Economic Integration of Wind Farms to Modern Power Networks
Direction to a self healing tehnology
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This project presents a differential evolution (DE) based methodology to relieve congestion and improve quality and cost efficacy of generated power, formulating a penalty based congestion constrained OPF problem in a hybrid thermal-wind power farm. Employing an approach of Demand sensitive loss factor (DSLF) to select the worst possible inadvertent states of the system and the weakest bus of the system in active, reactive loading the algorithm attempts to reschedule the generators to bring down the individual line flows to provide better congestion management keeping in view of minimization o...
This project presents a differential evolution (DE) based methodology to relieve congestion and improve quality and cost efficacy of generated power, formulating a penalty based congestion constrained OPF problem in a hybrid thermal-wind power farm. Employing an approach of Demand sensitive loss factor (DSLF) to select the worst possible inadvertent states of the system and the weakest bus of the system in active, reactive loading the algorithm attempts to reschedule the generators to bring down the individual line flows to provide better congestion management keeping in view of minimization of the cost of generation and the line losses not only at normal condition but also stressed loading condition and contingency cases. The results also illuminate a profitable economic situation in favour of proposed system at increased loading where line loss decreases total and total cost in conventional and proposed system converges, also not to forget the better operating conditions in comparison to conventional system.
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