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- Genre: Doctoral Dissertation
Description
An increase in the number of inverter-interfaced photovoltaic (PV) generators on existing distribution feeders affects the design, operation, and control of the distri- bution systems. Existing distribution system analysis tools are capable of supporting only snapshot and quasi-static analyses. Capturing the dynamic effects of the PV generators during the variation in the distribution system states is necessary when studying the effects of controller bandwidths, multiple voltage correction devices, and anti-islanding. This work explores the use of dynamic phasors and differential algebraic equations (DAE) for impact analysis of the PV generators on the existing distribution feeders.
The voltage unbalance induced by PV generators can aggravate the existing unbalance due to load mismatch. An increased phase unbalance significantly adds to the neutral currents, excessive neutral to ground voltages and violate the standards for unbalance factor. The objective of this study is to analyze and quantify the impacts of unbalanced PV installations on a distribution feeder. Additionally, a power electronic converter solution is proposed to mitigate the identified impacts and validate the solution's effectiveness through detailed simulations in OpenDSS.
The benefits associated with the use of energy storage systems for electric- utility-related applications are also studied. This research provides a generalized framework for strategic deployment of a lithium-ion based energy storage system to increase their benefits in a distribution feeder. A significant amount of work has been performed for a detailed characterization of the life cycle costs of an energy storage system. The objectives include - reduction of the substation transformer losses, reduction of the life cycle cost for an energy storage system, and accommodate the PV variability.
The distribution feeder laterals in the distribution feeder with relatively high PV generation as compared to the load can be operated as microgrids to achieve reliability, power quality and economic benefits. However, the renewable resources are intermittent and stochastic in nature. A novel approach for sizing and scheduling the energy storage system and microtrubine is proposed for reliable operation of microgrids. The size and schedule of the energy storage system and microturbine are determined using Benders' decomposition, considering the PV generation as a stochastic resource.
The voltage unbalance induced by PV generators can aggravate the existing unbalance due to load mismatch. An increased phase unbalance significantly adds to the neutral currents, excessive neutral to ground voltages and violate the standards for unbalance factor. The objective of this study is to analyze and quantify the impacts of unbalanced PV installations on a distribution feeder. Additionally, a power electronic converter solution is proposed to mitigate the identified impacts and validate the solution's effectiveness through detailed simulations in OpenDSS.
The benefits associated with the use of energy storage systems for electric- utility-related applications are also studied. This research provides a generalized framework for strategic deployment of a lithium-ion based energy storage system to increase their benefits in a distribution feeder. A significant amount of work has been performed for a detailed characterization of the life cycle costs of an energy storage system. The objectives include - reduction of the substation transformer losses, reduction of the life cycle cost for an energy storage system, and accommodate the PV variability.
The distribution feeder laterals in the distribution feeder with relatively high PV generation as compared to the load can be operated as microgrids to achieve reliability, power quality and economic benefits. However, the renewable resources are intermittent and stochastic in nature. A novel approach for sizing and scheduling the energy storage system and microtrubine is proposed for reliable operation of microgrids. The size and schedule of the energy storage system and microturbine are determined using Benders' decomposition, considering the PV generation as a stochastic resource.
ContributorsNagarajan, Adarsh (Author) / Ayyanar, Raja (Thesis advisor) / Vittal, Vijay (Committee member) / Heydt, Gerald (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2015
Description
Carbon nanomaterials have caught tremendous attention in the last few decades due to their unique physical and chemical properties. Tremendous effort has been made to develop new synthesis techniques for carbon nanomaterials and investigate their properties for different applications. In this work, carbon nanospheres (CNSs), carbon foams (CF), and single-walled carbon nanotubes (SWNTs) were studied for various applications, including water treatment, energy storage, actuators, and sensors.
A facile spray pyrolysis synthesis technique was developed to synthesize individual CNSs with specific surface area (SSA) up to 1106 m2/g. The hollow CNSs showed adsorption of up to 300 mg rhodamine B dye per gram carbon, which is more than 15 times higher than that observed for conventional carbon black. They were also evaluated as adsorbents for removal of arsenate and selenate from water and displayed good binding to both species, outperforming commercial activated carbons for arsenate removal in pH > 8. When evaluated as supercapacitor electrode materials, specific capacitances of up to 112 F/g at a current density of 0.1 A/g were observed. When used as Li-ion battery anode materials, the CNSs achieved a discharge capacity of 270 mAh/g at a current density of 372 mA/g (1C), which is 4-fold higher than that of commercial graphite anode.
Carbon foams were synthesized using direct pyrolysis and had SSA up to 2340 m2/g. When used as supercapacitor electrode materials, a specific capacitance up to 280 F/g was achieved at current density of 0.1 A/g and remained as high as 207 F/g, even at a high current density of 10 A/g.
A printed walking robot was made from common plastic films and coatings of SWNTs. The solid-state thermal bimorph actuators were multifunctional energy transducers powered by heat, light, or electricity. The actuators were also investigated for photo/thermal detection. Electrochemical actuators based on MnO2 were also studied for potential underwater applications.
