Contingency Analysis and Placement of DG to Improve Power Performance Indices

The power system constitutes a complex network where security is the priority. Contingency analysis emerges as a longstanding and widely embraced technique aimed at preemptively assessing the severity of potential outages and their ramifications, thereby facilitating necessary actions to uphold the power grid's security. Given the considerable number of components within the system, scrutinizing individual contingencies proves to be a laborious endeavour. However, it is imperative to identify those contingencies that could potentially trigger severe conditions within the power system. This is accomplished by using the fast decoupling load flow (FDLF) approach to compute performance indices, such as the reactive power performance index (PIv) and active performance index (PIp), for each transmission line outage. Subsequently, contingency ranking is performed within the MATLAB environment, furnishing operators with insights ranging from the most critical to the least significant outages in the power system. The integration of distributed generation (DG) into distribution networks is pursued with the objective of augmenting system performance indices. DGs are incorporated into load flow analysis employing either a constant power factor model (CPF) or a variable reactive power model (VRP), contingent upon the output power characteristics. These models are seamlessly integrated into the load flow analysis. The efficacy of this approach has been validated through testing on both IEEE 5-Bus and IEEE 14-Bus systems by integrating mathematical models of DGs.

Authors

Institutions

Publication Details

Published
2024-11-08
DOI
https://doi.org/10.1109/odicon62106.2024.10797550
Citations
1
Primary Topic
Engineering Applied Research
Type
article
Field-Weighted Citation Impact
0.26
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Contingency Analysis and Placement of DG to Improve Power Performance Indices

Raghvendra Tiwari, Biranchi Narayan Kar, Parul Dubey, Satish Chandra et al.
1 citations
Engineering Applied Research
0.26
article

Contingency Analysis and Placement of DG to Improve Power Performance Indices

Raghvendra Tiwari, Biranchi Narayan Kar, Parul Dubey, Satish Chandra, Amiya Kumar Naik, Pawan Dadaji Kamadi
article en
1 citations

Abstract

The power system constitutes a complex network where security is the priority. Contingency analysis emerges as a longstanding and widely embraced technique aimed at preemptively assessing the severity of potential outages and their ramifications, thereby facilitating necessary actions to uphold the power grid's security. Given the considerable number of components within the system, scrutinizing individual contingencies proves to be a laborious endeavour. However, it is imperative to identify those contingencies that could potentially trigger severe conditions within the power system. This is accomplished by using the fast decoupling load flow (FDLF) approach to compute performance indices, such as the reactive power performance index (PIv) and active performance index (PIp), for each transmission line outage. Subsequently, contingency ranking is performed within the MATLAB environment, furnishing operators with insights ranging from the most critical to the least significant outages in the power system. The integration of distributed generation (DG) into distribution networks is pursued with the objective of augmenting system performance indices. DGs are incorporated into load flow analysis employing either a constant power factor model (CPF) or a variable reactive power model (VRP), contingent upon the output power characteristics. These models are seamlessly integrated into the load flow analysis. The efficacy of this approach has been validated through testing on both IEEE 5-Bus and IEEE 14-Bus systems by integrating mathematical models of DGs.

Teerthanker Mahaveer University (IN), Motilal Nehru National Institute of Technology (IN), Siksha O Anusandhan University (IN), Symbiosis International University (IN), Raisoni Group of Institutions (IN)
Affordable and clean energy
Openalex Percentile: Top 42%
Engineering Applied Research
0.26
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.