Energy management method for energy storage system in PV-integrated EV charging station

Shi, Shenxing; Zhang, Yu; Ni, Luan; Yang, Qixing; Fang, Chen; Wang, Haojing; Wang, Yufei; Shi, Shuntian

doi:10.1109/icpeca51329.2021.9362623

Cited by 6 publications

(2 citation statements)

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“…Equation (6) indicates that the problem is linear with limits; for these reasons, the authors adopted a linear optimisation method for the solution, as explained in this subsection. Assuming that variables are functions of k, without a lack of generalities, the dependent variable is not reported hereafter.…”

Section: Proposed Linear Programming Optimization Methodsmentioning

confidence: 99%

“…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].…”

Section: Introductionmentioning

confidence: 99%

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Linear Programming-Based Power Management for a Multi-Feeder Ultra-Fast DC Charging Station

Rubino

Esempio

2023

Energies

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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.

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Section: Proposed Linear Programming Optimization Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%