Gencos wind–thermal scheduling problem using Artificial Immune System algorithm

• A hybrid wind–thermal generating system is proposed.
• An adaptive search inspired from AIS algorithm used for Gencos profit maximization.
• Reduce number of binary string variables required for modeling the constraints.
• Profit maximization and cost minimization analyzed for 10 thermal + 2 wind units.

This paper presents an Artificial Immune System approach for solving generation scheduling problem of a Genco comprised of thermal and wind energy systems. Wind–thermal scheduling problem determine the time of instant to start up and shut down the generating units over a scheduled time period, while satisfying the ‘system’ and ‘generator’ constraints including minimum up/down time; ramp rate limits of thermal units and wind power constraints. In this work, the impact of wind energy on short term generation scheduling problem is analyzed through the adaptive search which is inspired from the Artificial Immune System. The effectiveness of the proposed approach is demonstrated through a Genco consists of 10 thermal units with 2 wind farms and the results for the near optimal schedule are discussed.

Graphical representation of flow steps in AIS approach.Figure optionsDownload as PowerPoint slide