학술논문

Load shedding solution using multi-objective teaching-learning-based optimization
Document Type
Conference
Source
2018 International Conference on Innovative Trends in Computer Engineering (ITCE) Innovative Trends in Computer Engineering (ITCE), 2018 International Conference on. :447-452 Feb, 2018
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Power system stability
Reactive power
Linear programming
Sociology
Statistics
Optimization
Generators
Optimal load shedding
Blackout
Teaching-learning-based optimization
Contingency
Language
Abstract
Blackout has become one of the major serious threats to power system stability, security and reliability. To prevent blackout many correct control actions must be taken. One of these actions is the load shedding. This paper proposes new optimization technique known as teaching-learning-based optimization algorithm (TLBO) for solving steady state optimal load shedding problem. Different multi-objectives are considered to prevent the voltage instability which lead to partial or total blackout. load shedding Minimization, voltage stability maximization, and loadability maximization are taken as multi-objective. The developed algorithm is validated and tested on standard IEEE 30-bus test system considering contingency state. The TLBO results are compared with the other reported methods such as; gradient technique based on Kuhn-Tucker theorem (GTBKTT) and Improved harmony search algorithm (IHSA). The obtained results demonstrate the effectiveness of TLBO algorithm solution compared to other algorithms.