Electric utilities are increasingly incentivized to integrate new renewable energy generation resources to their systems; however, operations-related issues arise due to the non-dispatchable and stochastic nature of these renewable energy sources. These characteristics lead to a variety of issues for utilities, among which are voltage fluctuations, balancing dispatch against ramping events, short-duration power fluctuations, and the need to invest in peaking generation facilities just to accommodate the renewable energy. A traditional solution to these issues is to employ renewable generation-following techniques using either newly constructed gas peaking plants, or by shifting existing generation resources to this following responsibility. Unfortunately, use of these traditional methods introduces a new set of issues; namely, wear-and-tear due to more frequent cycling, reduced capacity factors, decreased plant efficiency, and additional investment in large-scale captital infrastructure. This thesis proposes an alternate solution: a utility-owned and utility-managed battery energy storage system sited on residential customer premises, deployed at scale to create a 200MW / 1320MWh distributed network of Residential Battery Energy Storage Systems (ResBESS). In partnership with Portland General Electric (PGE) stakeholders, a conceptual design was prepared for a ResBESS unit, a laboratory prototype of a single such storage system was constructed, and an alpha prototype is now being installed in a field demonstration project in Milwaukie, Oregon within PGE's service territory. The motivations, design constraints, and design methodology of the laboratory prototype are presented and discussed, and preliminary work from the field prototype build is examined to demonstrate the results of the thesis project.

This thesis focuses on the design and implementation of the Portable DC Light Bulb system for Cal Poly San Luis Obispo’s DC House Project. The DC Portable Light Bulb highlights the NiMH battery charging circuit, buck converter, and boost converter. The system is intended as a flashlight adaptor placed in between the dimmable DC light bulb and its screw base. The adaptor adds a portability feature to the DC light bulb to provide lighting wherever the user pleases. The Portable DC Light Bulb system is designed to operate with an input range of 24V-60V and regulate an output voltage of 34V for the DC light bulb. Computer simulations, calculations, and hardware results verifies the proposed Portable DC Light Bulb system’s design, function, and purpose.

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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.

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.

The communication schemes have rapidly changed the face of the human means of communication. The evolution from one generation to another has triggered many challenges on the design methodologies of RF designers. As the evolution ensued, the spectrally efficient modulation schemes have resulted in the substantial rise of PAPR, the peak-to-average power ratio. To enable the efficient amplification of the high PAPR signals, this thesis explores the areas of Load modulated Balanced amplifiers that can be inherently reconfigured to achieve a better efficiency than the conventional RF power amplifiers that see a significant drop in the efficiency as the signal is backed-off from the maximum power level. In the communication environment, the load mismatch to the power amplifier does result in the degraded efficiency profile which is detrimental to the performance of the communication system. Hence, the power amplifier stage needs to be mismatch resilient. A three mode reconfigurable balanced power amplifier that can tolerate the mismatch due to the antenna array in massive MIMO is presented. The transistor's analog-digital duality is exploited for deploying it as an amplifier and a switch in the designed amplifier stage to enable the reconfiguration between the respective modes of operation. In addition, the output matching topology is designed to be symmetric for the corresponding amplifier stages with an input branch-line quadrature coupler and a unique harmonic tuning methodology that is used to effectively achieve a higher order load modulation in one of the modes, HLMBA. The other two modes of the PA stage are mismatch resilient and their performance is also observed to be efficient with switch settings dedicated to offer mismatch resilience at varied terminations.

Power system is vulnerable to disastrous climate events due to sequential or successive equipment failure. In this dissertation, the problem of identifying the critical k-transmission lines that fail one after another in quick succession, and the distribution system restoration problem using tie-lines/sectionalizing switches formulated as a mixed-integer non-linear programming problem (MINLP) that determines load shed under various k-line removal scenarios are solved. These problems are combinatorial that have huge search space, and solution through enumeration is intractable for large power systems. For reduction of search space, the following mathematical tools are derived, (i) two power flow methods due to k-transmission line removal using the sparse perturbation matrices and power flow sensitivities, (ii) a power flow sensitivity namely k-th order LODF computed using a vector of non-zero numbers stored from the matrix multiplication terms of the first-order sensitivity equation for single line removal cases which reduces its computational complexity, and the sensitivity is computed for any k-line removal case without the necessity of storing it for all k-line removal cases, and (iii) a topological metric based on Laplacian of unweighted graph to identify some important lines between highly connected subgraphs whose disconnection partitions the power system into a few islands. Algorithms are presented using these mathematical tools to identify a reduced number of k-transmission lines in linear time that initiate cascading overload failure and islanding of power system, that are used to solve the MINLP iteratively for identification of critical k-line contingencies as compared to the exponential time complexity of brute-force search for solutions of the MINLP. To reduce the complexity of the restorative problem, a method is developed that exploits the information on pre-contingency power flow solution, network topology together with post-contingency line congestion requirements, and in combination with a greedy search algorithm, which reduces the search space of the problem. Case studies show that the algorithms significantly reduce the search space and computation time of the MINLPs.

Decreasing costs of renewable energy resources and net-zero emission energy production policy, set by U.S. government, are two preeminent factors that motivate power utilities to deploy more system- or consumer-centric distributed energy resources (DERs) to decarbonize electricity production. Since, deep energy decarbonization cannot be achieved without high penetration of renewable energy sources, utilities should develop and invest in new business models for power system operation and planning during the energy transition. Considering the pathways to deeply decarbonize power systems, first, this dissertation proposes a novel hierarchical peer-to-peer (P2P) energy market design in active distribution networks. The framework integrates the distributional locational marginal price to a multi-round double auction with average price mechanism to integrate the network usage charges into the bills of customers. Second, this dissertation investigates the role of grid-integrated hydrogen (H2) systems for improved utility operations and to supply fuel to transportation sector. Power quality concerns as well as risk of uncertain parameters are considered using conditional value at risk based epsilon constraint method. Third, this dissertation proposes a bi-level proactive rolling-horizon based scheduling of H2 systems in integrated distribution and transmission networks considering the flexibility of these assets as controllable load or generation, in addressing the utility operators' normal and emergency operation signals. Fourth, a detailed model is developed for grid-integrated Electrolyzer considering polarization curve and non-linear conversion efficiency of these assets in the P2P enabled distribution network. This framework shows that reasonable penetration of P2P energy exchanges can significantly lower the H2 production cost. Finally, this dissertation proposes a cyber-physical vulnerability assessment of P2P energy exchanges in an unbalanced active distribution networks. Simulation results of this dissertation show the effectiveness of the proposed frameworks.