新型配电台区配置多个共享储能(shared energy storage,SES)已成趋势,具有多资源协同的效果。但仅考虑SES自身价值难以实现其高效调用,需进一步关注共享储能个体差异对台区电网的多角度综合影响。为量化台区多共享储能共同作用下的单一...新型配电台区配置多个共享储能(shared energy storage,SES)已成趋势,具有多资源协同的效果。但仅考虑SES自身价值难以实现其高效调用,需进一步关注共享储能个体差异对台区电网的多角度综合影响。为量化台区多共享储能共同作用下的单一SES边际运行贡献,提出了基于改进沙普利(Shapley)值的台区多共享储能运行效能分配方法。考虑新能源消纳及碳减排,建立含SES运行组合的台区运行成本最小优化调度模型;考虑SES对台区经济性、可靠性与环境的影响,建立SES运行效能评估指标,基于改进层次分析与层间相关性结合的主客观赋权法建立运行效能评估模型;考虑不同SES对台区运行的单方面效能差异,构建计及经济贡献度、可靠性贡献度与环境贡献度的SES修正因子以改进Shapley值法,将多种SES组合的运行效能分配至单个SES。对含3个SES的改进IEEE 33节点台区电网仿真验证,结果表明所提方法有效量化与分配不同节点SES对台区的综合效用,增加了对台区有益影响的SES1和SES2运行效能。所提方法为台区共享储能的高效率调度及潜力发挥提供全新思路。展开更多
成果名称:Shapley's Conjecture on the Cores of Abstract Market Games主要作者:曹志刚,秦承忠,杨晓光奖项类别:著作论文奖获奖等级:二等奖获奖论文《Shapley's Conjecture on the Cores of Abstract Market Games》发表于博...成果名称:Shapley's Conjecture on the Cores of Abstract Market Games主要作者:曹志刚,秦承忠,杨晓光奖项类别:著作论文奖获奖等级:二等奖获奖论文《Shapley's Conjecture on the Cores of Abstract Market Games》发表于博弈论领域顶级期刊《Games and Economic Behavior》2018年第2期。论文研究成果初步解决了诺贝尔经济学奖获得者罗伊德·沙普利(Lloyd S. Shapley)提出的抽象市场博弈核非空的猜想。展开更多
Accurate reservoir permeability determination is crucial in hydrocarbon exploration and production.Conventional methods relying on empirical correlations and assumptions often result in high costs,time consumption,ina...Accurate reservoir permeability determination is crucial in hydrocarbon exploration and production.Conventional methods relying on empirical correlations and assumptions often result in high costs,time consumption,inaccuracies,and uncertainties.This study introduces a novel hybrid machine learning approach to predict the permeability of the Wangkwar formation in the Gunya oilfield,Northwestern Uganda.The group method of data handling with differential evolution(GMDH-DE)algorithm was used to predict permeability due to its capability to manage complex,nonlinear relationships between variables,reduced computation time,and parameter optimization through evolutionary algorithms.Using 1953 samples from Gunya-1 and Gunya-2 wells for training and 1563 samples from Gunya-3 for testing,the GMDH-DE outperformed the group method of data handling(GMDH)and random forest(RF)in predicting permeability with higher accuracy and lower computation time.The GMDH-DE achieved an R^(2)of 0.9985,RMSE of 3.157,MAE of 2.366,and ME of 0.001 during training,and for testing,the ME,MAE,RMSE,and R^(2)were 1.3508,12.503,21.3898,and 0.9534,respectively.Additionally,the GMDH-DE demonstrated a 41%reduction in processing time compared to GMDH and RF.The model was also used to predict the permeability of the Mita Gamma well in the Mandawa basin,Tanzania,which lacks core data.Shapley additive explanations(SHAP)analysis identified thermal neutron porosity(TNPH),effective porosity(PHIE),and spectral gamma-ray(SGR)as the most critical parameters in permeability prediction.Therefore,the GMDH-DE model offers a novel,efficient,and accurate approach for fast permeability prediction,enhancing hydrocarbon exploration and production.展开更多
文摘新型配电台区配置多个共享储能(shared energy storage,SES)已成趋势,具有多资源协同的效果。但仅考虑SES自身价值难以实现其高效调用,需进一步关注共享储能个体差异对台区电网的多角度综合影响。为量化台区多共享储能共同作用下的单一SES边际运行贡献,提出了基于改进沙普利(Shapley)值的台区多共享储能运行效能分配方法。考虑新能源消纳及碳减排,建立含SES运行组合的台区运行成本最小优化调度模型;考虑SES对台区经济性、可靠性与环境的影响,建立SES运行效能评估指标,基于改进层次分析与层间相关性结合的主客观赋权法建立运行效能评估模型;考虑不同SES对台区运行的单方面效能差异,构建计及经济贡献度、可靠性贡献度与环境贡献度的SES修正因子以改进Shapley值法,将多种SES组合的运行效能分配至单个SES。对含3个SES的改进IEEE 33节点台区电网仿真验证,结果表明所提方法有效量化与分配不同节点SES对台区的综合效用,增加了对台区有益影响的SES1和SES2运行效能。所提方法为台区共享储能的高效率调度及潜力发挥提供全新思路。
文摘成果名称:Shapley's Conjecture on the Cores of Abstract Market Games主要作者:曹志刚,秦承忠,杨晓光奖项类别:著作论文奖获奖等级:二等奖获奖论文《Shapley's Conjecture on the Cores of Abstract Market Games》发表于博弈论领域顶级期刊《Games and Economic Behavior》2018年第2期。论文研究成果初步解决了诺贝尔经济学奖获得者罗伊德·沙普利(Lloyd S. Shapley)提出的抽象市场博弈核非空的猜想。
基金supported by the Major National Science and Technology Programs in the“Thirteenth Five-Year”Plan period(Grant No.2017ZX05032-002-004)the Innovation Team Funding of Natural Science Foundation of Hubei Province,China(Grant No.2021CFA031)the Chinese Scholarship Council(CSC)and Silk Road Institute for their support in terms of stipend.
文摘Accurate reservoir permeability determination is crucial in hydrocarbon exploration and production.Conventional methods relying on empirical correlations and assumptions often result in high costs,time consumption,inaccuracies,and uncertainties.This study introduces a novel hybrid machine learning approach to predict the permeability of the Wangkwar formation in the Gunya oilfield,Northwestern Uganda.The group method of data handling with differential evolution(GMDH-DE)algorithm was used to predict permeability due to its capability to manage complex,nonlinear relationships between variables,reduced computation time,and parameter optimization through evolutionary algorithms.Using 1953 samples from Gunya-1 and Gunya-2 wells for training and 1563 samples from Gunya-3 for testing,the GMDH-DE outperformed the group method of data handling(GMDH)and random forest(RF)in predicting permeability with higher accuracy and lower computation time.The GMDH-DE achieved an R^(2)of 0.9985,RMSE of 3.157,MAE of 2.366,and ME of 0.001 during training,and for testing,the ME,MAE,RMSE,and R^(2)were 1.3508,12.503,21.3898,and 0.9534,respectively.Additionally,the GMDH-DE demonstrated a 41%reduction in processing time compared to GMDH and RF.The model was also used to predict the permeability of the Mita Gamma well in the Mandawa basin,Tanzania,which lacks core data.Shapley additive explanations(SHAP)analysis identified thermal neutron porosity(TNPH),effective porosity(PHIE),and spectral gamma-ray(SGR)as the most critical parameters in permeability prediction.Therefore,the GMDH-DE model offers a novel,efficient,and accurate approach for fast permeability prediction,enhancing hydrocarbon exploration and production.
