Reliability analysis of cyber security in an electrical power system associated WAN

The constant failure in cyber security in power systems and substation automation that has crippled business activities that mostly depend on power to run their routine activities are caused by Lack of Adequate Security Measures, Human Error, Outdated Software and Hardware, Insufficient Training and Awareness, Insider Threats, Weak Access Control Mechanisms, Inadequate Network Segmentation, Failure to Patch Vulnerabilities, Complexity of the System, Third-Party Vendor Risks and Denial of Service (DoS) Vulnerabilities. This is surmounted by introducing improved cyber security in power systems and substation automation using intelligent based system. To achieve this, it is done in this procedure characterizing and establishing the causes of failure in cyber security in power systems and substation automation, designing a SIMULINK model for cyber security in power systems and substation automation, designing a rule base that will reduce the causes of failure in cyber security in power systems and substation automation,training ANN in the rule base for effective reduction of causes of failure in cyber security in power systems and substation automation, developing an algorithm for the process, designing a SIMULINK model for improving cyber security in power systems and substation automation using intelligent based system and validating and justifying the percentage of improvement in the reduction of causes of failure in cyber security in power systems and substation automation. The results obtained were the conventional Lack of Adequate Security Measures that cause failure in improving cyber security in power systems and substation automation was 25%. On the other hand, when an intelligent based system was incorporated into the system, it drastically reduce the cause failure in improving cyber security in power systems and substation automation to 21.53%, the conventional outdated software and hardware that cause failure in improving cyber security in power systems and substation automation was 15%. Meanwhile, when an intelligent based system was inculcated in the system, it became reduced to 12.92% thereby enhancing the performance of cyber security in power systems and substation automation by 2.08%, the conventional Weak Access Control Mechanisms that cause failure in improving cyber security in power systems and substation automation was 8%. However, when an intelligent based system was integrated in the system, it was reduced to 6.9% and the conventional Denial of Service (DoS) Vulnerabilities that cause failure in improving cyber security in power systems and substation automation was 2% while when an intelligent based system was incorporated in the system, it automatically reduced to 1.7%. Finally, with these results obtained, It vehemently shows that the percentage improvement in cyber security in power systems and substation automation was 0.3%.

Guest Editorial: Situational awareness of integrated energy systems

The aim of this study was to investigate the levels of extremely low frequency magnetic fields levels from previous studies to evaluate the magnetic fields from power systems in living environment Four different power system environments were studied: transmission and distribution lines, substations, distribution substations and indoor mounting in the buildings. Results were gathered together to find out the essential sources of magnetic fields in living environment. The magnetic fields from 400 kV and 110 kV transmission lines, substations and indoor distribution substations exceeded the immunity level, 3.8 μT, for electric appliances.

