A deterministic linear programming model which optimizes the abatement of each SO2 emission source, is extended into a CCP form by introducing equations of probabilistic constrained through the incorporation of uncert...A deterministic linear programming model which optimizes the abatement of each SO2 emission source, is extended into a CCP form by introducing equations of probabilistic constrained through the incorporation of uncertainty in the source-receptor-specific transfer coefficients. Based on the calculation of SO2 and sulfate average residence time for Liuzhou City, a sulfur deposition model has been developed and the distribution of transfer coefficients have been found to be approximately log-normal. Sulfur removal minimization of the model shows that the abatement of emission sources in the city is more effective, while control cost optimization provides the lowest cost programmes for source abatement at each allowable deposition limit under varied environmental risk levels. Finally a practicable programme is recommended.展开更多
Recent research on deterministic methods for circulating cooling water systems optimization has been well developed. However, the actual operating conditions of the system are mostly variable, so the system obtained u...Recent research on deterministic methods for circulating cooling water systems optimization has been well developed. However, the actual operating conditions of the system are mostly variable, so the system obtained under deterministic conditions may not be stable and economical. This paper studies the optimization of circulating cooling water systems under uncertain circumstance. To improve the reliability of the system and reduce the water and energy consumption, the influence of different uncertain parameters is taken into consideration. The chance constrained programming method is used to build a model under uncertain conditions, where the confidence level indicates the degree of constraint violation. Probability distribution functions are used to describe the form of uncertain parameters. The objective is to minimize the total cost and obtain the optimal cooling network configuration simultaneously.An algorithm based on Monte Carlo method is proposed, and GAMS software is used to solve the mixed integer nonlinear programming model. A case is optimized to verify the validity of the model. Compared with the deterministic optimization method, the results show that when considering the different types of uncertain parameters, a system with better economy and reliability can be obtained(total cost can be reduced at least 2%).展开更多
Multiple objective stochastic linear programming is a relevant topic. As a matter of fact, many practical problems ranging from portfolio selection to water resource management may be cast into this framework. Severe ...Multiple objective stochastic linear programming is a relevant topic. As a matter of fact, many practical problems ranging from portfolio selection to water resource management may be cast into this framework. Severe limitations on objectivity are encountered in this field because of the simultaneous presence of randomness and conflicting goals. In such a turbulent environment, the mainstay of rational choice cannot hold and it is virtually impossible to provide a truly scientific foundation for an optimal decision. In this paper, we resort to the bounded rationality principle to introduce satisfying solution for multiobjective stochastic linear programming problems. These solutions that are based on the chance-constrained paradigm are characterized under the assumption of normality of involved random variables. Ways for singling out such solutions are also discussed and a numerical example provided for the sake of illustration.展开更多
Geological surface modeling is typically based on seismic data, well data, and models of regional geology. However, structural interpretation of these data is error-prone, especially in the absence of structural morph...Geological surface modeling is typically based on seismic data, well data, and models of regional geology. However, structural interpretation of these data is error-prone, especially in the absence of structural morphology information, Existing geological surface models suffer from high levels of uncertainty, which exposes oil and gas exploration and development to additional risk. In this paper, we achieve a reconstruction of the uncertainties associated with a geological surface using chance-constrained programming based on multisource data. We also quantifi ed the uncertainty of the modeling data and added a disturbance term to the objective function. Finally, we verifi ed the applicability of the method using both synthetic and real fault data. We found that the reconstructed geological models met geological rules and reduced the reconstruction uncertainty.展开更多
