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Security is an important aspect of modern large-scale infrastructure networks. In one hand, there has been a significant improvement in the efficiency and reliability of systems due to enhanced interconnection of intelligent devices. On the other hand, this provides an opportunity for strategic adversaries to exploit the vulnerabilities of the network and cause damage. An example of an infrastructure system that is a part of our daily lives, and is vulnerable to adversarial attacks is the power network. Enhancing power grids' security, performance and resilience has been an important research topic in engineering. A significant penetration of information communication technologies (ICT) in modern power systems, renders this network vulnerable to cyber attacks from strategic malicious entities. According to The North American Electric Reliability Corporation (NERC), every power system should be operated such that failure of a single component should not leave the rest of components heavily loaded. This is called N-1 rule in power networks. However higher order contingency conditions are inevitable due to cooperated cyber attacks or natural calamities. As a result N-k contingency analysis is an important notion of security and resilience of power grids. The central challenge of higher order cyber-physical contingency analysis is the exponential blow-up of the attack surface due to a large number of attack vectors. This gives rise to computational challenges in devising efficient attack mitigation strategies. Due to these challenges, most of the tools are effective in analysing contingencies caused by failure of one or two components in the power network. Moreover, current tools for contingency analysis do not consider the strategic and smart attackers, and consider different attack profiles as faults in the system. However, smart attackers can exploit such naive defense strategies and cause a significant damage to the system. In this work, we focus on challenges due to higher order contingency conditions resulting from cyber-attacks. Our approach provides efficient tools to consider higher order cyber-physical contingency analysis in a game-theoretic frame work, which enables the operator to exploit the strategic actions of the attacker. Moreover, we provide computationally efficient algorithms to deal with higher order contingency conditions, and find the optimal defense strategies which cannot be exploited by the smart attacker. Our contributions in this thesis are as follows: \textbf{Cyber-Physical contingency analysis modeling using Game-Theoretic framework:} We develop a game-theoretic model in which different actions of the attacker and the defender lead to different contingency conditions. We formulate the
10SCALE: A hybrid MPI and multithreading based work stealing approach for massive contingency analysis in power systems
SCALE: A hybrid MPI and multithreading based work stealing approach for massive contingency analysis in power systems
2Contingency Analysis and Ranking of Kurdistan Region Power System Using Voltage Performance Index
In this paper, analysis and ranking of single contingency due to the outage of transmission lines for a large scale power system of the Kurdistan Region (KR) are presented. Power System Simulator software (PSS®E33) is used to simulate the Kurdistan Region power system network and perform the contingency analysis for single line outage. This analysis is essential in order to predict and evaluate the voltage stability in case of contingency occurrence to know the most severe case and plan for managing it. All possible transmission line outages of the network are tested individually. After each branch disconnects, load flow analysis are applied by using Newton Raphson method then all bus voltages are recorded, and compared with them before the contingency. Voltage performance index is calculated for all possible contingencies to rank them according to their severity and determine the most severe contingency which is corresponding to the highest value of performance index. Also, the contingencies which cause load loss and amount of this load are observed.
Read more4An expert system for contingency analysis in power systems
An expert system is developed to determine the steady state security of a power system after a contingency. Line, transformer and generator outages are considered. For any load in the system, overloaded branches are determined by comparing the system load to three load levels closest to the actual system load and using generator shift or branch outage distribution factors. The expert system, in conjunction with the DC load flow, is designed to identify the harmless and harmful contingencies as well as the overload branches. If a contingency cannot be determined as harmless or harmful then an AC load flow is suggested. Turbo-Prolog is used for symbolic manipulations and reasoning. The developed system is applied to a 12 bus power system. The results indicate that the expert system can be used in contingency screening as well as online operation to assist the operator. >
Read more1Distributed Secure Consensus Estimation for Power Systems Against False Data Injection Attacks
ABSTRACTAs a result of the rapid growth of distributed state estimation in modern power systems, power networks are facing increasingly serious security problems, thus requiring the advancement of defense techniques against cyber attacks. This paper is devoted to investigating distributed consensus state estimation with a defense mechanism against false data injection (FDI) attacks for power systems. By introducing a transformation matrix, the local subsystem model associated with the mixed remote terminal unit and phasor measurement unit measurements is constructed. Taking into account historical estimation information on state variables without being attacked, a defense mechanism constructed by secure historical estimation value is presented to protect the estimator against FDI attacks while maintaining accuracy in estimation. Then a distributed Kalman consensus filter (DKCF) is hosted to estimate the dynamic states of power systems under FDI attack protector. Considering scalability in large‐scale power systems, a suboptimal DKCF with the designed protector is developed. By means of the Lyapunov‐based approach, a sufficient condition is provided to ensure that the proposed estimator equipped with the defense mechanism is stable. Finally, the proposed distributed state estimation algorithms are validated on an IEEE benchmark 14‐bus power system.
