Optimal Battery Energy Storage System Sizing and Placement in Low Voltage Distribution Network

Emerging robust electric vehicle charging using photovoltaics

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Abstract

Electric Vehicles (EVs) provide a promising sustainable clean mode of transportation with much fewer emissions compared to the traditional Internal Combustion Engine (ICE) vehicles. However, this can only be considered true if the energy sources used for charging EVs are also from clean energy form. Various Renewable Energy Sources (RES) are available to provide the EVs charging demand. Nevertheless, due to intermittency power generation characteristic of RES, there is a high risk of supply and demand power mismatch. A grid-connected topology system is commonly used as a backup for lack or over power supply from RES generation. Even though, this configuration may lead to new problems of under/over voltage issues and maximum transformer/lines loading capacity due to RES fluctuation power production. The storage system is considered necessary to be installed in the system as a buffer of the power mismatch and also reducing the grid stress. Excellent approximation of storage sizing and placement is mandatory to provide satisfactory influence to the overall system technically and economically.

This study proposes optimization strategy for optimal battery sizing and placement with optimal power management system in the EVs charging station using photovoltaics (PV) power in a low voltage distribution network using Mixed Integer Linear Programming (MINLP) algorithm. The lithium-ion battery is considered in this project because of its relatively high power and energy density characteristic along with low self-discharging. The radial low voltage CIGRE benchmark is adopted as a model topology to evaluate the performance of the proposed optimization strategy. Dynamic daily electricity price, residential load, and PV power profile of the Netherlands are taken into account in this project. Furthermore, the research project implements several case studies using DICOPT (Discrete and Continuous OPTimizer) solver in GAMS (General Algebraic Modelling System) software with MATLAB interfacing. As the main result, proper EVs charging strategy with optimal battery sizing and placement with the appropriate power management system is successfully maintaining the system away from the grid violation while at the same time reducing the total cost of the system.

Keywords: EV-PV charging, optimal battery sizing and placement, MINLP