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A comparative analysis of hybrid of traditional load flow methods for IEEE distributed power generation networks

Mohamed Hariri, Muhammad HafeezDaud, Noor DzulaikhaMohd Yusoff, Nor AzizahSyed Zaman, Syed Muhammad ZakwanMat Desa, Mohd Khairunaz
Indonesian Journal of Electrical Engineering and Computer Science (Sinta 1)Vol. 39 No. 1 (2025)1 Juli 2025
DOI10.11591/ijeecs.v39.i1.pp33-44

Abstrak

Analyzing power flow or load flow is crucial for planning, operating, maintaining, and controlling electrical power systems. Two traditional power flow methods namely the Newton-Raphson (NR) method are known for their accuracy and robustness nevertheless high computational intensity, and the fast decoupled load flow (FD) method, is valued for its computational efficiency and speed, however, generating less accurate data. This research aims to develop a hybrid load flow technique that integrates both strengths, achieving higher accuracy and faster convergence. The validation processes are based on several IEEE standard bus systems, including the 3-bus, 9-bus, 14-bus, and 30-bus systems. These systems, with different bus types and interconnections, represent real-world operations and help generate comprehensive data on iteration count, execution time, and the accuracy of the output data results. A new hybrid method generated from this research work compared to traditional load flow methods, provides a substantially well-balanced number of iteration counts, the fastest execution times, improved by 41.55%, and produces a similar accuracy of the data set. These improvements make the hybrid method highly advantageous in practical real-time applications and large-scale systems where both accuracy and speed are critical.

Kata Kunci

Electrical (Power)Power System AnalysisPower GenerationFast decoupled load flowIEEE bus systemsLoad flow analysisNewton-RaphsonPower generation control

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A comparative analysis of hybrid of traditional load flow methods for IEEE distributed power generation networks | Indonesian Journal of Electrical Engineering and Computer Science | Publiora