scholarly journals Artificial Intelligence Techniques for Power System Transient Stability Assessment

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 507
Author(s):  
Petar Sarajcev ◽  
Antonijo Kunac ◽  
Goran Petrovic ◽  
Marin Despalatovic
Keyword(s):  
Artificial Intelligence ◽  
Power System ◽  
Power Plants ◽  
Transient Stability ◽  
Model Building ◽  
Renewable Energy Sources ◽  
Optimization Techniques ◽  
Future Research ◽  
Stability Assessment ◽  
Advantages And Disadvantages

The high penetration of renewable energy sources, coupled with decommissioning of conventional power plants, leads to the reduction of power system inertia. This has negative repercussions on the transient stability of power systems. The purpose of this paper is to review the state-of-the-art regarding the application of artificial intelligence to the power system transient stability assessment, with a focus on different machine, deep, and reinforcement learning techniques. The review covers data generation processes (from measurements and simulations), data processing pipelines (features engineering, splitting strategy, dimensionality reduction), model building and training (including ensembles and hyperparameter optimization techniques), deployment, and management (with monitoring for detecting bias and drift). The review focuses, in particular, on different deep learning models that show promising results on standard benchmark test cases. The final aim of the review is to point out the advantages and disadvantages of different approaches, present current challenges with existing models, and offer a view of the possible future research opportunities.

scholarly journals MOSAIK and FMI-Based Co-Simulation Applied to Transient Stability Analysis of Grid-Forming Converter Modulated Wind Power Plants

2021 ◽  
Vol 11 (5) ◽  
pp. 2410
Author(s):  
Nakisa Farrokhseresht ◽  
Arjen A. van der Meer ◽  
José Rueda Torres ◽  
Mart A. M. M. van der Meijden
Keyword(s):  
Power System ◽  
Time Domain ◽  
Power Plants ◽  
Transient Stability ◽  
Renewable Energy Sources ◽  
Critical Factor ◽  
Primary Control ◽  
Simulation Approach ◽  
Wide Range ◽  
Grid Side

The grid integration of renewable energy sources interfaced through power electronic converters is undergoing a significant acceleration to meet environmental and political targets. The rapid deployment of converters brings new challenges in ensuring robustness, transient stability, among others. In order to enhance transient stability, transmission system operators established network grid code requirements for converter-based generators to support the primary control task during faults. A critical factor in terms of implementing grid codes is the control strategy of the grid-side converters. Grid-forming converters are a promising solution which could perform properly in a weak-grid condition as well as in an islanded operation. In order to ensure grid code compliance, a wide range of transient stability studies is required. Time-domain simulations are common practice for that purpose. However, performing traditional monolithic time domain simulations (single solver, single domain) on a converter-dominated power system is a very complex and computationally intensive task. In this paper, a co-simulation approach using the mosaik framework is applied on a power system with grid-forming converters. A validation workflow is proposed to verify the co-simulation framework. The results of comprehensive simulation studies show a proof of concept for the applicability of this co-simulation approach to evaluate the transient stability of a dominant grid-forming converter-based power system.

scholarly journals Transient Impact Analysis of High Renewable Energy Sources Penetration According to the Future Korean Power Grid Scenario

2018 ◽  
Vol 10 (11) ◽  
pp. 4140 ◽  
Author(s):  
Seungchan Oh ◽  
Heewon Shin ◽  
Hwanhee Cho ◽  
Byongjun Lee
Keyword(s):  
Renewable Energy ◽  
Power System ◽  
Electric Power ◽  
Power Plants ◽  
Transient Stability ◽  
Impact Analysis ◽  
Renewable Energy Sources ◽  
Electric Power System ◽  
Energy Sources ◽  
The Impact

Efforts to reduce greenhouse gas emissions constitute a worldwide trend. According to this trend, there are many plans in place for the replacement of conventional electric power plants operating using fossil fuels with renewable energy sources (RESs). Owing to current needs to expand the RES penetration in accordance to a new National power system plan, the importance of RESs is increasing. The RES penetration imposes various impacts on the power system, including transient stability. Furthermore, the fact that they are distributed at multiple locations in the power system is also a factor which makes the transient impact analysis of RESs difficult. In this study, the transient impacts attributed to the penetration of RESs are analyzed and compared with the conventional Korean electric power system. To confirm the impact of the penetration of RESs on transient stability, the effect was analyzed based on a single machine equivalent (SIME) configuration. Simulations were conducted in accordance to the Korean power system by considering the anticipated RES penetration in 2030. The impact of RES on transient stability was provided by a change in CCT by increasing of the RES penetration.

scholarly journals Grid-forming control strategies for black start by offshore wind power plants

2020 ◽  
Vol 5 (4) ◽  
pp. 1297-1313 ◽  
Author(s):  
Anubhav Jain ◽  
Jayachandra N. Sakamuri ◽  
Nicolaos A. Cutululis
Keyword(s):  
Power System ◽  
Wind Power ◽  
Power Plants ◽  
Large Scale ◽  
Control Strategies ◽  
Renewable Energy Sources ◽  
Stability Limit ◽  
Offshore Wind ◽  
Advantages And Disadvantages ◽  
Wind Power Plants

