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Full-infinite interval two-stage credibility constrained programming for electric power system management by considering carbon emission trading

机译:考虑碳排放交易的电力系统管理的全无限区间两阶段可信度受限编程

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摘要

In this study, a full-infinite interval two-stage credibility constrained programming (FITCP) method is developed for optimizing electric power system (EPS) by considering CO2 mitigation and air pollutant emission control. Through integrating full-infinite programming (FIP), interval two-stage programming (ITSP) and credibility constrained programming (CCP) within a general framework, the developed FITCP method can tackle multiple uncertainties in terms of interval values (both crisp and functional interval values), probabilistic and possibilistic distributions. Then, a FITCP-based electric power system (FITCP-EPS) model has been formulated for EPS planning where carbon emission trading (CET) scheme and air pollutant emission limitation are introduced to cope with the problem of carbon and air pollutant mitigation. Scenarios in response to diverse carbon mitigation levels, different trading schemes and different environmental policies are generated. Moreover, sensitive analysis and value of information analysis are conducted to help decision makers to have a clear view of the effects of data variation and uncertainty data collection. Results reveal that (i) CET scheme can bring more economic benefits for power plants especially when mitigation level is high; (ii) whether the CET is carried out or not, a corresponding construction of carbon capture and storage infrastructure should be implemented to achieve the mitigation target; (iii) the expected system benefit would increase [0, 2.17] % by resolving the uncertainty of CO2 emission levels. The results also indicate that FITCP-EPS model can not only provide an effective linkage between the pre-regulated generation targets and environmental policies, but also generate more decision options under different credibility levels and CO2 emission levels, which are useful for helping decision makers to make appropriate generation targets, plan electricity generation mix, as well as gain in-depth insight into the effects of carbon emission trading and pollutant control on EPS.
机译:在这项研究中,开发了一种全无限间隔两阶段可信性约束编程(FITCP)方法,以通过考虑减少CO2和控制空气污染物排放来优化电力系统(EPS)。通过在通用框架中集成全无限编程(FIP),间隔两阶段编程(ITSP)和可信度约束编程(CCP),开发的FITCP方法可以解决区间值(明晰区间和功能区间值)方面的多种不确定性),概率分布和可能性分布。然后,建立了基于FITCP的电力系统(FITCP-EPS)模型用于EPS规划,其中引入了碳排放交易(CET)方案和空气污染物排放限制,以解决碳和空气污染物缓解的问题。产生了针对不同碳减排水平,不同贸易计划和不同环境政策的情景。此外,进行敏感分析和信息分析的价值可帮助决策者清楚地了解数据变化和不确定性数据收集的影响。结果表明:(i)CET计划可以为发电厂带来更多的经济利益,尤其是在缓解水平较高的情况下; (ii)是否进行了CET,应实现相应的碳捕集与封存基础设施建设,以实现减排目标; (iii)通过解决二氧化碳排放水平的不确定性,预期的系统收益将增加[0,2.17]%。结果还表明,FITCP-EPS模型不仅可以在预先规定的发电目标与环境政策之间建立有效的联系,而且可以在不同的信誉水平和二氧化碳排放水平下产生更多的决策选择,这有助于帮助决策者制定适当的发电目标,计划发电组合,并深入了解碳排放交易和污染物控制对EPS的影响。

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