Primary Distribution Feeder Reinforcement Model With Network Constraints

Abstract

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.