Power supply capability evaluation for unbalanced three-phase distribution network with distributed generators

With the extensive penetration of distributed generators (DGs), especially photovoltaic generators and other intermittent DGs, the intrinsic characteristic of three-phase unbalanced condition of distribution network becomes even more prominent. It brings a new challenge to the evaluation of power su...

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Bibliographic Details
Published in:2017 IEEE Conference on Energy Internet and Energy System Integration (EI2) pp. 1 - 6
Main Authors: Jinquan Zhao, Bing Huang, Bin Zhu, Dawei Su, Haiwei Wu
Format: Conference Proceeding
Language:English
Published: IEEE 01.11.2017
Subjects:
Capacitors
distributed generator
distribution network
Encoding
Generators
Load flow
Load modeling
Mathematical model
power supply capability
quantum-behaved particle swarm optimization algorithm
Reactive power
three-phase unbalance
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Summary:With the extensive penetration of distributed generators (DGs), especially photovoltaic generators and other intermittent DGs, the intrinsic characteristic of three-phase unbalanced condition of distribution network becomes even more prominent. It brings a new challenge to the evaluation of power supply capability (PSC) for distribution network. The evaluation model of PSC for unbalanced three-phase distribution network with DGs is proposed. In this model with the objective of maximizing the power supply load for distribution network, the operation constraints of bus voltage magnitude, branch current, transformer capacity, packet switch capacitor and three-phase bus voltage unbalance degree are taken into account. An algorithm of quantum particle swarm optimization (QPSO) was put forward to solve this problem. The algorithm uses the advantages of superposition state and probability expression, which improves the ability for global optimization. The simulation results of the modified IEEE33-bus three-phase distribution system show that the proposed model and algorithm are effective.
DOI:10.1109/EI2.2017.8245529