Single Line Outage Research Articles

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

Because of factors such as low natural gas prices, low greenhouse gas emission and high efficiency has increased the penetration of natural gas-fired generators in electric power systems. Large gas consumption of gas-fired generators has caused intense interdependence of electricity and gas systems. Most often, the operational planning of power and gas systems is conducted through a co-optimisation model in which the total cost of electricity and gas systems is minimised and the constraints of both systems are considered. On the other hand, due to environmental concerns, the usage of fuel cell vehicles (FCVs) is increasing. Hydrogen refueling stations (HRSs) are needed for refueling FCVs. This paper puts forward a stochastic model for co-optimisation of wind-integrated power and gas systems, hosting HRSs, electric storage systems (ESS's) and responsive electricity and gas demands. The effect of ESS's, responsive demands, contingencies, wind uncertainties and demand response on operation of power-gas nexus is scrutinized. An incentive-based demand response program has been used for both electricity and gas demands. The case study is the Belgian gas network connected to the a 24-bus power system. The findings indicate that responsive electric demands reduce electric system cost by 9.4 %, while responsive gas demands reduce the gas network cost and total operation cost by 1 %. The contingency analysis on the power-gas nexus shows that single line outage contingencies in power system does not result in any demand shed and does not increase the operation cost of either electricity network or gas network.

Evaluation and Improvement of Power System Security with the Application of Machine Learning

The electricity grid has added many renewable and non-renewable energy sources to meet expanding demand. Sudden load variations exacerbate generator, transmission line, and distribution network issues. Load modelling choices are crucial for system prediction. This study indicates that ZIP load models with contingency criteria can accurately forecast load behaviour over time. The NR method predicts the contingency ranking with the High Bride Line Stability Ranking Index (HLSRI) under single line outage conditions, and an artificial neural network (ANN) is trained to predict the severity of the line outage and the system's behaviour. A mathematical model was utilised to analyse stability and cost with and without the UPFC and IPFC. Machine learning (ML) is used to rapidly predict the most affected transmission line during a contingency by clustering data using the J48 algorithm for the location of compensating devices. The PSO algorithm is used to develop an objective function to minimise fuel costs by maximising generating capacity. A transmission line failure and load variation might damage the electrical system. This study prioritises transmission line breakdowns and load changes. Power system security analysis provides power system status.

Enhancing power system security using soft computing and machine learning

Purpose. To guarantee proper operation of the system, the suggested method infers the loss of a single transmission line in order to calculate a contingency rating. Methods. The proposed mathematical model with the machine learning with particle swarm optimization algorithm has been used to observe the stability analysis with and without the unified power flow controller and interline power flow controller, as well as the associated costs. This allows for rapid prediction of the most affected transmission line and the location for compensation. Results. Many contingency conditions, such as the failure of a single transmission line and change in the load, are built into the power system. The single transmission line outage and load fluctuation used to determine the contingency ranking are the primary emphasis of this work. Practical value. In order to set up a safe transmission power system, the suggested stability analysis has been quite helpful.

Investigations on hybrid line stability ranking index with polynomial load modeling for power system security

Introduction. In recent years, numerous non-renewable and renewable energies are connected to the grid to meet the demand. Also, transient variation with loads poses the shortcomings for generating units, transmission and distribution networks. In this regard, the study on choice of suitable load modelling is essential to predict the system characteristics. The aspect of the research design is a ZIP load model, which, when combined with contingency criteria and constant-impedance, constant-current, and constant-power loads, produces realistic and long-term load representations. Purpose. The proposed technique, infers the single transmission line outage for obtaining the contingency ranking to ensure the system behavior. Methods. The proposed mathematical model with hybrid line stability ranking index has been used for observing the stability analysis with and without considering unified power flow controller. Results. The power system involves many unpredictable conditions or contingency conditions like single transmission line outage, double transmission line outage, generator outage and load variations. This paper mainly focuses on the single transmission line outage for obtaining the contingency ranking. Practical value. The recommended stability analysis has been very beneficial in establishing a secure transmission power system.

Optimal PMU Allocation Strategy for Completely Observable Networks With Enhanced Transient Stability Characteristics

The installation of phasor measurement units (PMUs) in contemporary electrical networks provides enhanced monitoring and control capabilities of the entire system. However, the placement of additional PMU devices is constrained by the relatively high cost and complicated communication infrastructure. Consequently, optimizing the allocation of PMU units is required to achieve complete visibility of the power system operation while minimizing the associated cost. This paper presents a coherent approach for solving the optimal PMU placement (OPP) in order to reduce the total number of PMUs that is required to completely observe the network. Furthermore, the proposed formulation of the OPP allocation problem considers several objectives such as cost minimization, redundancy and efficiency maximization in addition to various constraints like incorporation of zero-injection buses, single PMU failure, single line outage and consideration of flow measurements. Moreover, a two-stage approach is proposed to ensure the numerical observability of the obtained PMU placement. The proposed framework relies on solving a mixed integer linear programming problem for the OPP placement problem based on conventional measurements. The rank of the gain matrix is thereafter computed to check if the solution is numerically observable. In contrast to reported studies in the literature, transient stability enhancement is augmented in the formulation of the optimization problem such that the redundancy of predetermined buses is guaranteed without increasing the total number of installed PMU units. A novel spectral cluster-based online coherency grouping is employed to identify buses which possess the ideal characteristics in terms of transient stability support.

