Primary Distribution Feeder Reinforcement Model with Network Constraints

The paper evaluates the primary distribution feeder reinforcement options due to increased electrical demand. A sizing and allocation optimization model based on stochastic Mixed Integer Nonlinear Programming (MINLP) is proposed to realize and asses various electrical distribution feeder upgrade opt...

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Bibliographic Details
Published in:IEEE access 2023-01, Vol.11, p.1-1
Main Authors: Almehizia, Abdullah A., Al-Ismaili, Fahad S.
Format: Article
Language:English
Subjects:
Batteries
Cables
Clustering
Constraint modelling
Costs
Demand
Distribution network expansion
Energy storage
feeder upgrade
hybrid systems optimization
Industrial areas
Load modeling
Mixed integer
Nonlinear programming
Normal distribution
Optimization models
Photovoltaic cells
Planning
Power cables
Reactive power
Reinforcement
Storage systems
Transformers
Uncertainty
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Summary:The paper evaluates the primary distribution feeder reinforcement options due to increased electrical demand. A sizing and allocation optimization model based on stochastic Mixed Integer Nonlinear Programming (MINLP) is proposed to realize and asses various electrical distribution feeder upgrade options. The options include transformer reinforcement, adding new cables, installing Photovoltaic (PV) systems, and Battery Energy Storage systems (BESSs). Scenario generation and clustering address the demand and PV power uncertainties. A normal distribution is used to model the demand uncertainty and provide a sensitive insight into the system. The developed model was tested on an 18-bus distribution feeder from an industrial area in Riyadh, Saudi Arabia. The results identified BESS and PV systems as viable reinforcement options.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3309558