Read more4Project based teaching of power electronics in undergraduate power system course
This paper presents how power electronics concepts are utilized to teach the topics in power system analysis course. Power system analysis is one of the multiple core courses on power engineering in almost all Electrical Engineering programs around the world. At Grand Valley State University, it is the only course in power engineering offered to Electrical Engineering students during a twelve-week summer semester in junior year. This course covers the fundamental concepts and their applications in all three sections of a complex power system namely generation, transmission, and distribution systems. In recent years, there has been a significant change in the role and application of power electronics in modern power systems. However, at GVSU power electronics is a graduate course and it is also taken by some senior students with deep interest in it as an elective. Hence, attempts have been made to get all Electrical Engineering students, not only the willing seniors, introduced to power electronics and its applications in all three sections of a power system. These include teaching some power system concepts with applications of power electronics and administering power converter based course projects. This paper presents the design of the course to implement power electronics concepts and the implementation of course projects in power system analysis course. The pedagogical challenge is to enhance students' learning of modern power system. This paper shows how it enhanced and changed students' perception about the scope of power engineering.
Read more14Voltage reactive security analysis in power systems with automatic secondary voltage control
The complete methodology for the steady-state voltage/reactive security analysis of power systems with automatic secondary voltage control is proposed. Both the decentralised and the co-ordinated control concepts are incorporated in a comprehensive procedure, consisting of three principal steps: contingency selection, contingency analysis and corrective control. The contingency selection stage is based on the extended load flow model and a new voltage/reactive performance index. The contingency analysis is performed next, by using either the extended load flow model (for decentralised control), or the optimum power flow model (for co-ordinated control). Finally, a simplified linear programming model for corrective resetting of pilot-bus set-point voltages is proposed with the aim to increase voltage security margins. The complete methodology was verified on the eastern part of high-voltage power system of former Yugoslavia.
Read more41Using GENI for experimental evaluation of Software Defined Networking in smart grids
Using GENI for experimental evaluation of Software Defined Networking in smart grids
11ST-AGNet: Dynamic power system state prediction with spatial–temporal attention graph-based network
ST-AGNet: Dynamic power system state prediction with spatial–temporal attention graph-based network
5Improvements on the line outage distribution factor for power system security analysis
Improvements on the line outage distribution factor for power system security analysis
1Inventory of Bulk Electric System Inverter-Based Resource Performance in North America
The North American Electric Reliability Corporation (NERC) has been working collaboratively with industry stakeholders, inverter manufacturers, and inverter controls and modeling experts to analyze grid disturbances involving bulk power system connected solar photovoltaic resources. These analyses have led to disturbance reports as well as Level 2 NERC Alerts for sharing recommended mitigating actions and mandatory data collection. This paper provides an overview of the findings from these NERC Alerts and a status of bulk power system inverter-based resource performance in North America.
