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Validation of Bus Voltage Sensitivity Index for Optimal Renewable Energy Source Integration: A MATLAB and ETAP Comparative Study
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This study evaluates the effectiveness of the Bus Voltage Sensitivity Index (BVSI) in identifying weak buses and supporting optimal integration of reactive power and renewable energy sources in a 13-bus transmission network. A hybrid analytical-simulation framework was adopted, where BVSI values were computed analytically in MATLAB using controlled 1 MVAR reactive power injections and subsequently validated through detailed ETAP load-flow simulations. The BVSI was defined as the change in voltage magnitude per unit of reactive power injection (kV/MVAR and pu/MVAR). Analytical results identified Buses 3 and 4 within the 33 kV subnetwork as the most sensitive nodes, with Bus 3 exhibiting the highest BVSI of 0.074 kV/MVAR (0.002242 pu/MVAR), indicating reduced voltage stiffness and suitability for reactive compensation or RES placement. ETAP simulations confirmed similar voltage responses, with peak voltage improvements of approximately 0.07 kV at the same locations. Correlation analysis between MATLAB and ETAP results produced a strong coefficient of determination (R²=0.81746), supported by a low mean absolute error (MAE=0.0123 kV/MVAR) and mean absolute percentage error (MAPE=18.71%), demonstrating close agreement between analytical and nonlinear simulation outcomes. Practical validation was conducted by installing a 1 MVAR shunt capacitor at Bus 4 in the ETAP model, resulting in a 0.07 kV rise in voltage, a 2.07% reduction in total real power losses, and a 6.23% reduction in reactive power losses. The results confirm that the BVSI-ETAP framework provides a computationally efficient and practically validated approach for weak-bus identification, reactive power planning, and enhanced voltage stability in developing power systems.
Keywords: Bus Voltage Sensitivity Index, voltage stability, reactive power compensation, ETAP simulation, renewable energy integration, weak-bus identification.
Academic and Grant Writing Enclave (AGE) Publications
Title: Validation of Bus Voltage Sensitivity Index for Optimal Renewable Energy Source Integration: A MATLAB and ETAP Comparative Study
Description:
This study evaluates the effectiveness of the Bus Voltage Sensitivity Index (BVSI) in identifying weak buses and supporting optimal integration of reactive power and renewable energy sources in a 13-bus transmission network.
A hybrid analytical-simulation framework was adopted, where BVSI values were computed analytically in MATLAB using controlled 1 MVAR reactive power injections and subsequently validated through detailed ETAP load-flow simulations.
The BVSI was defined as the change in voltage magnitude per unit of reactive power injection (kV/MVAR and pu/MVAR).
Analytical results identified Buses 3 and 4 within the 33 kV subnetwork as the most sensitive nodes, with Bus 3 exhibiting the highest BVSI of 0.
074 kV/MVAR (0.
002242 pu/MVAR), indicating reduced voltage stiffness and suitability for reactive compensation or RES placement.
ETAP simulations confirmed similar voltage responses, with peak voltage improvements of approximately 0.
07 kV at the same locations.
Correlation analysis between MATLAB and ETAP results produced a strong coefficient of determination (R²=0.
81746), supported by a low mean absolute error (MAE=0.
0123 kV/MVAR) and mean absolute percentage error (MAPE=18.
71%), demonstrating close agreement between analytical and nonlinear simulation outcomes.
Practical validation was conducted by installing a 1 MVAR shunt capacitor at Bus 4 in the ETAP model, resulting in a 0.
07 kV rise in voltage, a 2.
07% reduction in total real power losses, and a 6.
23% reduction in reactive power losses.
The results confirm that the BVSI-ETAP framework provides a computationally efficient and practically validated approach for weak-bus identification, reactive power planning, and enhanced voltage stability in developing power systems.
Keywords: Bus Voltage Sensitivity Index, voltage stability, reactive power compensation, ETAP simulation, renewable energy integration, weak-bus identification.
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