significant obstacle to the long-term performance of solid oxide fuel cells (SOFCs). Many strategies to mitigate this effect have been investigated. However, they require the introduction and development of new materials and components. Furthermore, these methods do not ensure reliable SOFC performance for a sufficient amount of time for commercial viability. An avenue that has not been previously well explored is the in-situ removal of Cr-rich deposits. Here, electrochemical cleaning, a new poisoning mitigation method, is investigated. During cleaning, a mild anodic bias reverses the electrochemical deposition reactions that form chromium-rich deposits. Chromium vapor species are reformed, freeing up the active sites and recovering cell performance. Cells with LSM/YSZ composite air electrodes were exposed to Cr vapors at 800°C and then subjected to electrochemical cleaning. Changes to cell performance were assessed using current-voltage (IV) measurements. Post-test chromium quantification was conducted using energy dispersive x-ray spectroscopy (EDS). Scanning electron microscopy (SEM) revealed that electrochemical cleaning removes Cr2O3, one of two types of Cr-rich deposits that form in LSM-based cells. Using thermogravimetric analysis (TGA) and x-ray diffraction crystallography (XRD), the chemical decomposition of the other type of Cr-rich deposit, Mn, Cr spinel, was investigated as a deposit removal strategy. MnCr2O4 is not thermodynamically stable below 540°C under pure oxygen, forming Cr2O3 and Mn2O3. It was found that the rate of decomposition is quite low and likely not practically feasible on larger spinel particles. The easier method to fully recover cell performance is to electrochemically clean the cell at a frequency high enough that prevents the formation of a significant amount of Mn, Cr spinel (MnCr2O4). Thus, the potential for a diagnostic tool that determines the onset of spinel formation was investigated. A distribution of relaxation times (DRT) analysis was used to better understand physical changes that occur at the LSM and YSZ phases during cell activation and poisoning. Two DRT peaks were attributed to two specific oxygen reduction reaction (ORR) pathways, supported by known property changes that occur during cell operation. It was found that the deposition of Cr-rich deposits on the YSZ surface causes a positive frequency shift in the DRT peak associated with the ORR pathway starting at the YSZ/gas interface. Finally, the analysis and conclusions found for Cr poisoning in LSM-based cells is applied in a discussion on chromium poisoning mitigation and reversal strategies more Cr-tolerant mixed electronic/ionic conducting (MIEC) electrode materials.

University of Macau / Faculty of Science and Technology. / Department of Electrical and Computer Engineering

<p>The building was selected for a detailed study of heating consumption that is located in the city of Gävle and the top fifth energy consumption in this city in 2006. Classrooms, workshops, offices and a restaurant with kitchen compose the building of two floors.The aim of this thesis is to design the best approach to reduce consumption and achieve a high efficiency of energy utilization in these companies. The project is going to optimize the system.Series of measurements are taken to achieve the heat losses. The heat losses are calculated through the building in the first step. Afterwards, with the result of ventilation, heating and electrical usage an energy balance is made to calculate the efficiency of the installation through the building envelop.It is to study the indoor climate within a building, as well as energy consumption for the entire building. In addition, it is also used to measure the temperature of ventilation systems and check the schedule of air supply.Analyze the result of the value that is measured. Improve some part of this building that reduces the heating consumption.At last give some suggestion like construction a new roof reduce the heat loss and change some door that is not correct in the building.</p>