聚苯乙烯磺酸钠作用下Ⅰ型水合物的生成热力学与动力学

通过使用表面活性剂来提升水合物的生成速度和转化率是提高水合物技术经济价值的主要方法。因为泡沫过多不利于生产,低起泡性的聚苯乙烯磺酸钠（PSS）在水合物技术领域具有很好应用的潜力。本文根据对含PSS体系的水合物生成热力学研究,提出了乙烯-PSS溶液体系的热力学模型以定量描述PSS对水合物的热力学影响,该模型可较为准确地预测水合物的热力学临界生成压力：平均相对误差为1.1%,最大相对误差为3.8%。在上述研究基础上,本文研究了在PSS存在的情况下,PSS初始浓度和热力学推动力对Ⅰ型水合物的生成速度、最终转化率（水合物生成结束时的转化率）等参数的影响。结果表明,PSS对Ⅰ型水合物的热力学负面影响很小。PSS使水合物的最终转化率由59.6%±1.9%提升到80%以上,并使水合物的生成速度显著提升。当PSS初始浓度或压力低于特定值时,提高PSS初始浓度或压力可有效提升水合物的生成速度和最终转化率;但PSS初始浓度或压力高于特定值时,提高PSS初始浓度或压力对水合物生成速度和最终转化率的提升效果不再明显。     

Pb-Free solders: Part II. Application of ADAMIS database in modeling of Sn−Ag−Cu alloys with Bi additions

The ADAMIS database was used for calculation of the surface tension of the quaternary Sn−Ag−Cu−Bi liquid alloys by Butler's model. The resultant data were compared with those from the maximum bubble pressure measurements from Part I. The same thermodynamic database was next applied for the calculation of various phase equilibria. It was established that the Bi addition to the ternary Sn−Ag−Cu alloys (Sn-2.6Ag-0.46Cu and Sn-3.13Ag-0.74Cu in at.%; Sn-2.56Ag-0.26 Cu and Sn-2.86Ag-O.40Cu in mass%) causes lowering of the melting temperature and the surface tension to make the tested alloys closer to, traditional Sn−Pb solders. The simulation of the solidification by Scheil's model showed that the alloys with the higher Bi concentration are characterized by the lifting-off failure due to the segregation of Bi at the solder/substrate boundary. Thus, in modeling of new Pb-free solders, a compromise among various properties should be taken into consideration.     

基于博弈论的无线传感器网络保密容量优化研究

由于无线传感器网络传输数据时的广播性,很容易受到窃听。从信息论的角度,保证节点信道的保密容量,即可实现数据的安全传输。而在无线传感器网络中,节点与节点之间会产生相互干扰,从而影响信道各自的保密容量。使用非合作博弈求解无线传感器网络在节点发射功率受限、节点之间存在互相干扰的情况下选取各自的功率,达到纳什均衡,以获取最佳的收益。仿真结果表明,节点选取纳什均衡时的功率,可获得较好的保密容量,同时提高节点的可持续性。     

Solving linear generalized Nash equilibrium problems numerically

This paper considers the numerical solution of linear generalized Nash equilibrium problems (LGNEPs). Since many methods for nonlinear problems require the nonsingularity of some second-order derivative, standard convergence conditions are not satisfied in our linear case. We provide new convergence criteria for a potential reduction algorithm (PRA) that allow its application to LGNEPs. Furthermore, we discuss a projected subgradient method (PSM) and a penalty method that exploit some known Nikaido–Isoda function-based constrained and unconstrained optimization reformulations of the LGNEP. Moreover, it is shown that normalized Nash equilibria of an LGNEP can be obtained by solving a single linear program. All proposed algorithms are tested on randomly generated instances of economic market models that are introduced and analysed in this paper and that lead to LGNEPs with shared and with non-shared constraints. It is shown that these problems have some favourable properties that can be exploited to obtain their solutions. With the PRA and in particular with the PSM we are able to compute solutions with satisfying precision even for problems with up 10,000 variables.     

Bandwidth Allocation with Minimum Rate Constraints in Cluster-based Femtocell Networks

 Inter-femtocell interference becomes serious when femtocells are densely deployed. To mitigate the inter-femtocell interference, this paper proposes a cluster-based bandwidth allocation algorithm. We create femtocell clusters by constructing a weighted interference graph and allocate bandwidth to each cluster based on a Nash bargaining solution (NBS). Simulation results show that the cluster-based bandwidth allocation algorithm can reduce the inter-femtocell interference and meet the minimum rate constraint of each cluster.     

