Overview of Network Security Defense Technologies for Power Systems

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.

Guest Editorial: Situational awareness of integrated energy systems

With the development and maturity of electrical power system, the reliability and openness of smart grid iot system have been gradually solved and the application of iot in electrical power system has become a reality. By analyzing the influence of the introduction of electrical power system heterogeneous network on the real-time performance of the power system and studying the topological structure of electrical power system heterogeneous network, the network delay under the electrical power system heterogeneous network structure can be reduced, which has important guiding significance for the application of heterogeneous network in actual electrical power system. To this end, this paper not only presents a hierarchical integrated power system internet of things heterogeneous network architecture, but also proposes a protocol conversion method and combined with electrical power system heterogeneous network real-time analysis, from two aspects of network protocol and the driving mode of the node to electrical power system heterogeneous network wireless network nodes, the backbone network of wired/wireless heterogeneous network gateway and puts forward a method to improve real-time middleware OPC agreement.

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

In recent years, machine learning (ML) tools have gained tremendous momentum and received wide-spread attention in different segments of modern-day life. As part of digital transformation, the power system industry is one of the pioneers in adopting such attractive and efficient tools for various applications. Apparently, a nonthreatening, but slow-burning issue of the electric power systems is the low-frequency oscillations (LFO), which, if not dealt with appropriately and on time, could result in complete network failure. This paper addresses the role of a prominent ML family member, particle swarm optimization (PSO) tuned adaptive neuro-fuzzy inference system (ANFIS) for real-time enhancement of LFO damping in electric power system networks. It adopts and models two power system networks where in the first network, the synchronous machine is equipped with only a power system stabilizer (PSS), and in the other, the PSS of the synchronous machine is coordinated with the unified power flow controller (UPFC), a second-generation flexible alternating current transmission system (FACTS) device. Then, it develops the proposed ML approach to enhance LFO damping for both adopted networks based on the customary practices of statistical judgment. The performance measuring metrics of power system stability, including the minimum damping ratio (MDR), eigenvalue, and time-domain simulation, were used to analyze the developed approach. Moreover, the paper presents a comparative analysis and discussion with the referenced works’ achieved results to conclude the proposed PSO-ANFIS technique’s ability to enhance power system stability in real-time by damping out the unwanted LFO.

The new power system has a new operation mode of "the source follows the load, the load follows the network, and the source loads interact". With the continuous excavation of flexible regulation resources, new third-party entities such as virtual power plants or load integrators need to consider implementing differentiated network security protection requirements to ensure their fair access to business. At the same time, with the clarity of the regulation level of the new power system and the continuous participation of various entities in the construction, the company's network security protection boundary will no longer be "horizontal and vertical", but will become more uneven, with more types of interfaces and interfaces. It is necessary to refine the boundary protection measures according to different interaction needs. The new regulatory subject on the demand side of the new power system involves the privacy information of a large number of users. Data flow and sharing, cross access and collaborative analysis among the subjects have security problems such as unauthorized access and privacy leakage. This paper focuses on the scenario based intelligent desensitization and dynamic access control technology for power distribution and distributed new energy data resources, and combs various factors involved in the data access process, On the basis of obtaining the data access authority, the dynamic correlation analysis of the three elements of user role and access authority, sensitive data level, power allocation and distributed new energy business scenario is integrated, and finally the appropriate desensitization method is selected from the desensitization algorithm library, and finally the appropriate desensitization method is selected from the desensitization algorithm library to ensure the security protection capability of the new distribution network under the flexible, open and interactive energy scenario, Effectively respond to new major network security risks.

Nowadays, due to the increase in the demand for electrical energy and the development of technology, the electrical devices have a more complex structure. This situation has increased the importance of concept of the power quality in the electrical power system. This paper presents a deep learning-based system to recognize the power quality disturbances (PQDs) in the solar photovoltaic (SPV) plant integrated with power system networks. The PQDs are analyzed using continuous wavelet transform (CWT) and image files are obtained from scalograms of CWT. Then, these image files are used to recognize PQDs with the help of a hybrid deep learning approach based on convolutional neural network (CNN), neighbor component analysis (NCA), and support vector machine (SVM). In this hybrid deep learning approach, the image files are given as input to AlexNet and GoogLeNet. The NCA is applied to the features obtained from the last dropout layer of each architecture. The distinctive features obtained from the NCA process are classified using the SVM algorithm. In order to evaluate the proposed approach, PQD data are obtained from a modified IEEE 13-bus test system including the SPV system. Several analyses and comparisons are carried out to verify the success of the proposed approach. It has been found that the proposed hybrid deep learning approach has the ability to accurately recognize the PQDs even if the SPV plant integrated power system has a negative effect on power quality.

