Hybrid Single-level/Bi-level Optimization Methods For The Management Of Energy And Environmental Systems

With the increasing of energy consumption and the deterioration of ecological environment,energy system transition is becoming prominent.Energy saving and emission reductions,as an important objective of energy development,has become an effective measure to ensure China’s energy security,reduce environmental pollution,mitigate greenhouse gas emissions,and keep social and economic development sustainablility.However,the scale of research is becoming more and more complex.How to quantify the characterization of energy systems and analyze the influence of different measures,are the key to achieve energy conservation and emissions reduction for energy planning.In this study,the mathematical model and method would be used to quantify the complexity and uncertainty of the energy systems.At the same time.a number of energy and environmental planning models would be developed through integrating different reduction measures into the energy system models:(1)a superiority-inferiority interval full-infinite programming method is developed for analyzing the effect of energy efficiency under uncertainty,which can effectively tackle uncertainties expressed as fuzzy sets,crisp intervals and functional intervals,it also can directly reflect relationships among multiple fuzzy sets through varying superiority and inferiority degrees with a high computational efficiency.(2)a robust interval-fuzzy programming method is developed for supporting low-carbon transition of electricit-power system of Bazhou through clean development mechanism.The proposed method can deal with flexibility constraints and uncertainty of parameters in the objective function and constraints,incorporating risk aversion into the optimization model and providing robust solutions under different penalty values;the results can help decision makers establish a reasonable balance between the optimality and feasibility.(3)an interactive fuzzy chance-constrained resolution method is developed for supporting clean energy planning for Bazhou under uncertainty.It can not only tackle multiple uncertainties presented as fuzzy membership functions and probability distributions using an interactive resolution method,but also enable decision makers to seek optimal solutions between satisfaction degree of objective and feasibility of constraints.Different scenarios associated with energy policies are designed to analyze the impact of energy structure adjustment on energy consumption,system cost,capacity expansion,as well as emission reduction.(4)integrating interval-fuzzy stochastic programming into framework of carbon capture deployment,the developed model can be used for planning electric-power system with carbon emission abatement under uncertainty.The proposed method jointly considers the possible lack of knowledge in data and existing fuzziness.and can be used to tackle multiple uncertainties(interval values.fuzzy sets,and probability cdistributions).’Then scensitivity analyses related to carbon capture investment are performed to assess the influence of various factors(e.g.,fuel cost,investment,mitigation level etc.)on system cost.(5)a series of inexact bi-level programming methods are proposed for supporting energy and environmental systems management,which can address the tradeoffs among different decision makers in two decision-making levels through prioritizing the most important goal.The model is formulated for energy system of Beijing,in which the upper-level decision maker is environmental management and the lower-level decision maker is energy system planning.The process of calculation can balance the benefit of different decision-makers from a holistic perspective.The optimization results can provide technical support and policy suggestions for the regional energy systems planning and environmental management.Through introducting fuzzy mathematical programming(i.e.,superiority-inferiority fuzzy programming,robust programming,possibility programming),bi-level programming,as well as interval full-infinite programming,stochastic programming,a series of hybrid optimization methods are developed.Then,single-level and bi-level models for energy and environmental management are proposed through integrating the measures of emission reductions(i.e.,clean development mechanism,carbon capture technology and energy conversion efficiency)into the energy systems model.According to the real case study(Bazhou and Beijing),solutions of energy production,processing,energy conversion(power generation,heating),energy supply,pollutant emission,cost,and the system risk are obtained.Results not only quantify the impact of different emission reduction measures on energy and environmental systems under uncertainty,but also provide relevant policy suggestions for the transition of energy development.