Accurate short-term load forecasting in the power system may efficiently cut power generating costs while also improving the system's economic and environmental advantages. ARIMA Model, Parameter Regression Model, Kalman Filter Model, and other traditional short-term power demand forecasting methods are examples. Short-term load forecasting of power systems has become commonplace, thanks to the fast advancement of computer technology and the widespread application of AI technologies in the power sector. In this paper, we have designed a short-term load forecasting model using an enhanced ANN. The ANN model is enhanced by determining the optimal weights it using a hybrid combination of the optimization algorithm. In our work, we have hybrid the firefly and PSO algorithm. The performance analysis of the presented model is done to show its effectiveness over the existing models in MATLAB using various parameters.