多目标运输问题的区间模型及其算法

主要给出一类目标函数的系数、供应量和需求量均为区间数的多目标运输问题模型,根据参数的实际意义和区间数的序关系,针对所建立模型,利用区间规划的方法,将其转化为确定型的多目标运输问题,最后用模糊规划技术处理等价的多目标运输问题.数值例子表明算法的有效性和可行性.     

基于灰区间数决策的城市土地集约利用评价

城市土地集约利用评判是典型的区间数多属性决策问题,将基于灰色系统理论的多指标灰区间数关联决策模型应用于城市土地利用状况评价领域,通过引入灰区间数序列的范数完成多指标区间数决策矩阵的规范化处理,建立了多指标区间数整体逼近决策方法,使城市土地集约利用评判方法更加客观.最后通过扬州市城市土地利用状况为实例验证模型的有效性和实用性,为城市土地集约利用评价提供了一种新方法.     

一种具有区间数信息的多目标指派方法

针对具有区间数信息的多目标指派问题,给出了一种指派方法。首先,将不同类型目标的区间数损益矩阵规范化为区间数成本矩阵,并应用区间数运算法则构建区间数多目标指派问题的总成本矩阵。然后,通过事先定义的任意两个区间数的序关系,将区间数指派问题优化模型转化为一个双目标优化模型,并采用线性加权法将其转化为单目标优化模型来进行求解,同时还考虑了如何处理人员数量与任务数量不相等的情形的指派问题;最后,通过一个实例分析说明了本文给出方法的可行性和有效性。本文的方法丰富了已有的求解方法,具有实际应用价值。     

我国可再生能源替代的动力学模型构建及分析

化石能源资源可持续利用就是要保证可再生能源资源转化利用技术的不断提升、直至实现后者对前者潜力性替代.在量化可再生能源利用技术进步水平基础上,结合我国GDP增长目标的确立、化石能源耗竭进程的安排、CO_2减排目标的实现等问题,针对国内化石能源资源可持续利用和限定目标年(2050年)能耗总量两种情景,采用系统动力学模型对我国可再生能源2011-2045年的替代路径进行仿真.在保持化石能源资源年增探明储量10亿吨标煤条件下:维持可再生能源预期投资0.767%的年度GDP规模,国内化石能源资源可持续利用到2045年的GDP年均增速上限是7.01%,"十二五"期间RE累计投资总额为1.88万亿元,2020年的RE替代率为11.53%;在控制2050年我国总能耗为52亿吨标煤的情景下,GDP的年均增速上限是5.705%,"十二五"期间RE投资总额为1.805万亿元,2020年的RE替代率为12.84%.同时,对CO_2减排目标及可再生能源替代率目标的实现进行研究,并给出政策建议.     

带策略约束的区间数双矩阵博弈的双线性规划求解方法

传统区间数双矩阵博弈理论研究局中人支付值为区间数的策略选择问题,但没有考虑局中人策略选择可能受到各种约束.创建一种求解局中人策略选择受约束且支付值为区间数的双矩阵博弈（简称带策略约束的区间数双矩阵博弈）的简单、有效的双线性规划求解方法.首先,将局中人的博弈支付看作支付值区间中数值的函数.通过证明这种函数具有单调性,据此利用支付值区间的上、下界,构造了一对辅助双线性规划模型,可分别用于显式地计算任意带策略约束的区间数双矩阵博弈中局中人区间数博弈支付的上、下界及其相应的最优策略.最后,利用考虑策略约束条件下企业和政府针对发展低碳经济策略问题的算例,通过比较其与不考虑策略约束情形下的结果,说明了提出的模型和方法的有效性、优越性及可应用性.     

基于区间数的区域水资源可持续发展程度评价方法研究

针对区域水资源可持续发展程度评价问题,利用区间数理论提出了基于区间数的可持续发展程度评价模型。首先将评价可持续发展程度中的五个等级标准值定义为区间数,建立实测指标区间向量和理想指标区间向量。其次,利用变异系数法和等权法给出各评价指标的两种权重向量。然后通过计算实测指标向量与每个等级的理想指标区间向量间的贴近度,应用模糊模式识别中的"择近原则"确定拟评区域水资源可持续发展程度的等级。实例研究表明该模型建模方法简便有效,并在各种自然资源可持续发展程度评价中具有推广应用价值。     

