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Accurate forecasting of electricity prices has been a key factor for bidding strategies in the electricity markets. The increase in renewable generation due to large scale PV and wind deployment in California has led to an increase in day-ahead and real-time price volatility. This has also led to prices going negative due to the supply-demand imbalance caused by excess renewable generation during instances of low demand. This research focuses on applying machine learning models to analyze the impact of renewable generation on the hourly locational marginal prices (LMPs) for California Independent System Operator (CAISO). Historical data involving the load, renewable generation from solar and wind, fuel prices, aggregated generation outages is extracted and collected together in a dataset and used as features to train different machine learning models. Tree- based machine learning models such as Extra Trees, Gradient Boost, Extreme Gradient Boost (XGBoost) as well as models based on neural networks such as Long short term memory networks (LSTMs) are implemented for price forecasting. The focus is to capture the best relation between the features and the target LMP variable and determine the weight of every feature in determining the price.
The impact of renewable generation on LMP forecasting is determined for several different days in 2018. It is seen that the prices are impacted significantly by solar and wind generation and it ranks second in terms of impact after the electric load. The results of this research propose a method to evaluate the impact of several parameters on the day-ahead price forecast and would be useful for the grid operators to evaluate the parameters that could significantly impact the day-ahead price prediction and which parameters with low impact could be ignored to avoid an error in the forecast.
The impact of renewable generation on LMP forecasting is determined for several different days in 2018. It is seen that the prices are impacted significantly by solar and wind generation and it ranks second in terms of impact after the electric load. The results of this research propose a method to evaluate the impact of several parameters on the day-ahead price forecast and would be useful for the grid operators to evaluate the parameters that could significantly impact the day-ahead price prediction and which parameters with low impact could be ignored to avoid an error in the forecast.
ContributorsVad, Chinmay (Author) / Honsberg, C. (Christiana B.) (Thesis advisor) / King, Richard R. (Committee member) / Kurtz, Sarah (Committee member) / Arizona State University (Publisher)
Created2019
Description
Demand for green energy alternatives to provide stable and reliable energy
solutions has increased over the years which has led to the rapid expansion of global
markets in renewable energy sources such as solar photovoltaic (PV) technology. Newest
amongst these technologies is the Bifacial PV modules, which harvests incident radiation
from both sides of the module. The overall power generation can be significantly increased
by using these bifacial modules. The purpose of this research is to investigate and maximize
the effect of back reflectors, designed to increase the efficiency of the module by utilizing
the intercell light passing through the module to increase the incident irradiance, on the
energy output using different profiles placed at varied distances from the plane of the array
(POA). The optimum reflector profile and displacement of the reflector from the module
are determined experimentally.
Theoretically, a 60-cell bifacial module can produce 26% additional energy in
comparison to a 48-cell bifacial module due to the 12 excess cells found in the 60-cell
module. It was determined that bifacial modules have the capacity to produce additional
energy when optimized back reflectors are utilized. The inverted U reflector produced
higher energy gain when placed at farther distances from the module, indicating direct
dependent proportionality between the placement distance of the reflector from the module
and the output energy gain. It performed the best out of all current construction geometries
with reflective coatings, generating more than half of the additional energy produced by a
densely-spaced 60-cell benchmark module compared to a sparsely-spaced 48-cell reference
module.ii
A gain of 11 and 14% was recorded on cloudy and sunny days respectively for the
inverted U reflector. This implies a reduction in the additional cells of the 60-cell module
by 50% can produce the same amount of energy of the 60-cell module by a 48-cell module
with an inverted U reflector. The use of the back reflectors does not only affect the
additional energy gain but structural and land costs. Row to row spacing for bifacial
systems(arrays) is reduced nearly by half as the ground height clearance is largely
minimized, thus almost 50% of height constraints for mounting bifacial modules, using
back reflectors resulting in reduced structural costs for mounting of bifacial modules
solutions has increased over the years which has led to the rapid expansion of global
markets in renewable energy sources such as solar photovoltaic (PV) technology. Newest
amongst these technologies is the Bifacial PV modules, which harvests incident radiation
from both sides of the module. The overall power generation can be significantly increased
by using these bifacial modules. The purpose of this research is to investigate and maximize
the effect of back reflectors, designed to increase the efficiency of the module by utilizing
the intercell light passing through the module to increase the incident irradiance, on the
energy output using different profiles placed at varied distances from the plane of the array
(POA). The optimum reflector profile and displacement of the reflector from the module
are determined experimentally.
