Includes bibliographic references. / In the early 1990s, a new model emerged for the provision of electricity generation across developing regions. The model involved private sector participation in the form of independent power projects (IPP). Driving this change in business was insufficient public finance from host country governments, a reduction in concessionary loans from multilateral and bilateral development institutions, and a push for improved efficiency in a state-owned utility sector that was considered to be underperforming. This dissertation reviews how IPPs developed across both North Africa and Sub-Saharan Africa. The analysis focuses on the extent to which positive development outcomes (viz. reliable and affordable power) and investment outcomes (viz. favourable investment returns and the opportunity to grow investments) were both achieved. The dissertation posits that balancing development and investment outcomes leads to greater sustainability for projects. It further explores a range of elements that contribute to the success of projects, namely: the investment climate; policy, regulatory and planning frameworks; competitive procurement practices; availability of competitively procured fuel; favourable debt and equity arrangements, including new trends in the nature of IPP firms and credit enhancement arrangements; and new risk management techniques. In-depth case studies of IPP experiences in Egypt, Kenya and Tanzania are used to explore the question of balancing outcomes and sustainability. Reviews of IPP experiences in Cote d'Ivoire, Ghana, Morocco, Nigeria and Tunisia also supplement the analysis together with an evaluation of the foreign direct investment context and related theory. Framing the whole discussion is an examination of how the new model for electric power provision evolved and how power sector reform models need to be adjusted to better reflect the reality in developing countries and emerging economies.

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Cooling, Heating, and Power (CHP) systems have been around for decades, but systems that utilize 20 kW or less, designated as Micro-CHP, are relatively new. Micro-CHP systems show the most promise for a distributed generation scheme to decentralize the national energy grid. A demonstration site has been constructed at Mississippi State University to show the advantages of these systems. This study is designed to evaluate the performance of a Micro-CHP system and a conventional high-efficiency system. Performance and cost factors can be evaluated for the demonstration site operating under either the CHP system or the conventional system. These results are computed from an energy analysis on collected data. This dissertation introduces a new comparison factor to examine different CHP systems. This new factor is called the System Energy Transfer Ratio (SETR). Other considerations in this study include an extensive literature survey that reviews CHP systems, their components, modeling, and other topics concerning CHP systems operation. In addition, the demonstration facility will be discussed in detail presenting the various components and instrumentation. Furthermore, the energy analysis will be presented, examining the equations used to evaluate the raw data from the demonstration site. An uncertainty analysis will be presented for the experimental results. Raw data was collected for 7 months to present the following results. The combined cycle efficiency from the demonstration site was averaged at 29%. Maximum combined cycle efficiency was evaluated at 58%. The average combined boiler and engine cost, per hour of operation, is shown as $1.8 for heating and $3.9 for cooling. The cooling technology used, an absorption chiller, has been shown to exhibit an average COP of 0.27. The proposed SETR for the demonstration site is 22% and 15%, for heating and cooling, respectively. The conventional high-efficiency system, during cooling mode, was shown to have a COP of 4.7 with a combined cooling and building cost of $0.2/hour of operation. During heating mode, the conventional system had an efficiency of 47% with a fuel and building electrical cost of $0.28/hour of operation.

Recent developments in remote sensing technologies have made high resolution remotely sensed data such as hyperspectral and synthetic aperture radar (SAR) data readily available to detect and classify objects on the earth using pattern recognition. However, the dimensionality of such remotely sensed data is often large relative to the number of training samples available. Hence, dimensionality reduction technologies are often adopted to overcome the “curse of dimensionality” phenomenon. This present thesis focuses on the problem of dimensionality reduction of remote sensing data by proposing two algorithms for robust classification of hyperspectral and SAR data. Specifically, for hyperspectral image analysis, a genetic algorithm based feature selection and linear discriminant analysis based dimensionality reduction method is proposed, and, for SAR data, polarization channel based feature grouping followed by a multi-classifier, decision fusion technique is proposed. The algorithmic framework of the proposed approaches and experimental results will be presented in this thesis.

