Automation, Protection and Control of Substation Based on IEC 61850

Reliability of power system protection system has been a key issue in the substation operation due to the use of multi-vendor equipment of proprietary features, environmental issues, and complex fault diagnosis. Failure to address these issues could have a significant effect on the performance of the entire electricity grid. With the introduction of IEC 61850 standard, substation automation system (SAS) has significantly altered the scenario in utilities and industries as indicated in this thesis

Open source SCADA systems for small renewable power generation

Low cost monitoring and control is essential for small renewable power systems. While large renewable power systems can use existing commercial technology for monitoring and control, that is not cost-effective for small renewable generation. Such small assets require cost-effective, flexible, secure, and reliable real-time coordinated data monitoring and control systems. Supervisory control and data acquisition (SCADA) is the perfect technology for this task. The available commercial SCADA solutions are mostly pricey and economically unjustifiable for smaller applications. They also pose interoperability issues with the existing components which are often from multiple vendors. Therefore, an open source SCADA system represents the most flexible and the most cost-effective SCADA solution. This thesis has been done in two phases. The first phase demonstrates the design and dynamic simulation of a small hybrid power system with a renewable power generation system as a case study. In the second phase, after an extensive study of the proven commercial SCADA solutions and some open source SCADA packages, three different secure, reliable, low-cost open source SCADA options are developed using the most recent SCADA architecture, the Internet of Things. The implemented prototypes of the three open source SCADA systems were tested extensively with a small renewable power system (a solar PV system). The results show that the developed open source SCADA systems perform optimally and accurately, and could serve as viable options for smaller applications such as renewable generation that cannot afford commercial SCADA solutions

Maintenance Management of Wind Turbines

“Maintenance Management of Wind Turbines” considers the main concepts and the state-of-the-art, as well as advances and case studies on this topic. Maintenance is a critical variable in industry in order to reach competitiveness. It is the most important variable, together with operations, in the wind energy industry. Therefore, the correct management of corrective, predictive and preventive politics in any wind turbine is required. The content also considers original research works that focus on content that is complementary to other sub-disciplines, such as economics, finance, marketing, decision and risk analysis, engineering, etc., in the maintenance management of wind turbines. This book focuses on real case studies. These case studies concern topics such as failure detection and diagnosis, fault trees and subdisciplines (e.g., FMECA, FMEA, etc.) Most of them link these topics with financial, schedule, resources, downtimes, etc., in order to increase productivity, profitability, maintainability, reliability, safety, availability, and reduce costs and downtime, etc., in a wind turbine. Advances in mathematics, models, computational techniques, dynamic analysis, etc., are employed in analytics in maintenance management in this book. Finally, the book considers computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques that are expertly blended to support the analysis of multi-criteria decision-making problems with defined constraints and requirements

Incorporating voltage security into the planning, operation and monitoring of restructured electric energy markets

As open access market principles are applied to power systems, significant changes are happening in their planning, operation and control. In the emerging marketplace, systems are operating under higher loading conditions as markets focus greater attention to operating costs than stability and security margins. Since operating stability is a basic requirement for any power system, there is need for newer tools to ensure stability and security margins being strictly enforced in the competitive marketplace. This dissertation investigates issues associated with incorporating voltage security into the unbundled operating environment of electricity markets. It includes addressing voltage security in the monitoring, operational and planning horizons of restructured power system. This dissertation presents a new decomposition procedure to estimate voltage security usage by transactions. The procedure follows physical law and uses an index that can be monitored knowing the state of the system. The expression derived is based on composite market coordination models that have both PoolCo and OpCo transactions, in a shared stressed transmission grid. Our procedure is able to equitably distinguish the impacts of individual transactions on voltage stability, at load buses, in a simple and fast manner. This dissertation formulates a new voltage stability constrained optimal power flow (VSCOPF) using a simple voltage security index. In modern planning, composite power system reliability analysis that encompasses both adequacy and security issues is being developed. We have illustrated the applicability of our VSCOPF into composite reliability analysis. This dissertation also delves into the various applications of voltage security index. Increasingly, FACT devices are being used in restructured markets to mitigate a variety of operational problems. Their control effects on voltage security would be demonstrated using our VSCOPF procedure. Further, this dissertation investigates the application of steady state voltage stability index to detect potential dynamic voltage collapse. Finally, this dissertation examines developments in representation, standardization, communication and exchange of power system data. Power system data is the key input to all analytical engines for system operation, monitoring and control. Data exchange and dissemination could impact voltage security evaluation and therefore needs to be critically examined

Emerging technologies and future trends in substation automation systems for the protection, monitoring and control of electrical substations