Theoretically, a 60-cell bifacial module can produce 26% additional energy in
comparison to a 48-cell bifacial module due to the 12 excess cells found in the 60-cell
module. It was determined that bifacial modules have the capacity to produce additional
energy when optimized back reflectors are utilized. The inverted U reflector produced
higher energy gain when placed at farther distances from the module, indicating direct
dependent proportionality between the placement distance of the reflector from the module
and the output energy gain. It performed the best out of all current construction geometries
with reflective coatings, generating more than half of the additional energy produced by a
densely-spaced 60-cell benchmark module compared to a sparsely-spaced 48-cell reference
module.ii
A gain of 11 and 14% was recorded on cloudy and sunny days respectively for the
inverted U reflector. This implies a reduction in the additional cells of the 60-cell module
by 50% can produce the same amount of energy of the 60-cell module by a 48-cell module
with an inverted U reflector. The use of the back reflectors does not only affect the
additional energy gain but structural and land costs. Row to row spacing for bifacial
systems(arrays) is reduced nearly by half as the ground height clearance is largely
minimized, thus almost 50% of height constraints for mounting bifacial modules, using
back reflectors resulting in reduced structural costs for mounting of bifacial modules
ContributorsMARTIN, PEDRO JESSE (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Phelan, Patrick (Committee member) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2019
Description
Lithium conducting garnets in the family of Li7La3Zr2O12 (LLZO) are promising lithium conductors for solid-state batteries, due to their high ionic conductivity, thermal stability, and electrochemical stability with metallic lithium. Despite these advantages, LLZO requires a large energy input to synthesize and process. Generally, LLZO is synthesized using solid-state reaction (SSR) from oxide precursors, requiring high reaction temperatures (900-1000 °C) and producing powder with large particle sizes, necessitating high energy milling to improve sinterability. In this dissertation, two classes of advanced synthesis methods – sol-gel polymer-combustion and molten salt synthesis (MSS) – are employed to obtain LLZO submicron powders at lower temperatures. In the first case, nanopowders of LLZO are obtained in a few hours at 700 °C via a novel polymer combustion process, which can be sintered to dense electrolytes possessing ionic conductivity up to 0.67 mS cm-1 at room temperature. However, the limited throughput of this combustion process motivated the use of molten salt synthesis, wherein a salt mixture is used as a high temperature solvent, allowing faster interdiffusion of atomic species than solid-state reactions. A eutectic mixture of LiCl-KCl allows formation of submicrometer undoped, Al-doped, Ga-doped, and Ta-doped LLZO at 900 °C in 4 h, with total ionic conductivities between 0.23-0.46 mS cm-1. By using a highly basic molten salt medium, Ta-doped LLZO (LLZTO) can be obtained at temperatures as low as 550 °C, with an ionic conductivity of 0.61 mS cm-1. The formation temperature can be further reduced by using Ta-doped, La-excess pyrochlore-type lanthanum zirconate (La2Zr2O7, LZO) as a quasi-single-source precursor, which convert to LLZTO as low as 400 °C upon addition of a Li-source. Further, doped pyrochlores can be blended with a Li-source and directly sintered to a relative density up to 94.7% with high conductivity (0.53 mS cm-1). Finally, a propensity for compositional variation in LLZTO powders and sintered ceramics was observed and for the first time explored in detail. By comparing LLZTO obtained from combustion, MSS, and SSR, a correlation between increased elemental inhomogeneity and reduced ionic conductivity is observed. Implications for garnet-based solid-state batteries and strategies to mitigate elemental inhomogeneity are discussed.
