Most digital control architectures for power system applications require synchronization with the distribution system voltage. Therefore, a phase-locked loop (PLL), implemented in a DSP, is generally among the digital control blocks of the control system. The PLL analyzes the bus voltage and provides power system information for some of the other blocks to do further calculation. Thus, the performance of the PLL has a broad impact on the system performance. Small-scale power systems, such as naval systems, pose a challenging environment for PLL design due to voltage distortion and variation in the fundamental frequency that is large as compared to large terrestrial systems. Our objective is to improve the accuracy of the PLL digital block and hence enhance the digital control system. This research compares two PLL algorithms, as well as the use of a PI controller or lag controller with respect to their steady state and transient performance.

This thesis develops a time-domain integrated modeling approach for design of hybrid-electric marine propulsion systems that enables co-simulation of powertrain dynamics along with ship hydrodynamics. This work illustrates the model-based design and analysis methodology by performing a case study for an EV conversion of a short-cross ferry using the BC Ferries’ M.V. Klitsa. A data acquisition study was performed to establish the typical mission cycle of the ship for its crossing route between Brentwood Bay and Mill Bay, across the Saanich Inlet near Victoria, BC Canada. The data provided by the data acquisition study serves as the primary means of validation for the model’s ability to accurately predict powertrain loads over the vessel’s standard crossing. This functionality enables model-based powertrain and propulsion system design optimization through simulation to intelligently deploy hybrid-electric propulsion architectures. The ship dynamics model is developed using a Newton-Euler approach which incorporates hydrodynamic coefficient data produced by potential flow solvers. The radiation forces resulting from vessel motion are fit to continuous time-domain transfer functions for computational efficiency. The ship resistance drag matrix is parameterized using results from uRANS CFD studies that span the operating range of the vessel. A model of the existing well-mounted azimuthing propeller is developed to predict thrust production and mechanical torque for pseudo-second quadrant operation to represent all operating conditions seen in real operation. The propeller model is parameterized from the results of a series of uRANS CFD on the propeller geometry. A full battery-electric powertrain model is produced to study the accuracy of the model in predicting the drivetrain loads, as well as assessing the technological feasibility of an EV conversion for this particular vessel. A dual-polarization equivalent circuit model is created for a large-scale LTO battery pack. An average value model with MTPA control and dynamics loss model is developed for a commercially available electric drive system. Power loss models were developed for required converter topologies for computational efficiency. The model results for load prediction are compared to data acquired, and results indicate that the approach is effective for enabling the study of various powertrain architecture alternatives. / Graduate

All-electric ship power systems have limited generation capacity and finite rotating inertia compared with large power systems. Moreover, all-electric ship power systems include large portions of nonlinear loads and dynamic loads relative to the total power capacity, which may significantly reduce the stability margin. Pulse loads and other high-energy weapon loads in the system draw a large amount of power intermittently, which may cause significant frequency and voltage oscillations in the system. Thus, an effective real-time load management technique is needed to dynamically balance the load and generation to operate the system normally. Multi-agent systems, inspired by biological phenomena, aim to cooperatively achieve system objectives that are difficult to reach by a single agent or centralized controller. Since power systems include various electrical components with different dynamical systems, conventional homogeneous multi-agent system cooperative controllers have difficulties solving the real-time load management problem with heterogeneous agents. In this dissertation, a novel heterogeneous multi-agent system cooperative control methodology is presented based on artificial potential functions and reduced-order agent models to cooperatively achieve real-time load management for all-electric ship power systems. The technique integrates high-order system dynamics and various kinds of operational constraints into the multi-agent system, which improves the accuracy of the cooperative controller. The multi-agent system includes a MVAC multiagent system and a DC zone multi-agent, which are coordinated by an AC-DC communication agent. The developed multi-agent system framework and the notional all-electric ship power system model were simulated in PSCAD software. Case studies and performance analysis of the MVAC multi-agent system and the DC zone multi-agent system were performed. The simulation results indicated that propulsion loads and pulse loads can be successfully coordinated to reduce the impact of pulse loads on the power quality of all-electric ship power systems. Further, the switch status or power set-point of loads in DC zones can be optimally determined to dynamically balance the generation and load while satisfying the operational constraints of the system and considering load priorities. The method has great potential to be extended to other isolated power systems, such as microgrids.

