An approach to parallelize the simulation of AC-Radial Shipboard Power Systems (SPSs) using multicore computers is presented. Time domain simulations of SPSs are notoriously slow, due principally to the number of components, and the time-variance of the component models. A common approach to reduce the simulation run-time of power systems is to formulate the electrical network equations using modified nodal analysis, use Bergeron's travelling-wave transmission line model to create subsystems, and to parallelize the simulation using a distributed computer. In this work, an SPS was formulated using loop analysis, defining the subsystems using a diakoptics-based approach, and the simulation parallelized using a multicore computer. A program was developed in C# to conduct multithreaded parallel-sequential simulations of an SPS. The program first represents an SPS as a graph, and then partitions the graph. Each graph partition represents a SPS subsystem and is computationally balanced using iterative refinement heuristics. Once balanced subsystems are obtained, each SPS subsystem's electrical network equations are formulated using loop analysis. Each SPS subsystem is solved using a unique thread, and each thread is manually assigned to a core of a multicore computer. To validate the partitioning approach, performance metrics were created to assess the speed gain and accuracy of the partitioned SPS simulations. The simulation parameters swept for the performance metrics were the number of partitions, the number of cores used, and the time step increment. The results of the performance metrics showed adequate speed gains with negligible error. An increasing simulation speed gain was observed when the number of partitions and cores were augmented, obtaining maximum speed gains of <30x when using a quadcore computer. Results show that the speed gain is more sensitive to the number partitions than is to the number of cores. While multicore computers are suitable for parallel-sequential SPS simulations, increasing the number of cores does not contribute to the gain in speed as much as does partitioning. The simulation error increased with the simulation time step but did not influence the partitioned simulation results. The number of operations caused by protective devices was used to determine whether the simulation error introduced by partitioning SPS simulations produced a inconsistent system behavior. It is shown, for the time step sizes uses, that protective devices did not operate inadvertently, which indicates that the errors did not alter RMS measurement and, hence, were non-influential.

Electric transportation has been a well-studied research topic with electric ships gaining momentum. Ships can have a wide range in size from small cargo ships to military vessels. The benefits of electrification include meeting environmental sustainability goals and operational benefits in terms of flexibility and renewed operation. The power systems onboard a ship can be considered a microgrid, which is called a shipboard microgrid. This system poses unique challenges compared to land-based microgrids due to the resiliency requirements of being at sea. A control system for a hybrid- electric ship is proposed with both an energy storage system (ESS) and traditional diesel generators and gas turbines. This system balances economics with resilient control by calculating a baseline load distribution using the cost of operating each unit for the expected load profile. Additionally, the control system ensures that the generation capacity is available if the load does not follow the expected profile. To maintain flexibility, the system will redispatch the units as needed based on the actual load applied, while reducing the control efforts and maintaining the generation contingency. Therefore, the proposed shipboard microgrid control offers a control method that considers the cost of operation while maintaining the required standards of shipboard microgrid control. / Electrical and Computer Engineering

Medium-Voltage Direct-Current (MVDC) power system has been considered as the trending technology for future All-Electric Ships (AES) to produce, convert and distribute electrical power. With the wide employment of highrequency power electronics converters and motor drives in DC system, accurate and fast assessment of system dynamic behaviors , as well as the optimization of system transient performance have become serious concerns for system-level studies, high-level control designs and power management algorithm development. The proposed technique presents a coordinated and automated approach to determine the system adjustment strategy for naval power systems to improve the transient performance and prevent potential instability following a system contingency. In contrast with the conventional design schemes that heavily rely on the human operators and pre-specified rules/set points, we focus on the development of the capability to automatically and efficiently detect and react to system state changes following disturbances and or damages by incooperating different system components to formulate an overall system-level solution. To achieve this objective, we propose a generic model-based predictive management framework that can be applied to a variety of Shipboard Power System (SPS) applications to meet the stringent performance requirements under different operating conditions. The proposed technique is proven to effectively prevent the system from instability caused by known and unknown disturbances with little or none human intervention under a variety of operation conditions. The management framework proposed in this dissertation is designed based on the concept of Model Predictive Control (MPC) techniques. A numerical approximation of the actual system is used to predict future system behaviors based on the current states and the candidate control input sequences. Based on the predictions the optimal control solution is chosen and applied as the current control input. The effectiveness and efficiency of the proposed framework can be evaluated conveniently based on a series of performance criteria such as fitness, robustness and computational overhead. An automatic system modeling, analysis and synthesis software environment is also introduced in this dissertation to facilitate the rapid implementation of the proposed performance management framework according to various testing scenarios.

