En rapport avec la transition énergétique, d’importantes capacités de stockage énergétique sont nécessaires pour intégrer la forte variation de la production énergétique au travers des centrales éoliennes et photovoltaïques. La transformation de l’énergie électrique en énergie chimique sous forme d’hydrogène est l’une des possibles techniques. La technologie de stockage de l’hydrogène souterrain, selon laquelle l’hydrogène est stocké dans les formations souterraines semblables au stockage du gaz naturel est actuellement un axe de recherche de plusieurs états européens. Par comparaison au stockage du gaz naturel dans les formations souterraines et qui est établie depuis de nombreuses années, l'hydrogène a montré des différences significatives dans son comportement hydrodynamique et biochimique. Ces aspects ont été étudiés dans la présente thèse en utilisant différentes approches analytiques et numériques / In the context of energy revolution large quantities of storage capacity are required for the integration of strongly fluctuating energy production from wind and solar power plants. The conversion of electrical energy into chemical energy in the form of hydrogen is one of the technical possibilities. The technology of underground hydrogen storage (UHS), where hydrogen is stored in subsurface formations similar to the storage of natural gas, is currently in the exploratory focus of several European countries. Compared to the storage of natural gas in subsurface formations, which is established since many years, hydrogen shown some significant differences in its hydrodynamic and bio-chemical behavior. These aspects were investigated in the present thesis by different analytical and numerical approaches

Doctor of Philosophy / Electrical and Computer Engineering / Ruth D. Miller / Optimizing renewable distributed generation in distribution systems has gained popularity with changes in federal energy policies. Various studies have been reported in this regard and most of the studies are based on optimum wind and/or solar generation planning in distribution system using various optimization techniques such as analytical, numerical, and heuristic. However, characteristics such as high energy density, relatively lower footprint of land, availability, and local reactive power compensation ability, have gained increased popularity for optimizing distributed wind generation (DWG) in distribution systems. This research investigated optimum distributed generation planning (ODGP) using two primary optimization techniques: analytical and heuristic. In first part of the research, an analytical optimization method called “Combined Electrical Topology (CET)” was proposed in order to minimize the impact of intentional structural changes in distribution system topology, in distributed generation/ DWG placement. Even though it is still rare, DWG could be maximized to supply base power demand of three-phase unbalanced radial distribution system, combined with distributed battery energy storage systems (BESS). In second part of this research the usage of DWG/BESS as base power generation, and to extend the ability to sustain the system in a power grid failure for a maximum of 1.5 hours was studied. IEEE 37-node, three-phase unbalanced radial distribution system was used as the test system to optimize wind turbines and sodium sulfide (NaS) battery units with respect to network real power losses, system voltage profile, DWG/BESS availability and present value of cost savings. In addition, DWG’s ability to supply local reactive power in distribution system was also investigated. Model results suggested that DWG/NaS could supply base power demand of a threephase unbalanced radial distribution system. In addition, DWG/NaS were able to sustain power demand of a three-phase unbalanced distribution system for 1.5 hours in the event of a power grid failure.

abstract: This thesis addresses the issue of making an economic case for bulk energy storage in the Arizona bulk power system. Pumped hydro energy storage (PHES) is used in this study. Bulk energy storage has often been suggested for large scale electric power systems in order to levelize load (store energy when it is inexpensive [energy demand is low] and discharge energy when it is expensive [energy demand is high]). It also has the potential to provide opportunities to avoid transmission and generation expansion, and provide for generation reserve margins. As the level of renewable energy resources increases, the uncertainty and variability of wind and solar resources may be improved by bulk energy storage technologies. For this study, the MATLab software platform is used, a mathematical based modeling language, optimization solvers (specifically Gurobi), and a power flow solver (PowerWorld) are used to simulate an economic dispatch problem that includes energy storage and transmission losses. A program is created which utilizes quadratic programming to analyze various cases using a 2010 summer peak load from the Arizona portion of the Western Electricity Coordinating Council (WECC) system. Actual data from industry are used in this test bed. In this thesis, the full capabilities of Gurobi are not utilized (e.g., integer variables, binary variables). However, the formulation shown here does create a platform such that future, more sophisticated modeling may readily be incorporated. The developed software is used to assess the Arizona test bed with a low level of energy storage to study how the storage power limit effects several optimization outputs such as the system wide operating costs. Large levels of energy storage are then added to see how high level energy storage affects peak shaving, load factor, and other system applications. Finally, various constraint relaxations are made to analyze why the applications tested eventually approach a constant value. This research illustrates the use of energy storage which helps minimize the system wide generator operating cost by "shaving" energy off of the peak demand. The thesis builds on the work of another recent researcher with the objectives of strengthening the assumptions used, checking the solutions obtained, utilizing higher level simulation languages to affirm results, and expanding the results and conclusions. One important point not fully discussed in the present thesis is the impact of efficiency in the pumped hydro cycle. The efficiency of the cycle for modern units is estimated at higher than 90%. Inclusion of pumped hydro losses is relegated to future work. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2014