Voyage planning methods have advanced significantly in recent years to take advantage of the increasingly available computing power. With the aid of detailed weather predictions it is now possible to decide a route that is optimized with respect to some criterion. With the introduction of so called All Electric Ships; ships with diesel electric propulsion, varying the power production in order to adjust the propulsion has become easier. Incorporating a power management system with the voyage planning software on a ship allows for different techniques to reduce fuel consumption. In this thesis, three different approaches are developed, compared and combined. The first method handles the task of how to optimally share a load demand across a set of generators. The second is performing power production scheduling with respect to engine efficiencies, and finally in the third the potential in energy storage integration with the power management system is investigated. From the results, it is argued that the largest potential lies in the first approach where large fuel savings can be made without any large risk. The second approach shows potential for fuel reduction but this however is found to be heavily dependent on weather predictions and accuracy of the used models. Regarding energy storage it is found that while it is not economically feasible to increase the fuel efficiency, energy storage can be used to handle load transients and fulfil power redundancy requirements.

Multifunctional voltage source converters (VSCs) are desired for shipboard power systems. The opportunity to extend the functionality of a particular VSC on demand, combined with power system reconfiguration strategies may provide desired redundancy to back up power electronic converters that might be destroyed as a result of a battle damage or material casualty. The space for power electronics may be downsized if the VSCs are capable of performing multiple functions. In addition, the flexibility of the energy management can be enhanced in shipboard power systems if a single VSC can perform multiple functions. The functionality of a VSC in many cases is restricted to a single task or set of tasks by its control architecture. Despite the great number of different control strategies suggested for VSCs, nearly all use similar methods for generation of the reference signals. These methods generally depend upon the use of filters to extract reference signals for the components that are to be injected into or drawn from the system. These methods of control are not flexible. The main objective of the dissertation is the development of a flexible reference signal generator for VSCs that allows online maximization of its possible functions. Furthermore, the switching frequency of a VSC is generally above 10 kHz for many applications, and carries a significant amount of high frequency noise. This necessitates the use of EMI filters, which carry an extra cost and increase the overall bulk of the power electronics. This may not be acceptable for shipboard power systems, where the space and weight requirements are usually stringent. Thus, in addition to investigation of various reference signal generator (RSG) strategies for VSCs, alternative solutions to attenuate EMI levels in the shipboard power system environment are explored.

The goal of the work reported herein has been to model aspects of the electrical distribution system of an all-electric ship (AES) and to couple electrical load behavior with the thermal management network aboard the ship. The development of a thermally dependent electrical network has built upon an in-house thermal management simulation environment to replace the existing steady state heat loads with dynamic, thermally dependent, electrical heat loads. Quantifying the close relationship between thermal and electrical systems is of fundamental importance in a large, integrated system like the AES. This in-house thermal management environment, called the Dynamic Thermal Modeling and Simulation (DTMS) framework, provided the fundamental capabilities for modeling thermal systems and subsystems relevant to the AES. The motivation behind the initial work on DTMS was to understand the dynamics of thermal management aboard the ship. The first version, developed in 2007, captured the fundamental aspects of system-level thermal management while maintaining modularity and allowing for further development into other energy domains. The reconfigurable nature of the DTMS framework allowed for the expansion into the electrical domain with the creation of an electrical distribution network in support of thermal simulations. The dynamics of the electrical distribution system of the AES were captured using reconfigurable and physics-based circuit elements that allow for thermal feedback to affect the behavior of the system. Following the creation of the electrical network, subsystems and systems were created to simulate electrical distribution. Then, again using the modularity features of DTMS, a thermal resistive heat flow network was created to capture the transient behavior of heat flow from the electrical network to the existing thermal management framework. This network provides the intimate link between the thermal management framework and the electrical distribution system. Finally, the three frameworks (electrical, thermal resistive, and thermal management) were combined to quantify the impact that each system has relative to system-level operation. Simulations provide an indication of the unlimited configurations and potential design space a user of DTMS can explore to explore the design of an AES. / text

