This article presents the plan to design model predictive control (MPC) built load frequency control (LFC) action for a multi-area interconnected control framework. The multi-area control framework comprises of plants with differing sources of vitality. The HVDC tie-lines are considered as an interconnection within the control framework. Further, the most of the past studies in this area was to evaluate the performance of LFC based on step load disturbance and these strategies does not speak to the genuine time circumstances of the control framework operation which may cause the over regulation of the control framework. To improve the execution of LFC, a short term load forecasting (STLF) founded LFC using artificial neural network (ANN) is proposed in this paper. Assist, the real load pattern data is collected on hourly basis and process with the help of ANN for LFC studies. The predicted hourly load is utilized to supply future load to the LFC framework by means of look-ahead control calculation on the premise of 10 miniature interim and MPC based LFC are design to alter the set point to zero in order to match the generation with real load pattern in a best possible manner. The comparison between real and forecasted load utilizing MPC is given through computer reenactments for LFC and the application results of real scenario is presented to show efficacy of the proposed work.
A Very Short - Term Load forecasting using Kalman filter for Load Frequency Control with Economic Load Dispatch