Abstract
In this article, automatic generation control of two area interconnected system in restructured scenario is addressed. In each area two generation companies (GENCOs), one thermal and other hydro are considered. Dead band nonlinearity is incorporated for governors of the thermal GENCOs. Classical controllers, integral (I), proportional-I (PI) and PI-derivative (PID) are utilized as supplementary controllers. These controller gains are optimized with nature inspired antlion optimizer (ALO) technique. Analysis demonstrates the improved performance of PID controller over I and PI controllers in terms of minimum settling time and reduced peak overshoots in various contract conditions. Sensitivity analysis explores that ALO optimized PID controller parameters found at nominal system conditions are tough enough against variations in system loading and inertia constant parameter. Further, Studies proves the superiority of ALO technique over genetic algorithm and particle swarm techniques in providing the better dynamics and lesser values of cost function in different contract conditions.
| Original language | English |
|---|---|
| Title of host publication | 2017 Innovations in Power and Advanced Computing Technologies, i-PACT 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1-6 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781509056828 |
| DOIs | |
| Publication status | Published - 2017 |
| Event | 2017 Innovations in Power and Advanced Computing Technologies, i-PACT 2017 - Vellore, India Duration: 21-04-2017 → 22-04-2017 |
Publication series
| Name | 2017 Innovations in Power and Advanced Computing Technologies, i-PACT 2017 |
|---|---|
| Volume | 2017-January |
Conference
| Conference | 2017 Innovations in Power and Advanced Computing Technologies, i-PACT 2017 |
|---|---|
| Country/Territory | India |
| City | Vellore |
| Period | 21-04-17 → 22-04-17 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Artificial Intelligence
- Computer Networks and Communications
- Control and Optimization
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