Game Theory Algorithm of Reconfiguration for Shipboard Power System

船舶电力系统故障重构通过改变系统供电路径来恢复重要负载的供电，对增强系统的存活性有着重要意义。在多智能体（agent）架构的基础上，构建船舶电力系统博弈重构模型并提出求解方法。该模型以船舶电力系统中不同区域的agent作为博弈参与者，将船舶电力系统的重构问题转化为各agent之间的合作一竞争问题，从而保证重要负载的恢复供电。论文进一步提出该模型的求解算法，该算法首先判断博弈模式的合作与非合作属性，之后通过agent或agent联盟之间的博弈过程，计算各agent所属的负载／发电机的投切及转移策略。仿真算例表明，该算法能够快速有效地求解船舶电力系统重构问题，最大程度保证系统的存活性。

Distributed power control algorithm based on game theory for wireless sensor networks

Energy saving is the most important issue in research and development for wireless sensor networks. A power control mechanism can reduce the power consumption of the whole network. Because the character of wireless sensor networks is restrictive energy, this paper proposes a distributed power control algorithm based on game theory for wireless sensor networks which objects of which are reducing power consumption and decreasing overhead and increasing network lifetime. The game theory and OPNET simulation shows that the power control algorithm converges to a Nash Equilibrium when decisions are updated according to a better response dynamic.

Bargaining Game Theoretic Power Control in Selfish Cooperative Relay Networks

Wireless cooperative communications require appropriate power allocation （PA） between the source and relay nodes. In selfish cooperative communication networks, two partner user nodes could help relaying information for each other, but each user node has the incentive to consume his power solely to decrease its own symbol error rate （SER） at the receiver. In this paper, we propose a fair and efficient PA scheme for the decode-and-forward cooperation protocol in selfish cooperative relay networks. We formulate this PA problem as a two-user cooperative bargaining game, and use Nash bargaining solution （NBS） to achieve a win-win strategy for both partner users. Simulation results indicate that the NBS is fair in that the degree of cooperation of a user only depends on how much contribution its partner can make to decrease its SER at the receiver, and efficient in the sense that the SER performance of both users could be improved through the game.

Optimal Power Management for Antagonizing Between Radar and Jamming Based on Continuous Game Theory

To solve the problem of dynamic power resource allocation for cooperative penetration combat,the continuous game theory is introduced and a two-person general-sum continuous-game-based model is put forward with a common payoff function named collaborative detection probability of netted radar countermeasures.Comparing with traditional optimization methods,an obvious advantage of game-based model is an adequate consideration of the opposite potential strategy.This model guarantees a more effective allocation of the both sides′power resource and a higher combat efficiency during a combat.Furthermore,an analysis of the complexity of the proposed model is given and a hierarchical processing method is presented to simplify the calculating process.Simulation results show the validity of the proposed scheme.

Game-theoretic approach to power and admission control in hierarchical wireless sensor networks

Power efficiency and link reliability are of great impor- tance in hierarchical wireless sensor networks （HWSNs）, espe- cially at the key level, which consists of sensor nodes located only one hop away from the sink node called OHS. The power and admission control problem in HWSNs is comsidered to improve its power efficiency and link reliability. This problem is modeled as a non-cooperative game in which the active OHSs are con- sidered as players. By applying a double-pricing scheme in the definition of OHSs＇ utility function, a Nash Equilibrium solution with network properties is derived. Besides, a distributed algorithm is also proposed to show the dynamic processes to achieve Nash Equilibrium. Finally, the simulation results demonstrate the effec- tiveness of the proposed algorithm.

Dual Power Allocation Optimization Based on Stackelberg Game in Heterogeneous Network with Hybrid Energy Supplies

In heterogeneous network with hybrid energy supplies including green energy and on-grid energy, it is imperative to increase the utilization of green energy as well as to improve the utilities of users and networks. As the difference of hybrid energy source in stability and economy, thus, this paper focuses on the network with hybrid energy source, and design the utility of each user in the hybrid energy source system from the perspective of stability, economy and environment pollution. A dual power allocation algorithm based on Stackelberg game to maximize the utilities of users and networks is proposed. In addition, an iteration method is proposed which enables all players to reach the Stackelberg equilibrium(SE). Simulation results validate that players can reach the SE and the utilities of users and networks can be maximization, and the green energy can be efficiently used.

Game Theoretic Analysis of Joint Rate and Power Allocation in Cognitive Radio Networks

Spectrum sharing is an essential enabling functionality to allow the coexistence between primary user (PU) and cognitive users (CUs) in the same frequency band. In this paper, we consider joint rate and power allocation in cognitive radio networks by using game theory. The optimum rates and powers are obtained by iteratively maximizing each CU’s utility function, which is designed to guarantee the protection of primary user (PU) as well as the quality of service (QoS) of CUs. In addition, transmission rates of some CUs should be adjusted if corresponding actual signal-to-interference-plus-noise ratio (SINR) falls below the target SINR. Based on the modified transmission rate for each CU, distributed power allocation is introduced to further reduce the total power consumption. Simulation results are provided to demonstrate that the proposed algorithm achieves a significant gain in power saving.

