Hybrid Multi-level Stochastic Programming Methods For Multi-factor Energy Systems Management

Energy is the key resource to promote social and economic development and ensure human production and life.The rise of energy consumption and the consumption structure dominated by fossil energy have led to serious environmental problems.In addition,the process of energy production is water resource intensive.Water shortage have limited energy supply and thus increase the energy shortage risk.Energy system is a complex system with multi factors,multi processes,multi links and multi users,which has the characteristics of multiple uncertainties.Therefore,it is urgent to develop energy system planning models based on the robust uncertainty analysis methods for analyzimg the interactive effects among energy,economy,environment and water resources,and formulating scientific and effective development strategies to achieve sustainable development.To solve the above problems,this study developed the hybrid multi-level stochastic programming methods to deal with the uncertainty that parameters can be described as interval valuea,fuzzy sets and multi random variables,and hierarchical decision-making of multi-level managers.Based on the above robust methods,a multi-factor energy system management model can be conducted for planning the energy systems of cities,urban agglomerations and countries.Specifically:(1)an interval single-level programming method based on Monte Carlo simulation is developed for planning the China’s energy-water nexus(EWN)system during 2021-2050,which can deal with the exsited interval and random uncertainties.Three water resource constraint scenarios are set to explore the impact of water resource availability on the EWN system.Results indicate that strict water resource constraints can promote the development of renewable energy and the reorganization of coal-fired power generation technology,and promote energy structure towards water-saving,low-carbon and clean pattern.(2)an interval-fuzzy chance-constrained programming(IFCP)method has been developed by integrating chance-constrained programming,fuzzy programming,and interval-parameter programming within a general framework that can tackle uncertainties expressed as interval values,fuzzy sets,and probability distributions in the objective and constraints.Then,IFCP-EWN model has been formulated for planning energy-water nexus system of Hebei province considering the multiple water withdrawal links of thermal power generation(boiler water,cooling water and desulfurization water).Results can provide decision supports for identifying the optimal electricity supply patterns under different water resource risk scenarios,and achieving adjustment of the conflict among the economic objective,electricity demand and water resources shortage.(3)An interval bi-level joint-probabilistic programming(IBJP)approach is first developed through incorporating bi-level programming and interval jointprobabilistic programming within a framework.IBJP is capabling of balancing the tradeoff between two-level decision makers under uncertainty,tackling uncertainties expressed as joint probabilities and interval values,and examining the risk of violating joint-probabilistic constraints.Then,the developed method is applied to planning China’s EWN system over a long-term planning horizon(2021-2050),considering different cooling technologies(primary cooling,circulating cooling and air cooling).Results can disclose the impact of electricity shortage and/or water resources shortage on EWN system under the bi-level goal of minimizing system water withdrawal and system cost.(4)a copula-based stochastic multi-level programming(CSMP)approach is first developed,where the conflicting objectives with multiple hierarchical levels and the uncertainty presented as random variable with different probability distributions can be tackled.CSMP can also reflect the complex interactions among random variables and examine the risk of violating joint-probabilistic constraints.The CSMP is then applied to planning EEEN system of Pearl River Delta urban agglomeration during the period of 2021-2035.Multiple scenarios corresponding to different joint and individual violation risks of energy consumption and GDP are examined.Results will provide supporting for balancing the conflicts among multi-level decision makers in terms of economy development,environment protection,and ecosystem service value,analyzing the interactions between energy consumption and GDP,and disclosing the impact of individual and joint risks on EEEN system.Summarily,the hybrid multi-level stochastic programming methods are developed for planning multi-factor energy system through intergrating interval parameter programming,fuzzy programming,stochastic programming and multilevel programming methods.They can characterize the complexities and uncertainties existed in system and quantify the nexus among energy,economy,environment and water.Results can not only help decision-makers discern the desired sustainable development scheme,but also support policymaking.