带策略约束的区间数双矩阵博弈的双线性规划求解方法

传统区间数双矩阵博弈理论研究局中人支付值为区间数的策略选择问题,但没有考虑局中人策略选择可能受到各种约束.创建一种求解局中人策略选择受约束且支付值为区间数的双矩阵博弈(简称带策略约束的区间数双矩阵博弈)的简单、有效的双线性规划求解方法.首先,将局中人的博弈支付看作支付值区间中数值的函数.通过证明这种函数具有单调性,据此利用支付值区间的上、下界,构造了一对辅助双线性规划模型,可分别用于显式地计算任意带策略约束的区间数双矩阵博弈中局中人区间数博弈支付的上、下界及其相应的最优策略.最后,利用考虑策略约束条件下企业和政府针对发展低碳经济策略问题的算例,通过比较其与不考虑策略约束情形下的结果,说明了提出的模型和方法的有效性、优越性及可应用性.     

基于联系数的定性定量混合多属性区间数决策

针对多属性区间数决策中既有用定量属性又有用自然语言表示的定性属性的这类复杂问题,基于集对分析的联系数理论,把定性属性值先用区间数赋值,再把各属性值区间数转换成二元联系数,建立基于二元联系数的决策模型,利用模型中的确定性联系分量作出初决策,再利用模型中的不确定量作不确定分析,得到终决策.方法简称为"确定性计算+不确定性分析-两步决策法".把以上方法用于电力黑启动决策实例计算和分析,表明方法原理清晰,方法简明,结论可靠,有应用推广价值.     

基于区间犹豫模糊数的多属性决策方法研究及应用

本文针对区间犹豫模糊数的多属性决策问题,从直观可行的角度将区间犹豫模糊数转化为直觉模糊数,并提出重叠区间来减少属性值的元素个数,然后利用优化模型求解属性的权重,最后,从区间犹豫模糊数的机理出发,考虑问题的适用性,以区域企业评价的例子,引用上述方法,得出结论.     

基于三角形区间二型模糊数的综合评价模型

为解决评价过程中分类等级的边界不确定性问题,将二型模糊集引入到模糊综合评价模型中.利用分类等级的边界限值,分别构造三角形二型区间模糊数的上、下隶属函数,在此基础上由观测数据构建相应的区间值模糊评价矩阵,结合指标权重合成得到区间值综合评价向量,最后利用区间数排序的可能度方法得到评价对象的等级隶属向量并给出评价结果.实例分析表明了该模型的有效性。     

可再生能源系统的不确定性优化模型及求解

结合新提出的满意度方法和混合整数规划方法,给出了多态不确定性环境下可再生能源规划模型.该模型综合描述了多地区、多时期、多品种、多部门之间的可再生能源管理系统的复杂性、系统性、动态性和不确定性.最后的实例求解结果说明该模型能很好地反映能源安全性、系统可靠性与系统成本之间的关系,并能给出不同系统违反水平下的能源配置方式及增容计划,为决策者提供决策参考.     

低碳经济范式下能源结构优化程度评价研究

我国的能源瓶颈突出表现为结构性矛盾。本文以能源经济学为理论支撑,从低碳经济发展对能源结构要求的角度,提出了社会经济效益、能源规划效益、环境效益等三个维度,并分析了各个维度的构成要素;综合运用粗糙集理论和AHP法进行指标约简和权值计算,构建了低碳经济范式下能源结构优化程度评价指标体系。在此基础上,对各评价指标设置分级标准,通过未确知测度评价模型对2010年我国10个省份的能源结构优化程度进行多指标综合测度与评价,阐明了该评价方法的科学有效性及评价结果的合理性。     

Statistics and probability theory in renewable energy: Teaching and research

In this paper, the key-role and utility of statistics and probability theory in the field of renewable energy are emphasized and illustrated via specific examples. It is demonstrated that renewable energy is a very suitable field to effectively teach and implement many statistical and probabilistic concepts and techniques. From a research point of view, statistical and probabilistic methods have been successfully employed in evaluating renewable energy systems. These methods will continue to be of core interest for the renewable energy sector in the future, as new and more complex renewable energy systems are developed and installed. In this context, some future research directions in relation to the evaluation of renewable energy systems are also presented.     