风氢耦合系统参与现货市场的竞标策略及优化调度方法

为解决高比例风电市场竞标能力弱、市场消纳困难的问题,提出高比例风电耦合氢储能系统联合参与现货市场竞价的双层Stackelberg博弈模型。首先,研究风氢耦合系统内部能量转换关系,揭示风氢耦合系统的能量“时空平移”机理,在综合考虑风氢耦合系统收益和成本的基础上,建立风电投标和氢储能充放电决策模型;其次,兼顾风氢耦合系统和独立系统运营商的利益诉求,基于Stackelberg博弈建立以火电机组、风氢耦合系统为主体的市场出清模型;最后,针对双层模型求解困难的问题,运用KKT条件和强对偶理论将双层模型转换为易于求解的单层混合整数规划模型。仿真结果表明,所提策略对高比例风电的市场消纳起到了积极作用。

QoS awared power and admission controls based on non-cooperative game theory in wireless networks

In order to better accommodate heterogeneous quality of service (QoS) in wireless networks, an algorithm called QoS-aware power and admission controls (QAPAC) is proposed. The system is modeled as a non-cooperative game where the users adjust their transmit powers to maximize the utility, thus restraining the interferences. By using adaptive utility functions and tunable pricing parameters according to QoS levels, this algorithm can well meet different QoS requirements and improve system capacity compared with those that ignore the QoS differences.

Generation Reliability Evaluation in Deregulated Power Systems Using Game Theory and Neural Networks

Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In the present research, generation reliability is considered, and a method for its assessment is proposed using Game Theory (GT) and Neural Networks (NN). Also, due to the stochastic behavior of power markets and generators’ forced outages, Monte Carlo Simulation (MCS) is used for reliability evaluation. Generation reliability focuses merely on the interaction between generation complex and load. Therefore, in the research, based on the behavior of players in the market and using GT, two outcomes are considered: cooperation and non-cooperation. The proposed method is assessed on IEEE-Reliability Test System with satisfactory results. Loss of Load Expectation (LOLE) is used as the reliability index and the results show generation reliability in cooperation market is better than non-cooperation outcome.

电厂和政府行为策略演化博弈与仿真研究——基于农林生物质与煤耦合发电产业发展视角

“双碳”背景下,农林生物质与煤耦合发电成为煤电转型的新路径。政府如何制定有效的补贴和监管政策,以及电厂如何进行正确的策略选择是促进农林生物质与煤耦合发电产业发展的关键。通过构建政府和电厂的混合策略博弈模型,分析双方的博弈关系和行为策略动态演变过程,并运用系统动力学进行建模仿真,进一步探析关键因素对政府和电厂行为策略的影响路径。结果表明:政府和电厂的行为策略在较长时期里无法趋于稳定,而是在相互影响中波动变化。政府制定补贴和监管策略、提高耦合发电收益、降低耦合发电成本,都将促进更多电厂选择农林生物质与煤耦合发电,从而进一步促进产业发展。

前景理论视角下废旧动力电池回收监管演化博弈分析

废旧动力电池具有较强的负外部性,违背了新能源汽车设计的初衷。为促进废旧动力电池有效回收,将前景理论与演化博弈论耦合,综合考虑政府、企业(汽车生产)和公众之间的利益,促使政府和公众对企业进行共同监督,构建三方博弈模型。针对初始意愿、罚款组成、风险态度系数和损失规避系数的不同情况,进行模拟数值仿真,并结合现实中废旧动力电池的认识度、奖惩机制和盈利信心进行分析。研究表明:提高公众或政府的初始监督意愿,可以促进企业回收废旧动力电池;当企业的回收策略为亏损时,提高企业对公众的补偿金额、降低企业的风险态度系数和损失规避系数,可以促进企业积极回收;在废旧动力电池回收过程中,共同监督的效果优于单独监督。

含电动汽车和光伏的配电网演化动态博弈调度策略

针对大规模电动汽车的无序充电行为可能导致电网出现的三相不平衡问题,基于演化动态博弈模型,提出一种考虑三相负荷平衡和光伏消纳的电动汽车充电调度策略。首先,基于电动汽车接入时段的主观性以及光伏出力和负荷的不确定性,引入游牧集群和定居集群之间的演化动态博弈方程;然后,考虑用户侧和电网侧双方利益关系,设计以最小化电动汽车充电费用、三相负荷不平衡度和无功需求为目标的调度优化模型;最后,通过对某商业区配电网算例进行仿真求解,对比分析三相有功曲线、三相无功曲线以及荷电状态曲线的变化趋势。算例结果表明,该调度策略可有效降低三相不平衡度,满足无功补偿的需求以及改善用户充电成本。

