A stochastic vehicle schedule model for demand response and grid flexibility in a renewable-building-e-transportation-microgrid

Vehicle-to-building interaction as one of emerging and promising techniques shows powerful functions, to address intermittence of renewable energy, stochastic demand of buildings, power grid stability, and frequency regulation. The energy interaction magnitude is highly dependent on stochastic vehicle schedules, whereas a few studies focus on stochastic model development and guidelines on vehicle schedules. In this study, a series of stochastic models were developed to characterise the arrival time, departure time, and detention time-duration of vehicles in buildings. Considering the schedule difference between private cars and shuttle buses, both Chi-square distribution and Normal distribution were adopted, to quantify the distribution degree of vehicle numbers, together with parametrical analysis on standard deviation. Comparative analysis between different stochastic models can guide vehicle schedules and provide flexible vehicle-to-building interactions. Research results indicate that, normal distribution on arriving time and detention time-duration of vehicles shows the minimum annual import cost (ICannual) at 128.1 HK$/m2·a, while the normal distribution on arriving time and departure time with Chi-square distribution for detention time-duration shows the minimum equivalent CO2 emission (ECEannual) at 38.6 kg/m2·a. Furthermore, in respect to the distribution degree of vehicle numbers, the sharper curve for vehicle numbers in buildings (with lower standard deviation) will lead to a lower ECEannual and ICannual. Dynamic energy management strategy for the optimal stochastic vehicle schedule indicates that, marginal impacts on import cost saving can be provided to local power grid due to the limited difference between off-peak and peak grid electricity prices. This study provides new insight into the stochastic vehicle schedule model for an interactive vehicle-to-building energy interaction framework. Research results can provide frontier guidelines on stochastic vehicle schedules and flexible vehicle-to-building interactions for techno-economic-environmental performance improvement.