Shipboard Power Systems (SPS) play a significant role in next-generation Navy fleets. With the increasing power demand from propulsion loads, ship service loads, weaponry systems and mission systems, a stable and reliable SPS is critical to support different aspects of ship operation. It also becomes the technology-enabler to improve ship economy, efficiency, reliability, and survivability. Moreover, it is important to improve the reliability and robustness of the SPS while working under different operating conditions to ensure safe and satisfactory operation of the system. This dissertation aims to introduce novel and effective approaches to respond to different types of possible faults in the SPS. According to the type and duration, the possible faults in the Medium Voltage DC (MVDC) SPS have been divided into two main categories: transient and permanent faults. First, in order to manage permanent faults in MVDC SPS, a novel real-time reconfiguration strategy has been proposed. Onboard postault reconfiguration aims to ensure the maximum power/service delivery to the system loads following a fault. This study aims to implement an intelligent real-time reconfiguration algorithm in the RTDS platform through an optimization technique implemented inside the Real-Time Digital Simulator (RTDS). The simulation results demonstrate the effectiveness of the proposed real-time approach to reconfigure the system under different fault situations. Second, a novel approach to mitigate the effect of the unsymmetrical transient AC faults in the MVDC SPS has been proposed. In this dissertation, the application of combined Static Synchronous Compensator (STATCOM)-Super Conducting Fault Current Limiter (SFCL) to improve the stability of the MVDC SPS during transient faults has been investigated. A Fluid Genetic Algorithm (FGA) optimization algorithm is introduced to design the STATCOM's controller. Moreover, a multi-objective optimization problem has been formulated to find the optimal size of SFCL's impedance. In the proposed scheme, STATCOM can assist the SFCL to keep the vital load terminal voltage close to the normal state in an economic sense. The proposed technique provides an acceptable post-disturbance and postault performance to recover the system to its normal situation over the other alternatives.

Shipboard Power System (SPS) is known as an independent controlled small electric network powered by the distributed onboard generation system. Since many electric components are tightly coupled in a small space and the system is not supported with a relatively stronger grid, SPS is more susceptible to unexpected disturbances and physical damages compared to conventional terrestrial power systems. Among different distribution configurations, power-electronic based DC distribution is considered the trending technology for the next-generation U.S. Navy fleet design to replace the conventional AC-based distribution. This research presents appropriate control management frameworks to improve the Medium-Voltage DC (MVDC) shipboard power system performance. Model Predictive Control (MPC) is an advanced model-based approach which uses the system model to predict the future output states and generates an optimal control sequence over the prediction horizon. In this research, at first, a centralized MPC is developed for a nonlinear MVDC SPS when a high-power pulsed load exists in the system. The closed-loop stability analysis is considered in the MPC optimization problem. A comparison is presented for different cases of load prediction for MPC, namely, no prediction, perfect prediction, and Autoregressive Integrated Moving Average (ARIMA) prediction. Another centralized MPC controller is also designed to address the reconfiguration problem of the MVDC system in abnormal conditions. The reconfiguration goal is to maximize the power delivered to the loads with respect to power balance, generation limits and load priorities. Moreover, a distributed control structure is proposed for a nonlinear MVDC SPS to develop a scalable power management architecture. In this framework, each subsystem is controlled by a local MPC using its state variables, parameters and interaction variables from other subsystems communicated through a coordinator. The Goal Coordination principle is used to manage interactions between subsystems. The developed distributed control structure brings out several significant advantages including less computational overhead, higher flexibility and a good error tolerance behavior as well as a good overall system performance. To demonstrate the efficiency of the proposed approach, a performance analysis is accomplished by comparing centralized and distributed control of global and partitioned MVDC models for two cases of continuous and discretized control inputs.

