Research On Optimal Scheduling Of Virtual Power Plant Considering Demand Side Response

Under the guidance of the "30·60" dual-carbon target,the traditional power system is transforming towards a new power system dominated by new energy.The proportion of renewable energy in virtual power plant is continuously increasing,however.the inherent stochasticity and volatility of renewable energy output will unavoidably bring greater challenges to the optimal operation of virtual power plant.With the development of the energy internet and the deepening reform of the power system,more diverse types of entities will be aggregated by virtual power plant,the virtual power plant is gradually transitioning towards multi-energy flow comprehensive energy virtual power plant,and the market in which they can participate in transactions is no longer single.Traditional virtual power plant operating strategies and optimization scheduling methods are no longer adequate,hence a specific and feasible set of optimization operation strategy needs to be established,to ensure that all entities can make optimal decisions while balancing the interests of all parties involved.In addition,multiple uncertainties such as renewable energy output,demand response,and market prices in virtual power plant present higher requirements for system optimization and scheduling.Moreover,the energy coupling features of multi-energy flow comprehensive energy virtual power plant are obvious and the mechanism is complex,which makes it difficult to model and solve the system.Therefore,deep mining historical data information on uncertain factors and making full use of decoupling resources have positive implications for virtual power plants to formulate the optimal decisions.Starting from the modeling of comprehensive energy virtual power plants,the participation of virtual power plants in electricity-carbon joint market transactions is considered in this paper.Based on the master-slave game theory,the optimal operation strategy of virtual power plant is studied,the uncertainties and energy coupling characteristics in the operation process are analyzed,and then the optimization scheduling method of virtual power plants considering multiple uncertainties is studied,this provides a reference for virtual power plants to participate in collaborative optimal scheduling of multiple market transactions.The specific research contents are as follows:(1)An optimized scheduling basic model for comprehensive energy virtual power plant is established.The basic structure of the virtual power plant,which includes cogeneration units,renewable energy units,gas boilers,and demand response is constructed,and the operational characteristics of each unit within it is analyzed and modeled,providing a theoretical foundation for the optimized scheduling of virtual power plant.(2)A master-slave game optimization scheduling strategy for virtual power plant considering demand side response is proposed.For virtual power plant with comprehensive energy and demand response,a master-slave game framework for electricity-carbon joint market transactions is designed,and a master-slave game model is established to achieve the optimal scheduling strategy for virtual power plant to participate in joint market transactions.While satisfying the balance between supply and demand of the entire system,the interests of various entities within the virtual power plant are balanced.The feasibility and economy of optimizing the operation strategy of virtual power plants and participating in multi market transactions are verified through numerical simulation.(3)A distributed robust optimal scheduling strategy for virtual power plant considering multiple uncertainties is proposed.Considering the uncertainties in the operation process of virtual power plant and the thermal-electric coupling characteristics of combined heat and power unit,a low-temperature waste heat power generation system based on organic rankine cycle is introduced to increase the flexibility of the virtual power plant.Using data-driven distributed robust optimization method,a distributed robust optimization scheduling model considering multiple uncertainties is established.This model not only improves the flexibility and economic efficiency of the virtual power plant but also ensures that it has a stronger ability to resist the risks of multiple uncertainties.