Analysis of Power System Security using Big Data and Machine Learning Techniques

Angadi, Ravi V; Daram, Suresh Babu; Shanmugam, Prabhakar Karthikeyan

doi:10.1109/indicon49873.2020.9342458

Cited by 4 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…DT has many varieties such as classification decision tree (CDT), iterative dichotomiser 3 (ID3), classification and regression tree (CART), C4.5, j48, REPTree, ensemble DT, etc. Out of which ID3 and CART are most common [ 82 , 102 , 103 ]. In Ref.…”

Section: Methods Of Power System Security Assessmentmentioning

confidence: 99%

Techniques of power system static security assessment and improvement: A literature survey

Hailu¹,

Nyakoe²,

Muriithi³

2023

Heliyon

View full text Add to dashboard Cite

Section: Methods Of Power System Security Assessmentmentioning

confidence: 99%

Techniques of power system static security assessment and improvement: A literature survey

Hailu¹,

Nyakoe²,

Muriithi³

2023

Heliyon

View full text Add to dashboard Cite

“…To overcome the economic and technical challenges faced by independent power grids and achieve economic operation by sharing unevenly distributed resources and infrastructure, and bilateral electric power trading, power system interconnection becomes a common practice around the world [2,3]. Interconnection among power systems managed and controlled by di erent operators along with the increasing penetration of renewable energy-based generation brings about new challenges into the power system, such as increased complexity, uncertainty, interarea oscillation, and increased di culty to real-time power system security evaluation and control [4][5][6][7][8].…”

mentioning

confidence: 99%

Application of Data-Driven Tuned Fuzzy Inference System for Static Equivalencing of Power Systems with High Penetration of Renewable Energy

Hailu¹,

Nyakoe

Muriithi

2022

Journal of Electrical and Computer Engineering

View full text Add to dashboard Cite

To reduce the complexity of multiarea power systems during power flow study and security assessment, equivalencing of external power systems is essential. In this paper, external power systems are modeled as adaptive loads representing the tie-line flows varying with system operating conditions. The fuzzy inference system tuned by hybrid genetic-simulated annealing (HGSA-FIS) is proposed to predict the active and reactive power of adaptive loads from forecasted renewable energy (RE) generation and loads demand. The performance of proposed equivalent has been evaluated with an RTS-GMLC by comparing the power flow results in the internal system before and after equivalencing under varying RE and load demand scenarios. The results demonstrate the robustness of HGSA-FIS-based equivalent under varying RE generation and load demand. Furthermore, the proposed equivalent performs close to ANN-based equivalent and outperforms ANFIS-based equivalent. To practically implement the proposed approach, the neighboring system operators are required to exchange only the forecast data of RE generation and load demand, and the equivalent needs to be updated upon major grid changes.

show abstract

An approach to Contingency Severity Prediction using Data Analytic Techniques in a Power System

Daram,

Ak,

Angadi

et al. 2022

2022 International Conference on Smart and Sustainable Technologies in Energy and Power Sectors (SSTEPS)

View full text Add to dashboard Cite

Analysis of Power System Security using Big Data and Machine Learning Techniques

Cited by 4 publications

References 12 publications

Techniques of power system static security assessment and improvement: A literature survey

Techniques of power system static security assessment and improvement: A literature survey

Application of Data-Driven Tuned Fuzzy Inference System for Static Equivalencing of Power Systems with High Penetration of Renewable Energy

An approach to Contingency Severity Prediction using Data Analytic Techniques in a Power System

Contact Info

Product

Resources

About