Stochastic Optimal Scheduling Study of Virtual Power Plant Based on Multiple Distributed Resources

In the realm of distributed energy operation research, the virtual power plant emerges as a potent strategy to account for system uncertainties and enhance profits for all stakeholders. This paper considers uncertainties related to cybersecurity constraints, electrical and thermal loads, wind speed variations, and market tariff fluctuations. Subsequently, the optimal scheduling challenge for a virtual power plant incorporating multiple distributed resources is formulated utilizing the Generalized Algebraic Modeling System (GAMS) within the IEEE 33 Bus Distributed Test System, and is resolved through the CLPEX solver. Simulation outcomes reveal that the integration of a photovoltaic solar thermal system bolsters the expected profitability of the system and diminishes the virtual power plant's reliance on boilers and cogeneration units.