PJM输电权运行机制及其在我国区域电力市场阻塞管理中的应用

PJM电力市场采用节点边际电价(LMP)进行阻塞管理,利用点对点的金融性输电权(FTR)作为金融工具来分摊阻塞盈余、规避节点电价不稳定带来的市场风险。主要介绍了PJM电力市场中输电权的种类、输电权拍卖市场的特点、出清机制和结算方法。在此基础上,对我国区域电力市场的阻塞管理及输电权市场的设计提出了一些建议。     

Concepts and fuzzy logic

Weights are used to measure relative importance of multiple attributes or objectives, which influence evaluation or decision results to a great degree. Thus, analyzing weight sensitivity is an important work for a multi-attribute evaluation or decision. A measuring method based on the inclined angle of two vectors is proposed in this paper in order to solve the weight sensitivity of a multi-attribute evaluation with isotonicity characteristic. This method uses the cosine of the inclined angle to measure the weight sensitivity based on preferences or preference combinations. Concepts of sensitivity space, degree, and angle are given, and the relevant measurement method is discussed and proved. Also, this method is used for the choice of the water environment protection projects in Heyuan City.     

Multi-stage sequential uniform price auction mechanism for divisible goods

In this paper, we study the problem of auctioning a kind of continuous homogeneous divisible goods, and present a multi-stage sequential auction mechanism of divisible goods under uniform price. In this mechanism, the auction process is divided into multiple stages, all bidders satisfy the sequential rationality conditions, all bidders are asymmetric, every bidder is allowed to submit a nonincreasing continuous demand function in each round bidding, every bidder’s valuation to per unit of the goods is independent private information, and if a bidder does not obtain the quantity he wants in former stage auction, he still have another opportunity to obtain some quantity in the later stage auction. For this mechanism, we explore the formation process and composition of equilibrium points in each stage auction, and discuss the optimal strategy selection for bidders, then give the detail steps and an application example to show how to implement this multi-stage sequential auction mechanism. The conclusions can be drawn that our auction mechanism is an efficient incentive mechanism, and can effectively reduce many underpricing equilibrium and can yield higher expected income than a single uniform price auction for the auctioneer. It also can avoid the occurrence of failure auction (equilibrium does not exist), and effectively extend and improve the traditional single stage uniform price auction mechanism.     

基于JXTA的P2P实例的研究与实现

对JXTA做了比较深入的研究,介绍JXTA的概念、协议、框架,描述JXTA平台拍卖系统的设计和实现,最后对拍卖模型等关键部分进行设计分析。     

直觉模糊熵的几何构造方法及其应用

针对直觉模糊集中模糊性和直觉性对不确定信息的综合影响以及直觉模糊熵连续变化等问题,提出2种直觉模糊熵的几何构造方法,完善传统直觉模糊熵的构造准则。利用几何方法,分别通过建立等熵平面和等熵圆弧,结合距离构造2种新的直觉模糊熵,并证明其相关性质。论述直觉模糊熵的一般构造方法,对算例与现存的一些熵公式进行比较分析。将直觉模糊熵应用到多属性决策中,验证该方法的正确性和合理性。     

多无人机分布式协同异构任务分配

研究异构无人机对不同类型目标执行侦察、打击和评估任务的协同任务分配问题.采用信息论中熵的变化量对侦察与评估任务中所获取的信息量进行度量,将无人机对不同类型目标的打击能力抽象为对目标的毁伤概率,并考虑各个任务之间的相互关联,建立异构多无人机协同任务分配模型.设计了基于相邻局部通信的分布式拍卖算法,实现了多无人机协同任务分配问题的优化求解.仿真结果表明了所建模型的合理性和求解方法的有效性.     

Reducing mechanism design to algorithm design via machine learning

We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a broad class of revenue-maximizing pricing problems. Our reductions imply that for these problems, given an optimal (or β-approximation) algorithm for an algorithmic pricing problem, we can convert it into a (1+?)-approximation (or β(1+?)-approximation) for the incentive-compatible mechanism design problem, so long as the number of bidders is sufficiently large as a function of an appropriate measure of complexity of the class of allowable pricings. We apply these results to the problem of auctioning a digital good, to the attribute auction problem which includes a wide variety of discriminatory pricing problems, and to the problem of item-pricing in unlimited-supply combinatorial auctions. From a machine learning perspective, these settings present several challenges: in particular, the “loss function” is discontinuous, is asymmetric, and has a large range. We address these issues in part by introducing a new form of covering-number bound that is especially well-suited to these problems and may be of independent interest.     

An energy trading system with consideration of CO2 emissions

Abatement of CO₂ emission is one of the most important issues in the 21st century regarding preservation of the earth environment. This paper addresses a utility operations planning problem for distributed energy management systems (DEMSs), where we are to obtain optimal plans that minimize both costs and CO₂ emissions. A DEMS consists of multiple entities that seek their own economic profits. In this paper, we give a mathematical formulation of the utility operations planning problem for each entity, and propose an energy trading market, which utlizes a multi‐attribute auction protocol in order to deal with both a price and a CO₂ emission rate. Experimental results show that collaboration among entities through the market provides a more profitable plan for each entity and abatement of CO₂ emission is also achieved. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 162(4): 54–63, 2008; Published online in Wiley InterScience ( www.interscience.wiley. com ). DOI 10.1002/eej.20418     

基于英式拍卖的RMFS货位指派研究

目的 构建英式拍卖模型，以待指派商品品项(SKU)群的最低周转率为媒介，通过逐步提升最低周转率来实现待指派SKU与待指派区域货位数量的匹配。方法 针对移动机器人拣货系统(RMFS)中的货位指派，提出基于英式拍卖机制的货位指派方法，提升仓库拣货效率。结果 与随机指派相比，在不同仓库规模、订单规模、订单偏度的RMFS中采用英式拍卖货位指派机制，机器人行走路程下降比率在大型仓库中达30.17%，中型仓库的下降比率为27.31%，小型仓库的下降比率为24.13%。结论 采用英式拍卖机制在RFMS中进行货位指派可大幅度提高工作效率。     

电力市场智能模拟中代理决策模块的实现

在日前交易方式下，发电厂商为了追求长期最大利润，竞价策略显得尤其重要。通常，发电厂商运用的策略过于复杂，难以用传统的博弈论方法来建模。人工智能中强化学习 Q -learning算法是一种自适应的学习方法，使代理能够通过不断与环境进行交互所得到的经验进行学习，适合在电力市场智能模拟中运用。文中在开放源代码的电力市场智能模拟平台AMES上，增加了发电厂商代理基于 Q -learning的竞价决策程序模块，并在5节点测试系统上进行模拟。实验结果表明，运用基于 Q -learning算法竞价决策使代理可以较好地模拟发电厂商的经济特性，且在相同条件下表现出比AMES原有的VRE learning算法更强的探索能力。