Dynamic stability enhancement of TCSC‐based tidal power generation using quasi‐oppositional harmony search algorithm

Kumar, Akshay; Shankar, Gauri

doi:10.1049/iet-gtd.2017.1117

Cited by 10 publications

(4 citation statements)

References 31 publications

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“…Compared with commonly used intelligent algorithm, a lot of power flow calculations can be avoided by the proposed SOCR solving method. An intelligent harmony search (HS) algorithm in [38], [39] is used as the comparison algorithm. The size of the harmony library is 50, the probability of taking value from harmony library is 0.5, the fine-tuning probability is 0.2, and the number of creations is 200.…”

Section: ) Comparison Of Dispatching Methodsmentioning

confidence: 99%

Quick Hosting Capacity Evaluation Based on Distributed Dispatching for Smart Distribution Network Planning with Distributed Generation

Sun,

Jing,

et al. 2024

Journal of Modern Power Systems and Clean Energy

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The smart distribution network (SDN) is integrating increasing distributed generation (DG) and energy storage (ES). Hosting capacity evaluation is important for SDN planning with DG. DG and ES are usually invested by users or a third party, and they may form friendly microgrids (MGs) and operate independently. Traditional centralized dispatching method no longer suits for hosting capacity evaluation of SDN. A quick hosting capacity evaluation method based on distributed optimal dispatching is proposed. Firstly, a multi-objective DG hosting capacity evaluation model is established, and the hosting capacity for DG is determined by the optimal DG planning schemes. The steady-state security region method is applied to speed up the solving process of the DG hosting capacity evaluation model. Then, the optimal dispatching models are established for MG and SDN respectively to realize the operating simulation. Under the distributed dispatching strategy, the dualside optimal operation of SDN-MGs can be realized by several iterations of power exchange requirement. Finally, an SDN with four MGs is conducted considering multiple flexible resources. It shows that the DG hosting capacity of SDN oversteps the sum of the maximum active power demand and the rated branch capacity. Besides, the annual DG electricity oversteps the maximum active power demand value.

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Section: ) Comparison Of Dispatching Methodsmentioning

confidence: 99%

Quick Hosting Capacity Evaluation Based on Distributed Dispatching for Smart Distribution Network Planning with Distributed Generation

Sun,

Jing,

et al. 2024

Journal of Modern Power Systems and Clean Energy

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“…In Eq. ( 5), D 1 indicates an integer value from 1 to D dimensionality length and R 3 is an integer which indicates the search cycles [1,41].…”

Section: Design Of Oaofs Techniquementioning

confidence: 99%

“…The OAO is derived by the use of oppositional based learning (OBL) approach that stems from the concurrent estimation of opposite pairs of the base agent for improving the probability of meeting an equivalent agent [41]. Contrary to real number N ∈ [j L , j U ] is offered by N→ as:…”

Section: Design Of Oaofs Techniquementioning

confidence: 99%

Feature Selection with Deep Belief Network for Epileptic Seizure Detection on EEG Signals

Cherukuvada¹,

Kayalvizhi²

2023

Computers, Materials &Amp; Continua

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The term Epilepsy refers to a most commonly occurring brain disorder after a migraine. Early identification of incoming seizures significantly impacts the lives of people with Epilepsy. Automated detection of epileptic seizures (ES) has dramatically improved the life quality of the patients. Recent Electroencephalogram (EEG) related seizure detection mechanisms encountered several difficulties in real-time. The EEGs are the non-stationary signal, and seizure patterns would change with patients and recording sessions. Further, EEG data were disposed to wide noise varieties that adversely moved the recognition accuracy of ESs. Artificial intelligence (AI) methods in the domain of ES analysis use traditional deep learning (DL), and machine learning (ML) approaches. This article introduces an Oppositional Aquila Optimizer-based Feature Selection with Deep Belief Network for Epileptic Seizure Detection (OAOFS-DBNECD) technique using EEG signals. The primary aim of the presented OAOFS-DBNECD system is to categorize and classify the presence of ESs. The suggested OAOFS-DBNECD technique transforms the EEG signals into .csv format at the initial stage. Next, the OAOFS technique selects an optimal subset of features using the preprocessed data. For seizure classification, the presented OAOFS-DBNECD technique applies Artificial Ecosystem Optimizer (AEO) with a deep belief network (DBN) model. An extensive range of simulations was performed on the benchmark dataset to ensure the enhanced performance of the presented OAOFS-DBNECD algorithm. The comparison study shows the significant outcomes of the OAOFS-DBNECD approach over other methodologies. In addition, the result of the suggested approach has been evaluated using the CHB-MIT database, and the findings demonstrate accuracy of 97.81%. These findings confirmed the best seizure categorization accuracy on the EEG data considered.

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“…However, the application of such equipment is not limited to steady-state applications; it can be extended to transient stability [5]. The dynamic series control of transmission lines relies on the idea that the equivalent reactance of transmission lines can be controlled along transients to damp system oscillations, avoiding power system instability after large perturbations [6], or damping resonances, which can endanger the system stability [7].…”

Section: Introductionmentioning

confidence: 99%

Distributed FACTS for Power System Transient Stability Control

2020

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The high penetration of renewable energy sources, combined with a limited possibility to expand the transmission infrastructure, stretches the system stability in the case of faults. For this reason, operators are calling for additional control flexibility in the grid. In this paper, we propose the deployment of switchable reactors and capacitors distributed on the grid as a control resource for securing operations during severe contingencies and avoiding potential blackouts. According to the operating principles, the line reactance varies by switching on or off a certain number of distributed series reactors and capacitors and, therefore, the stabilizing control rule is based on a stepwise time-discrete control action. A control strategy, based on dynamic optimization, is proposed and tested on a realistic-sized transmission system.

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Dynamic stability enhancement of TCSC‐based tidal power generation using quasi‐oppositional harmony search algorithm

Cited by 10 publications

References 31 publications

Quick Hosting Capacity Evaluation Based on Distributed Dispatching for Smart Distribution Network Planning with Distributed Generation

Quick Hosting Capacity Evaluation Based on Distributed Dispatching for Smart Distribution Network Planning with Distributed Generation

Feature Selection with Deep Belief Network for Epileptic Seizure Detection on EEG Signals

Distributed FACTS for Power System Transient Stability Control

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