Research On Complex System Optimization And Management With Renewable Energy Accommodation Under Uncertainty

With the high-speed economic development and incremental population growth,energy consumption and demand have been daily on the increase,and the contradiction between energy supply and demand has become increasingly prominent.Meanwhile,the excessive consumption of fossil fuels has resulted in serious environmental pollution,which has restricted the sustainable development of soeciety,economy and environment.Nowdays,renewable energy with the advantages of clean,friendly,low-carbon and energy saving,has been the focus of world attention.However,there still exist some severe issues in the process of renewable energy development in China,for example,unreasonable planning,inadequate utilization and low consumption proportion of renewable energy.Moreover,there are mutilple of complicated factors in the energy system,such as the dynamic variation of energy demand,the uncertain policy of energy strucure adjustment and future energy,bringing challenges to energy system management.Therefore,it is significant to conduct research on the energy system optimization and management coupled with renewable energy accommodation,which would be helpful for transforming energy development pattern,enhancing renewable power generation porportation,optimizing energy resources allocation and improving environmental quality.Aiming to promote renewable energy development and optimize energy system management,based on the comprehensive analysis of the characteristics of regional energy system associated with uncertaintites and complexities,and the integrated inexact optimization methods through combining stochastic programming,fuzzy programming and interval programming,this research would develop a series of optimization models for regional energy system considering renewable energy accommodation under uncertainty.Through integrating stochastic programming,fuzzy programming and interval programming,these models could reflect the trade-off among system economy,environmental objective and system risk,and then would be applied to the energy planing of Shandong Province and Tangshan City,which could provide scientific decision supports for regional energy and environmental system management.In detail,the main research contents are as follows:(1)In order to handle the uncertainties of renewable energy output power,an interval two-stage stochastic fuzzy credibility programming has been developed through integrating interval-parameter programming,two-stage stochastic programming and fuzzy credibility constrained programming into a general framework for regional electric power system considering the risk caused by the forecasting error of renewable energy output.In the model,the fuzzy credibility constrained can be transformed into their equivalent forms;(2)For the situation of low proportion of renewable power generation,an interval two-stage stochastic robust programming model has been proposed for supporting the electric power system planning of Shandong Province,which would integrate interval-parameter programming,two-stage stochastic programming and stochastic robust programming.Though setting different renewable energy development objectives,the model would generate a series of electricity generation,imported power and facility expansion schemes;(3)To reflect the effects on renewable energy development from incentive policies,though introducing the subsidy policy,an interval two-stage stochastic robust mixed integer proramming has been developed for electric power system management of Tangshan City.The model can provide various of optimized schemes under different feed-in tariff scenarios and be helpful for decision makers to fomulate resonable development strateges within considering the benefit balance;(4)Based on the synthetical analysis of energy system features and prominent issues,an interval fuzzy mixed integer programming has been formulated for energy system management of Tangshan City under consideration of promoting renewable energy development.Energy resources allocation capacity expansion and polution mitigation plans are obtained.The model is benificial for decision makers to analyze the trade-off among system cost,energy supply security and environmental requirement,and manage regional energy system coupled with renewable energy.The obtained results indicated that the proposed inexact opitmization methods can effectively trackle complexities and uncertainties existing in complex energy system.The developed energy system planning model coupled with renewable energy accommodation can provide scientific decision alternatives and forward-looking suggestions for energy system management under uncertainty,and thus accelerate the development of renewable energy,propel the optimization and upgrade of energy structure,and achieve the sustainable development of energy system.