Security Constrained Reactive Power Scheduling Considering N-1 Contingency of Transmission Lines

This paper presents a methodology for reactive power scheduling (RPS) of power system in the form of AC optimal power flow (AC-OPF) problem. The objective function is minimization of system total active power losses. The OPF optimally determines reactive power output of generating units and synchronous condensers, tap-changers ratio, shunt capacitor banks and reactors. The effect of tap-changer is modeled in the active and reactive power flow of transformer. The proposed method grantees secure operation of system in normal operating condition and also in contingency of transmission line outage. The validity of proposed method is studied based on IEEE RTS 24-bus. Results show the capability of suggested AC-OPF for RPS of system in base case as well as contingency of single line outage.

Wind generator transient response analysis and improvement using BESS

Transient stability is very important for safety in the power system. In this paper, transient stability analysis of a wind power generator connected to distribution network is presented. The analysis was performed on a model of a realistic 12-bus system. In order to improve transient response capabilities of the system, battery energy storage system (BESS) is included in the simulations. It was demonstrated that BESS has significant influence on the stability of the network during the fault conditions. All simulations were performed in the DigSILENT Power Factory software. The analysis and assessment of the network was performed for the case of three-phase symmetrical fault with all lines in service and following a single line outage (failure and N-1 criterion). The results show that the connection of the wind generators to distribution network depends on the distance from the primary source of the grid (slack bus). However, BESS system can be used to improve transient stability response in which case distance from the primary source station is not critical. Also, this analysis adds additional evidence on the importance of transient stability calculations during the process of new generator unit connection to the power system.

A unified optimal power flow modeling for VSC-HVDC converter: a novel methodology for optimal installation based on average loadability index

PurposeThis paper aims to propose a novel methodology for optimal voltage source converter (VSC) station installation in hybrid alternating current (AC)/direct current (DC) transmission networks.Design/methodology/approachIn this analysis, a unified power flow model has been developed for the optimal power flow (OPF) problem for VSC-based high voltage direct current (VSC-HVDC) transmission network and solved using a particle swarm optimization (PSO) algorithm. The impact of the HVDC converter under abnormal conditions considering N-1 line outage contingency is analyzed against the congestion relief of the overall transmission network. The average loadability index is used as a severity indicator and minimized along with overall transmission line losses by replacing each AC line with an HVDC line independently.FindingsThe developed unified OPF (UOPF) model converged successfully with (PSO) algorithm. The OPF problem has satisfied the defined operational constraints of the power system, and comparative results are obtained for objective function with different HVDC test configurations represented in the paper. In addition, the impact of VSC converter location is determined on objective function value.Originality/valueA novel methodology has been developed for the optimal installation of the converter station for the point-to-point configuration of HVDC transmission. The developed unified OPF model and methodology for selecting the AC bus for converter installation has effectively reduced congestion in transmission lines under single line outage contingency.

Contingency 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.

Multi-Stage Dynamic Transmission Network Expansion Planning Using LSHADE-SPACMA

This paper introduces a multi-stage dynamic transmission network expansion planning (MSDTNEP) model considering the N-1 reliability constraint. The integrated planning problem of N-1 security and transmission expansion planning is essential because a single line outage could be a triggering event to rolling blackouts. Two suggested scenarios were developed to obtain the optimal configuration of the Egyptian West Delta Network’s realistic transmission (WDN) to meet the demand of the potential load growth and ensure the system reliability up to the year 2040. The size of a blackout, based on the amount of expected energy not supplied, was calculated to evaluate both scenarios. The load forecasting (up to 2040) was obtained based on an adaptive neuro-fuzzy inference system because it gives excellent results compared to conventional methods. The linear population size reduction—Success-History-based Differential Evolution with semi-parameter adaptation (LSHADE-SPA) hybrid—covariance matrix adaptation evolution strategy (CMA-ES) algorithm (LSHADE-SPACMA)—is applied to solve the problem. The semi-adaptive nature of LSHADE-SPACMA and the hybridization between LSHADE and CMA-ES are able to solve complex optimization problems. The performance of LSHADE-SPACMA in solving the problem is compared to other well-established methods using three testing systems to validate its superiority. Then, the MSDTNEP of the Egyptian West Delta Network is presented, and the numerical results of the two scenarios are compared to obtain an economic plan and avoid a partial or total blackout.