International Journal of Computational Engineering ScienceVol. 05, No. 01, pp. 81-89 (2004) No AccessEVOLUTIONARY PROGRAMMING BASED ECONOMIC DISPATCH WITH LINE FLOW CONSTRAINTSP. SOMASUNDARAM, K. KUPPUSAMY, and R. P. KUMUDINI DEVIP. SOMASUNDARAMSchool of Electrical and Electronics Engineering, Anna University, Chennai, Tamil Nadu 600 025, India Search for more papers by this author , K. KUPPUSAMYSchool of Electrical and Electronics Engineering, Anna University, Chennai, Tamil Nadu 600 025, India Search for more papers by this author , and R. P. KUMUDINI DEVISchool of Electrical and Electronics Engineering, Anna University, Chennai, Tamil Nadu 600 025, India Search for more papers by this author https://doi.org/10.1142/S1465876304002277Cited by:1 PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail AbstractThis paper presents an efficient, simple and new method for solving Economic Dispatch (ED) problem with line flow constraints through the application of Evolutionary Programming (EP). The controllable system quantities in the base-case state are optimized to minimize some defined objective function subject to the base-case operating constraints. A 10-bus system is taken for investigation. The ED results obtained using EP are compared with those obtained using quadratic programming. The investigations reveal that the proposed algorithm is relatively simple, reliable, efficient and suitable for on-line applications.Keywords:Power System OptimizationEconomic DispatchEvolutionary ProgrammingLine Flow Constraints References B. H. Chowdhury and S. Rahman, IEEE Transaction on power systems 5(4), 1248 (1990). Crossref, Google Scholar Nanda, L. Hari and M. L. Kothari, IEE Proceedings-C 141(1), 1 (1994). Google ScholarJ. Nandaet al., IEE Proceedings-C 139(1), 39 (1992). Google ScholarJ. Y. Fan and L. Zhang, IEEE Transactions on Power Systems 13(2), 320 (1998). Crossref, Google ScholarP. K. Hota, R. Chakrabarti and P. K. Chattopadhyay, Institute of Engineers (India) Journal-EL 81, 21 (2000). Google ScholarJ. Nanda and R. Badri Narayanan, Electrical Power and Energy Systems 24, 723 (2002). Crossref, Google Scholar D. B. Fogel , Evoluationary Computation: Toward a New Philosophy of Machine Intelligence ( IEEE Press , USA , 1995 ) . Google ScholarL. L. Lai and J. T. Ma, IEEE Transactions on Power Systems 12(1), 198 (1997). Crossref, Google ScholarH. T. Yang, P. C. Yang and C. L. Huang, IEEE Transactions on Power Systems 11(1), 112 (1996). Crossref, Google ScholarK. P. Wong and J. Yuryevich, IEEE Transactions on Power Systems 13(2), 301 (1998). Google ScholarT. Jayabarathi, G. Sadasivam and V. Ramachandran, Electric Power Systems Research 52, 261 (1999). Crossref, Google ScholarT. Jayabarathi and G. Sadasivam, European Transaction on Electrical Power 10(3), 167 (2000). Crossref, Google ScholarP. Attaviriyanupapet al., IEEE Transactions on Power Systems 17(2), 411 (2002). Crossref, Google Scholar FiguresReferencesRelatedDetailsCited By 1FDR PSO-based Transient Stability Constrained Optimal Power Flow Solution for Deregulated Power IndustryM. Anitha, S. Subramanian and R. Gnanadass28 Aug 2007 | Electric Power Components and Systems, Vol. 35, No. 11 Recommended Vol. 05, No. 01 Metrics History KeywordsPower System OptimizationEconomic DispatchEvolutionary ProgrammingLine Flow ConstraintsPDF download

Due to the increasing penetration of gas-fired units and power to gas facilities, the electrical power system and natural gas system are more and more bi-directionally coupled. To tackle the challenges on the optimal scheduling operation of an integrated gas and power systems (IGPS), this article focuses on developing a novel approach to build a continuous spatial-temporal optimal operation schedule model. In the light of different time constants of the electrical power and natural gas systems, the continuous spatial-temporal optimal operation schedule model of IGPS is formulated in function space. Additionally, Bernstein polynomials are used to reformulate the continuous spatial-temporal optimization problem of IGPS to mixed-integer linear programming. In the study cases, the simulation results of a simple integrated system and a combined IEEE 39-bus power system and Belgian natural gas network demonstrate the accuracy and effectiveness of the proposed model.

Nowadays the operation of electric power systems (EPS) requires that measures against cyber attacks be taken not only to protect the process equipment but also to upgrade the software involved in the power system control. State estimation (SE) is the most important function providing the EPS monitoring and control with reliable quality information. A state estimation tool acts as a barrier to the corruption of data on current operating conditions of the EPS in the control problem, including the data corruption caused by cyber attacks (CA) on data collection and processing systems. The paper presents a new decomposition approach to solve the SE problem under cyber attack: the calculation network is divided into areas that have a SCADA server and a Wide Area Measurement System (WAMS) concentrator at the center of every area. To detect the CA event and its localization, we propose to use a combination of a-priori and a-posteriori bad data detection (BDD).

