Multi-objective optimization(MOO)for the microwave metamaterial absorber(MMA)normally adopts evolutionary algo-rithms,and these optimization algorithms require many objec-tive function evaluations.To remedy this issue...Multi-objective optimization(MOO)for the microwave metamaterial absorber(MMA)normally adopts evolutionary algo-rithms,and these optimization algorithms require many objec-tive function evaluations.To remedy this issue,a surrogate-based MOO algorithm is proposed in this paper where Kriging models are employed to approximate objective functions.An efficient sampling strategy is presented to sequentially capture promising samples in the design region for exact evaluations.Firstly,new sample points are generated by the MOO on surro-gate models.Then,new samples are captured by exploiting each objective function.Furthermore,a weighted sum of the improvement of hypervolume(IHV)and the distance to sampled points is calculated to select the new sample.Compared with two well-known MOO algorithms,the proposed algorithm is vali-dated by benchmark problems.In addition,two broadband MMAs are applied to verify the feasibility and efficiency of the proposed algorithm.展开更多
A mathematical mechanism model was proposed for the description and analysis of the heat-stirring-acid leaching process.The model is proved to be effective by experiment.Afterwards,the leaching problem was formulated ...A mathematical mechanism model was proposed for the description and analysis of the heat-stirring-acid leaching process.The model is proved to be effective by experiment.Afterwards,the leaching problem was formulated as a constrained multi-objective optimization problem based on the mechanism model.A two-stage guide multi-objective particle swarm optimization(TSG-MOPSO) algorithm was proposed to solve this optimization problem,which can accelerate the convergence and guarantee the diversity of pareto-optimal front set as well.Computational experiment was conducted to compare the solution by the proposed algorithm with SIGMA-MOPSO by solving the model and with the manual solution in practice.The results indicate that the proposed algorithm shows better performance than SIGMA-MOPSO,and can improve the current manual solutions significantly.The improvements of production time and economic benefit compared with manual solutions are 10.5% and 7.3%,respectively.展开更多
This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously a...This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.展开更多
优化灌区渠系输配水技术是推动农业水资源高效利用的重要举措。针对新疆部分灌区渠系管理上沿用人工传递信息方法来决策配水方案,难以达到优化调配。以轮灌分组和配水流量为决策变量,建立了以渠道输水损失最小、轮灌组内配水时间差最小...优化灌区渠系输配水技术是推动农业水资源高效利用的重要举措。针对新疆部分灌区渠系管理上沿用人工传递信息方法来决策配水方案,难以达到优化调配。以轮灌分组和配水流量为决策变量,建立了以渠道输水损失最小、轮灌组内配水时间差最小为目标的灌区支、斗渠优化配水模型,采用多目标粒子群算法进行求解;在深入研究渠系优化配水模型及其算法求解的基础上,采用Visual Studio Code、Matlab开发工具,开发灌区渠系水优化配置系统,并通过实例进行检验分析。结果表明:优化后的配水方案较该时段实际灌溉方案,渗漏损失总量由48.49万m^(3)减少至23.78万m^(3),配水时间由30 d缩短为14.6 d。所建立的渠系优化配水模型贴近渠系实际运行情况,可以实现集中高效配水;开发的渠系水优化配置系统界面友好、参数简洁,能方便快速地为灌区的配水优化编组提供决策依据。展开更多
有效利用天然来水量预报信息可提高水电站汛期库容上限,在保证防洪安全的前提下充分利用水电资源,提升电网经济性。针对含高比例小水电的电力系统,提出一种综合考虑流域水电站群汛期预期来水量和弹性库容上限的优化调度策略。首先,提出...有效利用天然来水量预报信息可提高水电站汛期库容上限,在保证防洪安全的前提下充分利用水电资源,提升电网经济性。针对含高比例小水电的电力系统,提出一种综合考虑流域水电站群汛期预期来水量和弹性库容上限的优化调度策略。首先,提出基于最大信息系数(maximal information coefficient,MIC)的气象-水文预报因子筛选方法并构建基于注意力机制的Informer天然来水量预报模型;其次,考虑预报信息的准确性和水电站的预泄能力,提出基于机会约束优化的水电站弹性库容上限的确定方法,将其用于挖掘汛期水电站库容资源;最后,以浙江省丽水市某流域小水电站群为例进行算例分析,结果表明所提模型具有精确的预报效果,可以提高小水电站库容资源的利用效率,减少系统运行成本。展开更多
基金supported by the National Key Research and Development Program(2021YFB3502500).
