Matching Items (67)
Description
In recent years, wide bandgap (WBG) devices enable power converters with higher power density and higher efficiency. On the other hand, smart grid technologies are getting mature due to new battery technology and computer technology. In the near future, the two technologies will form the next generation of smart grid enabled by WBG devices. This dissertation deals with two applications: silicon carbide (SiC) device used for medium voltage level interface (7.2 kV to 240 V) and gallium nitride (GaN) device used for low voltage level interface (240 V/120 V). A 20 kW solid state transformer (SST) is designed with 6 kHz switching frequency SiC rectifier. Then three robust control design methods are proposed for each of its smart grid operation modes. In grid connected mode, a new LCL filter design method is proposed considering grid voltage THD, grid current THD and current regulation loop robust stability with respect to the grid impedance change. In grid islanded mode, µ synthesis method combined with variable structure control is used to design a robust controller for grid voltage regulation. For grid emergency mode, multivariable controller designed using H infinity synthesis method is proposed for accurate power sharing. Controller-hardware-in-the-loop (CHIL) testbed considering 7-SST system is setup with Real Time Digital Simulator (RTDS). The real TMS320F28335 DSP and Spartan 6 FPGA control board is used to interface a switching model SST in RTDS. And the proposed control methods are tested. For low voltage level application, a 3.3 kW smart grid hardware is built with 3 GaN inverters. The inverters are designed with the GaN device characterized using the proposed multi-function double pulse tester. The inverter is controlled by onboard TMS320F28379D dual core DSP with 200 kHz sampling frequency. Each inverter is tested to process 2.2 kW power with overall efficiency of 96.5 % at room temperature. The smart grid monitor system and fault interrupt devices (FID) based on Arduino Mega2560 are built and tested. The smart grid cooperates with GaN inverters through CAN bus communication. At last, the three GaN inverters smart grid achieved the function of grid connected to islanded mode smooth transition
ContributorsYao, Tong (Author) / Ayyanar, Raja (Thesis advisor) / Karady, George G. (Committee member) / Qin, Jiangchao (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2017
Description
The students of Arizona State University, under the mentorship of Dr George Karady, have been collaborating with Salt River Project (SRP), a major power utility in the state of Arizona, trying to study and optimize a battery-supported grid-tied rooftop Photovoltaic (PV) system, sold by a commercial vendor. SRP believes this system has the potential to satisfy the needs of its customers, who opt for utilizing solar power to partially satisfy their power needs.
An important part of this elaborate project is the development of a new load forecasting algorithm and a better control strategy for the optimized utilization of the storage system. The built-in algorithm of this commercial unit uses simple forecasting and battery control strategies. With the recent improvement in Machine Learning (ML) techniques, development of a more sophisticated model of the problem in hand was possible. This research is aimed at achieving the goal by utilizing the appropriate ML techniques to better model the problem, which will essentially result in a better solution. In this research, a set of six unique features are used to model the load forecasting problem and different ML algorithms are simulated on the developed model. A similar approach is taken to solve the PV prediction problem. Finally, a very effective battery control strategy is built (utilizing the results of the load and PV forecasting), with the aim of ensuring a reduction in the amount of energy consumed from the grid during the “on-peak” hours. Apart from the reduction in the energy consumption, this battery control algorithm decelerates the “cycling aging” or the aging of the battery owing to the charge/dis-charges cycles endured by selectively charging/dis-charging the battery based on need.
ii
The results of this proposed strategy are verified using a hardware implementation (the PV system was coupled with a custom-built load bank and this setup was used to simulate a house). The results pertaining to the performances of the built-in algorithm and the ML algorithm are compared and the economic analysis is performed. The findings of this research have in the process of being published in a reputed journal.
