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Description
Li-ion batteries are being used on a large scale varying from consumer electronics to electric vehicles. The key to efficient use of batteries is implementing a well-developed battery management system. Also, there is an opportunity for research for improving the battery performance in terms of size and capacity. For all

Li-ion batteries are being used on a large scale varying from consumer electronics to electric vehicles. The key to efficient use of batteries is implementing a well-developed battery management system. Also, there is an opportunity for research for improving the battery performance in terms of size and capacity. For all this it is imperative to develop Li-ion cell model that replicate the performance of a physical cell unit. This report discusses a dual polarization cell model and a battery management system implemented to control the operation of the battery. The Li-ion cell is modelled, and the performance is observed in PLECS environment.

The main aspect of this report studies the viability of Li-ion battery application in Battery Energy Storage System (BESS) in Modular multilevel converter (MMC). MMC-based BESS is a promising solution for grid-level battery energy storage to accelerate utilization and integration of intermittent renewable energy resources, i.e., solar and wind energy. When the battery units are directly integrated in submodules (SMs) without dc-dc interfaced converters, this configuration provides highest system efficiency and lowest cost. However, the lifetime of battery will be affected by the low-frequency components contained in arm currents, which has not been thoroughly investigated. This paper investigates impact of various low-frequency arm-current ripples on lifetime of Li-ion battery cells and evaluate performance of battery charging and discharging in an MMC-BESS without dc-dc interfaced converters.
ContributorsPuranik, Ishaan (Author) / Qin, Jiangchao (Thesis advisor) / Karady, George G. (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2018
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Description
The most important metrics considered for electric vehicles are power density, efficiency, and reliability of the powertrain modules. The powertrain comprises of an Electric Machine (EM), power electronic converters, an Energy Management System (EMS), and an Energy Storage System (ESS). The power electronic converters are used to couple the motor

The most important metrics considered for electric vehicles are power density, efficiency, and reliability of the powertrain modules. The powertrain comprises of an Electric Machine (EM), power electronic converters, an Energy Management System (EMS), and an Energy Storage System (ESS). The power electronic converters are used to couple the motor with the battery stack. Including a DC/DC converter in the powertrain module is favored as it adds an additional degree of freedom to achieve flexibility in optimizing the battery module and inverter independently. However, it is essential that the converter is rated for high peak power and can maintain high efficiency while operating over a wide range of load conditions to not compromise on system efficiency. Additionally, the converter must strictly adhere to all automotive standards.

Currently, several hard-switching topologies have been employed such as conventional boost DC/DC, interleaved step-up DC/DC, and full-bridge DC/DC converter. These converters face respective limitations in achieving high step-up conversion ratio, size and weight issues, or high component count. In this work, a bi-directional synchronous boost DC/DC converter with easy interleaving capability is proposed with a novel ZVT mechanism. This converter steps up the EV battery voltage of 200V-300V to a wide range of variable output voltages ranging from 310V-800V. High power density and efficiency are achieved through high switching frequency of 250kHz for each phase with effective frequency doubling through interleaving. Also, use of wide bandgap high voltage SiC switches allows high efficiency operation even at high temperatures.

Comprehensive analysis, design details and extensive simulation results are presented. Incorporating ZVT branch with adaptive time delay results in converter efficiency close to 98%. Experimental results from a 2.5kW hardware prototype validate the performance of the proposed approach. A peak efficiency of 98.17% has been observed in hardware in the boost or motoring mode.
ContributorsMullangi Chenchu, Hemanth (Author) / Ayyanar, Raja (Thesis advisor) / Qin, Jiangchao (Committee member) / Lei, Qin (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Over the years, the growing penetration of renewable energy into the electricity market has resulted in a significant change in the electricity market price. This change makes the existing forecasting method prone to error, decreasing the economic benefits. Hence, more precise forecasting methods need to be developed. This paper starts

Over the years, the growing penetration of renewable energy into the electricity market has resulted in a significant change in the electricity market price. This change makes the existing forecasting method prone to error, decreasing the economic benefits. Hence, more precise forecasting methods need to be developed. This paper starts with a survey and benchmark of existing machine learning approaches for forecasting the real-time market (RTM) price. While these methods provide sufficient modeling capability via supervised learning, their accuracy is still limited due to the single data source, e.g., historical price information only. In this paper, a novel two-stage supervised learning approach is proposed by diversifying the data sources such as highly correlated power data. This idea is inspired by the recent load forecasting methods that have shown extremely well performances. Specifically, the proposed two-stage method, namely the rerouted method, learns two types of mapping rules. The first one is the mapping between the historical wind power and the historical price. The second is the forecasting rule for wind generation. Based on the two rules, we forecast the price via the forecasted generation and the first learned mapping between power and price. Additionally, we observed that it is not the more training data the better, leading to our validation steps to quantify the best training intervals for different datasets. We conduct comparisons of numerical results between existing methods and the proposed methods based on datasets from the Electric Reliability Council of Texas (ERCOT). For each machine learning step, we examine different learning methods, such as polynomial regression, support vector regression, neural network, and deep neural network. The results show that the proposed method is significantly better than existing approaches when renewables are involved.
ContributorsLuo, Shuman (Author) / Weng, Yang (Thesis advisor) / Lei, Qin (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Switching surges are a common type of phenomenon that occur on any sort of power system network. These are more pronounced on long transmission lines and in high voltage substations. The problem with switching surges is encountered when a lot of power is transmitted across a transmission line
etwork, typically from