Read more13Chapter Seven - Role of big data analytic and machine learning in power system contingency analysis
Chapter Seven - Role of big data analytic and machine learning in power system contingency analysis
8Evaluating the Effect of Dynamic and Static Modelling on Cascading Failure Analysis in Power Systems
As the main cause of large blackouts, understanding the complex interactions involved in cascading failure propagation is a critical area of ongoing research. The static model of cascading failures is a well-accepted method to investigate the cascading effects in power systems. However, as the power system evolves, dynamic behaviours become more variable, it is necessary to evaluate the validity of the assumptions in the static model. This paper compares and validates a conventional static model with a novel dynamic model capturing frequency dynamics. N-2 contingency analysis is used to trigger cascading events and the unserved demand and the number of branch outages are used as metrics. Analysis using the 39-bus, 200-bus and 2000-bus benchmark systems reveal similarities and differences between the static and dynamic models and reveal, for the first time, how these differences vary as network size grows. Sensitivity analysis on system dispatch capabilities provides some initial guidance to help reduce the differences between models and helps with understanding of the relative importance of cascading mechanisms.
Read more43Understanding Electric Power Systems
Preface to the Second Edition. Acknowledgments. CHAPTER 1 Benefits of Electric Power and a History of theElectric Power Industry. 1.1 Societal Benefits of Electricity. 1.2 Origin of the Industry. 1.3 Development of the National Electric Power Grid. 1.4 The Golden Age. 1.5 Global Warming Crisis and Concerns about CarbonEmissions. 1.6 Restructuring, Competition, and the Industry OwnershipStructure. CHAPTER 2 Electric Power System. 2.1 Customers. 2.2 Sources of the Electric Energy Generation. 2.3 Delivery System. CHAPTER 3 Basic Electric Power Concepts. 3.1 Electric Energy. 3.2 Concepts Relating to the Flow of Electricity. 3.3 Characteristics of AC Systems. 3.4 Ohm's Law for Alternating Current. 3.5 Power in Alternating Current Circuits. 3.6 Power Flow. 3.7 Stability. CHAPTER 4 Electric Energy Consumption. 4.1 End Uses for Electricity. 4.2 Customer Classes. 4.3 Rate Classes. 4.4 Demand and Energy. 4.5 System Load. 4.6 Reactive Load. 4.7 Losses and Unaccounted-For Energy in the DeliverySystem. 4.8 Forecasts. CHAPTER 5 Electric Power Generation and Concerns AboutGreenhouse Gases. 5.1 Generation's Role. 5.2 Types of Generation. 5.3 Thermal Conversion: Using Fuel as the Energy Resource. 5.4 Thermal Conversion: Nonfuel Heat Sources. 5.5 Mechanical Energy Conversion. 5.6 Renewable Technologies and Greenhouse Gas Emissions. 5.7 Characteristics of Generating Plants. 5.8 Capital Cost of Generation. 5.9 Generator Life Extension. 5.10 Technology of Generation. 5.11 System Needs and Evaluation of Intermittent Resources. CHAPTER 6 Technology of the Electric TransmissionSystem. 6.1 Components. 6.2 HVAC. 6.3 Substations. 6.4 HVDC. 6.5 Advantages of AC over DC Operation. 6.5 Knowledge Required of Transmission Systems. CHAPTER 7 Distribution. 7.1 Function of Distribution. 7.2 Primary Distribution Feeders. 7.3 Distribution Capacity. 7.4 Losses. 7.5 Distribution Facility Ratings. 7.6 Metering. 7.7 Control of Distribution Voltages. 7.8 Distribution System Reliability. 7.10 Quality of Service. 7.11 Design of Distribution Systems. 7.12 Distributed Generation. 7.13 Operation of Distribution Systems. 7.14 Smart Grids and Microgrids. CHAPTER 8 Energy Storage and Other New Technologies. 8.1 Energy Storage. 8.2 Energy Storage Concepts and Technologies. 8.3 Smart Grid. 8.4 New Nuclear Plant Designs. 8.5 Carbon Sequestration and Clean Coal Technologies. 8.6 Superconductors. CHAPTER 9 Reliability. 9.1 Causes of Outages. 9.2 Costs of Power Outages. 9.3 Ways to Measure Reliability. 