Utilizing flexible, robust optimization for the integration of renewable energy sources and electric cars in a large-scale Vehicle-to-Grid (V2G) network
Аннотация
The development of electric Vehicle-To-Grid (V2G) interaction has the potential to enhance renewable energy consumption and maintain the relationship with the grid. Simultaneously, renewable energy can be harnessed for an adjacent microgrid or integrated into a larger grid to successfully reduce the unpredictability of Renewable Energy Sources (RES). This study presents a method to enhance the security and economics of microgrid systems, considering the growing presence of Electric Vehicles (EVs) and the unpredictable nature of RES. The uncertainty around wind power and the State Of Charge (SOC) of EVs is represented by predicted uncertainties. In the event of the most unfavorable circumstances, this suggested approach can enhance the utilization rate of sustainable energy sources. It does this by effectively managing the charging and discharging of EVs during periods of high demand and low demand, resulting in reduced operational expenses within the limitations of real-world conditions. This work proposes the introduction of a dispatch interval factor to address the issue of excessive caution in robust optimization. This coefficient allows for adjusting the level of caution while enhancing microgrid systems' economic efficiency. The statistical case studies provide evidence of the effectiveness and practicality of the suggested optimisation technique.