This study employs a chance-constrained data envelopment analysis (CDEA) approach with two models (model A and model B) to decompose provincial productivity growth in Vietnamese agriculture from 1995 to 2007 into tech...This study employs a chance-constrained data envelopment analysis (CDEA) approach with two models (model A and model B) to decompose provincial productivity growth in Vietnamese agriculture from 1995 to 2007 into technological progress and efficiency change. The differences between the chance - constrained programming model A and model B are assumptions imposed on the covariance matrix. The decomposition allows us to identify the contributions of technical change and the improvement in technical efficiency to productivity growth in Vietnamese production. Sixty-one provinces in Vietnam are classified into Mekong - technology and other -technology categories. We conduct a Mann-Whitney test to verify whether the two samples, the Mekong technology province sample and the other technology sample, are drawn from the same productivity change populations. The result of the Mann-Whitney test indicates that the differences between the Mekong technology category and the other technology category from two models are more significant. Two important questions are whether some provinces in the samples could maintain their relative efficiency rank positions in comparison with the others over the study period and how to further examine the agreements between the two models. The Kruskal - Wallis test statistic shows that technical efficiency from both models for some provinces are higher than those of them in the study period. The Malmquist results show that production frontier has contracted by around 1.3 percent and 0.31 percent from chance-constrained model A and model B, respectively, a year on average over the sample period. To examine the agreements or disagreements in the total factor productivity indexes we compute the correlation between Malmquist indexes, which is positive and not very high. Thus there is a little discrepancy between the two Malmquist indexes, estimated from the chance - constrained models A and B.展开更多
研究供电公司在两个交易市场中的购电分配策略问题。鉴于机会约束规划是一类随机优化方法,该方法允许在观测到随机变量的实现之前做出决策,只要该决策使得约束条件成立的概率高于某一给定的置信水平,并且能够给决策所引起的风险以显式...研究供电公司在两个交易市场中的购电分配策略问题。鉴于机会约束规划是一类随机优化方法,该方法允许在观测到随机变量的实现之前做出决策,只要该决策使得约束条件成立的概率高于某一给定的置信水平,并且能够给决策所引起的风险以显式的描述,提出基于机会约束规划的供电公司购电分配策略模型,采用M on te-C arlo模拟结合基因算法求解。算例仿真表明,该研究工作为构造考虑风险管理的供电公司购电分配策略问题提供了一个途径。展开更多
文章以风-光-柴-储系统为研究对象,为了研究新能源出力不确定性对该系统的影响,提出了一种新能源出力复合预测模型。为提高风-光-柴-储系统运行的经济性、环保性和安全性,提出了考虑新能源出力不确定性的风-光-柴-储系统调度模型,并采...文章以风-光-柴-储系统为研究对象,为了研究新能源出力不确定性对该系统的影响,提出了一种新能源出力复合预测模型。为提高风-光-柴-储系统运行的经济性、环保性和安全性,提出了考虑新能源出力不确定性的风-光-柴-储系统调度模型,并采用了带有Monte Carlo模拟的遗传算法对模型进行求解。文章采用了负荷缺失率(load loss rate,LLR)和置信概率对系统的安全性进行评价,并分析了其对系统调度结果的影响。仿真结果表明,文中所提出的考虑新能源出力不确定性的风-光-柴-储系统调度模型,可以降低新能源出力不确定性对系统的影响,且该方法可以有效地平衡系统的经济性和安全性。展开更多
为实现集成智能楼宇(intelligent building,IBs)的主动配电网(active distribution network,ADN)灵活运行,该文提出一种基于机会约束规划的含IBs的ADN分布式能量管理策略。首先,基于建筑物的热惯性,构建含空调柔性负荷的IBs数学模型;其...为实现集成智能楼宇(intelligent building,IBs)的主动配电网(active distribution network,ADN)灵活运行,该文提出一种基于机会约束规划的含IBs的ADN分布式能量管理策略。首先,基于建筑物的热惯性,构建含空调柔性负荷的IBs数学模型;其次,综合考虑楼宇侧与网络侧的运行约束,建立基于Dist Flow的集成IBs的ADN数学模型;然后,考虑到光伏(photovoltaic,PV)出力与外界温度的不确定性,利用机会约束规划将集成IBs的ADN优化问题转化为混合整数二阶锥规划(mixed integer second-order cone programming,MISOCP)问题;最后,为了保护配电网运营商与用户的隐私性,利用交替方向乘子法(alternating direction method of multipliers,ADMM)实现了集成IBs的ADN的分布式能量管理。基于ADMM的解耦机制,原MISOCP问题可以被分解为楼宇侧的混合整数线性规划(mixed-integer linear programming,MILP)子问题以及网络侧的二阶锥规划(second-order cone programming,SOCP)子问题进行求解。结果表明,在保障各主体信息隐私性的前提下,所提策略利用IBs灵活性实现了集成IBs的ADN全局最优能量管理。展开更多
文摘A deterministic linear programming model which optimizes the abatement of each SO2 emission source, is extended into a CCP form by introducing equations of probabilistic constrained through the incorporation of uncertainty in the source-receptor-specific transfer coefficients. Based on the calculation of SO2 and sulfate average residence time for Liuzhou City, a sulfur deposition model has been developed and the distribution of transfer coefficients have been found to be approximately log-normal. Sulfur removal minimization of the model shows that the abatement of emission sources in the city is more effective, while control cost optimization provides the lowest cost programmes for source abatement at each allowable deposition limit under varied environmental risk levels. Finally a practicable programme is recommended.
基金Financial support from the National Natural Science Foundation of China (22022816, 22078358)。
文摘Recent research on deterministic methods for circulating cooling water systems optimization has been well developed. However, the actual operating conditions of the system are mostly variable, so the system obtained under deterministic conditions may not be stable and economical. This paper studies the optimization of circulating cooling water systems under uncertain circumstance. To improve the reliability of the system and reduce the water and energy consumption, the influence of different uncertain parameters is taken into consideration. The chance constrained programming method is used to build a model under uncertain conditions, where the confidence level indicates the degree of constraint violation. Probability distribution functions are used to describe the form of uncertain parameters. The objective is to minimize the total cost and obtain the optimal cooling network configuration simultaneously.An algorithm based on Monte Carlo method is proposed, and GAMS software is used to solve the mixed integer nonlinear programming model. A case is optimized to verify the validity of the model. Compared with the deterministic optimization method, the results show that when considering the different types of uncertain parameters, a system with better economy and reliability can be obtained(total cost can be reduced at least 2%).
