Extended mixed integer quadratic programming for simultaneous distributed generation location and network reconfiguration

Introduction. To minimise power loss, maintain the voltage within acceptable range, and improve quality in distribution networks, reconfiguration optimal distributed generation placement are presented. Power flow analysis advanced optimization techniques that can handle significant combinatorial problems must be used network investigations. The approach to depends on size of network. Our methodology simultaneously addresses two nonlinear discrete construct an intelligent algorithm identify best solution. proposed work is novel it Extended Mixed-Integer Quadratic Programming (EMIQP) technique, a deterministic for determining topology will effectively minimize losses system by strategically sizing positioning Distributed Generation (DG) while taking into account. Using efficient Mixed Integer (QMIP) solver (IBM ®), resulting problem has quadratic form. ascertain range impact various variables, our outperforms cutting-edge algorithms described literature terms obtained loss reduction, according extensive numerical validation carried out typical IEEE 33- 69-bus systems at three different load factors. Practical value. Examining effectiveness concurrent DG allocation versus sole done using test cases. According findings, along with installation generator proper location, size, level, higher profile, effective.