Citation :

S. Jayachandra, Shaik RafiKiran, "Enhanced Power Loss Reduction Through Optimal RDG Location and Size Using Bi-GRU Integrated Golden Eagle Optimization," International Journal of Recent Engineering Science (IJRES), vol. 13, no. 3, pp. 6-23, 2026. Crossref, https://doi.org/10.14445/23497157/IJRES-V13I3P102

Abstract

The Renewable Distributed Generator (RDG) mainly including solar PV arrays and wind turbines are found to be an effective auxiliary power system to provide optimal power supply for increasing load demands. The sizing and location of these power generators face many challenges, such as power loss, voltage deviation, instability in voltage and shortage of power. In this paper, an Optimal Sizing and location of RDG (OSL-RDG) is carried out to overcome the conventional limitations. The methods involved in this approach are as follows: (i) the forecasting of load and weather conditions based on time is carried out by implementing the Bi-Gated Recurrent Unit (Bi-GRU) model, in which the uncertainties in the load demand are forecasted based on the historical load data. (ii) The optimal sizing and location of RDG is executed to minimize the voltage deviation, power loss and maximize the voltage stability. This is performed by implementing Multi-Objective Golden Eagle Optimization (MOGEO), in which the forecasted load demand and location characteristics are utilized to optimally place the RDG. (iii) The stable power flow is achieved by monitoring the load demand, in which the categorization of load takes place by Advantage Actor Critic with Generalized Advantage Estimation (A2C-GAE), which further minimizes the power loss. The presented model is simulated in MATLAB R2020a simulation tool and validated using the IEEE-33 bus. The evaluation of the proposed model is carried out in terms of performance metrics such as power loss, voltage stability and deviation, forecasting error and iteration time.

Keywords

Renewable Distributed Grid With Solar/Wind Turbine System, Load Forecasting, Optimal Sizing And Location, Stable Power Flow, Load Monitoring.

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