High efficiency of power converters placed between renewable energy sources and the utility grid is required to maximize the utilization of these sources. Power quality is another aspect that requires large passive elements (inductors, capacitors) to be placed between these sources and the grid. The main objective is to develop higher-level high frequency-based power converter system (HFPCS) that optimizes the use of hybrid renewable power injected into the power grid. The HFPCS provides high efficiency, reduced size of passive components, higher levels of power density realization, lower harmonic distortion, higher reliability, and lower cost. The dynamic modeling for each part in this system is developed, simulated and tested. The steady-state performance of the grid-connected hybrid power system with battery storage is analyzed. Various types of simulations were performed and a number of algorithms were developed and tested to verify the effectiveness of the power conversion topologies. A modified hysteresis-control strategy for the rectifier and the battery charging/discharging system was developed and implemented. A voltage oriented control (VOC) scheme was developed to control the energy injected into the grid. The developed HFPCS was compared experimentally with other currently available power converters. The developed HFPCS was employed inside a microgrid system infrastructure, connecting it to the power grid to verify its power transfer capabilities and grid connectivity. Grid connectivity tests verified these power transfer capabilities of the developed converter in addition to its ability of serving the load in a shared manner. In order to investigate the performance of the developed system, an experimental setup for the HF-based hybrid generation system was constructed. We designed a board containing a digital signal processor chip on which the developed control system was embedded. The board was fabricated and experimentally tested. The system’s high precision requirements were verified. Each component of the system was built and tested separately, and then the whole system was connected and tested. The simulation and experimental results confirm the effectiveness of the developed converter system for grid-connected hybrid renewable energy systems as well as for hybrid electric vehicles and other industrial applications.

Integration of renewable energy systems by the utility, customers, and the third party into the electric power system, most especially in the MV and LV distribution networks grew over the last decade due to the liberalization of the electricity market, rising energy demand, and increasing environmental concern. The distributed rooftop PV system contributes to relieve the overall load, reduce losses, avoid conventional generation upgrade, and better matching of demand on the LV distribution network. Originally, the LV distribution network is designed for unidirectional current flow, that is from the substation to customers. However, a high penetration of rooftop solar PVs (with power levels typically ranging from 1 – 10 kW) may lead to the current flowing in the reverse direction and this could result in a sudden voltage rise. These negative impacts on the network have discouraged the distribution network operators (DNOs) to allow increased PV penetration in the LV distribution network because some customers load, and equipment are sensitive to voltage perturbation. Presently, the most applied voltage rise mitigation strategy for high rooftop solar PV penetration is the total disconnect from the LV distribution network when the voltage at the point of common coupling (PCC) goes above statutory voltage limits. However, the sudden disconnection of the PV system from the grid can cause network perturbation and affect the security of the network. This action may also cause voltage instability in the network and can reduce the lifetime of grid equipment such as voltage regulators, air conditioner etc. Due to this negative impact, different voltage rise mitigation strategies such as the active transformer with on load tap changers (OLTC), distributed battery energy storage system and reactive power support (D-STATCOM, etc.) have been used to curtail voltage rise in the distribution network. However, the implementation of D-STATCOM device on a radial LV distribution network results in high line current and losses. This may be detrimental to the distribution network. Therefore, in this thesis, a coordinated active power reduction (CAPR) strategy is proposed using a modified PWM PI current control strategy to ramp down the output power and voltage of a grid-tied voltage source inverter (VSI). In the proposed strategy, a reactive reference is generated based on the measured voltage level at the PCC using a threshold voltage algorithm to regulate the amplitude of the modulating signal to increase the off time of the high frequency signal which shut down the PV array momentary in an extremely short time and allow the VSI to absorb some reactive power through the freewheeling diode and reduce voltage. The proposed CAPR strategy was designed and simulated on a scaled down simple radial LV distribution network in MATLAB®/Simulink® software environment. The results show that the CAPR can ramp down the PV output power, reduce reverse power flow and reduce the sudden voltage rise at the point of common coupling (PCC) within ±5% of the standard voltage limit. The study also compares the performance of the proposed CAPR strategy to that of the distributed static compensator (D-STATCOM) and battery energy storage system (BESS) with respect to response time to curtail sudden voltage rise, losses and reverse power flow. The investigation shows that the D-STATCOM has the faster response time to curtail voltage rise. However, the voltage rise reduction is accompanied by high current, losses and reverse active power flow. The introduction of the BESS demonstrates better performance than the D- STATCOM device in terms of reverse power flow and losses. The CAPR strategy performs better than both D-STATCOM and BESS in terms of line losses and reverse power flow reduction.

