Western System Coordinating Council Research Articles

Online Monitoring System of Electromechanical Transient Simulation Data of Distribution Network Based on Edge Computing

The current distribution network is developing toward the direction of information and intelligent distribution Internet of Things (IoT). In order to explore the online monitoring system for transient electromechanical simulation of distribution networks, this paper is based on the equivalent model of generator sets. Firstly, it describes the relevant theoretical knowledge of edge computing, designs the distribution IoT based on edge computing, and briefly introduces its network architecture. Secondly, based on the discrete-time domain equivalent model of generators, the electromechanical transient simulation distribution network is constructed by introducing the machine network division of the power network. Finally, the Western System Coordinating Council (WSCC)-3 units and 9 nodes are taken as an example, and simulation experiments are conducted under two fault simulation conditions to verify the effectiveness of the simulation model. The results show that under the two fault simulation conditions, the results of equivalent model simulation of generator terminal voltage and relative power angle change are like those of the Power System Analysis Software Package (PSASP). The changing trend of the two is similar and stable. After the PSASP results are stabilized at a value, the simulation results fluctuate extremely up and down the value. For example, under fault condition 1, the changing trend of the relative power angle of the No. 2 generator is first fluctuating and then becomes stable. After violent fluctuation, the relative power angle tends to be stable from about 20s to -12.35°. The result of PSASP software is stable at -12.35°. The transient electromechanical simulation of the generator equivalent model can provide some ideas for the online monitoring system of the distribution network.

Fault classification scheme for TCSC compensated transmission line using MODWPT-BTEC

This article proposes a fault classification algorithm for a Thyristor Controlled Series Compensated (TCSC) long transmission line. Such type of line imposes issues related to reactance modulation, voltage inversion, current inversion and TCSC control action. This scheme utilizes ½ cycle post-fault current signal, which is then processed by maximum overlap discrete wavelet packet transform (MODWPT), and energy feature is calculated. The proposed scheme has been validated on a modified Western System Coordinating Council (WSCC) 9 bus system with TCSC. Also, the scheme is certified for wind farm integration in grid connected mode. The bagged tree ensemble classifier outperformed various stable and ensemble combinations, including the decision tree, linear discriminative analysis, support vector machine, k-nearest neighbor, boosted/trees ensemble, and subspace/discriminant ensemble. The line with TCSC compensation is modeled using PSCAD/EMTDC software. The proposed scheme accurately classifies faults in all tested scenarios with 100% accuracy. The outcomes of the suggested algorithm along with a comparative study confirm the accuracy and fast protection measures for TCSC-compensated line.

Spiral-refraction mutation prairie dog algorithm: Optimization framework for engineering design of interconnected multimachine power system

Many real-world engineering problems, characterized by high-dimensionality, nonlinearity, nonconvexity, and multi-modality, demand advanced optimization methods. Traditional algorithms may struggle with these challenges. Prairie dog optimization (PDO) was proposed for function optimization but faces limitations in balancing exploration and exploitation due to two reasons. The first one is related to diversity features which may not be efficient, and the second one is related to having no leading mechanism for direct search feature towards the promising regions. With that in mind, this study introduces an enhanced PDO variant, improved PDO (IPDO), addressing PDO's drawbacks through two key strategies: refraction-based learning (RBL) and spiral search learning (SSL). RBL enhances exploration by generating refraction solutions, while SSL conducts deep local searches around the best solution, strengthening exploitation. IPDO's performance is evaluated on benchmarks, IEEE CEC2017/CEC2020 test suites, and real-world constraint engineering optimization problems. Comparative analyses, including statistical measures, convergence analysis, and boxplot analysis, demonstrate IPDO's superiority. Besides, the IPDO is applied to estimate more promising parameters of power system stabilizer utilized in an interconnected multimachine power system using Western System Coordinating Council three-machine, nine-bus power system. Results illustrate that the IPDO harvests the better estimation among the other methods, making it to be an efficient and powerful tool for dealing with the efficient operation of an interconnected multimachine power system which is a challenging real-world engineering problem.