An important part of this elaborate project is the development of a new load forecasting algorithm and a better control strategy for the optimized utilization of the storage system. The built-in algorithm of this commercial unit uses simple forecasting and battery control strategies. With the recent improvement in Machine Learning (ML) techniques, development of a more sophisticated model of the problem in hand was possible. This research is aimed at achieving the goal by utilizing the appropriate ML techniques to better model the problem, which will essentially result in a better solution. In this research, a set of six unique features are used to model the load forecasting problem and different ML algorithms are simulated on the developed model. A similar approach is taken to solve the PV prediction problem. Finally, a very effective battery control strategy is built (utilizing the results of the load and PV forecasting), with the aim of ensuring a reduction in the amount of energy consumed from the grid during the “on-peak” hours. Apart from the reduction in the energy consumption, this battery control algorithm decelerates the “cycling aging” or the aging of the battery owing to the charge/dis-charges cycles endured by selectively charging/dis-charging the battery based on need.
ii
The results of this proposed strategy are verified using a hardware implementation (the PV system was coupled with a custom-built load bank and this setup was used to simulate a house). The results pertaining to the performances of the built-in algorithm and the ML algorithm are compared and the economic analysis is performed. The findings of this research have in the process of being published in a reputed journal.
ContributorsHariharan, Aashiek (Author) / Karady, George G. (Thesis advisor) / Heydt, Gerald Thomas (Committee member) / Qin, Jiangchao (Committee member) / Allee, David R. (Committee member) / Arizona State University (Publisher)
Created2018
Description
The utilization of power cables is increasing with the development of renewable energy and the maintenance replacement of old overhead power lines. Therefore, effective monitoring and accurate fault location for power cables are very important for the sake of a stable power supply.
The recent technologies for power cable diagnosis and temperature monitoring system are described including their intrinsic limitations for cable health assessment. Power cable fault location methods are reviewed with two main categories: off-line and on-line data based methods.
As a diagnostic and fault location approach, a new passive methodology is introduced. This methodology is based on analyzing the resonant frequencies of the transfer function between the input and output of the power cable system. The equivalent pi model is applied to the resonant frequency calculation for the selected underground power cable transmission system.
The characteristics of the resonant frequencies are studied by analytical derivations and PSCAD simulations. It is found that the variation of load magnitudes and change of positive power factors (i.e., inductive loads) do not affect resonant frequencies significantly, but there is considerable movement of resonant frequencies under change of negative power factors (i.e., capacitive loads).
Power cable fault conditions introduce new resonant frequencies in accordance with fault positions. Similar behaviors of the resonant frequencies are shown in a transformer (TR) connected power cable system with frequency shifts caused by the TR impedance.
The resonant frequencies can be extracted by frequency analysis of power signals and the inherent noise in these signals plays a key role to measure the resonant frequencies. Window functions provide an effective tool for improving resonant frequency discernment. The frequency analysis is implemented on noise laden PSCAD simulation signals and it reveals identical resonant frequency characteristics with theoretical studies.
Finally, the noise levels of real voltage and current signals, which are acquired from an operating power plant, are estimated and the resonant frequencies are extracted by applying window functions, and these results prove that the resonant frequency can be used as an assessment for the internal changes in power cable parameters such as defects and faults.
The recent technologies for power cable diagnosis and temperature monitoring system are described including their intrinsic limitations for cable health assessment. Power cable fault location methods are reviewed with two main categories: off-line and on-line data based methods.
As a diagnostic and fault location approach, a new passive methodology is introduced. This methodology is based on analyzing the resonant frequencies of the transfer function between the input and output of the power cable system. The equivalent pi model is applied to the resonant frequency calculation for the selected underground power cable transmission system.
The characteristics of the resonant frequencies are studied by analytical derivations and PSCAD simulations. It is found that the variation of load magnitudes and change of positive power factors (i.e., inductive loads) do not affect resonant frequencies significantly, but there is considerable movement of resonant frequencies under change of negative power factors (i.e., capacitive loads).
Power cable fault conditions introduce new resonant frequencies in accordance with fault positions. Similar behaviors of the resonant frequencies are shown in a transformer (TR) connected power cable system with frequency shifts caused by the TR impedance.
The resonant frequencies can be extracted by frequency analysis of power signals and the inherent noise in these signals plays a key role to measure the resonant frequencies. Window functions provide an effective tool for improving resonant frequency discernment. The frequency analysis is implemented on noise laden PSCAD simulation signals and it reveals identical resonant frequency characteristics with theoretical studies.