This dissertation focuses on extending solution methods in the area of stochastic optimization. Attention is focused to three specific problems in the field. First, a solution method for mixed integer programs subject to chance constraints is discussed. This class of problems serves as an effective modeling framework for a wide variety of applied problems. Unfortunately, chance constrained mixed integer programs tend to be very challenging to solve. Thus, the aim of this work is to address some of these challenges by exploiting the structure of the deterministic reformulation for the problem. Second, a stochastic program for integrating renewable energy sources into traditional energy systems is developed. As the global push for higher utilization of such green resources increases, such models will prove invaluable to energy system designers. Finally, a process for transforming clinical medical data into a model to assist decision making during the treatment planning phase for palliative chemotherapy is outlined. This work will likely provide decision support tools for oncologists. Moreover, given the new requirements for the usage electronic medical records, such techniques will have applicability to other treatment planning applications in the future.

abstract: Current policies subsidizing or accelerating deployment of photovoltaics (PV) are typically motivated by claims of environmental benefit, such as the reduction of CO2 emissions generated by the fossil-fuel fired power plants that PV is intended to displace. Existing practice is to assess these environmental benefits on a net life-cycle basis, where CO2 benefits occurring during use of the PV panels is found to exceed emissions generated during the PV manufacturing phase including materials extraction and manufacture of the PV panels prior to installation. However, this approach neglects to recognize that the environmental costs of CO2 release during manufacture are incurred early, while environmental benefits accrue later. Thus, where specific policy targets suggest meeting CO2 reduction targets established by a certain date, rapid PV deployment may have counter-intuitive, albeit temporary, undesired consequences. Thus, on a cumulative radiative forcing (CRF) basis, the environmental improvements attributable to PV might be realized much later than is currently understood. This phenomenon is particularly acute when PV manufacture occurs in areas using CO2 intensive energy sources (e.g., coal), but deployment occurs in areas with less CO2 intensive electricity sources (e.g., hydro). This thesis builds a dynamic Cumulative Radiative Forcing (CRF) model to examine the inter-temporal warming impacts of PV deployments in three locations: California, Wyoming and Arizona. The model includes the following factors that impact CRF: PV deployment rate, choice of PV technology, pace of PV technology improvements, and CO2 intensity in the electricity mix at manufacturing and deployment locations. Wyoming and California show the highest and lowest CRF benefits as they have the most and least CO2 intensive grids, respectively. CRF payback times are longer than CO2 payback times in all cases. Thin film, CdTe PV technologies have the lowest manufacturing CO2 emissions and therefore the shortest CRF payback times. This model can inform policies intended to fulfill time-sensitive CO2 mitigation goals while minimizing short term radiative forcing. / Dissertation/Thesis / M.S. Civil and Environmental Engineering 2013

Master of Architecture / Department of Architecture / Gary J. Coates / Buildings account for a large part of total U.S. energy consumption and generate far more greenhouse gas emissions than any other sector of the economy. The purpose of this thesis is to demonstrate how buildings can be designed in a way that helps to mitigate global environmental problems, while resolving local urban design, architecture and social issues. This purpose was achieved by designing a zero-energy garage apartment for a site located along an alley in Manhattan, Kansas. The methodology for the design was to: identify a client; define project goals and design criteria; determine solar and geothermal renewable energy system requirements; design the garage apartment by employing energy efficient strategies relating to bioregional design and passive solar design; identify eco-friendly materials obtainable within a 500-mile radius of the site; and identify energy-efficient construction methods. The energy performance of the garage apartment was constantly monitored using eQUEST and Energy-10 simulation softwares. Operational definitions: Garage apartment- a building behind the main building[superscript]1, which is part of the same plot as the main building. It is also called a 'backhouse', 'granny flat' or a 'rear house'. Zero-energy house- for this thesis, a grid connected self-standing zero-energy house, which results in zero utility bills throughout the year.

Connecting more non-dispatchable renewable energy sources (RESs) will result in a higher power variability and a lower system inertia when the synchronous generators are replaced by inverter-connected RES. Inverter control can be divided in three categories: grid-following, grid-forming (GFM) and grid-supporting. A literature review of inverter control strategies identifies the GFM control as having an important role in maintaining system stability assuming near 100 % inverter-connected RES. Critical aspects of the inverter control are also identified; the control need to function autonomously, be able to remain connected during transient events and be insensitive to grid topology. Combining various RES is also shown to improve system stability. The combination of RES that has been investigated in most studies is wind, solar and wave power. Wave power is still a young technology compared to solar and wind power. It generates higher power fluctuations over short time periods with a significant difference between average and maximum power. Additionally, wave power parks (WPPs) are often connected via long cables which contribute reactive power to the grid. These challenges has to be considered to maintain system stability and power quality when connecting a WPP to the grid. In a Power Hardware-In-the-Loop study of how a WPP affects the power quality at the point of common coupling (PCC), it is found that the impact is highest for WPPs with fewer generators as the variability is reduced when several generators are excited at different times. Energy storage is also shown to have a significant impact on the power quality at the PCC with reduced flicker, total harmonic distortion and power and voltage variability. A simulation study also shows the positive impact of energy storage on power variability and the role of inverter control in reactive power compensation.