A graph embedding‐based approach for automatic cyber‐physical power system risk assessment to prevent and mitigate threats at scale

AbstractPower systems are facing an increasing number of cyber incidents, potentially leading to damaging consequences to both physical and cyber aspects. However, the development of analytical methods for the study of large‐scale power infrastructures as cyber‐physical systems is still in its early stages. Drawing inspiration from machine‐learning techniques, the authors introduce a method inspired by the principles of graph embedding that is tailored for quantitative risk assessment and the exploration of possible mitigation strategies of large‐scale cyber‐physical power systems. The primary advantage of the graph embedding approach lies in its ability to generate numerous random walks on a graph, simulating potential access paths. Meanwhile, it enables capturing high‐dimensional structures in low‐dimensional spaces, facilitating advanced machine‐learning applications, and ensuring scalability and adaptability for comprehensive network analysis. By employing this graph embedding‐based approach, the authors present a structured and methodical framework for risk assessment in cyber‐physical systems. The proposed graph embedding‐based risk analysis framework aims to provide a more insightful perspective on cyber‐physical risk assessment and situation awareness for power systems. To validate and demonstrate its applicability, the method has been tested on two cyber‐physical power system models: the Western System Coordinating Council (WSCC) 9‐Bus System and the Illinois 200‐Bus System, thereby showing its advantages in enhancing the accuracy of risk analysis and comprehensiveness of situational awareness.

Optimizing power system stability: A hybrid approach using manta ray foraging and Salp swarm optimization algorithms for electromechanical oscillation mitigation in multi‐machine systems

AbstractThis paper emphasizes the significance of ensuring adequate damping of electromechanical oscillations in power systems to ensure stable operation. Power System Stabilizers (PSSs) are influential in enhancing system damping and refining dynamic characteristics during transient conditions. However, the efficacy of PSSs is notably contingent on parameter values, particularly in the case of lead‐lag PSSs. In response to this challenge, the paper introduces a Tilt‐Integral‐Derivative (TID)‐based PSS, optimized through a novel optimization algorithm called Hybrid Manta Ray Foraging and Salp Swarm Optimization Algorithms (MRFOSSA). The MRFOSSA algorithm demonstrates robustness and enhanced convergence, validated through benchmark function tests, and outperforms competing algorithms. These superior characteristics of MRFOSSA were employed in optimal tuning of TID‐PSSs to uphold the stability of multi‐machine power systems. The MRFOSSA algorithm demonstrates robustness and enhanced convergence, outperforms competing algorithms in the optimal tuning of TID‐PSS within the Western System Coordinating Council (WSCC)‐3‐machines 9‐bus test system. In summary, the proposed TID‐PSS, coupled with the MRFOSSA algorithm, presents a promising avenue for enhancing power system stability.

Fault Detection and Isolation in Smart-Grid Networks of Intelligent Power Routers Modeled as Probabilistic Boolean Networks

A self-organizing complex-network modeling method, probabilistic Boolean networks, is presented as a model-based diagnostic system for detecting and isolating different types of faults, failures, and modes of operation in which a network of intelligent power routers is deployed over a standard power test case: the Western System Coordinating Council 9 Bus System. Such a system allows designers and engineering professionals to make educated decisions pertaining to the design of smart-grid systems endowed with intelligent power routers. There is a recurrent necessity to design reliable and fault-tolerant smart power systems, maintaining adequate operation and adherence to performance specifications, while keeping costs at the minimum. This diagnostics system will help achieve such goals: better design through thorough analysis of the conditions that lead to a fault on a smart grid, proper detection of these faults, and isolation of the respective assets.

Robust multi-machine power system stabilizer design using bio-inspired optimization techniques and their comparison

This paper reports a comparative study among four bio-inspired meta-heuristic techniques i.e. Sooty-Tern Optimization (STO), Grey Wolf Optimization (GWO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) to tune the robust Power System Stabilizer (PSS) parameters of the multi-machine power system. These approaches are successfully tested on two bench-mark systems: sixteen-machine, sixty-eight-bus New England Extended Power Grid (NEEPG) and three-machine, nine-bus Western System Coordinating Council (WSCC). The efficacy of planned PSS via STO and GWO is validated by extensive non-linear simulations, eigenvalue analysis, and performance indices for numerous operating conditions under decisive perturbations, and outcomes are matched with those of GA and PSO techniques. In addition, the robustness is also tested for these algorithms. The results indicate that the PSS design using STO and GWO improves the small-signal stability and damping performance for mitigating inter-area and local area modes of low-frequency oscillations compared to GA and PSO.

Relay algorithm for STATCOM compensated line using differential current ratio

Static synchronous compensators (STATCOMs) are used in the power transmission line to improve the voltage profile and stability. For a fault on the line, additional uneven reactive current from the compensator causes the maloperation of local data-based relaying schemes. In this work, using the current of both ends of the line, internal faults and faulty phases are identified by the ratio of both end’s current difference to the local one. Both the magnitude and angle of the ratio are utilized to enhance the dependability and security of the relay operation. The performance of the proposed technique is validated in Western System Coordinating Council (WSCC), a 9-bus system using data obtained from PSCAD. The authenticity of the proposed method is further validated using field data collected from a 400 kV shunt compensated line in the Indian power grid. The suggested strategy is resilient to changes in fault resistance, source impedance, fault location, current transformer saturation, various compensation levels, and high resistance faults (HRF). A comparison of the proposed Algorithm with existing methodologies demonstrates its superiority.

