Genetic algorithms based bidding strategies for system with intermittent generation and responsive demand

In this paper, Game Theory (GT) and its applications in power markets are introduced including the fundamental concept of Nash Equilibrium (NE) which is a universal and essential solution concept in GT. The system studied herein is a small system with 3 generation companies to find the best bidding strategies for each company and the market price to profit the whole market. In search for the NE, a numerical method based on the basic essential concept of GT, which is how the generation companies will interact with each other in a competitive commercial environment, has been successfully implemented and demonstrated on the 3-company system. The demand side is also introduced into the market as this also has a significant bearing on the bidding strategies and the market price. A comparison of numerical methodology to Genetic Algorithms (GAs) is made by implementing these into the same 3-company system. The results show that such a numerical method would be very inefficient for a commercial environment where hundreds of generation companies co-exist compared to GAs.