Citation: Rubino, L.; Rubino, G.; Esempio, R. Linear Programming-Based Power Management for a Multi-Feeder Ultra-Fast DC Charging Station. Energies 2023, 16, 1213. https:// doi.org/10.3390/en16031213 Academic Editor: Giovanni Lutzemberger Received: 21 December 2022 Revised: 11 January 2023 Accepted: 17 January 2023 Published: 22 January 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). energies Article Linear Programming-Based Power Management for a Multi-Feeder Ultra-Fast DC Charging Station Luigi Rubino 1, * ,† , Guido Rubino 2,† and Raffaele Esempio 1,† 1 Department of Engineering, University of Campania Luigi Vanvitelli, 81031 Aversa, CE, Italy 2 Department of Electrical and Information Engineering (DIEI), University of Cassino and South Lazio, 03043 Cassino, FR, Italy * Correspondence: luigi.rubino@unicampania.it; Tel.: +39-081-5010317 † These authors contributed equally to this work. Abstract: The growing number of electric vehicles (EVs) affects the national electricity system in terms of power demand and load variation. Turning our attention to Italy, the number of vehicles on the road is 39 million; this represents a major challenge, as they will need to be recharged constantly when the transition to electric technology is complete. If we consider that the average power is 55 GW and the installed system can produce 120 GW of peak power, we can calculate that with only 5% of vehicles in recharging mode, the power demand increases to 126 GW, which is approximately 140% of installed power. The integration of renewable energy sources will help the grid, but this solution is less useful for handling large load variations that negatively affect the grid. In addition, some vehicles committed to public utility must have a reduced stop time and can be considered to have higher priority. The introduction of priorities implies that the power absorption limit cannot be easily introduced by limiting the number of charging vehicles, but rather by computing the power flow that respects constraints and integrates renewable and local storage power contributions. The problem formulated in this manner does not have a unique solution; in this study, the linear programming method is used to optimise renewable resources, local storage, and EVs to mitigate their effects on the grid. Simulations are performed to verify the proposed method. Keywords: ultra-fast charging; electric vehicles (EVs); power management (PM); grid-connected converters 1. Introduction Recently, SoCial, economic, and environmental factors sustained by government poli- cies have increased interest in and support for the electrification of transportation [1,2]. In this context, most major car manufacturers have proposed new electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) that can reduce greenhouse gas emissions by phas- ing out all combustion vehicles [3]. Renewable sources affect power grid stability, owing to intermittent production, and by increasing the installed renewable power sources, negative effects will further increase [4]. Therefore, electricity companies are investing in large amounts of energy storage to stabilize the grid. For example, in Italy, the national electric power transmission SoCiety TERNA built an experimental storage plant that is physically distributed throughout the territory, reaching a total of 10 MW [5]. Currently, the most effective techniques with a reduced impact on the electricity grid are local generation from renewable sources using an energy storage system [6,7]. Based on this idea, some countries, such as Italy, encourage photovoltaic installation for residences with the addition of local storage [8,9]. It must also be considered that the increase in electric vehicles compared to the past brings a new problem; the high demand for electrical power during grid-to-vehicle (G2V) simultaneous charging can be higher than the power grid’s capability, leading to grid instability [10–14]. In [12], the load-shifting method was indicated as a possible solution to grid overload, owing to power peak shaving and power valley filling. In other words, by distributing power absorption during the day, the grid’s power can be averaged, resulting Energies 2023, 16, 1213. https://doi.org/10.3390/en16031213 https://www.mdpi.com/journal/energies