ContributorsWeller, Jon Mark (Author) / Chan, Candace K (Thesis advisor) / Crozier, Peter (Committee member) / Sieradzki, Karl (Committee member) / Arizona State University (Publisher)
Created2021
Description
Ensuring reliable operation of large power systems subjected to multiple outages is a challenging task because of the combinatorial nature of the problem. Traditional methods of steady-state security assessment in power systems involve contingency analysis based on AC or DC power flows. However, power flow based contingency analysis is not fast enough to evaluate all contingencies for real-time operations. Therefore, real-time contingency analysis (RTCA) only evaluates a subset of the contingencies (called the contingency list), and hence might miss critical contingencies that lead to cascading failures.This dissertation proposes a new graph-theoretic approach, called the feasibility test (FT) algorithm, for analyzing whether a contingency will create a saturated or over-loaded cut-set in a meshed power network; a cut-set denotes a set of lines which if tripped separates the network into two disjoint islands. A novel feature of the proposed approach is that it lowers the solution time significantly making the approach viable for an exhaustive real-time evaluation of the system. Detecting saturated cut-sets in the power system is important because they represent the vulnerable bottlenecks in the network. The robustness of the FT algorithm is demonstrated on a 17,000+ bus model of the Western Interconnection (WI).
Following the detection of post-contingency cut-set saturation, a two-component methodology is proposed to enhance the reliability of large power systems during a series of outages. The first component combines the proposed FT algorithm with RTCA to create an integrated corrective action (iCA), whose goal is to secure the power system against post-contingency cut-set saturation as well as critical branch overloads. The second component only employs the results of the FT to create a relaxed corrective action (rCA) that quickly secures the system against saturated cut-sets.
The first component is more comprehensive than the second, but the latter is computationally more efficient. The effectiveness of the two components is evaluated based upon the number of cascade triggering contingencies alleviated, and the computation time. Analysis of different case-studies on the IEEE 118-bus and 2000-bus synthetic Texas systems indicate that the proposed two-component methodology enhances the scope and speed of power system security assessment during multiple outages.
ContributorsSen Biswas, Reetam (Author) / Pal, Anamitra (Thesis advisor) / Vittal, Vijay (Committee member) / Undrill, John (Committee member) / Wu, Meng (Committee member) / Zhang, Yingchen (Committee member) / Arizona State University (Publisher)
Created2021
Description
Rapid increases in the installed amounts of Distributed Energy Resources are forcing a paradigm shift to guarantee stability, security, and economics of power distribution systems. This dissertation explores these challenges and proposes solutions to enable higher penetrations of grid-edge devices. The thesis shows that integrating Graph Signal Processing with State Estimation formulation allows accurate estimation of voltage phasors for radial feeders under low-observability conditions using traditional measurements. Furthermore, the Optimal Power Flow formulation presented in this work can reduce the solution time of a bus injection-based convex relaxation formulation, as shown through numerical results. The enhanced real-time knowledge of the system state is leveraged to develop new approaches to cyber-security of a transactive energy market by introducing a blockchain-based Electron Volt Exchange framework that includes a distributed protocol for pricing and scheduling prosumers' production/consumption while keeping constraints and bids private. The distributed algorithm prevents power theft and false data injection by comparing prosumers' reported power exchanges to models of expected power exchanges using measurements from grid sensors to estimate system state. Necessary hardware security is described and integrated into underlying grid-edge devices to verify the provenance of messages to and from these devices. These preventive measures for securing energy transactions are accompanied by additional mitigation measures to maintain voltage stability in inverter-dominated networks by expressing local control actions through Lyapunov analysis to mitigate cyber-attack and generation intermittency effects. The proposed formulation is applicable as long as the Volt-Var and Volt-Watt curves of the inverters can be represented as Lipschitz constants. Simulation results demonstrate how smart inverters can mitigate voltage oscillations throughout the distribution network. Approaches are rigorously explored and validated using a combination of real distribution networks and synthetic test cases. Finally, to overcome the scarcity of real data to test distribution systems algorithms a framework is introduced to generate synthetic distribution feeders mapped to real geospatial topologies using available OpenStreetMap data. The methods illustrate how to create synthetic feeders across the entire ZIP Code, with minimal input data for any location. These stackable scientific findings conclude with a brief discussion of physical deployment opportunities to accelerate grid modernization efforts.