The focus of this research is on identification, location, interruption, characterization and overall management of faults in conventional AC distribution systems as well as isolated MVDC power systems. The primary focus in AC distributions systems is on identifying and locating underground cable faults using voltage and current waveforms as the input data. Cable failure process is gradual and is characterized by a series of single-phase sub-cycle incipient faults with high arc voltage. They often go undetected and eventually result in a permanent fault in the same phase. In order to locate such incipient cable faults, a robust yet practical algorithm is developed taking into account the fault arc voltage. The algorithm is implemented in the time-domain and utilizes power quality monitor data to estimate the distance to the fault in terms of the line impedance. It can be applied to locate both sub-cycle as well as permanent faults. The proposed algorithm is evaluated and proved out using field data collected from utility distribution circuits. Furthermore, this algorithm is extended to locate evolving faults on overhead distribution lines. Evolving faults are faults beginning in one phase of a distribution circuit and spreading to another phase after a few cycles. The algorithm is divided into two parts, namely, the single line-to-ground portion of the fault and the line-to-line-to-ground portion of the fault. For the single line-to-ground portion of the fault, the distance to the fault is estimated in terms of the loop or self-reactance between the monitor and the fault. On the other hand, for the line-to-line-to-ground and line-to-line portion of the fault the distance is estimated in terms of the positive-sequence reactance. The secondary focus of fault management in AC distribution systems is on identifying fault cause employing voltage and current waveform data as well as meteorological information. As the first step, unique characteristics of cable faults are examined along with methods to identify such faults with suitable accuracy. These characteristics are also used to distinguish underground cable faults from other overhead distribution line faults. The overhead line faults include tree contact, animal contact and lightning induced faults. Waveform signature analysis, wavelet transforms and arc voltages during the fault event are used for fault cause identification and classification. A statistical based classification methodology to identify fault cause is developed by utilizing promising characteristics. Unlike the AC system infrastructure which is already in place, the DC system considered in this document is that of a notional electric ship. The nature of DC current, with the absence of a current zero as well as the presence of power electronic devices influencing the current behavior, makes interrupting DC fault currents challenging. As a part of this research an innovative DC fault interruption scheme is proposed for rectifier- fed MVDC systems. A fault at the terminals of a phase-controlled rectifier results in a high magnitude current impulse caused by the filter capacitor discharging into the fault resistance. It is proposed to use a series inductor to limit the magnitude of this current impulse. The addition of the inductor results in an underdamped series RLC circuit at the output terminals of the rectifier which causes the fault current to oscillate about zero. Furthermore, it is proposed to utilize a conventional AC circuit breaker to interrupt this fault current by exploiting the zero crossings resulting from the oscillations. Using the proposed scheme for the example case, the peak fault current magnitude as well as the interruption time is significantly reduced. / text

The United States Navy is committed to developing technology for an All-Electric Ship (AES) that promises to improve the affordability and capability of its next-generation warships. With the addition of power-intensive 21st century electrical systems, future thermal loads are projected to exceed current heat removal capacity. Furthermore, rising fuel costs necessitate a careful approach to total-ship energy management. Accordingly, the aim of this research is to develop computer tools for early-stage design of shipboard energy distribution systems. A system-level model is developed that enables ship designers to assess the effects of thermal and electrical system configurations on fuel efficiency and survivability. System-level optimization and design exploration, based on these energy system models, is challenging because the models are sometimes computationally expensive and characterized by discrete design variables and discontinuous responses. To address this challenge, a classifier-guided sampling (CGS) method is developed that uses a Bayesian classifier to pursue solutions with desirable performance characteristics. The CGS method is tested on a set of example problems and applied to the AES energy system model. Results show that the CGS method significantly improves the rate of convergence towards known global optima, on average, when compared to genetic algorithms. / text

This Master of Science thesis was written based on the shipbuilder Kockums AB feasibility study regarding the development of an All- Electric Ship for the Swedish Navy. The thesis was aiming at addressing voltage stability issues in a dc system fed by PWM rectifiers operating in parallel when supplying constant power loads. A basic computer model was developed for investigating the influence from various parameters on the system. It was shown that the voltage stability is dependent upon the ability to store energy in large capacitors. It was also shown that a voltage droop must be implemented maintaining load sharing within acceptable limits. Different cases of operation were modelled, faults were discussed, and the principal behaviour of the system during a short-circuit was investigated. It was shown that the short-circuit current is much more limited in this type of system in comparison to an ac system. It was concluded that more research and development regarding the components of the system must be performed.

This paper is an investigation into a quantitative selection process of either a mechanical or electrical system architecture for the transmission of propulsion power in naval combatant vessels. A database of historical naval ship characteristics was statistically analyzed to determine if there were any predominant ship parameters that could be used to predict whether a ship should be designed with a mechanical power transmission system or an electric one. A Principal Component Analysis was performed to determine the minimum number of dimensions required to define the relationship between the propulsion transmission architecture and the independent variables. Combining the results of the statistical analysis and the PCA, neural networks were trained and tested to separately predict the transmission architecture or the installed electrical generation capacity of a given class of naval combatant.