SWNTs were also used to fabricate printable electrodes for trace Cr(VI) detection, which displayed sensitivity up to 500 nA/ppb for Cr(VI). The limit of detection was shown to be as low as 5 ppb. A flow detection system based on CNT/printed electrodes was also demonstrated.
A facile spray pyrolysis synthesis technique was developed to synthesize individual CNSs with specific surface area (SSA) up to 1106 m2/g. The hollow CNSs showed adsorption of up to 300 mg rhodamine B dye per gram carbon, which is more than 15 times higher than that observed for conventional carbon black. They were also evaluated as adsorbents for removal of arsenate and selenate from water and displayed good binding to both species, outperforming commercial activated carbons for arsenate removal in pH > 8. When evaluated as supercapacitor electrode materials, specific capacitances of up to 112 F/g at a current density of 0.1 A/g were observed. When used as Li-ion battery anode materials, the CNSs achieved a discharge capacity of 270 mAh/g at a current density of 372 mA/g (1C), which is 4-fold higher than that of commercial graphite anode.
Carbon foams were synthesized using direct pyrolysis and had SSA up to 2340 m2/g. When used as supercapacitor electrode materials, a specific capacitance up to 280 F/g was achieved at current density of 0.1 A/g and remained as high as 207 F/g, even at a high current density of 10 A/g.
A printed walking robot was made from common plastic films and coatings of SWNTs. The solid-state thermal bimorph actuators were multifunctional energy transducers powered by heat, light, or electricity. The actuators were also investigated for photo/thermal detection. Electrochemical actuators based on MnO2 were also studied for potential underwater applications.
SWNTs were also used to fabricate printable electrodes for trace Cr(VI) detection, which displayed sensitivity up to 500 nA/ppb for Cr(VI). The limit of detection was shown to be as low as 5 ppb. A flow detection system based on CNT/printed electrodes was also demonstrated.
ContributorsWang, Chengwei, Ph.D (Author) / Chan, Candace K. (Thesis advisor) / Tongay, Sefaattin (Committee member) / Wang, Qing Hua (Committee member) / Seo, Dong (Committee member) / Arizona State University (Publisher)
Created2015
Description
With growing concern regarding environmental issues and the need for a more sustainable grid, power systems have seen a fast expansion of renewable resources in the last decade. The uncertainty and variability of renewable resources has posed new challenges on system operators. Due to its energy-shifting and fast-ramping capabilities, energy storage (ES) has been considered as an attractive solution to alleviate the increased renewable uncertainty and variability.
In this dissertation, stochastic optimization is utilized to evaluate the benefit of bulk energy storage to facilitate the integration of high levels of renewable resources in transmission systems. A cost-benefit analysis is performed to study the cost-effectiveness of energy storage. A two-step approach is developed to analyze the effectiveness of using energy storage to provide ancillary services. Results show that as renewable penetrations increase, energy storage can effectively compensate for the variability and uncertainty in renewable energy and has increasing benefits to the system.
With increased renewable penetrations, enhanced dispatch models are needed to efficiently operate energy storage. As existing approaches do not fully utilize the flexibility of energy storage, two approaches are developed in this dissertation to improve the operational strategy of energy storage. The first approach is developed using stochastic programming techniques. A stochastic unit commitment (UC) is solved to obtain schedules for energy storage with different renewable scenarios. Operating policies are then constructed using the solutions from the stochastic UC to efficiently operate energy storage across multiple time periods. The second approach is a policy function approach. By incorporating an offline analysis stage prior to the actual operating stage, the patterns between the system operating conditions and the optimal actions for energy storage are identified using a data mining model. The obtained data mining model is then used in real-time to provide enhancement to a deterministic economic dispatch model and improve the utilization of energy storage. Results show that the policy function approach outperforms a traditional approach where a schedule determined and fixed at a prior look-ahead stage is used. The policy function approach is also shown to have minimal added computational difficulty to the real-time market.
In this dissertation, stochastic optimization is utilized to evaluate the benefit of bulk energy storage to facilitate the integration of high levels of renewable resources in transmission systems. A cost-benefit analysis is performed to study the cost-effectiveness of energy storage. A two-step approach is developed to analyze the effectiveness of using energy storage to provide ancillary services. Results show that as renewable penetrations increase, energy storage can effectively compensate for the variability and uncertainty in renewable energy and has increasing benefits to the system.
With increased renewable penetrations, enhanced dispatch models are needed to efficiently operate energy storage. As existing approaches do not fully utilize the flexibility of energy storage, two approaches are developed in this dissertation to improve the operational strategy of energy storage. The first approach is developed using stochastic programming techniques. A stochastic unit commitment (UC) is solved to obtain schedules for energy storage with different renewable scenarios. Operating policies are then constructed using the solutions from the stochastic UC to efficiently operate energy storage across multiple time periods. The second approach is a policy function approach. By incorporating an offline analysis stage prior to the actual operating stage, the patterns between the system operating conditions and the optimal actions for energy storage are identified using a data mining model. The obtained data mining model is then used in real-time to provide enhancement to a deterministic economic dispatch model and improve the utilization of energy storage. Results show that the policy function approach outperforms a traditional approach where a schedule determined and fixed at a prior look-ahead stage is used. The policy function approach is also shown to have minimal added computational difficulty to the real-time market.
