Electric distribution network reconfiguration optimized for PV distributed generation and energy storage

•The design of a Binary Particle Swarm Optimization for a three-phase active losses minimization.•The use of Artificial Neural Networks for forecasting photovoltaic penetration.•The use of Energy Storages Systems is taking into account in the optimization. A new power grid PV-based generation techno...

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Bibliographic Details
Published in:Electric power systems research 2020-07, Vol.184, p.106319, Article 106319
Main Authors: Monteiro, Raul Vitor Arantes, Bonaldo, Jakson Paulo, da Silva, Raoni Florentino, Bretas, Arturo Suman
Format: Article
Language:English
Subjects:
Active power losses
Artificial Neural Networks
Binary particle swarm optimization
Distributed generation
Distribution grid
Electric power distribution
Electric power grids
Electric power systems
Electric vehicles
Electricity distribution
Electricity generation
Energy consumption
Energy storage
Energy storage system
Optimization
Particle swarm optimization
Photovoltaic cells
Power flow
Reconfiguration
Retrofitting
Storage systems
System reconfiguration
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Summary:•The design of a Binary Particle Swarm Optimization for a three-phase active losses minimization.•The use of Artificial Neural Networks for forecasting photovoltaic penetration.•The use of Energy Storages Systems is taking into account in the optimization. A new power grid PV-based generation technology presentes engineering challenges in regards to the control and operation of energy storage. Because the utility grid has bidirectional power-flow and further intelligent protection for intentional and unintentional islanding is required. Further, the high penetration of photovoltaics may increase active power losses, and reconfiguration studies must be conducted to analyze such losses and thus optimize system operation. Model based solutions become intractable considering the size of the search space. In this work a Binary Particle Swarm Optimization based solution is presented aiming distribution systems technical power losses reduction though system reconfiguration. Solution validation is carried on the IEEE 37 buses test feeder. A feasibility test is also addressed, and the results show that the BPSO and the use of energy storage systems are efficiently merged resulting in an electric distribution network reconfiguration optimized for PV distributed generation and energy storage, that can retrofit into existing power systems.
ISSN:0378-7796
1873-2046
DOI:10.1016/j.epsr.2020.106319