Tese de Mestrado Integrado. Engenharia Electrotécnica e de Computadores (Automação). Faculdade de Engenharia. Universidade do Porto. 201

Transitioning power distribution grid into nanostructured ecosystem : prosumer-centric sovereignty

PhD ThesisGrowing acceptance for in-house Distributed Energy Resource (DER) installations at lowvoltage level have gained much significance in recent years due to electricity market liberalisations and opportunities in reduced energy billings through personalised utilisation management for targeted business model. In consequence, modelling of passive customers’ electric power system are progressively transitioned into Prosumer-based settings where presidency for Transactive Energy (TE) system framework is favoured. It amplifies Prosumers’ commitments into annexing TE values during market participations and optimised energy management to earn larger rebates and incentives from TE programs. However, when dealing with mass Behind-The-Meter DER administrations, Utility foresee managerial challenges when dealing with distribution network analysis, planning, protection, and power quality security based on Prosumers’ flexibility in optimising their energy needs. This dissertation contributes prepositions into modelling Distributed Energy Resources Management System (DERMS) as an aggregator designed for Prosumer-centered cooperation, interoperating TE control and coordination as key parameters to market for both optimised energy trading and ancillary services in a Community setting. However, Prosumers are primarily driven to create a profitable business model when modelling their DERMS aggregator. Greedy-optimisation exploitations are negative concerns when decisions made resulted in detrimental-uncoordinated outcomes on Demand-Side Response (DSR) and capacity market engagements. This calls for policy decision makers to contract safe (i.e. cooperative yet competitive tendency) business models for Prosumers to maximise TE values while enhancing network’s power quality metrics and reliability performances. Firstly, digitalisation and nanostructuring of distribution network is suggested to identify Prosumer as a sole energy citizen while extending bilateral trading between Prosumer-to- Prosumer (PtP) with the involvements of other grid operators−TE system. Modelling of Nanogrid environment for DER integrations and establishment of local area network infrastructure for IoT security (i.e. personal computing solutions and data protection) are committed for communal engagements in a decentralise setting. Secondly, a multi-layered Distributed Control Framework (DCF) is proposed using Microsoft Azure cloud-edge platform that cascades energy actors into respective layers of TE control and coordination. Furthermore, modelling of flexi-edge computing architecture is proposed, comprising of Contract-Oriented Sensor-based Application Platform (COSAP) employing Multi-Agent System (MAS) to enhance data-sharing privacy and contract coalition agreements during PtP engagements. Lastly, the Agents of MAS are programmed with cooperative yet competitive intelligences attributed to Reinforcement Learning (RL) and Neural Networks (NN) algorithms to solve multimodal socio-economical and uncertainty problems that corresponded to Prosumers’ dynamic energy priorities within the TE framework. To verify the DERMS aggregator operations, three business models were proposed (i.e. greedy-profit margin, collegial-peak demand, reserved-standalone) to analyse comparative technical/physical and economic/social dimensions. Results showed that the proposed TE-valued DERMS aggregator provides participation versatility in the electricity market that enables competitive edginess when utilising Behind-The-Meter DERs in view of Prosumer’s asset scheduling, bidding strategy, and corroborative ancillary services. Performance metrics were evaluated on both domestic and industrial NG environments against IEEE Standard 2030.7-2017 & 2030.8-2018 compliances to ensure deployment practicability. Subsequently, proposed in-house protection system for DER installation serves as an add-on monitoring service which can be incorporated into existing Advance Distribution Management System (ADMS) for Distribution Service Operator (DSO) and field engineers use, ADMS aggregator. It provides early fault detections and isolation processes from allowing fault current to propagate upstream causing cascading power quality issues across the feeder line. In addition, ADMS aggregator also serves as islanding indicator that distinguishes Nanogrid’s islanding state from unintentional or intentional operations. Therefore, a Overcurrent Current Relay (OCR) is proposed using Fuzzy Logic (FL) algorithm to detect, profile, and provide decisional isolation processes using specified OCRs. Moreover, the proposed expert knowledge in FL is programmed to detect fault crises despite insufficient fault current level contributed by DER (i.e. solar PV system) which conventional OCR fails to trigger

An Information-Centric Communication Infrastructure for Real-Time State Estimation of Active Distribution Networks