Machine learning methods for power line outage identification

As Phasor Measurement Units (PMUs) become widely deployed, power systems can take advantage of the large amount of data provided by PMUs and leverage the advances in big data analytics to improve real-time monitoring and diagnosis. In this paper, we develop practical analytics that are not tightly coupled with the power flow analysis and state estimation, as these tasks require detailed and accurate information about the power system. We focus on power line outage identification, and use a machine learning framework to locate line outages. The same framework is used for the prediction of both single line and multiple line outages. We investigate a range of machine learning algorithms and feature extraction methods. The algorithms are designed to capture the essential dynamic characteristics of the power system when the topology change occurs abruptly. The proposed methods use only voltage phasor angles obtained by continuously monitoring the buses. We tested the proposed methods on their prediction performance under different levels of noise and missingness. It is shown that the proposed methods have better tolerance for noisy data and incomplete data when compared to the previous work that involves solving power flow equations or state estimation equations.

A Hybrid SATS Algorithm Based Optimal Power Flow for Security Enhancement Using SSSC

Security and performance of the power system is the prime concern in its planning and operation. It is essential to devise proper measures for maintenance and improvement of security in the power system. Static synchronous series compensator (SSSC) is a type of series flexible AC transmission system device. The present research proposes a hybrid simulated annealing and Tabu search (Hybrid SATS) algorithm with SSSC to solve security constrained optimal power flow problems. The primary objective of the research work is to enhance the security of the power system and minimise the generator fuel cost. Contingency ranking is used to select line outages. The line flow limit violations in various single line outages are relieved effectively by Hybrid SATS with SSSC method, which keeps power flows within their security limits. Simulation studies are carried out on standard IEEE 30 bus to identify effectiveness of the proposed hybrid method and the obtained outcomes are put in comparison to SA with SSSC and TS with SSSC methods.

External Topology Tracking Based on State Estimation

A state estimation based approach to obtain an external network equivalent and track topology changes is developed in this work. The proposed approach enables real-time detection and identification of topology-based external events. Following an orthogonal parameter estimator, an index related to the measurement residuals is tracked to detect external disturbances, which are classified based on reference values and actual system data. The method makes use of boundary bus voltages, external currents, an initial snapshot of the network topology, as well as the sensitivity of external changes to the equivalent network. Tests on the IEEE 300-bus and Brazilian 6092-bus systems highlight its capabilities in detecting and identifying shunt, single and double line outages and insertion events.

Stochastic electrical energy management of industrial Virtual Power Plant considering time-based and incentive-based Demand Response programs option in contingency condition

Abstract Nowadays, the sustainable energy management of industrial environments is of great importance because of their heavy loads and behaviors. In this paper, the Virtual Power Plant (VPP) idea is commented as a collected generation to be an appropriate approach for these networks handling. Here, Technical Industrial VPP (TIVPP) is characterized as a dispatching unit contains demands and generations situated in an industrial network. A complete structure is proposed here for possible conditions for different VPPs cooperation in the power market. This structure carries out a day-ahead and intra-day generation planning by choosing the best Demand Response (DR) programs considering wind power and market prices as the uncertain parameters. A risk management study is likewise taken into account in the proposed stages for contingency conditions. So, some component changes, like, regular demand changes and single-line outage are prepared in the framework to authorize the suggested concept in the contingency situation. To determine the adequacy and productivity of the proposed strategy, the IEEE-RTS modified framework is examined to test the technique and to evaluate some reassuring perspectives too. By the proposed methodology, the delectability of DR projects is uncovered in industrial networks and the improvement level of load shedding and the lower cost will be achieved.

A Markovian Influence Graph Formed From Utility Line Outage Data to Mitigate Large Cascades

We use observed transmission line outage data to make a Markovian influence graph that describes the probabili- ties of transitions between generations of cascading line outages. Each generation of a cascade consists of a single line outage or multiple line outages. The new influence graph defines a Markov chain and generalizes previous influence graphs by including multiple line outages as Markov chain states. The generalized influence graph can reproduce the distribution of cascade size in the utility data. In particular, it can estimate the probabilities of small, medium and large cascades. The influence graph has the key advantage of allowing the effect of mitigations to be analyzed and readily tested, which is not available from the observed data. We exploit the asymptotic properties of the Markov chain to find the lines most involved in large cascades and show how upgrades to these critical lines can reduce the probability of large cascades.