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As modern communication system technology develops, the demand for devices with smaller size, higher efficiency, and larger bandwidth has increased dramatically. To achieve this purpose, a novel architecture of load modulated balanced amplifier (LMBA) with a unique load-modulation characteristic different from any existing LMBAs and Doherty power amplifiers (DPAs) was presented, which is named as Pseudo-Doherty LMBA (PD-LMBA). Based on a special combination of control amplifier (carrier) and balanced amplifier (peaking) together with proper phase and amplitude controls, an optimal load-modulation behavior can be achieved for PD-LMBA leading to maximized efficiency over extended power back-off range. More importantly, the efficiency optimization can be achieved with only a static setting of phase offset at a given frequency, which greatly simplifies the complexity for phase control. Furthermore, the co-operations of the carrier and peaking amplifiers in PD-LMBA are fully de-coupled, thus lifting the fundamental bandwidth barrier imposed on Doherty-based active load modulation. However, since PD-LMBA has CA over-driving concerns, a new load-modulated power amplifier (PA) architecture, Asymmetric Load-Modulated Balanced Amplifier (ALMBA), is proposed based on PD-LMBA. And a subsequent improved type-continuous mode Hybrid Asymmetric Load Modulation Balanced Amplifier (H-ALMBA) has been developed. The two sub-amplifiers (BA1 and BA2) of the balanced topology in an LMBA are set as peaking amplifiers with different thresholds when cooperating with the control amplifier (CA) as the carrier, forming a hybrid load modulation behavior between Doherty and ALMBA. Compared to standard LMBA, the proposed H-ALMBA has a three-way load modulation with CA, BA1 and BA2 through proper amplitude control and phase alignment. Thus, this new mode offers extended power back-off range and enhanced back-off efficiency without suffering from difficulty and complexity in wideband design as imposed on three-way Doherty PAs. Based on comprehensive theoretical derivation and analysis, the proposed H-ALMBA is designed and implemented using commercial GaN transistors and wideband quadrature couplers. Moreover, the continuous-mode matching is applied to the carrier amplifier achieving a maximized wideband efficiency at power back-off. This is the first time that continuous mode and ALMBA have been used in combination, and very satisfactory results have been achieved, exhibiting the highest 10-dB output power back-off (OBO) drain efficiency (DE) ever reported for wideband load-modulation PAs. The developed prototype experimentally demonstrates wide bandwidth from 0.55-2.2 GHz. The measurement exhibits an efficiency of 63-82% at peak output power, 51-62% for 5-dB OBO, and 50-66% for 10-dB OBO within the design bandwidth. When stimulated by a 20-MHz long term evolution (LTE) signal with 10.5-dB peak to average power ratio (PAPR), a 50-55% average efficiency is measured over the entire bandwidth at an average output power around 33 dBm.

Power inductors, or reactors as they are called in the power industry, are one of the fundamental components of a power system. They serve various purposes in both conventional and emerging power systems including: power flow control, fault current limitation, reactive power compensation, harmonic filtering, and others. This dissertation explores the design and applications of conventional power inductors and ways to overcome their shortcomings and expand their functionalities. In addition, novel inductor designs are proposed and analyzed to address power system challenges. A series of inductors, including traditional constant reactance inductor, gapless ferromagnetic core reactor (GFCR) (both costant and variable reactance), and magnetic amplifier-based variable reactance reactor (both single-phase and three-phase), are considered and examined. The various unique inductor designs have been analyzed, both analytically and numerically, and their potential assessed for applications in modern power systems using novel simulation frameworks. A finite element analysis (FEA) based numerical modeling has been carried out for all inductors for accurate representation and analysis. On the other hand, analytical modeling based on magnetic equivalent circuit (MEC) has been presented, to complement the FEA-based approach and overcome its shortcomings. A comparative analysis of the processes provides insights into the effectiveness and accuracy of the proposed analytical models. Also, an advanced data-intensive machine learning (ML) approach to understanding the working of magnetic amplifier technology has been proposed. Additionally, a unique optimal power flow (OPF) formulation with variable reactance because of the power magnetic devices like a magnetic amplifier in a power system is presented. This dissertation covers the presentation of novel inductor designs and their advantages, analyses, and assessments to the broad scientific community and the industry. This kind of research is expected to pave the pathway for future innovations in inductor technologies for applications in modern power systems to make them more reliable, resilient, and efficient.

Smart grids and smart buildings are two highly interdependent energy infrastructure systems. Buildings rely on the grid to provide reliable power while their flexibility can also be utilized to enhance the reliability and efficiency of power system operations. The quantification of heating, ventilation, and air condition (HVAC) system flexibility is critical to the operations of both the grid and buildings in demand response (DR) programs. However, the flexibility quantification is challenging due to the non-linearity and non-convexity of thermal dynamics associated with HVAC components. This dissertation proposes a novel HVAC flexibility quantification method based on a semidefinite programming (SDP) formulation. The SDP is reformulated from the non-convex problem of HVAC power optimization, and can be solved efficiently in real-time. The physics-based HVAC model is incorporated to ensure the reliability and accuracy of solutions. The quantification results are organized into an HVAC flexibility table that can provide response strategies on adjusting HVAC setpoints in response to the grid signals received. The developed response strategies minimize occupant discomfort while satisfying grid requirements. A case study of a test building model is carried out to illustrate the flexibility quantification framework and compares the performance of two DR strategies. Buildings that are involved in the energy market need to follow certain power profiles. The robustness of power tracking is critical to the evaluation of their quality of service. Due to the easy accessibility of building automation systems, building sensor attacks can be launched to affect the power tracking accuracy. A robust HVAC control algorithm that can handle the uncertainty of sensor attack signal distribution is proposed to enhance the building power tracking. A Wasserstein distance-based ambiguity set is defined to bound the uncertain distortion between the predicted attack signal distribution and the true distribution. The worst-case distribution within the ambiguity set that has the largest expected power tracking error is solved. Then the robust control decision is made upon this worst-case distribution. In this way, the power tracking error can be reduced by 20%. The reliability of temperature maintenance is also enhanced by the proposed distributionally robust optimization. Besides sensor attack, the control signal of building automation system can also be overwritten if the proxy aggregator is attacked. This type of attack can impact the frequency stability of the entire system by manipulating load power across the system. To study the vulnerability of the system under control signal attack, an optimization-based attack model that incorporates the grid transient model and physics-based building model is proposed. The proposed attack model solves for the time series executable control signals that coordinate the system states and building limits at the minimum cost of building temperature deviation. This attack model is used for the vulnerability assessment of the IEEE 68-bus 16-machine system from two perspectives. The vulnerability of buses and aggregators can be obtained from the trajectories of the coordinated attack signals.