Small signal stability and dynamic performance investigation on multi-machines power system including DFIG wind farm

<p>The boundless potential of wind power in augmenting global energy production is a promising prospect. The efficient design and cost-effectiveness of doubly fed induction generator (DFIG) wind systems make them an optimistic solution for incorporating wind power on a massive scale. However, integrating these systems into power grids poses several challenges, including power system stability. This study examines the small signal stability and dynamic performance of a modified Western System Coordinating Council (WSCC) 9-bus system including a DFIG wind farm using load flow analysis, and both electromechanical oscillations and eigenvalue analysis. Three case studies were conducted based on the DFIG location and power increment.The simulation is carried out with the aid of the power system analysis toolbox (PSAT) that operates within the MATLAB environment. The study’s findings suggest that the perturbation and location of the DFIG relative to the system’s load have a minimal influence on the overall system’s stability and efficiency. However, when considering damping ratio, power angle, and rotor speed deviations, generators 1 and 2 with the perturbed DFIG installed on bus 8 are the most sensitive units to instability. Hence, larger perturbations and different DFIG’s location influence on power systems necessitates further analysis.</p>

Enhancing transient stability and dynamic response of wind-penetrated power systems through PSS and STATCOM cooperation

The large-scale integration of doubly-fed induction generator (DFIG) based wind power plants poses stability challenges for power system operation. This study investigates the transient stability and dynamic performance of a modified 3-machine, 9-bus Western System Coordinating Council (WSCC) system. The investigation was conducted by connecting the DFIG wind farm to the sixth bus via a low-impedance transmission line and installing power system stabilizers (PSSs) on all automatic voltage regulators (AVRs). A three-phase fault simulation was carried out to test the system, with and without power system stabilizers and a static synchronous compensator (STATCOM) device. Time-domain simulations demonstrate improved transient response with PSS-STATCOM control. A 50% reduction in settling time and 70% decrease in power angle undershoots at the slack bus are achieved following disturbances, even at minimum wind penetration levels. Load flow analysis shows the coordinated controllers maintain voltages within 0.5% of nominal at 60% wind penetration, while voltages at load buses can deviate up to 15% without control. Eigenvalue analysis indicates the PSS-STATCOM boosts damping ratios of critical oscillatory modes from nearly 0% to over 30% under high wind injection. Together, the present findings provide significant evidence that PSS and STATCOM cooperation enhances dynamic voltage regulation, angle stability, and damping across operating ranges, thereby maintaining secure operation in systems with high renewable integration.

Analyzing the Effects of MBPSS on the Transit Stability and High-Level Integration of Wind Farms during Fault Conditions

As the demand for renewable energy continues to increase, wind power has emerged as a prominent source of clean energy. However, incorporating wind energy into the power generation system at a high level can significantly impact the dynamic performance of the power system, resulting in increased uncertainties during operation. This study investigated the effectiveness of the Multi-Band Power System Stabilizer (MBPSS), a new power system stabilizer, in suppressing dynamic oscillations in a multi-machine power system connected to a wind farm. This research focused on analyzing the transient stability of a nine-bus network, commonly known as the Western System Coordinating Council (WSCC), integrated with a Doubly Fed Induction Generator (DFIG) using MATLAB/Simulink. The study evaluated the dynamic performance of the proposed system under fault conditions, including Line-to-Line-to-Line-to-Ground (LLLG) faults. Simulation results showed that MBPSS effectively dampened oscillations and improved the stability of the power system, even in the presence of severe faults and high-level integration of wind farms.

Enhanced sensitive phase alpha plane scheme against high resistance ground faults

Abstract Phase-based Alpha (α) Plane Relaying (APR) scheme has numerous advantages over the Current Differential Relay (CDR) for transmission line protection. Since the large Restraining Region (RR) in the APR makes high security against CT saturation, channel delay, line charging current and synchronization error. However, the APR loses its sensitivity for high resistance ground faults, especially single line to ground faults under outfeed conditions. Also, losing its dependability under close-in low resistance three-phase faults. Thereby, the sequence-based APR provides enhanced sensitivity with the cost of computational burden and complexity. Hence, in this paper, the concept of the average value (I Avg) of both end instantaneous currents is used as an auxiliary logic. In which, the polarity of I Avg is incorporated as an add-on logic to the conventional APR to confirm high resistance internal faults. Thereby, the requirement of sequence components can be avoided (negative and zero). To validate the proposed auxiliary logic, it is tested for the WSCC (Western System Coordinating Council) 9-bus, 110 kV, 50 Hz. System. The simulated results under various fault cases found authenticated results. In addition, the comparative assessment and validation with real-world data reveal the enhanced sensitivity of the proposed logic under high-resistance ground faults.