Semiparametric spatio‐temporal analysis of regional GDP growth with respect to renewable energy consumption levels

This article evaluates the impact of renewable energy consumption levels on GDP growth. Renewable energy sources may be significantly more costly as compared to classical (fossil) sources. Hence, high relative proportion of renewable energy has the potential of obstructing economic growth. On the other hand, in developed countries, renewable energy adoption processes are often subject to prominent state‐level incentives, administrative ingerence, and fiscal subsidies. For stratified and unbiased evaluation of the overall effect of renewables on GDP, this article applies a spatio‐temporal analysis of GDP growth at the regional NUTS2 level in a conveniently selected group of 11 spatially adjacent yet heterogeneous EU member states. As macroeconomic covariates are controlled for, along with spatial and temporal interdependencies, there is no sign of negative impact of renewable energy consumption on GDP growth. While the estimated overall effect is positive and statistically significant, its economic significance is small. Yet, given the data and economies considered, we may conclude that renewable energy consumption does not exert negative influence on economic growth rates.     

Renewable energy investments under different support schemes: A real options approach

This paper adopts a real options approach to analyze investment timing and capacity choice for renewable energy projects under different support schemes. The main purpose is to examine investment behavior under the most extensively employed support schemes, namely, feed-in tariffs and renewable energy certificate trading. We consider both multiple sources of uncertainty under each support scheme and uncertainty with respect to any change of support scheme, and we obtain both analytical (when possible) and numerical solutions. In a Nordic case study based on wind power, we find that the feed-in tariff encourages earlier investment. Nevertheless, as investment has been undertaken, renewable energy certificate trading creates incentives for larger projects. In our baseline scenario and taking the fixed feed-in tariff as a base, the revenue required to trigger investments is 61% higher with renewable certificates. At the same time, investment capacity is 61% higher.     

基于前景理论的智能输电系统改进灰靶风险决策模型研究

针对我国特高压建设与大规模可再生能源的接入带给智能输电系统的风险,文章提出一种在市场环境下输电系统的风险型多准则决策新方法。该方法基于已构建的智能输电系统风险评价指标体系,考虑指标属性与权重信息的不确定、模糊性以及决策者所持风险态度,结合改进的区间灰数与前景理论,构建了基于前景理论的改进灰靶风险决策模型,最后运用到智能输电系统风险决策案例验证了该方法的合理性和有效性。     

A PRAGMATIC MULTILEVEL APPROACH TO LARGE-SCALE RENEWABLE RESOURCE OPTIMIZATION: A TEST CASE

In recent years, public renewable resource management agencies have devoted substantial effort to local planning. This paper analyzes and evaluates a multilevel approach to utilizing these local planning analyses as an input in developing large–scale (national) resource management plans. This approach is evaluated in a test case with a two–level prototype model that is built from a global model that serves as a standard of comparison. The two–level prototype performs well at the highest level of analysis (involving aggregated variables) but is less reliable in terms of its implications for the lower level planning units.     

基于联系数不确定性分析的区间数多属性决策

区间数多属性决策通常是在某一算法下得到方案的排序,很少考虑区间数不确定性的影响,通过区间数转换成联系数,可以客观地反映区间数的不确定性,在此基础上,建立基于联系数的多属性决策模型,从而对不确定性进行较全面的取值分西,使决策结果更为合理.     

Coping with the Renewable Portfolio Standards: A utility’s perspective

Renewable Portfolio Standards require utilities to supply a percentage of their energy from renewables. Utilities demonstrate their compliance by purchasing renewable energy or renewable energy certificates. Certificates can be traded in a secondary market. This flexibility is intended to foster an efficient environment. Utilities, however, have not been reacting strategically. We formulate the utility’s problem as a stochastic dynamic program and present optimal policies for the utility to trade in the REC market and to purchase from the energy market.     

A decomposition approach to the two-stage stochastic unit commitment problem

The unit commitment problem has been a very important problem in the power system operations, because it is aimed at reducing the power production cost by optimally scheduling the commitments of generation units. Meanwhile, it is a challenging problem because it involves a large amount of integer variables. With the increasing penetration of renewable energy sources in power systems, power system operations and control have been more affected by uncertainties than before. This paper discusses a stochastic unit commitment model which takes into account various uncertainties affecting thermal energy demand and two types of power generators, i.e., quick-start and non-quick-start generators. This problem is a stochastic mixed integer program with discrete decision variables in both first and second stages. In order to solve this difficult problem, a method based on Benders decomposition is applied. Numerical experiments show that the proposed algorithm can solve the stochastic unit commitment problem efficiently, especially those with large numbers of scenarios.