Finally, the noise levels of real voltage and current signals, which are acquired from an operating power plant, are estimated and the resonant frequencies are extracted by applying window functions, and these results prove that the resonant frequency can be used as an assessment for the internal changes in power cable parameters such as defects and faults.
ContributorsKim, Youngdeug (Author) / Holbert, Keith Edwin (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Heydt, Gerald (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2015
Description
Present distribution infrastructure is designed mainly for uni-directional power flow with well-controlled generation. An increase in the inverter-interfaced photovoltaic (PV) systems requires a thorough re-examination of the design, operation, protection and control of distribution systems. In order to understand the impact of high penetration of PV generation, this work conducts an automated and detailed modeling of a power distribution system. The simulation results of the modeled distribution feeder have been verified with the field measurements.
Based on the feeder model, this work studies the impact of the PV systems on voltage profiles under various scenarios, including reallocation of the PV systems, reactive power support from the PV inverters, and settings of the load-tap changing transformers in coordination with the PV penetration. Design recommendations have been made based on the simulation results to improve the voltage profiles in the feeder studied.
To carry out dynamic studies related to high penetration of PV systems, this work proposes a differential algebraic equation (DAE) based dynamic modeling and analysis method. Different controllers including inverter current controllers, anti-islanding controllers and droop controllers, are designed and tested in large systems. The method extends the capability of the distribution system analysis tools, to help conduct dynamic analyses in large unbalanced distribution systems.
Another main contribution of this work is related to the investigation of the PV impacts on the feeder protection coordination. Various protection coordination types, including fuse-fuse, recloser-fuse, relay-fuse and relay-recloser have been studied. The analyses provide a better understanding of the relay and recloser settings under different configurations of the PV interconnection transformers, PV penetration levels, and fault types.
A decision tree and fuzzy logic based fault location identification process has also been proposed in this work. The process is composed of the off-line training of the decision tree, and the on-line analysis of the fault events. Fault current contribution from the PV systems, as well as the variation of the fault resistance have been taken into consideration. Two actual fault cases with the event data recorded were used to examine the effectiveness of the fault identification process.
Based on the feeder model, this work studies the impact of the PV systems on voltage profiles under various scenarios, including reallocation of the PV systems, reactive power support from the PV inverters, and settings of the load-tap changing transformers in coordination with the PV penetration. Design recommendations have been made based on the simulation results to improve the voltage profiles in the feeder studied.
To carry out dynamic studies related to high penetration of PV systems, this work proposes a differential algebraic equation (DAE) based dynamic modeling and analysis method. Different controllers including inverter current controllers, anti-islanding controllers and droop controllers, are designed and tested in large systems. The method extends the capability of the distribution system analysis tools, to help conduct dynamic analyses in large unbalanced distribution systems.
Another main contribution of this work is related to the investigation of the PV impacts on the feeder protection coordination. Various protection coordination types, including fuse-fuse, recloser-fuse, relay-fuse and relay-recloser have been studied. The analyses provide a better understanding of the relay and recloser settings under different configurations of the PV interconnection transformers, PV penetration levels, and fault types.
A decision tree and fuzzy logic based fault location identification process has also been proposed in this work. The process is composed of the off-line training of the decision tree, and the on-line analysis of the fault events. Fault current contribution from the PV systems, as well as the variation of the fault resistance have been taken into consideration. Two actual fault cases with the event data recorded were used to examine the effectiveness of the fault identification process.
ContributorsTang, Yingying (Author) / Ayyanar, Raja (Thesis advisor) / Karady, George G. (Committee member) / Heydt, Gerald (Committee member) / Vittal, Vijay (Committee member) / Arizona State University (Publisher)
Created2016
Description
With the growing importance of underground power systems and the need for greater reliability of the power supply, cable monitoring and accurate fault location detection has become an increasingly important issue. The presence of inherent random fluctuations in power system signals can be used to extract valuable information about the condition of system equipment. One such component is the power cable, which is the primary focus of this research.
This thesis investigates a unique methodology that allows online monitoring of an underground power cable. The methodology analyzes conventional power signals in the frequency domain to monitor the condition of a power cable.
