含水产养殖温室的乡村综合能源系统分布鲁棒日前调度OA北大核心CSTPCD

With the implementation of the national"double carbon"policy and the great strategy of"Rural Revitalization",the traditional rural energy system based on primary energy has been unable to meet the needs of rural energy utilization in the new era due to its high energy consumption,high pollution and other defects.Integrated energy systems (IES)combine multiple energy types to achieve coordinated scheduling of multiple energy sources,effectively reduce system operating costs and carbon emissions,and improve energy efficiency.However,most of the existing studies on ies focus on cities or industrial parks,and lack of relevant studies in rural areas.China is a large agricultural country,and the rural population accounts for more than 20％ of Chinese total population.This paper proposes an integrated rural energy system (IRES)optimization framework,and carries out research from three aspects:the modeling of typical smart agricultural load,the construction of rural integrated energy system model,and the optimal operation of IRES considering uncertainty,so as to provide reference for the transformation and development of rural energy system,and help the high-quality development of rural areas.Based on the above background,firstly,according to the principle of heat and moisture balance,the mathematical model of thermal environment of large aquaculture greenhouse is established.The model includes roof heat balance equation,indoor air heat balance equation and aquaculture water and heat balance equation.According to the principle of heat flow,the energy consumption model of aquaculture greenhouse is constructed,which provides a model basis for the optimal scheduling of IRES. Secondly,taking the energy consumption model of aquaculture greenhouse as the core,combined with energy production,conversion,storage equipment and various types of loads,a framework model of rural comprehensive energy system including electricity,heat and gas is established. Finally,aiming at the uncertainty of solar radiation,ambient temperature and residential power load in the dispatching process,a robust dispatching model based on IRES distribution is established by using Kullback Leibler divergence.The objective of the model is to minimize the operation cost in a dispatching cycle,and the prediction errors of solar radiation intensity,photovoltaic output power load,ambient temperature and residential power load are taken as random variables.The operation limits of rural load,biogas digesters,energy conversion and storage equipment and other components are expressed as deterministic constraints,and the random variables are expressed as distributed robust opportunity constraints.For the established distributed robust scheduling model,Bernstein approximation theory is used to transform the model into a deterministic mixed integer linear programming (MILP)model,which is solved by GUROBI solver. The results show that the IRES model constructed in this paper has significant advantages over the traditional rural energy model with high carbon emissions and high costs.In addition,compared with stochastic optimization and robust optimization,the distributed robust optimization method effectively balances the robustness and economy of the system.This study provides a theoretical reference for the transformation and development of rural energy structure,and contributes to the high-quality development of rural energy network.