A New Paradigm for Water Level Regulation using Three Pond Model with Fuzzy Inference System for Run of River Hydropower Plant

TL;DR

This paper introduces a three pond model combined with a fuzzy inference system to improve water level regulation in run-of-river hydropower plants, reducing flow dependency and enhancing disturbance absorption.

Contribution

It proposes a novel three pond system with fuzzy control, outperforming traditional single pond models and PID controllers in regulating water levels and handling disturbances.

Findings

Fuzzy inference system improves regulation accuracy.

Three pond model reduces flow dependency.

Enhanced disturbance absorption compared to traditional methods.

Abstract

The energy generation of a run of river hydropower plant depends upon the flow of river and the variations in the water flow makes the energy production unreliable. This problem is usually solved by constructing a small pond in front of the run of river hydropower plant. However, changes in water level of conventional single pond model results in sags, surges and unpredictable power fluctuations. This work proposes three pond model instead of traditional single pond model. The volume of water in three ponds is volumetrically equivalent to the traditional single pond but it reduces the dependency of the run of river power plant on the flow of river. Moreover, three pond model absorbs the water surges and disturbances more efficiently. The three pond system, modeled as non-linear hydraulic three tank system, is being applied with fuzzy inference system and standard PID based methods for smooth and efficient level regulation. The results of fuzzy inference system are across-the-board improved in terms of regulation and disturbances handling as compared to conventional PID controller.