scenario-based planning of participation of virtual power plants in storage and energy markets in terms of load response and market price uncertainty

Environmental concerns, advancements in the new energy industry, and rising power generation and transmission costs are driving the electricity industry towards innovation. this has led to the installation of distributed energy resources (ders) in many regions. virtual power plants (vpps), which manage decentralized energy systems by aggregating the capacity of various distributed generations (dgs), storage devices, and distributable loads, are used for trading energy and services. the research focuses on the planning of price-based unit commitment (pbuc) managed by vpps over a 24-hour period. simulation results demonstrate that the proposed framework effectively develops strategies for vpp market production and consumer interaction, especially with load-shedding capabilities. a key aspect of the study is examining the impact of uncertainties on vpp strategies. probability density functions and the monte carlo method are used to model and assess these uncertainties. simulations without energy price and demand uncertainties indicate that the model is suitable for strategizing vpp market production and consumer interaction. however, simulations that include market price uncertainties and predicted vpp loads show that vpp profits are influenced by market volatility. increased price and demand fluctuations significantly affect vpp strategies, sometimes resulting in losses during certain periods.