The Medium Voltage DC (MVDC) architecture of shipboard power system (SPS) with higher power density and enhanced power control is seen as a future prospect in warships by US Navy. Optimal operation of SPS is essential to enable efficient power and energy usage in the tightly coupled and power limited systems. It helps in obtaining adequate and reliable power supply by rescheduling generator output and energy storage devices for different operating scenarios and can also ensure power supply to critical loads during fault conditions. The self-commutated Voltage Source Converters (VSCs) with high dynamic performance and independent control over the real and reactive powers are best suited in the MVDC architecture. Therefore, an optimal operation tool is developed for the multi-terminal VSC based MVDC SPS which minimizes the system operating costs by optimally coordinating generators and energy storage, and will also implement preventive and corrective actions for managing credible contingencies.

Uninterrupted power supply is an important requirement for electric ship since it has to confront frequent travel and hostilities. However, the occurrence of faults in the shipboard power systems interrupts the power service continuity and leads to the severe damage on the electrical equipments. Faults need to be quickly detected and isolated in order to restore the power supply and prevent the massive cascading outage effect on the electrical equipments. This thesis presents an Artificial Neural Network (ANN) based method for the fault classification and location in MVDC shipboard power systems using the transient information in the fault voltage and current waveforms. The proposed approach is applied to the cable of an equivalent MVDC system which is simulated using PSCAD. The proposed method is efficient in detecting the type and location of DC cable faults and is not influenced by changes in electrical parameters like fault resistance and load.

With the improvements in computer technology, users in utilities expect to receive more advanced functions of their power system management applications by using the data distributed among computer applications. The conventional method of point-to-point interface is not efficient for building large-scale computer systems and is especially difficult for system integration. Integration efforts are carried on to facilitate software applications communicating with others. Defining the same description for a central database and exchangeable data format among applications is the first step for integration. Since current data models in the Common Information Model (CIM) are designed mostly for analyzing the terrestrial transmission power system, they are not sufficient for Shipboard Power Systems (SPS). In order to facilitate software integration in SPS, a fundamentally common semantic for SPS applications needs to be extended from the current CIM. Therefore, these analysis applications for SPS could communicate with each other based on a standard model. In this thesis, a pulsed load model is extended from CIM. This model is a general time dependent pulsed load and the simulation of pulsed railgun load validates the proposed data model. Also, stress upon the power grid caused by the pulsed load is analyzed and the continuous railgun operation is simulated. In addition, new CIM data models are built for passive and active filters to facilitate system simulation and further application. As an active filter is a device that incorporates complicated control strategies, much work focused on finding a general data model to accommodate most common active filters. Finally the simulation for active filter validates the proposed data model.

Future naval ships will be all-electric, with an integrated power system that combines the propulsion power system with the rest of the ship?s electrical distribution system. Reconfiguration of the power system will increase fight-through and survivability of ships, but will also require the systems that support the power system, such as the protection system, to be automatically updated to match current power system needs. This thesis presents an adaptive relaying scheme for shipboard power systems, to automatically modify relay settings after power system topology changes. Multiple Groups of relay settings are predetermined and stored in the digital relays that are protecting the power system. The active Group of settings is automatically determined based on the open/close status of breakers and switches. The developed protection scheme is tested on two test cases by digital simulation using CAPE software and on one case by closed-loop simulation with RTDS and SEL-351S relays.

Real time monitoring of the shipboard power system is a complex task to address. Unlike the terrestrial power system, the shipboard power system is a comparatively smaller system but with more complexity in terms of its system operation. This requires the power system to be continuously monitored to detect any type of fluctuations or disturbances. Planning metering systems in the power system of a ship is a challenging task not only due to the dimensionality of the problem, but also due to the need for reducing redundancy while improving network observability and efficient data collection for a reliable state estimation process. This research is geared towards the use of a Genetic Algorithm for intelligent placement of meters in a shipboard system for real time power system monitoring taking into account different system topologies and critical parameters to be measured from the system. The algorithm predicts the type and location of meters for identification and collection of measurements from the system. The algorithm has been tested with several system topologies.