For the research on crucial technologies of range-extended electric vehicle, the first problem to be solved is parameter matching and efficiency optimization for range-extended electric vehicle power and transmission system. Parameter matching and optimization of range-extended electric vehicle power and transmission system are multi-objective optimization problem. Evaluation and analysis of multi-objective optimization problem should be mutually independent and balanced. With the aim of guaranteeing vehicle’s comprehensive performance, a parameter matching and optimization method for range-extended electric vehicle power and transmission system is proposed in this paper. First, the house of quality model of range-extended electric vehicle is established to determine weight coefficient of vehicle performance indicator based on market requirements instead of experience. Based on co-simulation control model which is established in Matlab-Simulink and AVL-Cruise, 40 groups of orthogonal tests are performed, and the sensitivity of characteristic parameters is analyzed to explore the coupling law among vehicle performance indicators, so as to clarify the entry point for parameter matching and optimization. The simulation results show that the characteristic parameters not only have a significant influence but also have a coupling effect on the vehicle performance indicators. The analysis of variance shows that there is a limitation in optimal level combination of various factors only by range. Then, particle swarm optimization algorithm is selected to optimize the parameters of range-extended electric vehicle power and transmission system based on sensitivity analysis results obtained above. The study reveals that it is more efficient and reasonable to match the range-extended electric vehicle power and transmission system with a smaller battery capacity and a “medium-sized” auxiliary power unit which can achieve adequate dynamic performance, lower purchase cost, longer driving range and less energy consumption. Finally, a comparative simulation between the range-based analysis and particle swarm optimization-based analysis is conducted, the simulation results indicate that the optimized design parameters solution can significantly improve the technical indicators of the vehicle.

Electric Power. Electric Power Utilization. Transformers. Transmission Systems. Substations. Distribution Systems. Electric Power Utilization. Power System Analysis and Simulation. Power System Protection. Power System Transients. Power System Dynamics/Stability. Power System Operation/Control. Power System Planning (Reliability). Power Electronics. Power Quality.

R296-time wide area stability control of electric power system also increases the scale complexity and data transmission capacity of power communication network while realizing the interconnection of large interconnected power grids. The time delay caused by the randomness of signal transmission brings great difficulties to the analysis and control of the dynamic performance of the power system. In this paper, the problem of time delay and error code in communication network is analyzed, and the interaction between communication system and power system is analyzed by using the mathematical model of delay and error. Combined with the example of a provincial network and a particular power system, the effect of communication delay on the cascading failure of power and communication system is analyzed by OPNET simulation.

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.

The electric power system's seasonality would mitigate the problem of the energy volatility crisis. Seasonal identification is important in energy usage analysis to make a better an organization's energy performance. Identification of the seasonal component in a time series data is essential since it defines a fluctuation within an interval of time. This seasonal component can be identified as a periodic phenomenon. Signal processing models can be used in analyzing periodic data in the representation of sinusoidal function. Seasonal variations are an important factor influencing the behavior of an electric power and energy load. This paper introduces the application of deterministic functions in the Ornstein\textendash Uhlenbeck process as a sinusoidal signal processing model in identifying seasonal components represented in periodic terms. We conducted extensive experiments to validate the model on three datasets in electric power and energy systems namely electricity load, household electric power consumption, and power consumption of the three source stations. Further, it can be obtained that the periodic continuous-time-inhomogeneous signal of Ornstein\textendash Uhlenbeck model can be used to identify the seasonal term of the very short to medium horizon forecast of the electric power and energy system. Seasonal changes in energy consumption can be used in energy management in the scope of energy efficiency connected to renewable energy plans.

This paper constructs a risk assessment framework of power system for device-level information security, analyzes the typical protection configuration of power transformers, and takes transformer gas protection and differential protection as examples to put forward a method that analyzes the cyber security in electric power system, which targets transformer protection parameters. We estimate the risk of power system accounting for the cyber security of transformer through utilizing Monte Carlo method and two indexes, which are the loss of load probability and the expected demand not supplied. The proposed approach is tested with IEEE 9 bus system and IEEE 118 bus system.