As the power system undergoes continuous digitization and networking, the associated network security challenges have become increasingly prominent. Addressing these issues, the zero trust framework emerges as a cutting-edge security concept that underscores sustained vigilance toward users, devices, and applications within the network environment. Its core principle involves minimizing the scope of trust granted to the smallest possible extent. This study delves into the application of the zero trust framework in crafting the architecture of power system networks, with the primary objective of enhancing network security and thwarting potential threats. The article commences by scrutinizing the network security requirements of internet applications and subsequently proposes a zero trust architecture as a security solution. The construction of a zero trust-based smart grid security protection architecture follows, encompassing elements such as terminal trusted perception agents, multi-source data aggregation platforms, intelligent trust evaluation platforms, dynamic access control platforms, and trusted access agents. Finally, the efficacy of the zero trust framework in power system network architecture is validated through case studies and simulation experiments. The research findings highlight a significant enhancement in the network security of the power system with the incorporation of the zero trust framework. This, in turn, establishes an effective security mechanism conducive to the digital transformation of future power systems. In summary, the study contributes a novel security approach and technical solution for the design of power system network architecture, offering valuable insights and reference for the development of the power system network security field.

Intelligent Monitoring and Control Architecture for Future Electrical Power Systems

This paper analyzes Internet sites often present invasion of widespread computer virus, network security has become very prominent, but mainly include infrastructure security, border security, network, network connection security, management of safety in four areas. Good solution to network security, we must start from the four areas. The current firewall technology, vulnerability scanning, intrusion detection, virtual private network technology, encryption and decryption technology, viruses are anti-kill technology to solve a certain level of security technology. As an overall network security protection, a technology is difficult to do alone, must combine a variety of security technologies complement each other. The only way to the need to protect the network put up a barrier, in the normal network access, while security is well ensured accordingly.

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.

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.

Flexible AC Transmission System (FACTS) controllers are advanced power electronic devices employed in electrical power systems to enhance system stability, reliability, and power transfer capabilities. These controllers enable dynamic and flexible control of various transmission parameters such as voltage, current, impedance, and phase angle, thereby improving the overall power system performance. FACTS devices are broadly classified into series, shunt, series- series, and series-shunt configurations, each designed to manage reactive power and regulate voltage either by injecting voltage in series or current in shunt with the transmission line. Well-known FACTS devices include Static Var Compensators (SVC), Static Synchronous Compensators (STATCOM), Thyristor Controlled Series Capacitors (TCSC), Static Synchronous Series Compensators (SSSC), and Unified Power Flow Controllers (UPFC), each serving specific roles in power flow control, voltage regulation, and transient stability enhancement. The integration of these controllers provides significant benefits such as increased transmission line capacity, improved voltage stability, minimized transmission losses, and damping of power system oscillations. They are capable of rapid response during transient disturbances, effectively mitigating voltage collapses and enhancing system resilience against faults and contingencies. FACTS controllers not only improve steady-state operational parameters but also address dynamic stability and transient conditions, enabling power systems to operate closer to their stability limits while maintaining security. Their deployment helps avoid costly infrastructural expansions by optimizing existing transmission assets, which is critical given environmental and economic constraints. Recent advances in semiconductor technologies and control algorithms have made FACTS devices more reliable, efficient, and adaptable to modern grids, including renewable integration and deregulated power markets. In summary, FACTS controllers play a vital role in modern power systems by providing flexible, efficient, and reliable solutions for power flow management, voltage control, and system stability enhancement, thereby supporting the evolving demands of today's complex electrical networks.

Electric power system is one of the largest and complex infrastructures made by mankind during the last century. The total investment associated with it in trillions of dollars. As it is a very expensive, large and complex physical system, secure network operation without having any system wide instability issue and catastrophic consequences is sought. As a result power system educators and researchers are constantly scrutinizing power system with changing scenarios and coming up with the new solutions to keep the most important infrastructure intact in order to make the economy and society sustainable. It is tough, but not impossible, and expensive to build physical test power systems to perform various researches. Hence, the test power systems models have been playing a key role for better understanding, development, and deployment of new solutions in power system problems. There have been many test systems with varying complexities and sizes used all around the world. However, there is no common platform where the most of these test systems are documented so that the educators and researchers can chose an appropriate test system suitable for their studies. The paper presents a collection of commonly used test systems for various dynamic stability studies.

Operation of coupled power-gas networks with hydrogen refueling stations, responsive demands and storage systems: A novel stochastic framework