Multi-objective economic emission load dispatch solution using gravitational search algorithm and considering wind power penetration

In this paper an economic emission load dispatch (EELD) problem is solved to minimize the emission of nitrogen oxides (NOX) and fuel cost, considering both thermal generators and wind turbines. The effects of wind power on overall NOX emission are also investigated here. To find the optimum emission dispatch, optimum fuel cost, best compromising emission and fuel cost, a newly developed optimization technique, called Gravitational Search Algorithm (GSA) has been applied. GSA is based on the Newton’s law of gravity and mass interactions. In GSA, the searcher agents are collection of masses which interact with each other using laws of gravity and motion of Newton. IEEE 30-bus system having six conventional thermal generators has been considered as test system. Two extra wind turbines are also placed at two weak load bus of the system. Two Weak load buses have been selected based on their L-index value. After placing the wind power sources, those buses have been considered as generator bus. Minimum fuel cost, minimum emission and best compromising solution obtained by GSA are compared with those of biogeography-based optimization (BBO). The results show that the GSA surpasses the other available techniques in terms of solution quality and computational efficiency.

► The paper has solved economic emission dispatch problem including wind generation.
► The paper considered both single and multi-objective emission dispatch problems.
► The wind power modelling, available in published paper has been incorporated here.
► Gravitational Search Algorithm (GSA) has been implemented to solve the problem.
► Performance of GSA has been found to be better, when compared with BBO.