ContributorsSaha, Shammya Shananda (Author) / Johnson, Nathan (Thesis advisor) / Scaglione, Anna (Thesis advisor) / Arnold, Daniel (Committee member) / Boscovic, Dragan (Committee member) / Arizona State University (Publisher)
Created2021
Description
Desorption processes are an important part of all processes which involve utilization of solid adsorbents such as adsorption cooling, sorption thermal energy storage, and drying and dehumidification processes and are inherently energy-intensive. Here, how those energy requirements can be reduced through the application of ultrasound for three widely used adsorbents namely zeolite 13X, activated alumina and silica gel is investigated. To determine and justify the effectiveness of incorporating ultrasound from an energy-savings point of view, an approach of constant overall input power of 20 and 25 W was adopted. To measure the extent of the effectiveness of using ultrasound, the ultrasonic-power-to-total power ratios of 0.2, 0.25, 0.4 and 0.5 were investigated and the results compared with those of no-ultrasound (heat only) at the same total power. Duplicate experiments were performed at three nominal frequencies of 28, 40 and 80 kHz to observe the influence of frequency on regeneration dynamics. Regarding moisture removal, application of ultrasound results in higher desorption rate compared to a non-ultrasound process. A nonlinear inverse proportionality was observed between the effectiveness of ultrasound and the frequency at which it is applied. Based on the variation of desorption dynamics with ultrasonic power and frequency, three mechanisms of reduced adsorbate adsorption potential, increased adsorbate surface energy and enhanced mass diffusion are proposed. Two analytical models that describe the desorption process were developed based on the experimental data from which novel efficiency metrics were proposed, which can be employed to justify incorporating ultrasound in regeneration and drying processes.
ContributorsDaghooghi Mobarakeh, Hooman (Author) / Phelan, Patrick (Thesis advisor) / Wang, Liping (Committee member) / Wang, Robert (Committee member) / Calhoun, Ronald (Committee member) / Deng, Shuguang (Committee member) / Arizona State University (Publisher)
Created2021
Description
As India expanded its grid infrastructure, decentralized renewable energy technologies, such as off-grid solar, also emerged in parallel as an electrification solution. This dissertation critically examines the role of off-grid solar in facilitating rural electrification efforts in India. Specifically, it applies the frameworks of the multi-level perspective, capabilities approach, and energy justice to achieve three objectives: (1) trace the evolution of off-grid solar in India; (2) understand the role of solar micro-grids in improving household capabilities and well-being; (1) examine whether and how community-scale solar micro-grids can operate as just means of electrification. This research relies on qualitative case-study methods. The historical research in Paper 1 is based on published policy documents and interviews with energy experts in India. It finds that landscape-regime-niche actor relations and politics were crucial in shaping off-grid solar transition outcomes. There is also a narrative component, as the key narratives of energy security, environmental degradation, climate change and energy for development converged to create spaces for state and non-state interactions that could nurture the development of off-grid solar. The community-level research in Papers 2 and 3 analyze a local energy initiative of community operated solar micro-grid using semi-structured interviews and participant observations from three villages in Maharashtra. Solar micro-grids play an important part in expanding people’s choices and opportunities. The benefits are not uniform across all people, however. Increases in energy-related capabilities vary by economic class and gender, and to some extent this means certain biases can get reinforced. In addition, the inability of solar micro-grids to keep up with the changing electrification landscape and daily practices means that the challenges of affordability, reliability and community engagement emerged as important concerns over-time. Empirically, this dissertation finds that off-grid energy initiatives must be carefully designed to be in alignment with local values and realities. Theoretically, it adds to debates on justice in energy transitions by showcasing the regime-led innovations, and temporality elements of energy justice local energy initiatives.
