Abstract

Charge scheduling can mitigate against issues arising from excessive electric vehicle (EV) charging loads and is commonly implemented using time-of-use pricing. A charge scheduling strategy to suit vertically structured power systems without relying on time-of-use pricing has not yet been reported, despite being needed by industry. Therefore, a novel charge scheduling strategy to meet this need is proposed in this paper. Key aspects include the provision of a decision-making framework that accommodates for the considerations of transmission and distribution network operators, and the allowance for dynamically changing charging loads through timely forecast updates with reduced communication requirements. A case study based on the Indonesian Java-Bali power system is undertaken to demonstrate the strategy’s effectiveness. Different and realistic EV uptake scenarios are considered, using probabilistic modeling, survey work, and a Monte Carlo modeling approach. Even under slow EV charging conditions case study results show assets are overloaded and high electricity production costs are incurred. These are alleviated through adopting the proposed strategy.

Highlights

  • It suits the scheduling of slow electric vehicle (EV) overnight charging that is expected to be predominant in societies with high levels of EV penetration in residential networks, and which will result in peak loading occurring at night times

  • The proposed smart scheduling strategy allows for coordination between EVs, distribution system (DSO), and a transmission system (TSO)

  • The targeted EV fleets selected by the proposed charging strategies are private EV cars and motorcycles when they plug into networks between 17:30 and 07:00 h

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Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. This paper proposes a novel strategy for vertically structured power systems that is based on charging load prediction obtained from EVs connected to the grid and awaiting charging It suits the scheduling of slow EV overnight charging that is expected to be predominant in societies with high levels of EV penetration in residential networks, and which will result in peak loading occurring at night times. It does not rely on the existence of complex dynamic electricity price signals to control charging demand, and is specific to vertically structured power systems through taking advantage of the nature of power systems in this form to coordinate DSOs and a TSO in a manner to reduce communication requirements. These results are shown from the perspective of a TSO

The Proposed Charge Scheduling Framework and Procedure
The EV Load Model
EV Penetration Scenarios
EV Types
EV Charging Behavior
Simulation Results and Discussion
Conclusions
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