abstract: 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. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2015

abstract: 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. / Dissertation/Thesis / Doctoral Dissertation Materials Science and Engineering 2015

abstract: The complicated, unpredictable, and often chaotic hot water usage pattern of typical households severely limits the effectiveness and efficiency of traditional solar hot water heater systems. Similar to large scale concentrating solar power plants, the use of thermal energy storage techniques to store collected solar energy as latent heat has the potential to improve the efficiency of solar hot water systems. Rather than being used to produce steam to generate electricity, the stored thermal energy would be used to heat water on-demand well after the sun sets. The scope of this thesis was to design, analyze, build, and test a proof of concept prototype for an on-demand solar water heater for residential use with latent heat thermal energy storage. The proof of concept system will be used for future research and can be quickly reconfigured making it ideal for use as a test bed. This thesis outlines the analysis, design, and testing processes used to model, build, and evaluate the performance of the prototype system. The prototype system developed to complete this thesis was designed using systems engineering principles and consists of several main subsystems. These subsystems include a parabolic trough concentrating solar collector, a phase change material reservoir including heat exchangers, a heat transfer fluid reservoir, and a plumbing system. The system functions by absorbing solar thermal energy in a heat transfer fluid using the solar collector and transferring the absorbed thermal energy to the phase change material for storage. The system was analyzed using a mathematical model created in MATLAB and experimental testing was used to verify that the system functioned as designed. The mathematical model was designed to be adaptable for evaluating different system configurations for future research. The results of the analysis as well as the experimental tests conducted, verify that the proof of concept system is functional and capable of producing hot water using stored thermal energy. This will allow the system to function as a test bed for future research and long-term performance testing to evaluate changes in the performance of the phase change material over time. With additional refinement the prototype system has the potential to be developed into a commercially viable product for use in residential homes. / Dissertation/Thesis / Masters Thesis Engineering 2015

abstract: This thesis examines using thermal energy storage as a demand side management tool for air-conditioning loads with the goal of increasing photovoltaic penetration. It uses Arizona State University (ASU) as a case study. The analysis is completed with a modeling approach using typical meteorological year (TMY) data, along with ASU’s historical load data. Sustainability, greenhouse gas emissions, carbon neutrality, and photovoltaic (PV) penetration are all considered along with potential economic impacts. By extrapolating the air-conditioning load profile from the existing data sets, it can be ensured that cooling demands can be met at all times under the new management method. Using this cooling demand data, it is possible to determine how much energy is required to meet these needs. Then, modeling the PV arrays, the thermal energy storage (TES), and the chillers, the maximum PV penetration in the future state can be determined. Using this approach, it has been determined that ASU can increase their solar PV resources by a factor of 3.460, which would amount to a PV penetration of approximately 48%. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2016

abstract: 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. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2016

abstract: 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. / Dissertation/Thesis / Doctoral Dissertation Engineering 2016

abstract: Fluids such as steam, oils, and molten salts are commonly used to store and transfer heat in a concentrating solar power (CSP) system. Metal oxide materials have received increasing attention for their reversible reduction-oxidation (redox) reaction that permits receiving, storing, and releasing energy through sensible and chemical potential. This study investigates the performance of a 111.7 MWe CSP system coupled with a thermochemical energy storage system (TCES) that uses a redox active metal oxide acting as the heat transfer fluid. A one-dimensional thermodynamic model is introduced for the novel CSP system design, with detailed designs of the underlying nine components developed from first principles and empirical data of the heat transfer media. The model is used to (a) size components, (b) examine intraday operational behaviors of the system against varying solar insolation, (c) calculate annual productivity and performance characteristics over a simulated year, and (d) evaluate factors that affect system performance using sensitivity analysis. Time series simulations use hourly direct normal irradiance (DNI) data for Barstow, California, USA. The nominal system design uses a solar multiple of 1.8 with a storage capacity of six hours for off-sun power generation. The mass of particles to achieve six hours of storage weighs 5,140 metric tonnes. Capacity factor increases by 3.55% for an increase in storage capacity to eight hours which requires an increase in storage volume by 33% or 737 m3, or plant design can be improved by decreasing solar multiple to 1.6 to increase the ratio of annual capacity factor to solar multiple. The solar reduction receiver is the focal point for the concentrated solar energy for inducing an endothermic reaction in the particles under low partial pressure of oxygen, and the reoxidation reactor induces the opposite exothermic reaction by mixing the particles with air to power an air Brayton engine. Stream flow data indicate the solar receiver experiences the largest thermal loss of any component, excluding the solar field. Design and sensitivity analysis of thermal insulation layers for the solar receiver show that additional RSLE-57 insulation material achieves the greatest increase in energetic efficiency of the five materials investigated. / Dissertation/Thesis / Masters Thesis Civil and Environmental Engineering 2017