Optimally Scheduling Virtual Power Plants Based on Demand Response Across Multiple Timescales

As the construction of new power systems continues to accelerate, an increasing number of small decentralized energy sources are linked to the electricity grid. However, their stochastic, volatile, and decentralized characteristics bring multiple uncertainties to the power system. First, this paper proposes an optimization method for transactions in virtual power plants at different time intervals, both before and during the day, based on demand response. The intra-day scheduling model now includes demand response based on pricing. Secondly, accurate regulation of customer loads is carried out, while a small-scale virtual power plant system is used for arithmetic simulation. Finally, the results demonstrate that the proposed multi-timescale optimal scheduling strategy effectively mitigates power fluctuations while ensuring the system's economic efficiency.