Switching surges are a common type of phenomenon that occur on any sort of power system network. These are more pronounced on long transmission lines and in high voltage substations. The problem with switching surges is encountered when a lot of power is transmitted across a transmission line
etwork, typically from a concentrated generation node to a concentrated load. The problem becomes significantly worse when the transmission line is long and when the voltage levels are high, typically above 400 kV. These overvoltage transients occur following any type of switching action such as breaker operation, fault occurrence/clearance and energization, and they pose a very real danger to weakly interconnected systems. At EHV levels, the insulation coordination of such lines is mainly dictated by the peak level of switching surges, the most dangerous of which include three phase line energization and single-phase reclosing. Switching surges can depend on a number of independent and inter-dependent factors like voltage level, line length, tower construction, location along the line, and presence of other equipment like shunt/series reactors and capacitors.

This project discusses the approaches taken and methods applied to observe and tackle the problems associated with switching surges on a long transmission line. A detailed discussion pertaining to different aspects of switching surges and their effects is presented with results from various studies published in IEEE journals and conference papers. Then a series of simulations are presented to determine an arrangement of substation equipment with respect to incoming transmission lines; that correspond to the lowest surge levels at that substation.
ContributorsShaikh, Mohammed Mubashir (Author) / Qin, Jiangchao (Thesis advisor) / Heydt, Gerald T (Committee member) / Lei, Qin (Committee member) / Arizona State University (Publisher)
Created2018
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Description
The demand for cleaner energy technology is increasing very rapidly. Hence it is

important to increase the eciency and reliability of this emerging clean energy technologies.

This thesis focuses on modeling and reliability of solar micro inverters. In

order to make photovoltaics (PV) cost competitive with traditional energy sources,

the economies of scale have

The demand for cleaner energy technology is increasing very rapidly. Hence it is

important to increase the eciency and reliability of this emerging clean energy technologies.

This thesis focuses on modeling and reliability of solar micro inverters. In

order to make photovoltaics (PV) cost competitive with traditional energy sources,

the economies of scale have been guiding inverter design in two directions: large,

centralized, utility-scale (500 kW) inverters vs. small, modular, module level (300

W) power electronics (MLPE). MLPE, such as microinverters and DC power optimizers,

oer advantages in safety, system operations and maintenance, energy yield,

and component lifetime due to their smaller size, lower power handling requirements,

and module-level power point tracking and monitoring capability [1]. However, they

suer from two main disadvantages: rst, depending on array topology (especially

the proximity to the PV module), they can be subjected to more extreme environments

(i.e. temperature cycling) during the day, resulting in a negative impact to

reliability; second, since solar installations can have tens of thousands to millions of

modules (and as many MLPE units), it may be dicult or impossible to track and

repair units as they go out of service. Therefore identifying the weak links in this

system is of critical importance to develop more reliable micro inverters.

While an overwhelming majority of time and research has focused on PV module

eciency and reliability, these issues have been largely ignored for the balance

of system components. As a relatively nascent industry, the PV power electronics

industry does not have the extensive, standardized reliability design and testing procedures

that exist in the module industry or other more mature power electronics

industries (e.g. automotive). To do so, the critical components which are at risk and

their impact on the system performance has to be studied. This thesis identies and

addresses some of the issues related to reliability of solar micro inverters.

This thesis presents detailed discussions on various components of solar micro inverter

and their design. A micro inverter with very similar electrical specications in

comparison with commercial micro inverter is modeled in detail and veried. Components

in various stages of micro inverter are listed and their typical failure mechanisms

are reviewed. A detailed FMEA is conducted for a typical micro inverter to identify

the weak links of the system. Based on the S, O and D metrics, risk priority number

(RPN) is calculated to list the critical at-risk components. Degradation of DC bus

capacitor is identied as one the failure mechanism and the degradation model is built

to study its eect on the system performance. The system is tested for surge immunity

using standard ring and combinational surge waveforms as per IEEE 62.41 and

IEC 61000-4-5 standards. All the simulation presented in this thesis is performed

using PLECS simulation software.
ContributorsManchanahalli Ranganatha, Arkanatha Sastry (Author) / Ayyanar, Raja (Thesis advisor) / Karady, George G. (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Due to the increasing trend of electricity price for the future and the price reduction of solar electronics price led by the policy stimulus and the technological improvement, the residential distribution solar photovoltaic (PV) system’s market is prosperous. Excess energy can be sold back to the grid, however peak demand