Decarbonisation of different energy sectors of society is becoming a pressing issue globally withnumerous legislations and objectives being set to decarbonise electrical grids worldwide. Somehave already been met; however, islanded grids still heavily rely on fossil fuels to meet their electrical demand due to the weakness of their grid and limited available space forcing them to use space-efficient technologies such as diesel generators. This is the case of Fuerteventura in the Canary Islands (Spain) which produces 80-90% of its electricity from fossil fuels. This study will analyse the feasibility of decarbonising the electrical grid of Fuerteventura using a decentralised grid system with wind, solar, and battery storage to achieve 100% renewable generation. To select the best hybrid energy system for the case study, a 9-step methodology has been presented and followed in which both descriptive (qualitative) and quantitative data have been used to provide the background knowledge of the study and the inputs for the analysis which is done using the microgrids optimisation model HOMER. The analysis aims to understand the grid and renewable resources on the island to later develop the different scenarios to be reviewed. The three different scenarios, wind-battery, solar-battery, and wind-solar-battery were modelled and simulated using the latest HOMER software. Results showed reduced LCOE and capital costs in the wind-solar-battery scenario compared to the wind-battery and solar-battery scenarios due to increased use of wind and lower capacity of installed batteries needed. Space availability was shown to be a problem for the scenarios using wind as the turbines would occupy 5% of the islands surface. Environmental and visual impacts would also be noticeable under the wind-battery and wind-solar-battery scenarios as the entire island is a Biosphere Nature Reserve and is a well-known touristic destination for natural virgin beaches. Additionally, the results showed that all 3 scenarios had excess electricity values above 50% of the total electrical production and still experienced some capacity shortages. To solve this, diversification of the generation and storage facilities, implementation of DSM (Demand side management) and V2G (Vehicle-to-grid), and interconnection of the islands is proposed with the latter being the most realistic solution. The study concludes the wind-solar-battery is the most technological and economically feasible solution although several issues need to be addressed for a similar project to be implemented on a real island.

Electrification of households in rural area and isolated regions plays a significant impact on the balanced economic development. Brazil grows with a high population growth rate, but still parts of rural area and isolated regions do not have the accessibility of electric power. This study focuses on the feasibility study of a hybrid PV-wind-biomass power system for rural electrification at Nazaré Paulista in southeast Brazil. This study was performed by using the hybrid renewable energy system software HOMER. The wind and solar data was collected from Surface meteorology and Solar Energy-NASA, and the biomass data was collected and estimated from other previous studies. The result shows, the hybrid PV-wind-biomass renewable system can meet 1,601 kWh daily demands and 360 kW peak load of the selected rural area. The power system composed of 200 kW PV panels, 200 kW biomass generator, 400 battery banks, and 200 kW converter. All the calculations were performed by Homer and the selection were based on the Net Present Cost (NPC) and Levelized cost of energy (COE). Because of the fossil fuels’ negative impacts on human health and environment, all the energy sources for this system are renewable energies which have less pollution.

A global transition to renewable energy is required to address the sustainability challenge and mitigate the socio-ecological consequences of climate change. This thesis explores what factors contribute to slowing down the transition to renewable energy in Southeast Asia. The region was chosen due to its rising energy demand, high energy poverty rates and unsustainable energy generation. The objective is to identify what barriers and enablers inhibit and encourage the financing of decentralized solar energy systems (DSES) in the region.  The study applied a qualitative approach where five exploratory and 12 semi-structured interviews were conducted to gain rich and diverse insights into the current state of DSES within Southeast Asia. The PESTLE analytical framework was used to code the results in a systematic way. This study found several barriers inhibiting an increased deployment of DSES. These included ineffective regulatory frameworks, systemic corruption and market monopolization of DSES, financial issues related to the small size of projects as well as technical and financial capacity among local actors. At the same time, the study identified multiple enablers to address these challenges, including policies encouraging transparency and standardization, capacity building for maintenance or financial literacy and falling project costs due to technological innovation.