Implementing Optimization Techniques in PSS Design for Multi-Machine Smart Power Systems: A Comparative Study

This study performed a comparative analysis of five new meta-heuristic algorithms specifically adopted based on two general classifications; namely, nature-inspired, which includes artificial eco-system optimization (AEO), African vulture optimization algorithm (AVOA), gorilla troop optimization (GTO), and non-nature-inspired or based on mathematical and physics concepts, which includes gradient-based optimization (GBO) and Runge Kutta optimization (RUN) for optimal tuning of multi-machine power system stabilizers (PSSs). To achieve this aim, the algorithms were applied in the PSS design for a multi-machine smart power system. The PSS design was formulated as an optimization problem, and the eigenvalue-based objective function was adopted to improve the damping of electromechanical modes. The expressed objective function helped to determine the stabilizer parameters and enhanced the dynamic performance of the multi-machine power system. The performance of the algorithms in the PSS’s design was evaluated using the Western System Coordinating Council (WSCC) multi-machine power test system. The results obtained were compared with each other. When compared to nature-inspired algorithms (AEO, AVOA, and GTO), non-nature-inspired algorithms (GBO and RUN) reduced low-frequency oscillations faster by improving the damping of electromechanical modes and providing a better convergence ratio and statistical performance.

A Trilevel Model for Segmentation of the Power Transmission Grid Cyber Network

Network segmentation of a power grid's communication system can make the grid more resilient to cyberattacks. We develop a novel trilevel programming model to optimally segment a grid communication system, taking into account the actions of an information technology (IT) administrator, attacker, and grid operator. The IT administrator is allowed to segment existing networks, and the attacker is given a budget to inflict damage on the grid by attacking the segmented communication system. Finally, the grid operator can redispatch the grid after the attack to minimize damage. The resulting problem is a trilevel interdiction problem that we solve using a branch and bound algorithm for bilevel problems. We demonstrate the benefits of optimal network segmentation through case studies on the 9-bus Western System Coordinating Council (WSCC) system and the 30-bus IEEE system. These examples illustrate that network segmentation can significantly reduce the threat posed by a cyberattacker.

Distance protection with fault resistance compensation for lines connected to PV plant

The output power of the inverter-interfaced photovoltaic (PV) plant has the continuous variations due to the properties of PV modules and environmental conditions. These variations fundamentally affect the performance of the conventional distance protection during nonmetallic faults. This paper proposes a positive sequence network-based distance protection scheme for the transmission lines connected to the PV plants. Different from the adaptive mho and quadrilateral characteristics, the proposed scheme is independent of PV plant parameters and fault resistance. In this method, the Thevenin equivalent parameters of the grid seen from the PV plant are calculated. Thevenin equivalent parameters are calculated using prefault current and voltage data at the local terminal, without additional costs related to the requirements of the communication channel. The obtained parameters are used in the fault resistance compensation. Furthermore, by eliminating the fault resistance effect on the relay impedance, the exact fault location is also calculated. Since the fault line impedance formula is derived only from the positive sequence network, the proposed method is applicable to different grid codes. The efficiency of the proposed scheme is evaluated on the Western System Coordinating Council (WSCC) 9-bus and IEEE 30-bus test systems. The obtained simulation results verify the validity of the proposed scheme under various fault and PV plant conditions.

Decentralized reinforce‐control of renewable dynamic virtual power plant enabling it to offer ancillary services: An attempt towards net‐zero targets

AbstractThis article presents internal model control (IMC) based decentralized reinforce‐control of renewable dynamic virtual power plant (DVPP) so that, it can be integrated into the power system as a substitution of fuel‐based conventional generators. Such grid integration towards net‐zero targets could not be possible without providing additional ancillary service (AS) to the power system, as the traditional AS would fall short with the retirement/substitution of conventional generators. The theory of DVPP from a technical perspective (i.e., TDVPP) is presented in a detailed and simplified manner, including the formulation of a generalized control objective (desired specification) for DVPP integration. The solution approach includes two steps: (1) disaggregation of desired specification and (2) decentralized reinforce‐control to match the disaggregated specification. The theory and solution approach for DVPP integration is presented in a generalized manner enabling the DVPP to offer multiple ASs, but the case study is limited only to frequency control AS (FCAS) in this article. The study is performed on the ‘western system coordinating council (WSCC)’ test system, in which an attempt is made towards net‐zero targets by substituting the largest thermal generator with renewable DVPP ensuring the grid's operation or dynamics safe.