Due to the increasing trend of electricity price for the future and the price reduction of solar electronics price led by the policy stimulus and the technological improvement, the residential distribution solar photovoltaic (PV) system’s market is prosperous. Excess energy can be sold back to the grid, however peak demand of a residential customer typically occurs in late afternoon/early evening when PV systems are not a productive. The solar PV system can provide residential customers sufficient energy during the daytime, even the exceeding energy can be sold back to the grid especially during the day with good sunlight, however, the peak demand of a regular family always appears during late afternoon and early evening which are not productive time for PV system. In this case, the PV customers only need the grid energy when other customers also need it the most. Because of the lower contribution of PV systems during times of peak demand, utilities are beginning to adjust rate structures to better align the bills paid by PV customers with the cost to the utility to serve those customers. Different rate structures include higher fixed charges, higher on-peak electricity prices, on-peak demand charges, or prices based on avoided costs. The demand charge and the on-peak energy charge significantly reduced the savings brought by the PV system. This will result in a longer the customer’s payback period. Eventually PV customers are not saving a lot in their electricity bill compare to those customers who do not own a PV system.



A battery system is a promising technology that can improve monthly bill savings since a battery can store the solar energy and the off-peak grid energy and release it later during the on-peak hours. Sponsored by Salt River Project (SRP), a smart home model consists 1.35 kW PV panels, a 7.76 kWh lithium-ion battery and an adjustable resistive load bank was built on the roof of Engineering Research Center (ERC) building. For analysis, data was scaled up by 6/1.35 times to simulate a real residential PV setup. The testing data had been continuously recorded for more than one year (Aug.2014 - Oct.2015) and a battery charging strategy was developed based on those data. The work of this thesis deals with the idea of this charging strategy and the economic benefits this charging strategy can bring to the PV customers. Part of this research work has been wrote into a conference paper which is accepted by IEEE PES General Meeting 2016. A new and larger system has been installed on the roof with 6 kW PV modules and 6 kW output integrated electronics. This project will go on and the method come up by this thesis will be tested.
ContributorsWang, Xin'an (Author) / Karady, George G. (Thesis advisor) / Smedley, Grant (Committee member) / Qin, Jiangchao (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2016
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Description
After a major disturbance, the power system response is highly dependent on protection schemes and system dynamics. Improving power systems situational awareness requires proper and simultaneous modeling of both protection schemes and dynamic characteristics in power systems analysis tools. Historical information and ex-post analysis of blackouts reaffirm the critical role

After a major disturbance, the power system response is highly dependent on protection schemes and system dynamics. Improving power systems situational awareness requires proper and simultaneous modeling of both protection schemes and dynamic characteristics in power systems analysis tools. Historical information and ex-post analysis of blackouts reaffirm the critical role of protective devices in cascading events, thereby confirming the necessity to represent protective functions in transient stability studies. This dissertation is aimed at studying the importance of representing protective relays in power system dynamic studies. Although modeling all of the protective relays within transient stability studies may result in a better estimation of system behavior, representing, updating, and maintaining the protection system data becomes an insurmountable task. Inappropriate or outdated representation of the relays may result in incorrect assessment of the system behavior. This dissertation presents a systematic method to determine essential relays to be modeled in transient stability studies. The desired approach should identify protective relays that are critical for various operating conditions and contingencies. The results of the transient stability studies confirm that modeling only the identified critical protective relays is sufficient to capture system behavior for various operating conditions and precludes the need to model all of the protective relays. Moreover, this dissertation proposes a method that can be implemented to determine the appropriate location of out-of-step blocking relays. During unstable power swings, a generator or group of generators may accelerate or decelerate leading to voltage depression at the electrical center along with generator tripping. This voltage depression may cause protective relay mis-operation and unintentional separation of the system. In order to avoid unintentional islanding, the potentially mis-operating relays should be blocked from tripping with the use of out-of-step blocking schemes. Blocking these mis-operating relays, combined with an appropriate islanding scheme, help avoid a system wide collapse. The proposed method is tested on data from the Western Electricity Coordinating Council. A triple line outage of the California-Oregon Intertie is studied. The results show that the proposed method is able to successfully identify proper locations of out-of-step blocking scheme.
ContributorsHedman, Mojdeh Khorsand (Author) / Vittal, Vijay (Thesis advisor) / Ayyanar, Raja (Committee member) / Pal, Anamitra (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2017
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Description

Lithium ion batteries are quintessential components of modern life. They are used to power smart devices — phones, tablets, laptops, and are rapidly becoming major elements in the automotive industry. Demand projections for lithium are skyrocketing with production struggling to keep up pace. This drive is due mostly to the

Lithium ion batteries are quintessential components of modern life. They are used to power smart devices — phones, tablets, laptops, and are rapidly becoming major elements in the automotive industry. Demand projections for lithium are skyrocketing with production struggling to keep up pace. This drive is due mostly to the rapid adoption of electric vehicles; sales of electric vehicles in 2020 are more than double what they were only a year prior. With such staggering growth it is important to understand how lithium is sourced and what that means for the environment. Will production even be capable of meeting the demand as more industries make use of this valuable element? How will the environmental impact of lithium affect growth? This thesis attempts to answer these questions as the world looks to a decade of rapid growth for lithium ion batteries.

ContributorsMelton, John (Author) / Brian, Jennifer (Thesis director) / Karwat, Darshawn (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05