文摘Multiple objective stochastic linear programming is a relevant topic. As a matter of fact, many practical problems ranging from portfolio selection to water resource management may be cast into this framework. Severe limitations on objectivity are encountered in this field because of the simultaneous presence of randomness and conflicting goals. In such a turbulent environment, the mainstay of rational choice cannot hold and it is virtually impossible to provide a truly scientific foundation for an optimal decision. In this paper, we resort to the bounded rationality principle to introduce satisfying solution for multiobjective stochastic linear programming problems. These solutions that are based on the chance-constrained paradigm are characterized under the assumption of normality of involved random variables. Ways for singling out such solutions are also discussed and a numerical example provided for the sake of illustration.
基金by National Science and Technology Major Project(Grant No.2017ZX05018004004)the National Natural Science Foundation of China (No.U1562218 & 41604107).
文摘Geological surface modeling is typically based on seismic data, well data, and models of regional geology. However, structural interpretation of these data is error-prone, especially in the absence of structural morphology information, Existing geological surface models suffer from high levels of uncertainty, which exposes oil and gas exploration and development to additional risk. In this paper, we achieve a reconstruction of the uncertainties associated with a geological surface using chance-constrained programming based on multisource data. We also quantifi ed the uncertainty of the modeling data and added a disturbance term to the objective function. Finally, we verifi ed the applicability of the method using both synthetic and real fault data. We found that the reconstructed geological models met geological rules and reduced the reconstruction uncertainty.
文摘This study employs a chance-constrained data envelopment analysis (CDEA) approach with two models (model A and model B) to decompose provincial productivity growth in Vietnamese agriculture from 1995 to 2007 into technological progress and efficiency change. The differences between the chance - constrained programming model A and model B are assumptions imposed on the covariance matrix. The decomposition allows us to identify the contributions of technical change and the improvement in technical efficiency to productivity growth in Vietnamese production. Sixty-one provinces in Vietnam are classified into Mekong - technology and other -technology categories. We conduct a Mann-Whitney test to verify whether the two samples, the Mekong technology province sample and the other technology sample, are drawn from the same productivity change populations. The result of the Mann-Whitney test indicates that the differences between the Mekong technology category and the other technology category from two models are more significant. Two important questions are whether some provinces in the samples could maintain their relative efficiency rank positions in comparison with the others over the study period and how to further examine the agreements between the two models. The Kruskal - Wallis test statistic shows that technical efficiency from both models for some provinces are higher than those of them in the study period. The Malmquist results show that production frontier has contracted by around 1.3 percent and 0.31 percent from chance-constrained model A and model B, respectively, a year on average over the sample period. To examine the agreements or disagreements in the total factor productivity indexes we compute the correlation between Malmquist indexes, which is positive and not very high. Thus there is a little discrepancy between the two Malmquist indexes, estimated from the chance - constrained models A and B.
文摘研究供电公司在两个交易市场中的购电分配策略问题。鉴于机会约束规划是一类随机优化方法,该方法允许在观测到随机变量的实现之前做出决策,只要该决策使得约束条件成立的概率高于某一给定的置信水平,并且能够给决策所引起的风险以显式的描述,提出基于机会约束规划的供电公司购电分配策略模型,采用M on te-C arlo模拟结合基因算法求解。算例仿真表明,该研究工作为构造考虑风险管理的供电公司购电分配策略问题提供了一个途径。
文摘文章以风-光-柴-储系统为研究对象,为了研究新能源出力不确定性对该系统的影响,提出了一种新能源出力复合预测模型。为提高风-光-柴-储系统运行的经济性、环保性和安全性,提出了考虑新能源出力不确定性的风-光-柴-储系统调度模型,并采用了带有Monte Carlo模拟的遗传算法对模型进行求解。文章采用了负荷缺失率(load loss rate,LLR)和置信概率对系统的安全性进行评价,并分析了其对系统调度结果的影响。仿真结果表明,文中所提出的考虑新能源出力不确定性的风-光-柴-储系统调度模型,可以降低新能源出力不确定性对系统的影响,且该方法可以有效地平衡系统的经济性和安全性。
文摘为实现集成智能楼宇(intelligent building,IBs)的主动配电网(active distribution network,ADN)灵活运行,该文提出一种基于机会约束规划的含IBs的ADN分布式能量管理策略。首先,基于建筑物的热惯性,构建含空调柔性负荷的IBs数学模型;其次,综合考虑楼宇侧与网络侧的运行约束,建立基于Dist Flow的集成IBs的ADN数学模型;然后,考虑到光伏(photovoltaic,PV)出力与外界温度的不确定性,利用机会约束规划将集成IBs的ADN优化问题转化为混合整数二阶锥规划(mixed integer second-order cone programming,MISOCP)问题;最后,为了保护配电网运营商与用户的隐私性,利用交替方向乘子法(alternating direction method of multipliers,ADMM)实现了集成IBs的ADN的分布式能量管理。基于ADMM的解耦机制,原MISOCP问题可以被分解为楼宇侧的混合整数线性规划(mixed-integer linear programming,MILP)子问题以及网络侧的二阶锥规划(second-order cone programming,SOCP)子问题进行求解。结果表明,在保障各主体信息隐私性的前提下,所提策略利用IBs灵活性实现了集成IBs的ADN全局最优能量管理。