First, the proposed approach is analyzed theoretically with the help of mathematical computations. Frequency domain analysis techniques are then used to compute the power spectral density (PSD) of the system signals. The importance of inherent noise in the system, a key requirement of this methodology, is also explained. The behavior of resonant frequencies, which are unique to every system, are then analyzed under different system conditions with the help of mathematical expressions.
Another important aspect of this methodology is its ability to accurately estimate cable fault location. The process is online and hence does not require the system to be disconnected from the grid. A single line to ground fault case is considered and the trend followed by the resonant frequencies for different fault positions is observed.
The approach is initially explained using theoretical calculations followed by simulations in MATLAB/Simulink. The validity of this technique is proved by comparing the results obtained from theory and simulation to actual measurement data.
This thesis investigates a unique methodology that allows online monitoring of an underground power cable. The methodology analyzes conventional power signals in the frequency domain to monitor the condition of a power cable.
First, the proposed approach is analyzed theoretically with the help of mathematical computations. Frequency domain analysis techniques are then used to compute the power spectral density (PSD) of the system signals. The importance of inherent noise in the system, a key requirement of this methodology, is also explained. The behavior of resonant frequencies, which are unique to every system, are then analyzed under different system conditions with the help of mathematical expressions.
Another important aspect of this methodology is its ability to accurately estimate cable fault location. The process is online and hence does not require the system to be disconnected from the grid. A single line to ground fault case is considered and the trend followed by the resonant frequencies for different fault positions is observed.
The approach is initially explained using theoretical calculations followed by simulations in MATLAB/Simulink. The validity of this technique is proved by comparing the results obtained from theory and simulation to actual measurement data.
ContributorsGovindarajan, Sudarshan (Author) / Holbert, Keith E. (Thesis advisor) / Heydt, Gerald (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2016
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 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.
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
Description
The electromagnetic fields near power lines that may produce adverse effects on humans are of increasing interest in a variety of situations, thus making it worthwhile to develop general-purpose software that estimates both the electric and magnetic fields accurately. This study deals with the simulations of the electric and magnetic fields near high-voltage power lines for the triangular, horizontal and vertical conductor arrangements under both balanced and unbalanced conditions.
For all three conductor arrangements, the shapes of the electric field distribution curves are different with the vertical arrangement best for minimizing right of way consideration, while the shapes of the magnetic field distributions curves are similar. Except for the horizontal arrangement, the maximum electric field magnitudes with shield conductors are larger than those without shield conductors. Among the three different arrangements, the maximum field value of the vertical arrangement is most vulnerable to the unbalanced conditions.
For both the electric and magnetic fields, increasing the heights of phase conductors gradually results in diminishing return in terms of the field reduction. In this work, both the maximum electric field magnitudes and the maximum magnetic field magnitudes produced by 500 kV power lines at 1 m height from the ground are all within the permissible exposure levels for the general public. At last, the dynamic trajectories of both fields with time are simulated and interpreted, with each field represented by a vector rotating in a plane describing an ellipse, where the vector values can be compared to high-speed vector measurements.
For all three conductor arrangements, the shapes of the electric field distribution curves are different with the vertical arrangement best for minimizing right of way consideration, while the shapes of the magnetic field distributions curves are similar. Except for the horizontal arrangement, the maximum electric field magnitudes with shield conductors are larger than those without shield conductors. Among the three different arrangements, the maximum field value of the vertical arrangement is most vulnerable to the unbalanced conditions.
For both the electric and magnetic fields, increasing the heights of phase conductors gradually results in diminishing return in terms of the field reduction. In this work, both the maximum electric field magnitudes and the maximum magnetic field magnitudes produced by 500 kV power lines at 1 m height from the ground are all within the permissible exposure levels for the general public. At last, the dynamic trajectories of both fields with time are simulated and interpreted, with each field represented by a vector rotating in a plane describing an ellipse, where the vector values can be compared to high-speed vector measurements.
