Proposed a Modified Hybrid Gravitational Search Algorithm-Teaching-Learning Optimization Based Method Searching the solution quality in the proposed MHGT method compared to the standard GSA and TLBO methods Implementation of the proposed MHGT method to a new 19-bus Turkey wind-thermal power system for the solution of In this study, modified hybrid gravitational search algorithm (GSA)-teaching-learning based optimization (TLBO) algorithm (MHGT) method has been developed to solve the economic dispatch problem of windthermal power systems. The proposed MHGT method was developed by modifying the global search superiority in GSA and powerful local search specialty in TLBO for the solution of constrained optimization problem. With the MHGT method, it is aimed to reach the global minimum result with the least number of iterations and to get rid of the local minimum. Figure A shows the GSA in the first search space. The second search space is based on the optimal result of the GSA algorithm. Then, TLBO run in this second search space. Figure A. Graphical representation of the MHGT method Purpose: The proposed MHGT method is aimed to solve the economic dispatch problem of 6 bus and Turkey-19 bus wind-thermal power system. Theory and Methods: In this study, firstly, equations of hybrid method were given and MHGT method was applied to benchmark test functions. Then the proposed MHGT method was applied to 6 bus and Turkey-19 bus wind-thermal power system. Results: The success of the proposed MHGT method in benchmark functions was determined by Wilcoxon signedrank test. The proposed MHGT method is wind-thermal power system of economic dispatch problem solving achievement is shown in the graphs and figures. Conclusion: It is concluded that the proposed MHGT method finds the solution in short execution time and less fuel cost with more reliably and more efficiently in terms of both fuel cost and execution time.