Artificial neural networks have been widely used to predict the mechanical properties of alloys in material research.This study aims to investigate the implicit relationship between the compositions and mechanical pro...Artificial neural networks have been widely used to predict the mechanical properties of alloys in material research.This study aims to investigate the implicit relationship between the compositions and mechanical properties of as-cast Mg-Li-Al alloys.Based on the experimental collection of the tensile strength and the elongation of representative Mg-Li-Al alloys,a momentum back-propagation(BP)neural network with a single hidden layer was established.Particle swarm optimization(PSO)was applied to optimize the BP model.In the neural network,the input variables were the contents of Mg,Li and Al,and the output variables were the tensile strength and the elongation. The results show that the proposed PSO-BP model can describe the quantitative relationship between the Mg-Li-Al alloy's composition and its mechanical properties.It is possible that the mechanical properties to be predicted without experiment by inputting the alloy composition into the trained network model.The prediction of the influence of Al addition on the mechanical properties of as-cast Mg-Li-Al alloys is consistent with the related research results.展开更多
In the new competitive electricity market, the accurate operation management of Micro-Grid (MG) with various types of renewable power sources (RES) can be an effective approach to supply the electrical consumers more ...In the new competitive electricity market, the accurate operation management of Micro-Grid (MG) with various types of renewable power sources (RES) can be an effective approach to supply the electrical consumers more reliably and economically. In this regard, this paper proposes a novel solution methodology based on bat algorithm to solve the op- timal energy management of MG including several RESs with the back-up of Fuel Cell (FC), Wind Turbine (WT), Photovoltaics (PV), Micro Turbine (MT) as well as storage devices to meet the energy mismatch. The problem is formulated as a nonlinear constraint optimization problem to minimize the total cost of the grid and RESs, simultaneously. In addition, the problem considers the interactive effects of MG and utility in a 24 hour time interval which would in- crease the complexity of the problem from the optimization point of view more severely. The proposed optimization technique is consisted of a self adaptive modification method compromised of two modification methods based on bat algorithm to explore the total search space globally. The superiority of the proposed method over the other well-known algorithms is demonstrated through a typical renewable MG as the test system.展开更多
为降低微电网发电侧运行成本,同时优化微电网需求侧用户的用电体验,建立了将需求侧管理(DSM:Demand Side Management)纳入微电网经济优化的模型。该模型包括一个光伏发电装置,两个柴油发电机和一个蓄电池,需求侧用户根据动态定价机制作...为降低微电网发电侧运行成本,同时优化微电网需求侧用户的用电体验,建立了将需求侧管理(DSM:Demand Side Management)纳入微电网经济优化的模型。该模型包括一个光伏发电装置,两个柴油发电机和一个蓄电池,需求侧用户根据动态定价机制作出响应并对负荷进行转移,以节省电费。将用户感到的不便与负荷转移时间建立联系,运用遗传算法同时优化发电侧经济性和需求侧用户体验。仿真结果表明,实施DSM后,发电成本显著降低,用户获得了一定的经济效益。展开更多
基金supported by the Program of New Century Excellent Talents of the Ministry of Education of China(NCET-08-0080)the National High Technology Research and Development Program("863"Program)of China(2009AA03Z525)+1 种基金the Fundamental Research Funds for the Central Universities(DUT11ZD115)the Science and Technology Fund of Dalian City(2009J21DW003)
文摘Artificial neural networks have been widely used to predict the mechanical properties of alloys in material research.This study aims to investigate the implicit relationship between the compositions and mechanical properties of as-cast Mg-Li-Al alloys.Based on the experimental collection of the tensile strength and the elongation of representative Mg-Li-Al alloys,a momentum back-propagation(BP)neural network with a single hidden layer was established.Particle swarm optimization(PSO)was applied to optimize the BP model.In the neural network,the input variables were the contents of Mg,Li and Al,and the output variables were the tensile strength and the elongation. The results show that the proposed PSO-BP model can describe the quantitative relationship between the Mg-Li-Al alloy's composition and its mechanical properties.It is possible that the mechanical properties to be predicted without experiment by inputting the alloy composition into the trained network model.The prediction of the influence of Al addition on the mechanical properties of as-cast Mg-Li-Al alloys is consistent with the related research results.
文摘In the new competitive electricity market, the accurate operation management of Micro-Grid (MG) with various types of renewable power sources (RES) can be an effective approach to supply the electrical consumers more reliably and economically. In this regard, this paper proposes a novel solution methodology based on bat algorithm to solve the op- timal energy management of MG including several RESs with the back-up of Fuel Cell (FC), Wind Turbine (WT), Photovoltaics (PV), Micro Turbine (MT) as well as storage devices to meet the energy mismatch. The problem is formulated as a nonlinear constraint optimization problem to minimize the total cost of the grid and RESs, simultaneously. In addition, the problem considers the interactive effects of MG and utility in a 24 hour time interval which would in- crease the complexity of the problem from the optimization point of view more severely. The proposed optimization technique is consisted of a self adaptive modification method compromised of two modification methods based on bat algorithm to explore the total search space globally. The superiority of the proposed method over the other well-known algorithms is demonstrated through a typical renewable MG as the test system.
文摘为降低微电网发电侧运行成本,同时优化微电网需求侧用户的用电体验,建立了将需求侧管理(DSM:Demand Side Management)纳入微电网经济优化的模型。该模型包括一个光伏发电装置,两个柴油发电机和一个蓄电池,需求侧用户根据动态定价机制作出响应并对负荷进行转移,以节省电费。将用户感到的不便与负荷转移时间建立联系,运用遗传算法同时优化发电侧经济性和需求侧用户体验。仿真结果表明,实施DSM后,发电成本显著降低,用户获得了一定的经济效益。