ContributorsLi, Nan (Author) / Hedman, Kory W (Thesis advisor) / Tylavksy, Daniel J (Committee member) / Heydt, Gerald T (Committee member) / Sankar, Lalitha (Committee member) / Arizona State University (Publisher)
Created2016
Description
This research mainly focuses on improving the utilization of photovoltaic (PV) re-sources in distribution systems by reducing their variability and uncertainty through the integration of distributed energy storage (DES) devices, like batteries, and smart PV in-verters. The adopted theoretical tools include statistical analysis and convex optimization. Operational issues have been widely reported in distribution systems as the penetration of PV resources has increased. Decision-making processes for determining the optimal allo-cation and scheduling of DES, and the optimal placement of smart PV inverters are con-sidered. The alternating current (AC) power flow constraints are used in these optimiza-tion models. The first two optimization problems are formulated as quadratically-constrained quadratic programming (QCQP) problems while the third problem is formu-lated as a mixed-integer QCQP (MIQCQP) problem. In order to obtain a globally opti-mum solution to these non-convex optimization problems, convex relaxation techniques are introduced. Considering that the costs of the DES are still very high, a procedure for DES sizing based on OpenDSS is proposed in this research to avoid over-sizing.
Some existing convex relaxations, e.g. the second order cone programming (SOCP) relaxation and semidefinite programming (SDP) relaxation, which have been well studied for the optimal power flow (OPF) problem work unsatisfactorily for the DES and smart inverter optimization problems. Several convex constraints that can approximate the rank-1 constraint X = xxT are introduced to construct a tighter SDP relaxation which is referred to as the enhanced SDP (ESDP) relaxation using a non-iterative computing framework. Obtaining the convex hull of the AC power flow equations is beneficial for mitigating the non-convexity of the decision-making processes in power systems, since the AC power flow constraints exist in many of these problems. The quasi-convex hull of the quadratic equalities in the AC power bus injection model (BIM) and the exact convex hull of the quadratic equality in the AC power branch flow model (BFM) are proposed respectively in this thesis. Based on the convex hull of BFM, a novel convex relaxation of the DES optimizations is proposed. The proposed approaches are tested on a real world feeder in Arizona and several benchmark IEEE radial feeders.
Some existing convex relaxations, e.g. the second order cone programming (SOCP) relaxation and semidefinite programming (SDP) relaxation, which have been well studied for the optimal power flow (OPF) problem work unsatisfactorily for the DES and smart inverter optimization problems. Several convex constraints that can approximate the rank-1 constraint X = xxT are introduced to construct a tighter SDP relaxation which is referred to as the enhanced SDP (ESDP) relaxation using a non-iterative computing framework. Obtaining the convex hull of the AC power flow equations is beneficial for mitigating the non-convexity of the decision-making processes in power systems, since the AC power flow constraints exist in many of these problems. The quasi-convex hull of the quadratic equalities in the AC power bus injection model (BIM) and the exact convex hull of the quadratic equality in the AC power branch flow model (BFM) are proposed respectively in this thesis. Based on the convex hull of BFM, a novel convex relaxation of the DES optimizations is proposed. The proposed approaches are tested on a real world feeder in Arizona and several benchmark IEEE radial feeders.
ContributorsLi, Qifeng (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald T (Committee member) / Mittelmann, Hans D (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2016
Description
Nanoholes on the basal plane of graphene can provide abundant mass transport channels and chemically active sites for enhancing the electrochemical performance, making this material highly promising in applications such as supercapacitors, batteries, desalination, molecule or ion detection, and biosensing. However, the current solution-based chemical etching processes to manufacture these nanoholes commonly suffer from low process efficiency, scalability, and controllability, because conventional bulk heating cannot promote the etching reactions. Herein, a novel manufacturing method is developed to address this issue using microwave irradiation to facilitate and control the chemical etching of graphene. In this process, microwave irradiation induces selective heating of graphene in the aqueous solution due to an energy dissipation mechanism coupled with the dielectric and conduction losses. This strategy brings a remarkable reduction of processing time from hour-scale to minute-scale compared to the conventional approaches. By further incorporating microwave pretreatment, it is possible to control the population and area percentage of the in-plane nanoholes on graphene. Theoretical calculations reveal that the nanoholes emerge and grow by a repeating reduction–oxidation process occurring at the edge-sites atoms around vacancy defects on the graphene basal plane. The reduced holey graphene oxide sheets obtained via the microwave-assisted chemical etching method exhibit great potentials in supercapacitors and electrocatalysis. Excellent capacitive performance and electrocatalytic activity are observed in electrochemical measurements. The improvements against the non-holey counterpart are attributed to the enhanced kinetics involving ion diffusion and heterogeneous charge transfer.
ContributorsWang, Dini (Author) / Nian, Qiong (Thesis advisor) / Alford, Terry (Committee member) / Wang, Qing Hua (Committee member) / Zhuang, Houlong (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