ContributorsRajagopalan, Sushil (Author) / Breetz, Hanna (Thesis advisor) / Klinsky, Sonja (Thesis advisor) / Singh, Kartikeya (Committee member) / Arizona State University (Publisher)
Created2021
Description
Granular materials demonstrate complexity in many physical attributes with various shapes and sizes, varying from several centimeters down to less than a few microns. Some materials are highly cohesive, while others are free-flowing. Despite such complexity in their physical properties, they are extremely important in industries dealing with bulk materials. Through this research, the factors affecting flowability of particulate solids and their interaction with projectiles were explored. In Part I, a novel set of characterization tools to relate various granular material properties to their flow behavior in confined and unconfined environments was investigated. Through this work, a thorough characterization study to examine the effects of particle size, particle size distribution, and moisture on bulk powder flowability were proposed. Additionally, a mathematical model to predict the flow function coefficient (FFC) was developed, based on the surface mean diameter and moisture level, which can serve as a flowability descriptor.
Part II of this research focuses on the impact dynamics of low velocity projectiles on granular media. Interaction of granular media with external foreign bodies occurs in everyday events like a human footprint on the beach. Several studies involving numerical and experimental methods have focused on the study of impact dynamics in both dry and wet granular media. However, most of the studies involving impact dynamics considered spherical projectiles under different conditions, while practical models should involve more complex, realistic shapes. Different impacting geometries with conserved density, volume, and velocity on a granular bed may experience contrasting drag forces upon penetration. This is due to the difference in the surface areas coming into contact with the granular media. In this study, a set of non-spherical geometries comprising cuboids, cylinders, hexagonal prisms and triangular prisms with constant density, volume, and impact velocities, were released onto a loosely packed, non-cohesive, dry granular bed. From these experimental results, a model to determine the penetration depth of projectiles upon impact was developed and how it is influenced by the release height and surface area of the projectiles in contact with the granular media was studied.
ContributorsVajrala, Spandana (Author) / Emady, Heather N (Thesis advisor) / Marvi, Hamidreza (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2021
Description
An acute and crucial societal problem is the energy consumed in existing commercial buildings. There are 1.5 million commercial buildings in the U.S. with only about 3% being built each year. Hence, existing buildings need to be properly operated and maintained for several decades. Application of integrated centralized control systems in buildings could lead to more than 50% energy savings.
This research work demonstrates an innovative adaptive integrated lighting control approach which could achieve significant energy savings and increase indoor comfort in high performance office buildings. In the first phase of the study, a predictive algorithm was developed and validated through experiments in an actual test room. The objective was to regulate daylight on a specified work plane by controlling the blind slat angles. Furthermore, a sensor-based integrated adaptive lighting controller was designed in Simulink which included an innovative sensor optimization approach based on genetic algorithm to minimize the number of sensors and efficiently place them in the office. The controller was designed based on simple integral controllers. The objective of developed control algorithm was to improve the illuminance situation in the office through controlling the daylight and electrical lighting. To evaluate the performance of the system, the controller was applied on experimental office model in Lee et al.’s research study in 1998. The result of the developed control approach indicate a significantly improvement in lighting situation and 1-23% and 50-78% monthly electrical energy savings in the office model, compared to two static strategies when the blinds were left open and closed during the whole year respectively.
This research work demonstrates an innovative adaptive integrated lighting control approach which could achieve significant energy savings and increase indoor comfort in high performance office buildings. In the first phase of the study, a predictive algorithm was developed and validated through experiments in an actual test room. The objective was to regulate daylight on a specified work plane by controlling the blind slat angles. Furthermore, a sensor-based integrated adaptive lighting controller was designed in Simulink which included an innovative sensor optimization approach based on genetic algorithm to minimize the number of sensors and efficiently place them in the office. The controller was designed based on simple integral controllers. The objective of developed control algorithm was to improve the illuminance situation in the office through controlling the daylight and electrical lighting. To evaluate the performance of the system, the controller was applied on experimental office model in Lee et al.’s research study in 1998. The result of the developed control approach indicate a significantly improvement in lighting situation and 1-23% and 50-78% monthly electrical energy savings in the office model, compared to two static strategies when the blinds were left open and closed during the whole year respectively.