A growing number of buildings are integrating building-integrated photovoltaics (BIPV) devices to increase energy efficiency and reduce energy costs. A building's heating and cooling loads are impacted by the thermal resistance of the air duct BIPV because of the change in thermal resistance. Therefore, augmenting the efficiency of (BIPV) devices will benefit many building architectures and mechanical engineering applications. This work introduces a low-cost and low- maintenance air duct system design augmenting BIPV systems. This novel approach increases airflow velocity and decreases air temperature for BIPV, resulting in improved performance for the PV system electricity output, increased PV lifespan due to reduced temperatures, and improved overall energy efficiency of the building. Specifically, we show how to model and simulate the BIPV system analyzing both the PV devices and building energy. We present a quantitative study to demonstrate this air duct system can reduce energy usage by up to 2.7% depending on the climate zone. The air duct system performs best in warm and sunny climates based on our simulations. Finally, we use computational fluid dynamics (CFD) to study the additional advantages of this air duct model. Due to the lower temperature of the PV surface, the results indicate that air ducts can improve the electrical energy production of PV modules by up to 3%. This benefit is not limited to energy production; it will also contribute to a longer life cycle for PV modules by lower temperature-induced degradation. Lastly, our study simulates a wide variety of parameter options to understand the optimal design integration of the BIPV system's impact on a building's energy loads.

With the increasing demand for faster date rates and extensive user connectivities, the complex modulation schemes and large-scaled arrays have been widely researched and employed in the modern wireless links e.g., 5G and beyond-5G systems. These pose major challenges to design the power amplifiers (PAs) to accommodate the system level evolution. As the critical part, the power amplifiers (PAs) dominate the output power, efficiency, linearity and reliability of the radio frequency (RF) transmitter. Consequently, the PA's capability of maintaining an efficient, linear and reliable signal amplification operation is essential to the communication systems. On the other hand, due to the deployment of massive multiple input/multiple output (MIMO) technique, the highly integrated active antenna systems replaced traditional 50Ω-based PA with sectorized antenna architectures. This brings the fact that, as the beam is steered in the antenna array, the dynamic load impedance observed from PAs can be up to 2: 1 Voltage Standing Wave Ratio (VSWR) due to the time-varying phasing and output power between the adjacent antenna elements and PAs, thus severely deteriorate PAs' performance. To resolve aforementioned challenges, a novel design theory of Quasi-balanced Doherty power amplifier (QB-DPA) is first presented in this dissertation, which opens a new vision to counteract the mismatch-induced degradation using reconfigurable PA architectures. In this QB-DPA design, the isolation port of the PA's output coupler is alternatively terminated to 50-Ω load and ground to enable the balanced and Doherty modes. With the implementation of the silicon-on-insulator (SOI)-based single-pole-double-throw (SPDT) switch to realize the reconfiguration, the physical prototype is demonstrated exhibiting remarkable DPA performance, in terms of the linearity, efficiency and output power. Subsequently, a series/parallel QB-DPA theory that not only can improve the back-off efficiency of QB-DPA, but also significantly restore the load-mismatch degradation is proposed. This novel topology includes and unifies QB-DPA modes at balanced, series and parallel Doherty, respectively. Moreover, a novel linearity-enhanced combiner is introduced for nominal 50-Ω load to improve the linearity at both series and parallel QB-DPA modes. The reconfiguration between series and parallel operations largely restore the performance degradation when the PAs suffer a dynamic antenna mismatch condition. Finally, a wideband mismatch-resilient QB-DPA is presented. Through parallel/series reconfiguration and reciprocal biasing, it is for the first time shown that the QB-DPA is able to maintain a stable output power as well as enhanced efficiency and linearity across 2 : 1 VSWR circle, and this operation can be seamlessly extended to a wide bandwidth which holds promising potential for application to array-based massive MIMO systems.