大学学科治理中的权力运行:现实困境与机制超越

权力运行是大学学科治理的核心议题,其中,行政权力与学术权力相互混淆、渗透问题被长期关切,然而治理效果有限。以博弈论为基础构建以“局中人-策略-利益”为核心要素的分析框架,尝试新思路求解老问题。研究发现,权力双方通过收益和成本的评估差值而作出自利最大化策略,欠缺对大学学科治理整体利益考量,因而导致利益争夺的局中人困境、决策变更的策略困境、格局失衡的利益困境。为更好突破困境,引导权力良序运行,需要构建基于利益共同体的共生机制破解局中人困境,构建基于小数据矩阵的理性决策机制破解策略困境,强化目标管理通过调适决策的价值理性和工具理性破解利益困境。

考虑碳-绿证的多主体多园区合作博弈优化调度

在“双碳”背景下,多园区联合调度发展迅速,需考虑如何兼顾多园区的经济性、环保性以及对新能源的消纳能力。提出考虑碳-绿证的多园区合作博弈调度策略。根据各园区功能特性建立多园区系统框架,并以园区运营商为领导者,储能电站、风电场和电网为跟随者,组建多主体联盟;利用碳-绿证配额机制对多园区新能源消纳量以及碳排放量进行分段量化,改善园区碳排放和风光消纳情况;选取功率交互贡献度作为合作博弈中Shapely法的权重,均衡各园区的成本和收益。仿真分析表明,所提模型和策略有效提高了园区的经济性和环保性,保证了联盟中各主体的收益平衡。

面向新型电力系统的储能规划方法研究进展及展望

储能是新型电力系统非常重要的灵活性调节资源,在源网荷各端均可发挥重要的作用,在中国,储能的发展已经进入规模化发展期,如何合理、经济地利用好储能的关键是规划配置方法。在对储能规划方法研究现状的基础上,分析了储能投资运营主体多元化、应用场景和运行模式复杂化、储能技术多样化等新变化对储能规划方法的影响;提出了新能源聚集区考虑时空互补和共享机制的储能规划方法、电网侧充分市场竞争下的储能与输配电系统协同规划方法,以及用户侧电、热、氢多元储能合作/竞争共存下的规划方法。面向新型电力系统的储能规划,未来应注重电力系统不同发展阶段的整体协调性、储能投资运营主体多元化内生博弈机制的影响,以及规划方案在多目标多场景下的迁移学习方法。

地缘政治视域下中国参与亚运会历程中的重要议题及杭州亚运会的时代成就

已经胜利落幕的杭州亚运会是在中国境内举办的第3届亚运会。采用文献资料法与历史研究法,回顾中国的亚运会参与史,进一步分析亚运会与亚洲地缘政治格局和体育格局的互动影响后发现,参与亚运会是中国走向世界体育、参与国际体育事务的重要桥梁;是中国施展体育外交坚实且富有弹性的“第一步”,是推动亚洲地缘关系,巩固在亚地位的重要渠道;是处理两岸关系的重要场域。在两个大局背景下,杭州亚运会在加强中国与亚洲国家的联系,促进亚洲国家的交流与团结,树立“可亲可爱”的中国形象,宣传“心心相融”的在亚外交倡议,推动两岸交流,夯实和平统一基础等方面体现出重要的时代价值,并为中国以体育促外交的未来发展提出新的议题。

Shapley值及其应用

Shapley值是合作博弈理论中最重要的概念之一,其在经济学、社会管理等领域具有十分广泛的应用.本文回顾了合作博弈的Shapley值的理论研究,并从Shapley-Shubik权力指数、拼车费用分摊、图博弈的Page-Shapley值以及SHAP方法与机器学习等4个方面介绍了Shapley值的应用进展.

超密集网络中基于多基站博弈均衡的分布式无线资源管理算法

移动边缘计算和超密集网络技术在扩大移动设备计算能力和增加网络容量方面有明显的优势.然而,在两者融合的场景下,如何有效降低基站之间的同信道干扰,减少任务传输的时延和能耗是一个重要研究课题.本文设计了一个基于多基站博弈均衡的分布式无线资源管理算法.将小基站之间的无线资源管理问题转化为博弈问题,提出一种基于奖励驱动的策略选择算法.基站通过迭代不断更新其策略的选择概率,最终优化子信道分配和发射功率的调控.仿真结果表明,我们的算法在提高信道利用率和降低任务处理的时延和能耗方面具有优势.

个人信息的内生安全机制及其实现

个人信息处理的技术性、隐蔽性,使自上而下的“命令式”监管范式失效。数字时代,个人信息治理的重点是防止个人信息处理者滥用数据权力威胁国家安全、盘剥和操控个体。为有效控制数据权力这一风险源,国家应当督促个人信息处理者建立健全涵盖制度保障、组织程序保障的个人信息内生安全机制。通过监管激活个人信息处理者内部的自我规制机制,增强其内部的组织控制和行为规范化程度,消减个人信息处理的负外部性,实现个人信息处理的正和博弈。通过监管督促个人信息处理者强化内部治理机制,严格落实个人信息保护影响评估制度,遵从“三同步”要求将个人信息保护法规定的各项义务嵌入产品“代码”中,防控个人信息处理过程中妨害个人自主性、减损人格尊严的风险。