La situation compromettante de l'environnement due à la pollution, et les coûts élevés des combustibles fossiles ont engagé des nouvelles politiques et réglementations et ont fortement incité l’augmentation de l’utilisation de nouvelles sources d'énergie renouvelables. De nombreux pays dans le monde ont augmenté de façon importante le développement de ces sources d'énergie. Deux des systèmes d'énergies renouvelables les plus couramment utilisés sont les systèmes éoliens (SE) et les systèmes photovoltaïques (SP). SE convertissent l'énergie du vent en énergie électrique au moyen d'un processus électromécanique et SP convertissent directement l'énergie solaire en énergie électrique au moyen d'un processus semi-conducteur. Ces systèmes présentent de nombreux défis qui doivent être résolus afin de gagner du terrain sur les systèmes d'énergies traditionnelles. L'un de ces défis est d'augmenter l'efficacité du système avec la commande des éléments de puissance. Afin d'atteindre cet objectif, il est nécessaire de mieux comprendre le comportement dynamique de ces systèmes et de développer des nouveaux modèles mathématiques et des nouvelles techniques de commande. Ces techniques nécessitent souvent des informations du système qui ne sont pas disponibles --- ou sont trop chères si on devait les mesurer. Pour résoudre ce problème, il est nécessaire de créer des algorithmes qui puissent estimer cette information, cependant, ce n'est pas une tâche facile, car les signaux des sources d'énergie dans SE et SP (c.-à-d. la vitesse du vent, rayonnement solaire, température) entrent dans les modèles mathématiques par une relation non linéaire. Ces algorithmes doivent pouvoir estimer ces signaux --- ou les signaux qui dépendent d’eux--- avec une bonne précision. Aussi, il est nécessaire de concevoir des lois de commande qui opèrent les systèmes à leur point maximum de puissance. Dans ce travail, nous proposons des nouveaux algorithmes d'estimation et des lois de commande qui sont liés à l'augmentation de l'efficacité énergétique dans SE et SP. Des travaux antérieurs liés à l'estimation des signaux mentionnés, les considéraient comme constants. Dans cette thèse, les algorithmes d'estimation proposés considèrent l'état variable des ces signaux. Dans toutes ces nouvelles propositions, la stabilité asymptotique est prouvée en utilisant les théories de Lyapunov. Les lois de commande sont calculées en utilisant les modèles non linéaires des systèmes. En outre, certaines des ces solutions sont étendues au cas général, qui peut être utilisé sur une large classe des systèmes non linéaires. Le premier, est un estimateur de paramètres pour les systèmes non linéaires. Il permet d'estimer les paramètres non linéaires variant dans le temps. La deuxième proposition est la conception d’un schéma pour une classe de systèmes non linéaires adaptatifs qui permet de compenser les incertitudes et les perturbations qui satisfont à la "condition de correspondance". / The compromising situation of the environment due to pollution, and the high costs of the fossil fuels have originated new policies and regulations that have stimulating the interest on alternative energy sources. Many countries around the world have increased in an important way the penetration of these energy sources. Two of the most widely used renewable energy systems are the wind turbines systems (WTS) and the photovoltaic systems (PVS). WTS convert wind energy in electric energy by means of an electromechanical process and PVS convert solar energy directly in electric energy by means of a semiconductive process. These systems show many challenges that need to be solved in order to gain ground to the traditional energy systems. One of these challenges is increase the overall system efficiency by controlling the power conditioning elements. In order to achieve this, is necessary to better understand the dynamic behavior of these systems and develop new mathematical models and new control techniques. These techniques often require system information that is not possible ---or is too expensive--- measure. In order to solve this problem, is necessary to create algorithms that are able to estimate this information, however, this is not an easy task, because the signals of the energy sources in WTS and PVS (i.e., wind speed, irradiance, temperature) enter in the mathematical models in a nonlinear relation. These algorithms have to be able to estimate these signals ---or the signals that depend on them--- with good precision. Also, it is necessary to design control laws that operate the systems at their maximum power point. In this work, we propose novel estimation algorithms and control laws that are related with the increase of the energetic efficiency in WTS and PVS. Previous works related with estimation of the mentioned signals considered them as constants. In this thesis, the proposed estimation algorithms consider the time-varying condition of these signals. In all of these novel propositions, uniform asymptotic stability is proved using Lyapunov theories. The control laws are derived using the overall nonlinear models of the systems. In addition, some of these solutions are extended to the general case, which can be used on a large-class of nonlinear systems. The first one, is a novel parameter estimator for nonlinear systems. It allows to estimate time-varying nonlinear parameters. The second general proposition is a framework for a class of adaptive nonlinear systems that allows to compensate for uncertainties and perturbations that satisfy the matching condition.