Coordinated Optimisation of Rural Renewable Energy Accommodation Considering the Spatiotemporal Transfer Characteristics of Urban–Rural Electric Buses

The rapid integration of rural distributed photovoltaics has improved rural energy self-sufficiency. However, because of low rural load density, insufficient midday electricity demand, and limited distribution-network export capability, surplus photovoltaic electricity is difficult to accommodate efficiently on site. To improve rural renewable energy utilisation without relying on large-scale stationary storage or distribution-network expansion, this study proposes an urban–rural coordinated scheduling optimisation method for electric buses with spatiotemporal transfer characteristics. First, the schedulable characteristics of agricultural flexible loads are characterised, and urban–rural electric buses are modelled as mobile energy storage resources linking rural photovoltaic-surplus areas and urban load centres by exploiting their fixed routes, predictable dwell windows, and cross-regional operation. On this basis, a coordinated optimisation model is established with the minimisation of rural photovoltaic curtailment as the primary objective, while also considering disturbances to agricultural production schedules and fluctuations in urban net load. Finally, comparative analyses are carried out under multiple progressive configuration schemes. The results show that the proposed method increases the rural renewable energy accommodation rate from 74.29% to 97.26% while effectively suppressing urban grid load fluctuations. The average daily net cost of the bus fleet is reduced by 9.61% compared with the conventional operation strategy. The results indicate that the coordinated scheduling of agricultural flexible loads and urban–rural electric buses can simultaneously improve rural renewable energy accommodation and smooth urban loads, thereby providing a feasible pathway for coordinated urban–rural energy and transport operation under high penetration of distributed photovoltaics.