Forecasting Tariff Rates and Enhancing Power Quality in Microgrids: The Synergistic Role of LSTM and UPQC


  • Satyabrata Sahoo School of Electrical Engineering, KIIT Deemed to be University, India
  • Sarat Chandra Swain School of Electrical Engineering, KIIT Deemed to be University, India
  • Ritesh Dash School of EEE, REVA University, India
  • Padarbinda Samal School of Electrical Engineering, KIIT Deemed to be University, India
Volume: 14 | Issue: 1 | Pages: 12506-12511 | February 2024 |


The current paper presents an original approach into the microgrid control framework by incorporating LSTM-based optimization with specific emphasis on refining the gain parameters of a Proportional-Integral-Derivative (PID) controller. This integration represents a significant advancement in improving the overall efficiency of microgrid control systems. By creatively applying LSTM optimization, the paper achieves dynamic adjustments of the PID controller's parameters, resulting in more precise regulation of output power quality. Through the utilization of the Unified Power Quality Conditioner (UPQC) in conjunction with LSTM-based optimization, the paper establishes a compelling link between improved power quality and the resultant tariff rates. This highlights their combined influence on enhancing power quality and calibrating tariff rates, providing a fresh perspective on optimizing microgrid operations.


formatting, microgrid, forecasting, LSTM, power quality, UPQC


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How to Cite

S. Sahoo, S. C. Swain, R. Dash, and P. Samal, “Forecasting Tariff Rates and Enhancing Power Quality in Microgrids: The Synergistic Role of LSTM and UPQC”, Eng. Technol. Appl. Sci. Res., vol. 14, no. 1, pp. 12506–12511, Feb. 2024.


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