Hybrid Optimization of Multi objective Economic Load Dispatch using Gravitational Search Flower Pollination Algorithm

The main objective of the power system is to supply the total power requirement to the users at minimum possible fuel cost and with minimum emissions. Combined economic and emission load dispatch determines the optimal generation of the power system by minimizing the fuel cost and emission levels simultaneously. Economic Load Dispatch is the most remarkable problem in optimization for forecasting the generation in the area of thermal generating units in power system. In this work, a new Hybrid Gravitational Search Flower Pollination (GSFPA) based algorithm is proposed for achieving improved results in the ELD problem where gravitational search is used to decide the step size in levy flight mechanism. In the new technique gravitational search algorithm works in coordination with flower pollination algorithm to find desired and refined results. The proposed algorithm will be tested for IEEE 14 and 39 bus system to prove its credibility. This algorithm has less number of operators and hence it can be easily coded in any programming language. To prove the feasibility of this algorithm its performance is compared with other existing algorithms.