Complex Network Framework Based Comparative Study of Power Grid Centrality Measures

New closeness and betweenness based centrality measures have been evaluated in this paper. Power grid is modeled as a directed graph. The graph is analyzed in terms of complex network theory to identify influential nodes which control power flow pattern throughout the whole grid and as a result can create cascade if removed unintentionally or targetedly. Various measures of impacts have been analyzed to show that power grid has scale-free network characteristics, i.e., it is very much vulnerable to targeted node removal. Measures of impacts include characteristic path length, connectivity loss and blackout size. Rank similarity analysis have been carried out to show that nominal condition of power system gives critical nodes which remain critical with changes in system operating conditions as well.DOI:http://dx.doi.org/10.11591/ijece.v3i4.331

Efficient Database Generation for Data-driven Security Assessment of Power Systems

Power system security assessment methods require large datasets of operating points to train or test their performance. As historical data often contain limited number of abnormal situations, simulation data are necessary to accurately determine the security boundary. Generating such a database is an extremely demanding task, which becomes intractable even for small system sizes. This paper proposes a modular and highly scalable algorithm for computationally efficient database generation. Using convex relaxation techniques and complex network theory, we discard large infeasible regions and drastically reduce the search space. We explore the remaining space by a highly parallelizable algorithm and substantially decrease computation time. Our method accommodates numerous definitions of power system security. Here we focus on the combination of N-k security and small-signal stability. Demonstrating our algorithm on IEEE 14-bus and NESTA 162-bus systems, we show how it outperforms existing approaches requiring less than 10% of the time other methods require.Comment: Database publicly available at: https://github.com/johnnyDEDK/OPs_Nesta162Bus - Paper accepted for publication at IEEE Transactions on Power System

Node Type Distribution and Its Impacts on Performance of Power Grids

The theory of complex networks has been studied extensively since its inception. However, until now, the impact of the node-type distributions is related to network topology and cannot be evaluated independently. In this paper, a network structure is modeled via an adjacency matrix (network topology) and a set of node type distribution vectors. Three specific issues that need to be considered for node type distributions in smart grid testing and planning are summarized in this paper. First, a set of metrics are proposed and defined to evaluate the impact of node-type distributions on network performance independently. Second, another metric named the generation distribution factor is proposed to evaluate the distribution of generation buses resulting from the specific function and purpose of power grids and by considering the distribution of load buses as given conditions. Third, another metric, i.e., the power supply redundancy metric based on entropy, is proposed to evaluate the inequality of load in power supply. Finally, a discrimination factor is defined to ensure the overall evaluation and comparison of different networks is made for this inequality. All proposed metrics can be applied to the IEEE-30, IEEE-118, IEEE-300 bus systems, as well as Italian power grid components. The simulation results indicate that the IEEE-118 system has the best node type distribution and minimum discrimination; the Italian system has the worst node-type distribution and most serious discrimination of load power supply

Applications of Complex Network Analysis in Electric Power Systems

This paper provides a review of the research conducted on complex network analysis (CNA) in electric power systems. Moreover, a new approach is presented to find optimal locations for microgrids (MGs) in electric distribution systems (EDS) utilizing complex network analysis. The optimal placement in this paper points to the location that will result in enhanced grid resilience, reduced power losses and line loading, better voltage stability, and a supply to critical loads during a blackout. The criteria used to point out the optimal placement of the MGs were predicated on the centrality analysis selected from the complex network theory, the center of mass (COM) concept from physics, and the recently developed controlled delivery grid (CDG) model. An IEEE 30 bus network was utilized as a case study. Results using MATLAB (MathWorks, Inc., Nattick, MA, USA) and PowerWorld (PowerWorld Corporation, Champaign, IL, USA) demonstrate the usefulness of the proposed approach for MGs placement

A framework for assessing robustness of water networks and computational evaluation of resilience.

