Research on Demand Response Analysis Method for Electric Vehicle Charging Behavior Based on Differentiated Scenarios

Electric vehicles (EVs) have become the core path for carbon reduction in the transportation sector due to their zero emissions and high efficiency advantages. With the breakthrough of V2G technology, EV charging and discharging optimization and vehicle network collaborative control have become the key to improving system efficiency. However, existing research mostly focuses on cost optimization and ignores the differences in multiple scenarios, making it difficult to balance multiple objectives such as economy, power grid stability, and user demand. In response to this gap, this article constructs a multidimensional differentiation analysis framework to analyze the charging characteristics of different types of electric vehicles. Taking typical industrial and residential differentiation scenarios as examples, the total composite load curve of electric vehicles after integration is quantified, and an electric vehicle demand response scheduling model is established to verify the impact of charging behavior optimization on the power grid. Research has shown that the scenario based analysis system can effectively coordinate vehicle network interaction, providing theoretical support and practical paths for solving the problem of new energy consumption and achieving the coordinated emission reduction of transportation and energy systems under the “dual carbon” goal.