9.4 Planning and Operating a Reliable and Adequate PowerSystem. 9.5 Summary. CHAPTER 10 Physical Network: North American ElectricReliability Corporation (NERC) and Its Standards. 10.1 NERC as Electric Reliability Organization. 10.2 NERC Standards. 10.3 Development of Standards. CHAPTER 11 Physical Network: Operation of the ElectricBulk Power. 11.1 Balancing Authorities. 11.2 Reliability Coordinators. 11.3 Transmission Operators. 11.4 Voltage and Reactive Control. 11.5 Emergencies. 11.6 Information Exchange. CHAPTER 12 Physical Network: Planning of the ElectricBulk Power System. 12.1 Planning Standards. 12.2 Generation Planning. 12.3 Transmission Planning. 12.4 Least Cost Planning. 12.5 New Planning Environment. CHAPTER 13 Regulatory Network: Legislation. 13.1 Pricing and Regulation. 13.2 Federal Legislation. 13.3 Federal Utility Holding Company Act (PUHCA). 13.4 Federal Power Act. 13.5 Other 1930 Federal Laws. 13.6 Department of Energy Organization Act. 13.7 Public Utility Regulatory Policies Act (PURPA). 13.8 Energy Policy Act of 1992 (EPAct02). 13.9 Energy Policy Act of 2005 (EPAct05). 13.10 Energy Independence and Security Act of 2007. 13.11 Environmental Laws. 13.12 2009 American Recovery and Reinvestment Act. CHAPTER 14 Regulatory Network: Regulators. 14.1 Regulators. CHAPTER 15 Information, Communication, and ControlNetwork and Security. 15.1 Smart Grid. 15.2 Financial and Business Operations. 15.3 System Operations. 15.4 Distribution Operations. 15.5 Cyber Security. 15.6 Nuclear Plant Security. CHAPTER 16 Fuel and Energy Network. 16.1 Resource Procurement. 16.2 Fuel Transportation. 16.3 Fuel Diversity. 16.4 Fossil Fuels Used. 16.5 Renewable Energy. 16.6 Fuel Purchasing. 16.7 Emission Rights. CHAPTER 17 Business Network: Market Participants. 17.1 Investment and Cost Recovery. 17.2 Changing Industry Structure. 17.3 New Structures. 17.4 New Corporate Ownership. CHAPTER 18 Money Network: Wholesale Markets. 18.1 Energy Markets. 18.2 Transmission. 18.3 Customer Late Issues. 18.4 Market versus Operational Control. 18.5 Market Power Issues. 18.6 Future. CHAPTER 19 Professional and IndustryOrganizations. 19.1 Professional Organizations. 19.2 Industry Associations. 19.3 Public Interest Groups. 19.4 Research Organizations. Index.
Read moreSimulation Case Studies on an Advanced Sensitivity Analysis for New Extended Bus Types in the Modern Power Systems
A simulation analysis in power system planning and operations considers the sensitivity of power flow, stability, and security of the system in response to changes in system states. Traditionally, these analyses have the power system defined by three bus types; a generator bus (<tex>$PQ$</tex>), a load bus (<tex>$PV$</tex>) and the reference bus (<tex>$V\theta$</tex>). As the contribution from variable renewable energy sources (such as wind and solar) increase along with proliferation of new electronic control devices, these traditional bus types are no longer sufficient. Reliance on the traditional bus types for sensitivity analysis may not guarantee simulation accuracy and may lead to poor decisions, thereby jeopardizing system reliability and stability. To address this issue, this paper proposes new bus types (such as <tex>$PQV, Q\theta, QV, PQV\theta$</tex>) that arise in modern power systems, and determines the corresponding parametric sensitivity calculation formulas based equations of the new bus types. The updated sensitivity analysis is implemented on two simulation case studies; the IEEE 14-bus test system, and on an example of power system with 262 buses. Results show that the use of the traditional bus types leads to significant error, whereas the use of extended bus types produces more accurate results.
Read more12A robustness-enhanced frequency regulation scheme for power system against multiple cyber and physical emergency events
A robustness-enhanced frequency regulation scheme for power system against multiple cyber and physical emergency events
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