Coordinated Optimal Scheduling Of Combined Heat And Power-Virtual Power Plants

The high proportion of renewable energy is constantly infiltrating into the virtual power plant,and the randomness and fluctuaction of renewable energy raise higher requirements for the optimal dispatching of virtual power plants.The energy conversion and information interaction between the power system and the heating system are increasingly frequent.The development of combined heat and power-virtual power plants is not only an effective means to integrate all kinds of distributed energy units to realize synergetic dispatching,but also an important fulcrum for deepening power reform and optimizing economic structure.In the operation dispatching of the combined heat and power-virtual power plant,the traditional operation mode and profit allocation of the power system are not conducive to the consumption of renewable energy and the enthusiasm of various stakeholders.It is urgent to establish a set of practical operation strategies to determine the optimal decision-making and balance the interests of various stakeholders.In addition,the uncertainties of renewable energy output,load demand,and market price bring severe challenges to the collaborative optimization of the combined heat and power-virtual power plant.Moreover,the mechanism of heat and power coupled system is complex,and the involved nonlinear and nonconvex models bring difficulties to the system modeling and solution.It is necessary to fully mine the historical data information of uncertainties to make optimal decisions,increase the renewable energy consumption,and realize the bidirectional interaction between the generation side and the consumption side.Based on the modeling of the combined heat and power-virtual power plant system considering uncertainties,the optimal profit allocation strategy of the combined heat and power-virtual power plant is studied in this paper.Combined with the characteristics of the heat network,the optimal scheduling method of combined heat and power-virtual power plant based on data-driven is studied,which provides a reference for the collaborative optimization of the combined heat and power-virtual power plant,and ensures the safety,economy,and reliability of energy from production,transmission,and usage.The main contents of the thesis are as follows:(1)The optimal scheduling model of the combined heat and power-virtual power plant considering uncertainties is established.The concept of the combined heat and power-virtual power plant including renewable energy units,energy storage devices,combined heat and power units,electric heating pumps,and demand response is proposed.Considering the operation characteristics of the internal power supply,the analysis and modeling of the internal units are carried out.The uncertainties in the optimization process of the combined heat and power-virtual power plant are classified and the solutions are proposed to achieve the optimal power balance and economic objectives of the system.(2)A stochastic optimal scheduling strategy of the combined heat and power-virtual power plant based on cooperative game is proposed.Considering the uncertainty of renewable power generation,a cooperative game model is established to realize the optimal dispatching of the combined heat and power-virtual power plant.An improved Shapley value method is proposed to optimize resource allocation and reduce the reduction of renewable energy while meeting the interests of all stakeholders and the power and heat balance of the whole system in the coupled heat and power network.(3)A distributionally robust optimal scheduling strategy of the combined heat and power-virtual power plant considering the characteristics of heat supply network is proposed.Based on the operation mode of the heating system,the heating network model considering the characteristics of the heating network is established,and the HOMIE model is introduced to increase the flexibility of the system.Based on the Wasserstein distance,a distributionally robust optimization scheduling model is built to reduce the conservatism of decision making.By introducing the real-time programming of the electricity price and adjusting the output of each power generation in real time,the operation economy of the combined heat and power-virtual power plant is effectively improved on the premise of meeting the user's comfort.(4)A data-driven stochastic robust optimal scheduling strategy for the combined heat and power-virtual power plants is proposed.Based on the historical datasets of the wind power output,the photovoltaic output,and the load demand,a data-driven ambiguity set is constructed based on Dirichlet process mixture model and variational inference algorithm.Aiming at the two-stage problem of the combined heat and power-virtual power plant participated in the energy market and reserve market,a two-stage stochastic robust optimal scheduling model is established to fully utilize internal resources and obtain higher revenue.A tailored column and constraint generation algorithm is proposed to solve the problem,which can effectively improve the processing speed.