## 4 Conclusions  
The presented literature review on forecasting models for the aggregate capacity provided by EVs in support of the electricity grid highlights several critical input attributes that impact the effectiveness and accuracy of these forecasts. Analyzing these attributes is crucial to optimizing the integration of electric vehicles into the grid, improving energy management, and ensuring a proper response to fluctuations in energy demand and supply. The key input attributes to forecast aggregate capacity include battery capacity, charging time, and available residual energy, as well as travel patterns and user charging habits. Battery capacity directly affects the amount of energy that can be stored and subsequently delivered back to the grid, while travel patterns and charging habits determine the frequency and amount of energy available at any given time. In addition, the residual charge in vehicles, which represents the energy left in the battery after a trip, is crucial to accurate aggregate capacity forecasts. Studies highlight that environmental variables, such as extreme temperatures and humidity, as well as user behavior factors, such as frequency and distance of travel, significantly impact aggregate capacity. Climatic conditions can affect battery performance and availability, while user habits determine when and how often vehicles are available to supply energy to the grid. The effectiveness of the forecasting models is also influenced by the technologies and charging infrastructure available. The implementation of smart charging stations and advanced energy management is essential to optimize the use of the aggregate capacity of electric vehicles. Furthermore, the electricity grid management systems must be able to integrate and coordinate the energy resources provided by electric vehicles effectively. Despite the progress, there are still significant challenges in accurately forecasting aggregate capacity. Variability in user behavior and environmental conditions requires the development of more sophisticated and adaptable predictive models. Improving the collection and analysis of data on charging behaviors and environmental conditions and developing advanced algorithms that can anticipate and manage fluctuations in energy availability are essential. To optimize the use of the aggregate capacity of electric vehicles, supportive regulatory and policy frameworks are needed to promote the adoption of advanced charging technologies and the integration of vehicles into the grid. Policies should encourage user participation in V2G programs and invest in infrastructure that facilitates vehicle-grid interaction. Therefore, the transition to a decarbonized transportation system is seen as difficult in comparison to other economic sectors. Decarbonizing urban mobility can be achieved through a variety of technological and regulatory approaches. But a decarbonized urban transportation system cannot be achieved only by technical advances. They have to be supplemented with actions that target travel patterns and cause a change in the daily mobility behaviors of people. To achieve climate neutrality, reduce traffic, air pollution emissions, noise pollution, and other negative consequences of excessive reliance on fossil fuel-based transportation, organizations in the public sector (local and regional authorities) and the private sector (businesses, organizations, and institutions) must develop urban mobility management plans that include such challenges in mobility strategy. Such a literature review can be seen as a first step to guiding future research to include a manifold picture of the user into V2G research, and the findings guide its further advancement. How users' requirements and demand characteristics are included in innovative business schemes should be addressed in the review, resolving stakeholders' concerns and establishing supportive regulatory frameworks.