Optimal Secondary Frequency Regulation With ON-OFF Loads in Power Networks

Load-side participation can provide support to the power network by appropriately adapting the demand when required. In addition, it enables an economically improved power allocation. In this study, we consider the problem of providing an optimal power allocation among generation and ON-OFF loads within the secondary frequency control timeframe. In particular, we consider a mixed-integer optimization problem, which ensures that the secondary frequency control objectives (i.e., generation–demand balance and the frequency attaining its nominal value at steady state) are satisfied. We present analytic conditions on the generation and ON-OFF load profiles such that an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\epsilon $ </tex-math></inline-formula> -optimality interpretation of the steady-state power allocation is obtained, providing a nonconservative value for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\epsilon $ </tex-math></inline-formula> . Moreover, we develop a hierarchical control scheme that provides ON-OFF load values that satisfy the proposed conditions. We study the interaction of the proposed control scheme with the physical dynamics of the power network and provide analytic stability guarantees. Our results are verified with numerical simulations on the Western System Coordinating Council (WSCC) 9-bus system and the Northeast Power Coordinating Council (NPCC) 140-bus system, where it is demonstrated that the proposed algorithm yields a close to optimal power allocation.

A concept for discrimination of electrical fault from cyber attack in smart electric grid

Abstract This letter proposes a concept to discriminate an electrical fault from a cyber attack in the modern power system. A cyber attack factor is introduced which may mislead the bus voltage stability virtually at load buses. The proposed cyber attack models are validated by executing multiple cyber attacks at a time on Western system coordinating council (WSCC) 9 bus test power system by using Siemens PSS/E and MATLAB softwares. Further, the impact of electrical fault and cyber attack on the WSCC 9 bus test power systems voltage stability has been analysed to develop a discrimination algorithm in reference to chosen load index. Despite its simplicity, the proposed discrimination algorithm is robust, accurate and quite suitable to develop intelligent measures for mal-operations against cyber attacks in the smart electric grid.

Mathematical-based models for solution of the load flow problem

Load flow (LF) analysis is one of the most important aspects in power system studies. It is the most significant and necessary way to investigate the problems in power system operation and planning. The LF problem comprises a set of nonlinear algebraic equations that must be solved mathematically through iterations. The solution convergence is the most important criteria that is largely affected by the size of power system, which continues to increase in the current modern power system field. Thus, there is no guarantee that the iterative approaches will converge to a valid solution for problems with such large dimensions. This paper develops generalized, effective and simple mathematical models for the solution of the LF problem. The problem is first solved by Gauss–Seidel (GS) method in order to generate the training data. Eureqa software is then adopted for the purpose of data training and mathematical models generation. The models relate bus voltage magnitudes and angles as output parameters with the load active and reactive power values as input parameters. To study the validity of the proposed approach, the mathematical models have been developed for two benchmark test systems; IEEE 5-bus test system and 9-bus test system developed by Western Systems Coordinating Council (WSCC). When compared with the outputs resulting from GS technique, the results have shown efficient and accurate capability of the generated models for evaluating bus voltages magnitudes and angles as well as generated reactive power. The models have also been compared with other published research. The results have shown efficient performance of the developed models.

Frequency dynamics-aware real-time marginal pricing of electricity

This paper presents a frequency dynamics-aware marginal pricing method for real-time electricity markets. The proposed method captures the impact of system frequency dynamics on the marginal price of electricity in the presence of aggressive net-load variations made more likely by greater renewable integration. We formulate a dynamics-aware economic dispatch (ED) by augmenting the traditional single-snapshot ED with constraints pertaining to system frequency dynamics, and frequency deviations from the synchronous speed are penalized in the modified objective function. The resulting ED embeds two distinct time steps to optimize over fast system dynamics and slower decisions on generator set-points. We prove that the dynamics-aware marginal price is the (suitably scaled) Lagrange multiplier of the power balance constraint and that it converges in steady state to the marginal price obtained from traditional ED solved with comparable system load. Numerical case studies involving the Western System Coordinating Council test system validate our findings and confirm added revenue opportunities for generators contributing to frequency regulation.