Abstract. Large-scale integration of renewable energy sources with power-electronic converters is pushing the power system closer to its dynamic stability limit. This has increased the risk of wide-area blackouts. Thus, the changing generation profile in the power system necessitates the use of alternate sources of energy such as wind power plants, to provide black-start services in the future. However, this requires grid-forming and not the traditionally prevalent grid-following wind turbines. This paper introduces the general working principle of grid-forming control and examines four of such control schemes. To compare their performance, a simulation study has been carried out for the different stages of energization of onshore load by a high-voltage direct-current (HVDC)-connected wind power plant. Their transient behaviour during transformer inrush, converter pre-charging and de-blocking, and onshore block-load pickup has been compared and analysed qualitatively to highlight the advantages and disadvantages of each control strategy.

scholarly journals Power System Transient Stability Assessment Using Stacked Autoencoder and Voting Ensemble

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3148
Author(s):  
Petar Sarajcev ◽  
Antonijo Kunac ◽  
Goran Petrovic ◽  
Marin Despalatovic
Keyword(s):  
Power System ◽  
New England ◽  
Transient Stability ◽  
Renewable Energy Sources ◽  
Ensemble Classifier ◽  
Support Vector ◽  
Test Case ◽  
Stability Assessment ◽  
Dynamic Simulations ◽  
Stacked Autoencoder

Increased integration of renewable energy sources brings new challenges to the secure and stable power system operation. Operational challenges emanating from the reduced system inertia, in particular, will have important repercussions on the power system transient stability assessment (TSA). At the same time, a rise of the “big data” in the power system, from the development of wide area monitoring systems, introduces new paradigms for dealing with these challenges. Transient stability concerns are drawing attention of various stakeholders as they can be the leading causes of major outages. The aim of this paper is to address the power system TSA problem from the perspective of data mining and machine learning (ML). A novel 3.8 GB open dataset of time-domain phasor measurements signals is built from dynamic simulations of the IEEE New England 39-bus test case power system. A data processing pipeline is developed for features engineering and statistical post-processing. A complete ML model is proposed for the TSA analysis, built from a denoising stacked autoencoder and a voting ensemble classifier. Ensemble consist of pooling predictions from a support vector machine and a random forest. Results from the classifier application on the test case power system are reported and discussed. The ML application to the TSA problem is promising, since it is able to ingest huge amounts of data while retaining the ability to generalize and support real-time decisions.

scholarly journals Power System Transient Stability Assessment Based on Snapshot Ensemble LSTM Network

2021 ◽  
Vol 13 (12) ◽  
pp. 6953
Author(s):  
Yixing Du ◽  
Zhijian Hu
Keyword(s):  
Power Systems ◽  
Power System ◽  
Transient Stability ◽  
Short Term Memory ◽  
Risk Function ◽  
Stability Margin ◽  
Risk Level ◽  
Stability Assessment ◽  
Lstm Network ◽  
Hierarchical Assessment

Data-driven methods using synchrophasor measurements have a broad application prospect in Transient Stability Assessment (TSA). Most previous studies only focused on predicting whether the power system is stable or not after disturbance, which lacked a quantitative analysis of the risk of transient stability. Therefore, this paper proposes a two-stage power system TSA method based on snapshot ensemble long short-term memory (LSTM) network. This method can efficiently build an ensemble model through a single training process, and employ the disturbed trajectory measurements as the inputs, which can realize rapid end-to-end TSA. In the first stage, dynamic hierarchical assessment is carried out through the classifier, so as to screen out credible samples step by step. In the second stage, the regressor is used to predict the transient stability margin of the credible stable samples and the undetermined samples, and combined with the built risk function to realize the risk quantification of transient angle stability. Furthermore, by modifying the loss function of the model, it effectively overcomes sample imbalance and overlapping. The simulation results show that the proposed method can not only accurately predict binary information representing transient stability status of samples, but also reasonably reflect the transient safety risk level of power systems, providing reliable reference for the subsequent control.

scholarly journals Optimal Placement and Sizing of an Energy Storage System Using a Power Sensitivity Analysis in a Practical Stand-Alone Microgrid

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1598
Author(s):  
Dongmin Kim ◽  
Kipo Yoon ◽  
Soo Hyoung Lee ◽  
Jung-Wook Park
Keyword(s):  
Sensitivity Analysis ◽  
Energy Storage ◽  
Power System ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Energy Storage System ◽  
Optimization Techniques ◽  
Optimal Placement ◽  
Stable Operation ◽  
Analytical Approaches

The energy storage system (ESS) is developing into a very important element for the stable operation of power systems. An ESS is characterized by rapid control, free charging, and discharging. Because of these characteristics, it can efficiently respond to sudden events that affect the power system and can help to resolve congested lines caused by the excessive output of distributed generators (DGs) using renewable energy sources (RESs). In order to efficiently and economically install new ESSs in the power system, the following two factors must be considered: the optimal installation placements and the optimal sizes of ESSs. Many studies have explored the optimal installation placement and the sizing of ESSs by using analytical approaches, mathematical optimization techniques, and artificial intelligence. This paper presents an algorithm to determine the optimal installation placement and sizing of ESSs for a virtual multi-slack (VMS) operation based on a power sensitivity analysis in a stand-alone microgrid. Through the proposed algorithm, the optimal installation placement can be determined by a simple calculation based on a power sensitivity matrix, and the optimal sizing of the ESS for the determined placement can be obtained at the same time. The algorithm is verified through several case studies in a stand-alone microgrid based on practical power system data. The results of the proposed algorithm show that installing ESSs in the optimal placement could improve the voltage stability of the microgrid. The sizing of the newly installed ESS was also properly determined.

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