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<p>Enhancing Available Transfer Capability (ATC) is crucial in today’s deregulated power systems. Power can be transferred from the sending end to the receiving end only if adequate ATC is available. Operators are encouraged to make the best use of existing infrastructure to improve ATC margins. Flexible AC Transmission Systems (FACTS) devices help by regulating phase angle, voltage, and reactance, which changes load flow and controls bus voltages. In this study, the Whale Optimization Algorithm (WOA) is used to find the optimal location and control settings of a Distribution Static Compensator (DSTATCOM). ATC forecasting under 3 and 6% load growth is done using linear regression, with the inclusion of DSTATCOM. Equations linking load growth to ATC for various sinking buses are developed. Forecast accuracy is improved using quadratic regression in which the errors are under 1% and sometimes as low as 0.01%. This approach helps operators and planners prepare for future transmission needs under growing demand.</p>

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Integrated ATC enhancement and load growth forecasting via WOA-based optimal DSTATCOM placement

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月29日

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  • Arumuga Babu M,
  • Anbuchandran S,
  • Silas Stephen D,
  • Sankar R

摘要

Enhancing Available Transfer Capability (ATC) is crucial in today’s deregulated power systems. Power can be transferred from the sending end to the receiving end only if adequate ATC is available. Operators are encouraged to make the best use of existing infrastructure to improve ATC margins. Flexible AC Transmission Systems (FACTS) devices help by regulating phase angle, voltage, and reactance, which changes load flow and controls bus voltages. In this study, the Whale Optimization Algorithm (WOA) is used to find the optimal location and control settings of a Distribution Static Compensator (DSTATCOM). ATC forecasting under 3 and 6% load growth is done using linear regression, with the inclusion of DSTATCOM. Equations linking load growth to ATC for various sinking buses are developed. Forecast accuracy is improved using quadratic regression in which the errors are under 1% and sometimes as low as 0.01%. This approach helps operators and planners prepare for future transmission needs under growing demand.