ContributorsXiao, Lei (Author) / Holbert, Keith E. (Thesis advisor) / Karady, George G. (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2015
Description
The inherent intermittency in solar energy resources poses challenges to scheduling generation, transmission, and distribution systems. Energy storage devices are often used to mitigate variability in renewable asset generation and provide a mechanism to shift renewable power between periods of the day. In the absence of storage, however, time series forecasting techniques can be used to estimate future solar resource availability to improve the accuracy of solar generator scheduling. The knowledge of future solar availability helps scheduling solar generation at high-penetration levels, and assists with the selection and scheduling of spinning reserves. This study employs statistical techniques to improve the accuracy of solar resource forecasts that are in turn used to estimate solar photovoltaic (PV) power generation. The first part of the study involves time series forecasting of the global horizontal irradiation (GHI) in Phoenix, Arizona using Seasonal Autoregressive Integrated Moving Average (SARIMA) models. A comparative study is completed for time series forecasting models developed with different time step resolutions, forecasting start time, forecasting time horizons, training data, and transformations for data measured at Phoenix, Arizona. Approximately 3,000 models were generated and evaluated across the entire study. One major finding is that forecasted values one day ahead are near repeats of the preceding day—due to the 24-hour seasonal differencing—indicating that use of statistical forecasting over multiple days creates a repeating pattern. Logarithmic transform data were found to perform poorly in nearly all cases relative to untransformed or square-root transform data when forecasting out to four days. Forecasts using a logarithmic transform followed a similar profile as the immediate day prior whereas forecasts using untransformed and square-root transform data had smoother daily solar profiles that better represented the average intraday profile. Error values were generally lower during mornings and evenings and higher during midday. Regarding one-day forecasting and shorter forecasting horizons, the logarithmic transformation performed better than untransformed data and square-root transformed data irrespective of forecast horizon for data resolutions of 1-hour, 30-minutes, and 15-minutes.
ContributorsSoundiah Regunathan Rajasekaran, Dhiwaakar Purusothaman (Author) / Johnson, Nathan G (Thesis advisor) / Karady, George G. (Thesis advisor) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2016
Description
Overhead high voltage transmission lines are widely used around the world to deliver power to customers because of their low losses and high transmission capability. Well-coordinated insulation systems are capable of withstanding lightning and switching surge voltages. However, flashover is a serious issue to insulation systems, especially if the insulator is covered by a pollution layer. Many experiments in the laboratory have been conducted to investigate this issue. Since most experiments are time-consuming and costly, good mathematical models could contribute to predicting the insulator flashover performance as well as guide the experiments. This dissertation proposes a new statistical model to calculate the flashover probability of insulators under different supply voltages and contamination levels. An insulator model with water particles in the air is simulated to analyze the effects of rain and mist on flashover performance in reality. Additionally, insulator radius and number of sheds affect insulator surface resistivity and leakage distance. These two factors are studied to improve the efficiency of insulator design. This dissertation also discusses the impact of insulator surface hydrophobicity on flashover voltage.
Because arc propagation is a stochastic process, an arc could travel on different paths based on the electric field distribution. Some arc paths jump between insulator sheds instead of travelling along the insulator surfaces. The arc jumping could shorten the leakage distance and intensify the electric field. Therefore, the probabilities of arc jumping at different locations of sheds are also calculated in this dissertation.
The new simulation model is based on numerical electric field calculation and random walk theory. The electric field is calculated by the variable-grid finite difference method. The random walk theory from the Monte Carlo Method is utilized to describe the random propagation process of arc growth. This model will permit insulator engineers to design the reasonable geometry of insulators, to reduce the flashover phenomena under a wide range of operating conditions.
Because arc propagation is a stochastic process, an arc could travel on different paths based on the electric field distribution. Some arc paths jump between insulator sheds instead of travelling along the insulator surfaces. The arc jumping could shorten the leakage distance and intensify the electric field. Therefore, the probabilities of arc jumping at different locations of sheds are also calculated in this dissertation.
The new simulation model is based on numerical electric field calculation and random walk theory. The electric field is calculated by the variable-grid finite difference method. The random walk theory from the Monte Carlo Method is utilized to describe the random propagation process of arc growth. This model will permit insulator engineers to design the reasonable geometry of insulators, to reduce the flashover phenomena under a wide range of operating conditions.
ContributorsHe, Jiahong (Author) / Gorur, Ravi (Thesis advisor) / Ayyanar, Raja (Committee member) / Holbert, Keith E. (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2016
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 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.
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