Arid regions tend to take careful measures to ensure water supplies are secured to consumers, to help provide the basis for further development. Water distribution network is the most expensive part of the water supply infrastructure and it must maintain performance during unexpected incidents. Many aspects of performance have previously been discussed separately, including reliability, vulnerability, flexibility and resilience. This study aimed to develop a framework to bring together these aspects as found in the literature and industry practice, and bridge the gap between them. Semi-structured interviews with water industry experts were used to examine the presence and understanding of robustness factors. Thematic analysis was applied to investigate these and inform a conceptual framework including the component and topological levels. Robustness was described by incorporating network reliability and resiliency. The research focused on resiliency as a network-level concept derived from flexibility and vulnerability. To utilise this new framework, the study explored graph theory to formulate metrics for flexibility and vulnerability that combine network topology and hydraulics. The flexibility metric combines hydraulic edge betweenness centrality, representing hydraulic connectivity, and hydraulic edge load, measuring utilised capacity. Vulnerability captures the impact of failures on the ability of the network to supply consumers, and their sensitivity to disruptions, by utilising node characteristics, such as demand, population and alternative supplies. These measures together cover both edge (pipe) centric and node (demand) centric perspectives. The resiliency assessment was applied to several literature benchmark networks prior to using a real case network. The results show the benefits of combining hydraulics with topology in robustness analysis. The assessment helps to identify components or sections of importance for future expansion plans or maintenance purposes. The study provides a novel viewpoint overarching the gap between literature and practice, incorporating different critical factors for robust performance

A maximum-flow-based complex network approach for power system vulnerability analysis

This paper proposes a maximum-flow-based complex network approach for the analysis of the vulnerability of power systems. A new centrality index is proposed, taking into consideration the maximum flow from the source (generator) nodes to the sink (load) nodes, for assessing the network. The Max-Flow Min-Cut Theorem, also known as Ford-Fulkerson Theorem, is used for evaluating the capacity of links. The proposed methodology is then used to identify vulnerable lines of the IEEE 118 bus system and its effectiveness is demonstrated through simulation studie

Vulnerability analysis and fault location in power systems using complex network theory

This thesis is dedicated to the study of Complex Network Theory with applications in power systems. The focus of the study is to analyze and solve power system problems by treating and modelling it as a network and applying the concepts from this theory. The work can be broadly classified into two parts: vulnerability analysis and fault location. Two different centrality indices are proposed to analyze power system vulnerabilities. The first method utilizes shortest path betweenness approach and a centrality index is defined based on the power flow equation using reactance as the measure of portion of power flowing through any line. A few limitations of this method are improved in the second, where power system is considered to be capacitated and directed in any steady state and another centrality index based on the maximum flow algorithm is defined using admittance as weight to model the network. Based on Kirchhoff’s law, admittances are considered to be a measure of proportion and ease with which current or power flows through any line. Further, using maximum flow algorithm, lines are marked as important based on the fraction of total flow they carry between nodes. It is demonstrated by simulations on the IEEE 39 and IEEE 118 bus systems that failure of transmission lines identified as critical or vulnerable has a major impact on the efficiency and performance of the network, unlike the failure of random connections which have little or no effect. In another study, cascading failures in power systems are assessed using line outage distribution factor and power transfer distribution factor together with Complex Network Theory. This work identifies the group of transmission lines which may be affected if any one line fails and investigates the sequence and depth to which the failure may propagate. Using the IEEE 14 bus system, it explains how the failure of one line can sometimes lead to a cascading failure and eventual blackout. The next part of the research applies Complex Network Theory together with travelling wave based fault location techniques to locate faults in power systems. This study is further divided into two parts. The first part analyzes a power generation network, where the double-ended travelling wave theory is used to calculate the time stamp of fault transients at each node and then network topology of the system is used to first identify the faulty link and then calculate the fault distance. Finally, the single-ended travelling wave method is used to locate faults in power distribution systems. Due to the radial structure of transmission lines in such systems, more than one fault candidates may appear in the calculations, out of which only one is real. This ambiguity is resolved by taking advantage of the spanning tree like structure and using depth first search to identify the actual fault. The results reveal that the proposed methodologies are capable of locating single faults in power systems with reasonable accuracy

