Putting Teeth into Open Architectures: Infrastructure for Reducing the Need for Retesting

Proceedings Paper (for Acquisition Research Program)The Navy is currently implementing the open-architecture framework for developing joint interoperable systems that adapt and exploit open-system design principles and architectures. This raises concerns about how to practically achieve dependability in software-intensive systems with many possible configurations when: 1) the actual configuration of the system is subject to frequent and possibly rapid change, and 2) the environment of typical reusable subsystems is variable and unpredictable. Our preliminary investigations indicate that current methods for achieving dependability in open architectures are insufficient. Conventional methods for testing are suited for stovepipe systems and depend strongly on the assumptions that the environment of a typical system is fixed and known in detail to the quality-assurance team at test and evaluation time. This paper outlines new approaches to quality assurance and testing that are better suited for providing affordable reliability in open architectures, and explains some of the additional technical features that an Open Architecture must have in order to become a Dependable Open Architecture.Naval Postgraduate School Acquisition Research ProgramApproved for public release; distribution is unlimited

An Advanced Machine Learning Based Energy Management of Renewable Microgrids Considering Hybrid Electric Vehicles’ Charging Demand

Renewable microgrids are new solutions for enhanced security, improved reliability and boosted power quality and operation in power systems. By deploying different sources of renewables such as solar panels and wind units, renewable microgrids can enhance reducing the greenhouse gasses and improve the efficiency. This paper proposes a machine learning based approach for energy management in renewable microgrids considering a reconfigurable structure based on remote switching of tie and sectionalizing. The suggested method considers the advanced support vector machine for modeling and estimating the charging demand of hybrid electric vehicles (HEVs). In order to mitigate the charging effects of HEVs on the system, two different scenarios are deployed; one coordinated and the other one intelligent charging. Due to the complex structure of the problem formulation, a new modified optimization method based on dragonfly is suggested. Moreover, a self-adaptive modification is suggested, which helps the solutions pick the modification method that best fits their situation. Simulation results on an IEEE microgrid test system show its appropriate and efficient quality in both scenarios. According to the prediction results for the total charging demand of the HEVs, the mean absolute percentage error is 0.978, which is very low. Moreover, the results show a 2.5% reduction in the total operation cost of the microgrid in the intelligent charging compared to the coordinated scheme

ARCHITECTURE FOR A CBM+ AND PHM CENTRIC DIGITAL TWIN FOR WARFARE SYSTEMS

The Department of the Navy’s continued progression from time-based maintenance into condition-based maintenance plus (CBM+) shows the importance of increasing operational availability (Ao) across fleet weapon systems. This capstone uses the concept of digital efficiency from a digital twin (DT) combined with a three-dimensional (3D) direct metal laser melting printer as the physical host on board a surface vessel. The DT provides an agnostic conduit for combining model-based systems engineering with a digital analysis for real-time prognostic health monitoring while improving predictive maintenance. With the DT at the forefront of prioritized research and development, the 3D printer combines the value of additive manufacturing with complex systems in dynamic shipboard environments. To demonstrate that the DT possesses parallel abilities for improving both the physical host’s Ao and end-goal mission, this capstone develops a DT architecture and a high-level model. The model focuses on specific printer components (deionized [DI] water level, DI water conductivity, air filters, and laser motor drive system) to demonstrate the DT’s inherent effectiveness towards CBM+. To embody the system of systems analysis for printer suitability and performance, more components should be evaluated and combined with the ship’s environment data. Additionally, this capstone recommends the use of DTs as a nexus into more complex weapon systems while using a deeper level of design of experiment.Outstanding ThesisCivilian, Department of the NavyCommander, United States NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyApproved for public release. Distribution is unlimited

Protection of Active Distribution Networks and Their Cyber Physical Infrastructure

Today’s Smart Grid constitutes several smaller interconnected microgrids. However, the integration of converter-interfaced distributed generation (DG) in microgrids has raised several issues such as the fact that fault currents in these systems in islanded mode are way less than those in grid connected microgrids. Therefore, microgrid protection schemes require a fast, reliable and robust communication system, with backup, to automatically adjust relay settings for the appropriate current levels according to the microgrid’s operation mode. However, risks of communication link failures, cyber security threats and the high cost involved to avoid them are major challenges for the implementation of an economic adaptive protection scheme. This dissertation proposes an adaptive protection scheme for AC microgrids which is capable of surviving communication failures. The contribution is the use of an energy storage system as the main contributor to fault currents in the microgrid’s islanded mode when the communication link fails to detect the shift to the islanded mode. The design of an autonomous control algorithm for the energy storage’s AC/DC converter capable of operating when the microgrid is in both grid-connected and islanded mode. Utilizing a single mode of operation for the converter will eliminate the reliance on communicated control command signals to shift the controller between different modes. Also, the ability of the overall system to keep stable voltage and frequency levels during extreme cases such as the occurrence of a fault during a peak pulse load period. The results of the proposed protection scheme showed that the energy storage -inverter system is able to contribute enough fault current for a sufficient duration to cause the system protection devices to clear the fault in the event of communication loss. The proposed method was investigated under different fault types and showed excellent results of the proposed protection scheme. In addition, it was demonstrated in a case study that, whenever possible, the temporary disconnection of the pulse load during the fault period will allow the utilization of smaller energy storage device capacity to feed fault currents and thus reduce the overall expenditures. Also, in this dissertation we proposed a hybrid hardware-software co-simulation platform capable of modeling the relation between the cyber and physical parts to provide a protection scheme for the microgrid. The microgrid was simulated on MATLAB/Simulink SimPowerSystems to model the physical system dynamics, whereas all control logic was implemented on embedded microcontrollers communicating over a real network. This work suggested a protection methodology utilizing contemporary communication technologies between multi-agents to protect the microgrid