ContributorsKarizi, Nasim (Author) / Reddy, T. Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Dasgupta, Partha (Committee member) / Kroelinger, Michael D. (Committee member) / Arizona State University (Publisher)
Created2015
Description
This is a two part thesis:
Part 1 of this thesis determines the most dominant failure modes of field aged photovoltaic (PV) modules using experimental data and statistical analysis, FMECA (Failure Mode, Effect, and Criticality Analysis). The failure and degradation modes of about 5900 crystalline-Si glass/polymer modules fielded for 6 to 16 years in three different photovoltaic (PV) power plants with different mounting systems under the hot-dry desert climate of Arizona are evaluated. A statistical reliability tool, FMECA that uses Risk Priority Number (RPN) is performed for each PV power plant to determine the dominant failure modes in the modules by means of ranking and prioritizing the modes. This study on PV power plants considers all the failure and degradation modes from both safety and performance perspectives, and thus, comes to the conclusion that solder bond fatigue/failure with/without gridline/metallization contact fatigue/failure is the most dominant failure mode for these module types in the hot-dry desert climate of Arizona.
Part 2 of this thesis determines the best method to compute degradation rates of PV modules. Three different PV systems were evaluated to compute degradation rates using four methods and they are: I-V measurement, metered kWh, performance ratio (PR) and performance index (PI). I-V method, being an ideal method for degradation rate computation, were compared to the results from other three methods. The median degradation rates computed from kWh method were within ±0.15% from I-V measured degradation rates (0.9-1.37 %/year of three models). Degradation rates from the PI method were within ±0.05% from the I-V measured rates for two systems but the calculated degradation rate was remarkably different (±1%) from the I-V method for the third system. The degradation rate from the PR method was within ±0.16% from the I-V measured rate for only one system but were remarkably different (±1%) from the I-V measured rate for the other two systems. Thus, it was concluded that metered raw kWh method is the best practical method, after I-V method and PI method (if ground mounted POA insolation and other weather data are available) for degradation computation as this method was found to be fairly accurate, easy, inexpensive, fast and convenient.
Part 1 of this thesis determines the most dominant failure modes of field aged photovoltaic (PV) modules using experimental data and statistical analysis, FMECA (Failure Mode, Effect, and Criticality Analysis). The failure and degradation modes of about 5900 crystalline-Si glass/polymer modules fielded for 6 to 16 years in three different photovoltaic (PV) power plants with different mounting systems under the hot-dry desert climate of Arizona are evaluated. A statistical reliability tool, FMECA that uses Risk Priority Number (RPN) is performed for each PV power plant to determine the dominant failure modes in the modules by means of ranking and prioritizing the modes. This study on PV power plants considers all the failure and degradation modes from both safety and performance perspectives, and thus, comes to the conclusion that solder bond fatigue/failure with/without gridline/metallization contact fatigue/failure is the most dominant failure mode for these module types in the hot-dry desert climate of Arizona.
Part 2 of this thesis determines the best method to compute degradation rates of PV modules. Three different PV systems were evaluated to compute degradation rates using four methods and they are: I-V measurement, metered kWh, performance ratio (PR) and performance index (PI). I-V method, being an ideal method for degradation rate computation, were compared to the results from other three methods. The median degradation rates computed from kWh method were within ±0.15% from I-V measured degradation rates (0.9-1.37 %/year of three models). Degradation rates from the PI method were within ±0.05% from the I-V measured rates for two systems but the calculated degradation rate was remarkably different (±1%) from the I-V method for the third system. The degradation rate from the PR method was within ±0.16% from the I-V measured rate for only one system but were remarkably different (±1%) from the I-V measured rate for the other two systems. Thus, it was concluded that metered raw kWh method is the best practical method, after I-V method and PI method (if ground mounted POA insolation and other weather data are available) for degradation computation as this method was found to be fairly accurate, easy, inexpensive, fast and convenient.
ContributorsShrestha, Sanjay (Author) / Tamizhmani, Govindsamy (Thesis advisor) / Srinivasan, Devrajan (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2014