AI SearchMulti-objective distributed generation optimal placement in distribution system using nondominated sorting particle swarm optimization
Call Number: AIT Thesis no.ET-10-32 Material type:
SeriesSeries: Asian Institute of Technology. Thesis ; no. ET-10-32Publication details: Pathum Thani, Thailand : Asian Institute of Technology, 2010Description: 57 leaves : ill. + 1 online resourceSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology, 2010 Summary: This thesis proposes the non-dominated sorting particle swarm optimization (NSPSO) algorithm for multi-objective optimal placement for distributed generation (DG) in the distribution system to minimize the total real power loss and DG investment cost Four difference types of DG are used including DG supplying real power only, DG supplying reactive power only, DG supplying real power and consuming the reactive power, and DG supplying both real and reactive power. The Pareto front based non-dominated sorting particle swarm optimization algorithm (NSPSO) is representing non-dominated sorting solutions of two multi-objective functions. A fuzzy decision making analysis is used to obtain the final trade off optimal solution. The 33 and 69 bus radial test systems are used in the simulation. The NSPSO can obtain pareto front between real power loss and investment cost for optimally placed multi distributed generations on four different types of DG
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A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Energy
Thesis (M.Eng.) - Asian Institute of Technology, 2010
This thesis proposes the non-dominated sorting particle swarm optimization (NSPSO) algorithm for multi-objective optimal placement for distributed generation (DG) in the distribution system to minimize the total real power loss and DG investment cost Four difference types of DG are used including DG supplying real power only, DG supplying reactive power only, DG supplying real power and consuming the reactive power, and DG supplying both real and reactive power. The Pareto front based non-dominated sorting particle swarm optimization algorithm (NSPSO) is representing non-dominated sorting solutions of two multi-objective functions. A fuzzy decision making analysis is used to obtain the final trade off optimal solution. The 33 and 69 bus radial test systems are used in the simulation. The NSPSO can obtain pareto front between real power loss and investment cost for optimally placed multi distributed generations on four different types of DG
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