Saving energy at sea: seafarers’ adoption, appropriation and enactment of technologies supporting energy efficiency

The shipping industry is currently facing a major challenge related to environmental sustainability and energy efficiency. New regulations and ambitious international goals that aim at mitigating carbon-based emissions with 50 %, demands on profitability, along with a growing awareness about the climate change, has prompted the maritime sector to increasingly focus on how to improve energy efficiency and reduce fuel consumption in ship operations. This thesis aims at describing and understanding the challenges of improving energy efficiency seen from the lens of crew members’ work and to investigate the adoption, appropriation and use of particular technologies, purported to support energy efficiency in ship operation. Using an ethnographic approach and drawing on various practice-based concepts and theories such as communities of practice, activity theory and the imbrication of material and social agency, the four papers (I – IV) included in the thesis were based on extensive field studies in two shipping companies and onboard 11 passenger ferries. The empirical studies revealed that the introduction of new technologies and their subsequent incorporation in and change of established skills and practices is a complex social process depending on the knowing and learning of practitioners as well as their activities, meanings, identities and norms as developed and negotiated in specific settings over time. The thesis contributes to our general understanding of the situated process of adoption, appropriation and use of new technologies in the maritime domain and the sociomaterial nature of energy efficiency

Reconfiguration and Self-healing Mechanisms in Distribution Systems with High Distributed Generation (DG) Penetration

Recently, interest in Smart Grid (SG) as a tool for modernization and automation of the current distribution system has rapidly increased. This interest can be explained by the common belief that SG technologies greatly enhance system reliability, power quality and overall efficiency. One of the most important objectives of an SG is to accommodate a wide variety of generation options. This objective aligns with the new trends and policies that encourage higher penetration levels of Distributed Generation (DG) according to environmental, regulatory and economical concerns. Most DG units are either renewable or low emission energy sources, thus meeting the Canadian emission portfolios, while they remain attractive for both utilities and customers for different reasons. DG units can postpone large investment in transmission and central generation, reduce energy losses, and increase system reliability and power quality. SG is centered on several objectives such as self-healing, motivating consumers to participate in grid operation, resisting attacks, accommodating a wide variety of DG units and storage devices, and optimizing assets. Yet, one of the main goals of SG is to increase the reliability of power systems. Reliability is a vital factor in power system performance, due to the full dependence of today’s life on electricity and the high cost of system outages, especially for critical loads. Therefore, one of the main salient features of SG is its ability of self-healing. The insertion of DG units changes distribution networks from being passive with unidirectional power flow and a single power source (the primary substation) towards active networks with multi-directional power flow and several power sources (the primary substation, along with DG units). As a result, the interconnection of DG units creates several impacts on different practices such as voltage profile, power flow, power quality, stability, reliability, fault detection, and restoration. Current policies call for the direct disconnection of all DG units once any failure occurs in the network. However, with a high DG power penetration, the utilities cannot operate the system efficiently without the DG units’ support. Furthermore, automatic disconnection of the DG units during faults reduces the expected benefits associated with DG units drastically. Motivated by the above facts, the overall target of this thesis is to introduce distribution system mechanisms to facilitate realizing the concept of Smart Distribution System (SDS) in both normal and emergency modes. In particular, three main functions are dealt with in this research work: distribution network reconfiguration, DG allocation and self-healing. First, for distribution network reconfiguration, a method based on genetic algorithm is presented to address the reconfiguration problem for distribution systems while the effect of load variation and the stochastic power generation of renewable-based DG units are taken into consideration. The presented method determines the annual distribution network reconfiguration scheme considering switching operation costs in order to minimize annual energy losses by determining the optimal configuration for each season of the year. Second, for DG allocation, a joint optimization algorithm has been proposed to tackle the DG allocation and network reconfiguration problems concurrently, as these two issues are inherently coupled. The two problems are dealt with together while the objectives are minimizing the cost, as an economic issue, and greenhouse gas emissions, as an environmental issue. The proposed method takes the probabilistic nature of both the renewable energy resources and loads into account. The last operation function dealt with in this thesis is distribution system restoration. In order to accomplish this function, two stages are presented: In the first stage, numerous practical aspects related to service restoration problem have been investigated. These aspects include variations in the load and customer priorities, price discounts for in-service customers based on their participation in a load-curtailment scheme that permits other customers to be supplied, the presence of manual and automated switches, and the incorporation of DG units (dispatchable and wind-based units) in the restoration process. In the second stage, the smart grid concept and technologies have been applied to construct a self-healing framework to be applied in smart distribution systems. The proposed multi-agent system is designed to automatically locate and isolate faults, and then decide and implement the switching operations to restore the out-of-service loads. Load variation has been taken into consideration to avoid the need for further reconfigurations during the restoration period. An expert-based decision-making algorithm has been used to govern the control agents. The rules have been extracted from the practical issues related to the service restoration problem, discussed in the first stage

