Energy planning has become important in developing countries and growing economies. The balance between energy production and consumption is based on good planning. The basis of the planning lies in high accuracy estimation, where time series techniques are often used. The Holt-Winters exponential smoothing method, which is one of the time series techniques and includes seasonality, was used in this study. In the study, genetic algorithm method was used to determine the parameters in Holt-Winters exponential smoothing (HWES) method and electrical load forecasts were made by using these parameters. Mean absolute deviation (MAD) was used as the optimization target function in parameter determination. The parameters determined by genetic algorithm were generated with 200 monthly data on a monthly basis and 12 month load values were used in the estimation. MAPE, MAD and MPE errors were shown in the study and the proposed approach was found to be suitable for the estimation of electrical load.