Reconfiguration of power networks based on graph-theoretic algorithms

The intentional area partitioning and automated distribution system restoration are two important Smart Grid technologies to enhance the robustness of a power network and improve the system reliability. In this dissertation, the research work is focused on deriving and implementing efficient graph-theoretic algorithms to analyze and solve such two real-world problems in power systems as follows. In response to disturbances, a self-healing system reconfiguration that splits a power network into self-sufficient islands can stop the propagation of disturbances and avoid cascading events. An area partitioning algorithm that minimizes both real and reactive power imbalance between generation and load within islands is proposed. The proposed algorithm is a smart grid technology that applies a highly efficient multilevel multi-objective graph partitioning technique. The simulation results obtained on a 200- and a 22,000- bus test systems indicate that the proposed algorithm improves the voltage profile of an island after the system reconfiguration compared with the algorithm that only considers real power balance. In doing so, the algorithm maintains the computational efficiency. The distribution system restoration is aimed at restoring loads after a fault by altering the topological structure of the distribution network by changing open/closed states of some tie switches and sectionalizing switches in the distribution system. A graph-theoretic distribution system restoration strategy that maximizes the amount of load to be restored and minimizes the number of switching operations is developed. Spanning tree based algorithms are applied to find the candidate restoration strategies. Unbalanced three-phase power flow calculation is performed to guarantee that the proposed system topology meets all electrical and operational constraints. Simulation results obtained from realistic feeder models demonstrate the effectiveness of the proposed approach

Wide-Area Time-Synchronized Closed-Loop Control of Power Systems And Decentralized Active Distribution Networks

The rapidly expanding power system grid infrastructure and the need to reduce the occurrence of major blackouts and prevention or hardening of systems against cyber-attacks, have led to increased interest in the improved resilience of the electrical grid. Distributed and decentralized control have been widely applied to computer science research. However, for power system applications, the real-time application of decentralized and distributed control algorithms introduce several challenges. In this dissertation, new algorithms and methods for decentralized control, protection and energy management of Wide Area Monitoring, Protection and Control (WAMPAC) and the Active Distribution Network (ADN) are developed to improve the resiliency of the power system. To evaluate the findings of this dissertation, a laboratory-scale integrated Wide WAMPAC and ADN control platform was designed and implemented. The developed platform consists of phasor measurement units (PMU), intelligent electronic devices (IED) and programmable logic controllers (PLC). On top of the designed hardware control platform, a multi-agent cyber-physical interoperability viii framework was developed for real-time verification of the developed decentralized and distributed algorithms using local wireless and Internet-based cloud communication. A novel real-time multiagent system interoperability testbed was developed to enable utility independent private microgrids standardized interoperability framework and define behavioral models for expandability and plug-and-play operation. The state-of-theart power system multiagent framework is improved by providing specific attributes and a deliberative behavior modeling capability. The proposed multi-agent framework is validated in a laboratory based testbed involving developed intelligent electronic device prototypes and actual microgrid setups. Experimental results are demonstrated for both decentralized and distributed control approaches. A new adaptive real-time protection and remedial action scheme (RAS) method using agent-based distributed communication was developed for autonomous hybrid AC/DC microgrids to increase resiliency and continuous operability after fault conditions. Unlike the conventional consecutive time delay-based overcurrent protection schemes, the developed technique defines a selectivity mechanism considering the RAS of the microgrid after fault instant based on feeder characteristics and the location of the IEDs. The experimental results showed a significant improvement in terms of resiliency of microgrids through protection using agent-based distributed communication

A Survey of Smart Grid Systems on Electric Power Distribution Network and Its Impact on Reliability

This paper presents an excerpt of a more comprehensive survey of smart grid systems on electric power distribution networks and its impact on reliability. The survey was carried out as part of the feasibility study in Nigeria to determine its enhance-ability on the smartness of a conventional (traditional) distribution network. A smart grid is not a single technology but multiplex technologies in which the combination of different areas of engineering, communication and energy management systems are done. Consequently, a comprehensive review of various approaches and their impact on reliability of the network is presented. Furthermore, this paper introduces the smart grid technology and its features, reliability impacts and emerging issues and challenges that arise from the smart grid system applications. The benefit of this comprehensive survey is to provide a reference point for educational advancement on the recently published articles in the areas of smart grid systems on electric power distribution network as well as to stimulate further research interest

Self-Repairable Smart Grids Via Online Coordination of Smart Transformers

The introduction of active devices in Smart Grids, such as smart transformers, powered by intelligent software and networking capabilities, brings paramount opportunities for online automated control and regulation. However, online mitigation of disruptive events, such as cascading failures, is challenging. Local intelligence by itself cannot tackle such complex collective phenomena with domino effects. Collective intelligence coordinating rapid mitigation actions is required. This paper introduces analytical results from which two optimization strategies for self-repairable Smart Grids are derived. These strategies build a coordination mechanism for smart transformers that runs in three healing modes and performs collective decision-making of the phase angles in the lines of a transmission system to improve reliability under disruptive events, i.e., line failures causing cascading failures. Experimental evaluation using self-repairability envelopes in different case networks, ac power flows, and varying number of smart transformers confirms that the higher the number of smart transformers participating in the coordination, the higher the reliability and the capability of a network to self-repair

Boundary detection and enhancement strategy for power system bus bar stabilization:investigation under fault conditions for islanding operation

Distribution systems can form islands when faults occur. Each island represents a subsection with variable boundaries subject to the location of fault(s) in the system. A subsection with variable boundaries is referred to as an island in this paper. For operation in autonomous mode, it is imperative to detect the island configurations and stabilize these subsections. This paper presents a novel scheme for the detection of island boundaries and stabilizing the system during autonomous operation. In the first stage, a boundary detection method is proposed to detect the configuration of the island. In the second stage, a dynamic voltage sensitivity factor (DVSF) is proposed to assess the dynamic performance of the system. In the third stage, a wide area load shedding program is adopted based on DVSF to shed the load in weak bus-bars and stabilize the system. The proposed scheme is validated and tested on a generic 18-bus system using a combination of EMTDC/PSCAD and MATLAB software’s

Intentional Controlled Islanding in Wide Area Power Systems with Large Scale Renewable Power Generation to Prevent Blackout

Intentional controlled islanding is a solution to prevent blackouts following a large disturbance. This study focuses on determining island boundaries while maintaining the stability of formed islands and minimising load shedding. A new generator coherency identification framework based on the dynamic coupling of generators and Support Vector Clustering method is proposed to address this challenge. A Mixed Integer Linear Programming model is formulated to minimize power flow disruption and load shedding, and ensure the stability of islanding. The proposed algorithm was validated in 39-bus and 118-bus test systems