A two-layer optimal scheduling method for multi-energy virtual power plant with source-load synergy

With the increasing penetration of clean energy sources such as wind power and photovoltaic in the grid, the volatility, intermittency, and randomness of their power output have impacted the safe and stable operation of the grid. To address the challenges posed by scheduling and the potential wastage of renewable energy due to these factors, a two-layer optimal scheduling model for a virtual power plant that takes into account source-load synergy is proposed in this paper. In the upper model, emphasis is placed on demand response strategies to optimize load-side dispatch. This includes encouraging customers to adjust their electricity consumption patterns through time-of-use pricing and effectively managing controllable loads for peak shaving and valley filling. These actions collectively aim to maximize the virtual power plant's overall performance. The upper-tier model then communicates the power output to the lower-tier model. In the lower model, we consider the costs associated with wind, photovoltaic, thermal, and energy storage power generation to optimize power-side scheduling. This approach ensures a comprehensive optimization process, addressing both demand and power generation aspects of the virtual power plant's operations. Compared to existing research, this paper takes into account the impact of various clean energy sources, meticulously categorizes controllable loads, and conducts in-depth modeling and analysis of demand response. Finally, the results of optimal scheduling of the virtual power plant under different scenes are compared and analyzed using examples, to validate the effectiveness of the proposed method.