Over the last few decades several innovative ideas have been explored in the energy storage areas, ranging in size, capacity, design complexity, and targeted applications. Some of them are designed for large scale power system applications, others for smallor medium-scale renewable energy or hybrid power systems, while the others are designed to perform short-term energy storage ride through for critical infrastructure (communication systems, hospitals, military facilities, etc.). Energy storage has become an enabling technology for renewable energy applications, grid integration and enhancing power quality and stability in the power transmission and distribution, having a great potential to improve power grid quality and stability and to provide an alternative to fossil fuel-based energy generation. The major constraints for renewable energy penetration are the availability, intermittency, and variability, which can be addressed through energy storage. The energy storage choice depends on specific usage requirements, often incorporating several energy storage systems in order to increase system reliability, capacity, and supply security. In the electric power system, the renewable energy promise lies in its potential to increase grid efficiency, reliability, or in optimizing power flows and supporting variable power supplies. The parameters used in comparisons of various energy storage technologies include efficiency, energy capacity and density, run time, costs, system's response time, lifetime in years and cycles, self-discharge, and maturity of each energy storage technology. The most common energy storage technologies include compressed air, pumped hydro, batteries, fuel cells, flywheels, and super-capacitors. The last four are suitable for the medium scale applications. The chapter discussed energy storage technologies and gives an up to date comparative summary of their performances. After completing this chapter, the readers are able to understand the role, importance, configurations and topologies of energy storage systems, operation principles, characteristics, performances, and operation of major energy storage systems used in power systems, buildings, and industrial facilities. Another benefit is that readers are able to understand the critical role and necessity of energy storage systems in power and renewable energy systems, the differences between large-, mediumand small-scale energy storage systems, and how a system is selected on specific applications based on system characteristics and performances. Major energy storage technologies discussed in this chapter are compressed air energy storage, pumped hydropower storage systems, batteries, flywheels, hydrogen energy storage, fuel cells, supercapacitors, and superconducting energy storage systems. Thermal energy storage systems are covered in detail in the next chapter. This chapter provides comprehensive reviews of the energy storage technologies and gives an up to date comparative summary of their performances, characteristics, and applications.

Recent moderate and strong California earthquakes demonstrate that parts of electric power systems are very vulnerable to damage. Most damage is due to the failure of porcelain elements in high-voltage substation equipment, although, performance is also strongly influenced by specific equipment designs and installation practices. Damage to various lifelines and structures has impaired the performance of some communication and control systems after earthquakes. This manual issues methods to improve the earthquake response of electric power systems. It deals with major power system elements - power generating stations, transmission and distribution lines, substations, system communications and control, and ancillary facilities and functions. A large portion of the document is devoted to high-voltage substations, as this is where most power system damage has been concentrated. The topics include: sources and effects of earthquakes; overview of earthquake performance of power systems and facilities; approach to improved earthquake performance; substations; transmission and distribution lines and support structures; power generating facilities; system control; communication systems; and ancillary facilities and functions.

An electric power system (EPS) with high-power-delivery and low-system-mass is required for wide body all electric aircraft (AEA). Cables are an essential component of this future EPS. At the cruising height of a wide-body aircraft the pressure is about 16.8 kPa. At that pressure, heat transfer to the ambient air by convection is strongly limited, so the distribution of temperature field across the aircraft cables is expected to be different from atmospheric pressure. The temperature field across the cable depends on the velocity field of the ambient air, which depends on the pressure and temperature. Also, to obtain the electric field of DC cables in the electric aircraft power system, the conductivity of the insulation, a function of temperature and electric field, should be calculated. In this paper, a 5 kV DC cable is studied at 16.8 kPa pressure to compare the cable's electric field and temperature field at low pressure to the atmospheric pressure. In our earlier research, we suggested novel EPS topologies for wide body AEA, and 5 kV DC is the voltage level that was taken into consideration. Moreover, the maximum permissible flowing current of the cable is investigated at the pressure of 16.8 kPa regarding the thermal limits of the cable. It is shown that at low pressures the temperature of the cable is highly increased compared to atmospheric pressure, so permissible current is lower than rated current.