Modelling and control techniques for multiphase electric drives: a phase variable approach

Multiphase electric drives are today one of the most relevant research topics for the electrical engineering scientific community, thanks to the many advantages they offer over standard three-phase solutions (e.g., power segmentation, fault-tolerance, optimized performances, torque/power sharing strategies, etc...). They are considered promising solutions in many application areas, like industry, traction and renewable energy integration, and especially in presence of high-power or high-reliability requirements. However, contrarily to the three-phase counterparts, multiphase drives can assume a wider variety of different configurations, concerning both the electrical machine (e.g., symmetrical/asymmetrical windings disposition, concentrated/distributed windings, etc...) and the overall drive topology (e.g., single-star configuration, multiple-star configuration, open-end windings, etc…). This aspect, together with the higher number of variables of the system, can make their analysis and control more challenging, especially when dealing with reconfigurable systems (e.g., in post-fault scenarios). This Ph.D. thesis is focused on the mathematical modelling and on the control of multiphase electric drives. The aim of this research is to develop a generalized model-based approach that can be used in multiple configurations and scenarios, requiring minimal reconfigurations to deal with different machine designs and/or different converter topologies, and suitable both in healthy and in faulty operating conditions. Standard field-oriented approaches for the analysis and control of multiphase drives, directly derived as extensions of the three-phase equivalents, despite being relatively easy and convenient solutions to deal with symmetrical machines, may suffer some hurdles when applied to some asymmetrical configurations, including post-fault layouts. To address these issues, a different approach, completely derived in the phase variable domain, is here developed. The method does not require any vector space decomposition or rotational transformation but instead explicitly considers the mathematical properties of the multiphase machine and the effects of the drive topology (which typically introduces some constraints on the system variables). In this thesis work, the proposed approach is particularized for multiphase permanent magnet synchronous machines and for multiphase synchronous reluctance machines. All the results are obtained through rigorous mathematical derivations, and are supported and validated by both numerical analysis and experimental tests. As proven considering many different configurations and scenarios, the main benefits of the proposed methodology are its generality and flexibility, which make it a viable alternative to standard modelling and control algorithms

Agent based modeling of power distribution systems

The electric power system is a very vast network and becoming more complex each day. The traditional vertically monopolistic structure has been deregulated and replaced by gencos, transcos and, discos; increasing the power system intricacy. During the past few decades there has been remarkable development in software and hardware technologies for the analysis and design activities in power system planning, operation, and control. However, much still depends on the judgment of human experts. A single fault in power system can lead to multiple faults and can collapse the whole system. Power System needs a more decentralized control mechanism for solving these problems. One novel solution would be Multi-agent Systems. A Multi-agent system is a collection of agents, which perceives the system changes and acts on the system in order to achieve its goals. Recent technology developments in the area of Multi-agent systems making it a viable solution for today\u27s complicated power network.;A Multi-agent system model is developed for fault detection and reconfiguration in this thesis work. These models are developed based on graph theory tree models and mathematical models. A set of objective functions are specified in the mathematical model for the restoration of the network.;The agent platform for the fault detection is developed by Java Agent Development Framework. The restoration algorithm is programmed in MATLAB and applied to the distribution system modeled in the commercial software, Distributed Engineering Workstation and Power World Simulator. The test system in this thesis is, a distribution system developed by Southern California Edison called Circuit of the Future.;The Multi-agent system can detect the fault precisely and reconfigures the circuit using the reconfiguration algorithm. The reconfiguration will happen in a way that it always try to supply all the critical loads in the network. When there are multiple solutions available for reconfiguration, the one with good voltage profile and less power loss is selected as the solution. The algorithm makes use of shunt compensation and priority based load shedding in order to control the voltage across the network. Agents make use of learning to speed up the reconfiguration process