Game‐Based Valley‐Fill Charging Coordination for Large‐Population Plug‐in Electric Vehicles

Charging coordination of large‐population autonomous plug‐in electric vehicles (PEVs) in the power grid can be formulated as a class of constrained optimization problems. To overcome the computational complexity, a game‐based method is proposed for the charging problems of the PEV population, which is composed of homogeneous subpopulations, such that individuals update their best charging strategies simultaneously with respect to a common electricity price determined by the total demand. To mitigate the oscillation behavior caused by the greedy behavior for the cheap electricity by individuals, a deviation cost is introduced to penalize against the deviation of the individual strategy from the average value of the homogeneous subpopulation. By adopting a proper deviation cost and following a best strategy update mechanism, the game systems may converge to the socially optimal valley‐fill Nash equilibrium. Simulation examples are studied to illustrate the results.     

Sampling average approximation method for a class of stochastic Nash equilibrium problems

We consider a class of stochastic Nash equilibrium problems (SNEP). Under some mild conditions, we reformulate the SNEP as a stochastic mixed complementarity problem (SMCP). We apply the well-known sample average approximation (SAA) method to solve the SMCP. We further introduce a semismooth Newton method to solve the SAA problems. The comprehensive convergence analysis is given as well. In addition, we demonstrate the proposed approach on a stochastic Nash equilibrium model in the wholesale gas–oil markets.     

A suboptimal joint bandwidth and power allocation for cooperative relay networks＂ a cooperative game theoretic approach

In commercial networks, user nodes operating on batteries are assumed to be selfish to consume their resources (i.e., bandwidth and power) solely maximizing their own benefits (e.g., the received signal-to-noise ratios (SNRs) and datarates). In this paper, a cooperative game theoretical framework is proposed to jointly perform the bandwidth and power allocation for selfish cooperative relay networks. To ensure a fair and efficient resource sharing between two selfish user nodes, we assume that either node can act as a source as well as a potential relay for each other and either node is willing to seek cooperative relaying only if the datarate achieved through cooperation is not lower than that achieved through noncooperation (i.e., direct transmission) by consuming the same amount of bandwidth and power resource. Define the cooperative strategy of a node as the number of bandwidth and power that it is willing to contribute for relaying purpose. The two node joint bandwidth and power allocation (JBPA) problem can then be formulated as a cooperative game. Since the Nash bargaining solution (NBS) to the JBPA game (JBPAG) is computationally difficult to obtain, we divide it into two subgames, i.e., the bandwidth allocation game (BAG) and the power allocation game (PAG). We prove that both the subgames have unique NBS. And then the suboptimal NBS to the JBPAG can be achieved by solving the BAG and PAG sequentially. Simulation results show that the proposed cooperative game scheme is efficient in that the performance loss of the NBS result to that of the maximal overall data-rate scheme is small while the maximal-rate scheme is unfair. The simulation results also show that the NBS result is fair in that both nodes could experience better performance than they work independently and the degree of cooperation of a node only depends on how much contribution its partner can make to improve its own performance.     

非合作博弈均衡在确定性Ad hoc网络中的应用

首先介绍了非合作博弈均衡(纳什均衡),并将纳什均衡的基本原理应用到Ad hoc网络中节点间的数据传输中,对采用纳什均衡的几种常用的策略也做了介绍,并着重对其中的TFT策略进行了讨论.并用"Small World"这一概念替代传统的"最短路径"概念,同时对Small-World做了介绍.随后针对Ad hoc网络的某些拓扑结构,将"纳什均衡"策略和目前其他一些激励机制进行了比较和讨论.认为在目前的Ad hoc网络中,非合作博弈均衡(纳什均衡)是比较理想,比较简单的一种分组传输策略.     

考虑不确定性的风-光-储合作联盟参与含需求响应的主辅联合市场的竞价交易模型

清洁能源逐渐成为电力市场的竞争主体,考虑风光出力不确定性和探究高效的市场运行机制成为电力现货市场建设进程中的关键问题。采用非参数核密度估计法和多元Gaussian-Copula函数生成典型出力场景来描述风光出力的不确定性和时空相关性。上层模型基于纳什谈判理论最大化风-光-储合作联盟收益,采用麻雀搜索算法优化风光发电商的报价策略。下层模型以购电总成本最小为目标,设计了多主体参与含价格型需求响应的主辅联合市场的出清机制。最后分析了风光出力的典型场景和市场出清结果的合理性。通过算例验证了该优化模型能够提升合作个体的收益,降低了购电总成本和负荷的峰谷差。