© 2010-2012 IEEE.The evolution toward emerging active distribution networks (ADNs) can be realized via a real-time state estimation (RTSE) application facilitated by the use of phasor measurement units (PMUs). A critical challenge in deploying PMU-based RTSE applications at large scale is the lack of a scalable and flexible communication infrastructure for the timely (i.e., sub-second) delivery of the high volume of synchronized and continuous synchrophasor measurements. We address this challenge by introducing a communication platform called C-DAX based on the information-centric networking (ICN) concept. With a topic-based publish-subscribe engine that decouples data producers and consumers in time and space, C-DAX enables efficient synchrophasor measurement delivery, as well as flexible and scalable (re)configuration of PMU data communication for seamless full observability of power conditions in complex and dynamic scenarios. Based on the derived set of requirements for supporting PMU-based RTSE in ADNs, we design the ICN-based C-DAX communication platform, together with a joint optimized physical network resource provisioning strategy, in order to enable the agile PMU data communications in near real-time. In this paper, C-DAX is validated via a field trial implementation deployed over a sample feeder in a real-distribution network; it is also evaluated through simulation-based experiments using a large set of real medium voltage grid topologies currently operating live in The Netherlands. This is the first work that applies emerging communication paradigms, such as ICN, to smart grids while maintaining the required hard real-time data delivery as demonstrated through field trials at national scale. As such, it aims to become a blueprint for the application of ICN-based general purpose communication platforms to ADNs

Elimination of systematic faults and maintenance uncertainties on the City of Johannesburg's roads Intelligent Transport Systems

Road transport mobility continues to be a challenge to the City of Johannesburg (CoJ)’s economy in general. Traffic signals, their remote monitoring and control systems are the current implemented Intelligent Transport Systems (ITS), but daily systematic faults and maintenance uncertainties on such systems decrease the effectiveness of traffic engineers’ intersections optimization techniques. Inefficient electrical power supply to such ITS is a challenge, with conditional power cuts and fluctuations, uncertainties on traffic control system faults. Another factor leading to the problem is the communication channel which is using traditional modems which are not reliable. Reporting through both customer complaints and such unreliable remote monitoring systems makes maintenance to be ineffective. In this dissertation, the factors leading to the faults and uncertainties are considered. The proposed solution considers the important concerns of ITS, such as electrical power source performance optimization technique, road traffic control systems compatibility and communications systemsElectrical and Mining EngineeringM. Tech. (Electrical Engineering

Anomaly Detection in BACnet/IP managed Building Automation Systems

Building Automation Systems (BAS) are a collection of devices and software which manage the operation of building services. The BAS market is expected to be a $19.25 billion USD industry by 2023, as a core feature of both the Internet of Things and Smart City technologies. However, securing these systems from cyber security threats is an emerging research area. Since initial deployment, BAS have evolved from isolated standalone networks to heterogeneous, interconnected networks allowing external connectivity through the Internet. The most prominent BAS protocol is BACnet/IP, which is estimated to hold 54.6% of world market share. BACnet/IP security features are often not implemented in BAS deployments, leaving systems unprotected against known network threats. This research investigated methods of detecting anomalous network traffic in BACnet/IP managed BAS in an effort to combat threats posed to these systems. This research explored the threats facing BACnet/IP devices, through analysis of Internet accessible BACnet devices, vendor-defined device specifications, investigation of the BACnet specification, and known network attacks identified in the surrounding literature. The collected data were used to construct a threat matrix, which was applied to models of BACnet devices to evaluate potential exposure. Further, two potential unknown vulnerabilities were identified and explored using state modelling and device simulation. A simulation environment and attack framework were constructed to generate both normal and malicious network traffic to explore the application of machine learning algorithms to identify both known and unknown network anomalies. To identify network patterns between the generated normal and malicious network traffic, unsupervised clustering, graph analysis with an unsupervised community detection algorithm, and time series analysis were used. The explored methods identified distinguishable network patterns for frequency-based known network attacks when compared to normal network traffic. However, as stand-alone methods for anomaly detection, these methods were found insufficient. Subsequently, Artificial Neural Networks and Hidden Markov Models were explored and found capable of detecting known network attacks. Further, Hidden Markov Models were also capable of detecting unknown network attacks in the generated datasets. The classification accuracy of the Hidden Markov Models was evaluated using the Matthews Correlation Coefficient which accounts for imbalanced class sizes and assess both positive and negative classification ability for deriving its metric. The Hidden Markov Models were found capable of repeatedly detecting both known and unknown BACnet/IP attacks with True Positive Rates greater than 0.99 and Matthews Correlation Coefficients greater than 0.8 for five of six evaluated hosts. This research identified and evaluated a range of methods capable of identifying anomalies in simulated BACnet/IP network traffic. Further, this research found that Hidden Markov Models were accurate at classifying both known and unknown attacks in the evaluated BACnet/IP managed BAS network