文摘Multi-objective optimization(MOO)for the microwave metamaterial absorber(MMA)normally adopts evolutionary algo-rithms,and these optimization algorithms require many objec-tive function evaluations.To remedy this issue,a surrogate-based MOO algorithm is proposed in this paper where Kriging models are employed to approximate objective functions.An efficient sampling strategy is presented to sequentially capture promising samples in the design region for exact evaluations.Firstly,new sample points are generated by the MOO on surro-gate models.Then,new samples are captured by exploiting each objective function.Furthermore,a weighted sum of the improvement of hypervolume(IHV)and the distance to sampled points is calculated to select the new sample.Compared with two well-known MOO algorithms,the proposed algorithm is vali-dated by benchmark problems.In addition,two broadband MMAs are applied to verify the feasibility and efficiency of the proposed algorithm.
基金Project(2006AA060201) supported by the National High Technology Research and Development Program of China
文摘A mathematical mechanism model was proposed for the description and analysis of the heat-stirring-acid leaching process.The model is proved to be effective by experiment.Afterwards,the leaching problem was formulated as a constrained multi-objective optimization problem based on the mechanism model.A two-stage guide multi-objective particle swarm optimization(TSG-MOPSO) algorithm was proposed to solve this optimization problem,which can accelerate the convergence and guarantee the diversity of pareto-optimal front set as well.Computational experiment was conducted to compare the solution by the proposed algorithm with SIGMA-MOPSO by solving the model and with the manual solution in practice.The results indicate that the proposed algorithm shows better performance than SIGMA-MOPSO,and can improve the current manual solutions significantly.The improvements of production time and economic benefit compared with manual solutions are 10.5% and 7.3%,respectively.
文摘This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.
文摘优化灌区渠系输配水技术是推动农业水资源高效利用的重要举措。针对新疆部分灌区渠系管理上沿用人工传递信息方法来决策配水方案,难以达到优化调配。以轮灌分组和配水流量为决策变量,建立了以渠道输水损失最小、轮灌组内配水时间差最小为目标的灌区支、斗渠优化配水模型,采用多目标粒子群算法进行求解;在深入研究渠系优化配水模型及其算法求解的基础上,采用Visual Studio Code、Matlab开发工具,开发灌区渠系水优化配置系统,并通过实例进行检验分析。结果表明:优化后的配水方案较该时段实际灌溉方案,渗漏损失总量由48.49万m^(3)减少至23.78万m^(3),配水时间由30 d缩短为14.6 d。所建立的渠系优化配水模型贴近渠系实际运行情况,可以实现集中高效配水;开发的渠系水优化配置系统界面友好、参数简洁,能方便快速地为灌区的配水优化编组提供决策依据。
文摘有效利用天然来水量预报信息可提高水电站汛期库容上限,在保证防洪安全的前提下充分利用水电资源,提升电网经济性。针对含高比例小水电的电力系统,提出一种综合考虑流域水电站群汛期预期来水量和弹性库容上限的优化调度策略。首先,提出基于最大信息系数(maximal information coefficient,MIC)的气象-水文预报因子筛选方法并构建基于注意力机制的Informer天然来水量预报模型;其次,考虑预报信息的准确性和水电站的预泄能力,提出基于机会约束优化的水电站弹性库容上限的确定方法,将其用于挖掘汛期水电站库容资源;最后,以浙江省丽水市某流域小水电站群为例进行算例分析,结果表明所提模型具有精确的预报效果,可以提高小水电站库容资源的利用效率,减少系统运行成本。
