In this study, a generalizedfuzzy chance constrained programming method is developed for the energy system planning in Guangzhou under multiple uncertainties. Through integrating the generalizedfuzzyprogramming and...
详细信息
In this study, a generalizedfuzzy chance constrained programming method is developed for the energy system planning in Guangzhou under multiple uncertainties. Through integrating the generalizedfuzzyprogramming and chance-constrained programming into an inexact optimization framework, this method can handle uncertainties expressed as probability distributions, fuzzy sets and fuzzy random variables. Solutions of energy supply, power generation, capacity expansion, air pollutant emissions, forest planning, and system cost under different levels of a-cutare obtained considering the constraint violation risk. The results show that the consumption of coal will decline gradually, while natural gas will become the main source of energy supply in the future;the power structure of the city changes from coal to clean energy (e.g., solar, wind, hydro and other renewable energy), and the city's energy supply security is enhanced by stimulating the utilization of renewable energy and reducing the utilization of imported energy. Moreover, a rational use of ecological land is of great significance. Forests can absorb carbon dioxide and will play a positive role in reducing greenhouse effects. When the preferred a value is predetermined by the decision makers, the energy selections can also be obtained directly from the resulting fuzzy membership function. The solutions obtained in the study will help managers to optimize the existing city energy structure, make decisions according to different preferences between system cost and the violation of the constraint, and thus reflect the corresponding energy supply security level. (C) 2018 Elsevier Ltd. All rights reserved.
This study developed a copula-based fuzzy chance-constrained programming (CFCCP) model and applied it to electric power generation systems planning under multiple uncertainties. The CFCCP model was formulated by incor...
详细信息
This study developed a copula-based fuzzy chance-constrained programming (CFCCP) model and applied it to electric power generation systems planning under multiple uncertainties. The CFCCP model was formulated by incorporating existing joint-probabilistic constrained programming and generalized fuzzy linear programming techniques within a general mixed-integer linearprogramming framework. The CFCCP model can not only effectively reflect uncertain interactions among random variables even when the random variables follow different probability distributions and have previously unknown correlations, but can also provide information about the membership grades for the decision variables and objective-function values. Thus, it would have a wider application scope than existing optimization models for power generation systems planking. Its applicability has been demonstrated through a case study of electric power generation planning within a region of North China. As a result, fuzzy interval solutions related to power generation and capacity expansion patterns of electricity-generation facilities, and primary energy supply structures were generated within six scenarios of constraint-violation levels under different a-cut levels. The results are helpful to investigate dynamic features of the regional power generation system, identify desired decision alternatives, and analyze the influences of interactions among multiple uncertainties on system outputs. (C) 2016 Elsevier Ltd. All rights reserved.
暂无评论