Performance evaluation of neuro-fuzzy clustering for hydro thermal power system

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Abstract

To meet increasing power demands and reduce carbon emission additional renewable sources of power are added to existing thermal unit. Even network frequency change by 1% due to change in speed, may result in loss of synchronization with the rest of power system and finally resulting in power system black-out. Inter-connection of hydro units to existing thermal system can allow to transmission system to operate at full capacity. The paper investigates LFC by adding non-linearity’s to the thermal and hydro-thermal systems. Further PID and Neuro-Fuzzy Controllers are compared for these systems. A multi section steam turbine with re-heater was used for a single area system modeled in MATLAB, later two single area systems were combined to create a two area system, and its dynamics are studied by creating load perturbations. Form simulation studies it is shown that the proposed Neuro-Fuzzy controller was able to attain a setting time of 10 Sec which is comparatively lower than other existing speed controllers. The time domain response result of hydropower system proves that it provides more rapid output response and minimal overshoot.

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Maurya, A. K., Banerjee, G. K., & Kumar, P. (2019). Performance evaluation of neuro-fuzzy clustering for hydro thermal power system. International Journal of Engineering and Advanced Technology, 9(1), 5986–5994. https://doi.org/10.35940/ijeat.A1678.109119

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