Dynamic Combined Economic Emission Dispatch Including Wind Generators by Real Coded Genetic Algorithm

Madhumita Kumari, Kirti Pal

OAI: oai:igi-global.com:292510 • DOI: 10.4018/IJAMC.292510

With the growing environmental depletion, the shift in the focus towards minimizing the emissions of gases released in the conventional generators and further incorporation of a cleaner alternate renewable source of energy such as wind or solar to the existing system is of utmost importance. The research paper aims to build an environmentally resilient electric power system. Real coded genetic algorithm- powerful optimization technique is employed to solve the dynamic combined economic emission dispatch i.e. DCEED strategy for two proposed algorithm. The first proposed DCEED algorithm includes fuel cost of only conventional generators while in the second algorithm along with conventional generators, wind powered generators with varying power output characteristic is added. A comparative analysis of both the algorithms in terms of total combined cost, emission level and fuel cost is taken into account and it is observed that in spite of wind uncertainty the proposed method is more economical.

Algorithms Computer Science and Information Technology Artificial Intelligence