Optimal PMUs placement considering ZIBs and single line and PMUs outages

Phasor measurement unit (PMU) is among the most important measurement devices in modern power systems. It measures the voltage and current phasors which have both magnitude and phase angle using a common timing reference. These measurements are utilized in real time applications of electrical power systems. The main drawback of PMUs is its high cost so if PMUs are used to collect or send online real data from a system to a data centre or a decision maker, the used number of PMUs should be minimum with full observability of system measurements. This paper proposes a flower pollination algorithm (FPA) to find the optimal number and locations of PMUs in power systems. The optimization objectives of the work are the minimization of PMUs number, the achievement of complete observability of power system states, and the maximization of measurement redundancy. Existence of zero-injection buses in the system decreases the number of PMUs that is required to fulfil the complete observability of system states. Furthermore, additional constraints for remaining system full observable following failure of single PMU and single line outage are also included to increase the system reliability. The performance and efficiency of the proposed FPA is tested on IEEE standard networks such as 14-bus, 30-bus, 57-bus and 118-bus and new England 39-bus network. The obtained simulation results approve the ability of the proposed optimization method to find the optimal allocation of PMUs in different cases with fulfilling complete observability and reliability of electric power systems. The superiority of FPA is also verified by comparing its results of other optimization algorithms.

A general PMU placement approach considering both topology and system aspects of contingencies

In a wide area measurement system, line tripping as well as the following transient and dynamic post-contingency conditions affect the full observability of power systems and possibly the accuracy of the wide area monitoring system. In this paper, a general methodology is presented to solve the phasor measurement unit (PMU) placement problem considering both the system and the topology aspects of disturbances. To do that, the connectivity matrix-based PMU placement problem is firstly formulated in its basic binary integer form to meet the full observability of power systems. Next, the post-disturbance variations in power systems, as the system aspect, are integrated with the conventional placement problem to ensure the more accurate pre- and post-disturbance monitoring of power systems. In addition, the algorithm is developed to achieve the highest possible reliability for single transmission line outages, i.e. N – 1 contingencies, as the topology aspect. Other topology-related issues, including zero injections, PMU channel limitations, and pre-existing measurements are included in the new formulation as well. Since the effects of the two aspects of disturbances on the placement solution are conflicting, and as the magnitude of the system aspect is much stronger than that of topology aspects, compensations are added to balance the conflicting effects by mitigating the strong effect of the system aspect on the overall formulation. Therefore, the proposed methodology will lead to a placement scheme, by which providing the full observability of the system under a high number of single line outages as well as obtaining the more accurate post-disturbance monitoring of power systems are assured. The performance and effectiveness of the proposed methodology are demonstrated in two medium and large test systems.

A Probabilistic Multi-Objective Model for Phasor Measurement Units Placement in the Presence of Line Outage

Optimal phasor measurement units (PMU) placement was developed to determine the number and locations of PMUs on the premise of full observability of the whole network. In order to enhance reliability under contingencies, redundancy should also be considered beside the number of PMUs in optimal phasor measurement units placement problem. Thus, in this paper, a multi-objective model was established to consider the two conflicting components simultaneously, solved by ε-constraint method and the fuzzy satisfying approach. The redundancy here was formulated as average possibility of observability including random component outages, and full possibility formula was applied to calculate the average possibility of observability in the case of single line outage. Finally, the model was employed to the IEEE-57 bus system, and the results verified that the developed model could provide a placement scheme with higher reliability.

The Reactive Power Compensation Planning for N-1 Line Outage Based on Line Fault Betweenness

An inappropriate compensation capacity can cause oscillation or even collapse of the grid. This paper focus on the RPP problem considering single line outage in the grid. Firstly, the line fault betweenness (LFB) is proposed to identify the preoutage and post-outage impact on vulnerable lines. Then, considering the cost and power quality of the grid, a multi-objective optimization is adopted to analysis the result of compensation planning and solved by the multi-objective genetic algorithm and F1-scores. Finally, the IEEE-39 test system is employed to illustrate the important lines with LFB ranking and the decision of reactive power compensation planning. The compensation result reveals the improvement on power factor of generators and load voltage offset reduction.

A Sensitivity-Based Approach for the Detection of Multiple-Line Outages Using Phasor Measurements

A new approach for identifying multiple line outages in electric power systems by using data obtained from synchrophasor measurements is proposed in this paper. A novelty of the proposal is the application of the sensitivity theory to the system's alternating current power flow model to determine the most likely contingency scenario, with not previous knowledge of the number of line outages. Since the proposal considers both voltage and current synchrophasor measurements, a set of observable lines is defined such that their outages are identified directly from those measurements. In this context, the more observed transmission lines there are, the smaller the search space for identifying potential outages in unobserved transmission lines. On the other hand, the detection problem of multiple-line outages is decomposed into the sequential uncovering of different single-line outages by using the concept of total derivative. The reduction of the search space and the decomposition of the multiple-line outages problem significantly reduce the computational burden of the proposed approach. Finally, numerical results demonstrate that the proposal presents a very satisfactory percentage of success for identifying the correct set of line outages, even when a limited number of PMUs is embedded in the system.