With the new electrification policies, microgrids will play a key role in the future. This study implements an optimization algorithm for sizing the storage system in an Electric Vehicle (EV) park equipped with PV roofs (2000 kWp) and 40 Charging Stations (CSs), of which 30 are 22 kW and 10 are 120 kW. The model aims to optimize the size of the storage system to ensure an optimal energy balance, maximize the self-consumption of the energy produced, and minimize the cost of buying energy from the grid. The model considers seasonal photovoltaic generation profiles and load scenarios as inputs to simulate system behaviour realistically. The approach complements the prioritized management of available power to the CSs with an economic analysis of the storage system. The results show how the tradeoff between investment costs, reduction of energy deficits, and revenues from the sale of surplus energy determines the optimal storage capacity. The model is first simulated in island mode, simulating worst-case conditions, to identify the ideal capacity of 850 kWh, then the maximum profitability under normal conditions is tested, which results in 52.39 k€ earned in 10 years. The proposed framework offers a versatile solution to improve the economic and energy sustainability of EV charging infrastructure.
Optimized Microgrid Implementation Strategy: A Model for Energy and Profit Efficient ESS
Colombo, Cristian Giovanni;Longo, Michela;
2025-01-01
Abstract
With the new electrification policies, microgrids will play a key role in the future. This study implements an optimization algorithm for sizing the storage system in an Electric Vehicle (EV) park equipped with PV roofs (2000 kWp) and 40 Charging Stations (CSs), of which 30 are 22 kW and 10 are 120 kW. The model aims to optimize the size of the storage system to ensure an optimal energy balance, maximize the self-consumption of the energy produced, and minimize the cost of buying energy from the grid. The model considers seasonal photovoltaic generation profiles and load scenarios as inputs to simulate system behaviour realistically. The approach complements the prioritized management of available power to the CSs with an economic analysis of the storage system. The results show how the tradeoff between investment costs, reduction of energy deficits, and revenues from the sale of surplus energy determines the optimal storage capacity. The model is first simulated in island mode, simulating worst-case conditions, to identify the ideal capacity of 850 kWh, then the maximum profitability under normal conditions is tested, which results in 52.39 k€ earned in 10 years. The proposed framework offers a versatile solution to improve the economic and energy sustainability of EV charging infrastructure.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