Smart Energy Management for Smart Grids

This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book

Mitigation of cascade failures in complex networks: theory and application

Complex networks such as transportation networks, the Internet, and electrical power grids are fundamental parts of modern life, and their robustness under any attack or fault has always been a concern. Failure and intentional removal of components in complex networks might affect the flow of information and change balance of flows in the network. This phenomenon may require load redistribution all over the network. Component overloaded can act as a trigger for a chain of overload failures. This overload, could, for example, increase the amount of information a router must transmit and ultimately make internet congestion. One of the major applications of complex network theory is to study power systems. Power systems are the most complex human-made infrastructures, and almost every individual's life is dependent on electrical energy and resilient functioning of power systems. Recently, there have been many reports about massive power outages leaving vast areas without power that sometimes takes a few days to have the power back. One of the most critical areas in the power system is the root cause analysis of such catastrophes and trying to resolve them. From an electrical engineering point of view, these power outages occur following an initial failure due to problems, such as generators tripping, transformers overheating, faulty power generation units, damage to the transmission system, substations or distribution systems, or overloading of the power system. A faulty protection relay or malicious attack to control centres can also trigger it. In any of these cases, the failed component will be out of service immediately and to keep the robust power delivery to all customers, their loads should be redistributed across the power system, and henceforth some of them might become overloaded as well, and accordingly get out of service. This chain of failures can be propagated all over the system and lead to a catastrophic blackout. This thesis conducts a full study on how to mitigate cascade failures in complex networks. First, cascade depth is applied to quantify nodes criticality for cascade failures. Then, a wide range of node centrality parameters is considered to find out the relationship between the node vitality and these centralities. To discover the structure of cascade propagation in complex networks, the edge geodesic distance is considered for computing the structural distance between two arbitrary edges in the network. Then, starting with the single edge removal events, the route that cascade tends to spread is studied. In the next step, the impact of two or three concurrent edge removals on the way the cascade spreads are examined. Besides, the power system vulnerability is studied using the maximum flow algorithm based on Ford-Fulkerson method and critical capacity parameters are identified. A synthetic model with the same properties as a real power system is generated and examined. For a power line, to be overloaded, a new method is developed to overpass across the network and shortlist the busbars for load reduction. Next, a novel sensitivity method is formulated based on AC load flow analysis to rank the loads according to their effect on the lines power flow

ICT-Enabled Control and Energy Management of Community Microgrids for Resilient Smart Grid Operation

Our research has focused on developing novel controllers and algorithms to enhance the resilience of the power grid and increase its readiness level against major disturbances. The U.S. power grid currently encounters two main challenges: (1) the massive and extended blackouts caused by natural disasters, such as hurricane Sandy. These blackouts have raised a national call to explore innovative approaches for enhanced grid resiliency. Scrutinizing how previous blackouts initiated and propagated throughout the power grid, the major reasons are lack of situational awareness, lack of real-time monitoring and control, underdeveloped controllers at both the transmission and distribution levels, and lack of preparation for major emergencies; and (2) the projected high penetration of renewable energy resources (RES) into the electric grid, which is mainly driven by federal and state regulatory actions to reduce GHG emissions from new and existing power plants, and to encourage Non Wire Solutions (NWS). RESs are intermittent by nature imposing a challenge to forecast load and maintain generation/demand balance. The conceived vision of the smart grid is a cyber-physical system that amalgamates high processing power and increased dependence on communication networks to enable real-time monitoring and control. This will allow for, among other objectives, the realization of increased resilience and self-healing capabilities. This vision entails a hierarchical control architecture in which a myriad of microgrids, each locally controlled at the prosumer level, coordinates within the distribution level with their correspondent distribution system operator (i.e. area controllers). The various area controllers are managed by a Wide Area Monitoring, Protection and Control operator. The smart grid has been devised to address the grid main challenges; however, some technical barriers are yet to be overcome. These barriers include the need to develop new control techniques and algorithms that enable flexible transitions between operational modes of a single controller, and effective coordination between hierarchical control layers. In addition, there is a need to understand the reliability impacts of increased dependence on communication networks. In an attempt to tackle the aforementioned barriers, in my work, novel controllers to manage the prosumer and distribution networks were developed and analyzed. Specifically, the following has been accomplished at the prosumer level, we: 1) designed and implemented a DC MG testbed with minimal off-the-shelf components to enable testing new control techniques with significant flexibility and reconfiguration capability; 2) developed a communication-based hybrid state/event driven control scheme that aims at reducing the communication load and complexity, processor computations, and consequently system cost while maintaining resilient autonomous operation during all possible scenarios including major emergencies; and 3) analyzed the effect of communication latency on the performance of centralized ICT-based DC microgrids, and developed mathematical models to describe the behavior of microgrids during latency. In addition, we proposed a practical solution to mitigate severe impacts of latency. At the distribution level, we: 1) developed a model for an IEEE distribution test network with multiple MGs integrated[AM1] [PL2] ; 2) developed a control scheme to manage community MGs to mitigate RES intermittency and enhance the grid resiliency, deferring the need for infrastructure upgrade; and 3) investigated the optimal placement and operation of community MGs in distribution networks using complex network analysis, to increase distribution networks resilience. At the transmission level (T.L), New York State T.L was modeled. A case study was conducted on Long Island City to study the impact of high penetration of renewable energy resources on the grid resilience in the transmission level. These research accomplishments should pave the way and help facilitate a smooth transition towards the future smart grid.