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 se...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.展开更多
Due to its capability of solving decision-making problems involving multiple entities and objectives, as well as complex action sequences, game theory has been a basic mathematical tool of economists, politicians, and...Due to its capability of solving decision-making problems involving multiple entities and objectives, as well as complex action sequences, game theory has been a basic mathematical tool of economists, politicians, and sociologists for decades. It helps them understand how strategic interactions impact rational decisions of individual players in competitive and uncertain environment, if each player aims to get the best payoff. This situation is ubiquitous in engineering practices. This paper streamlines the foundations of engineering game theory, which uses concepts, theories and methodologies to guide the resolution of engineering design, operation, and control problems in a more canonical and systematic way. An overview of its application in smart grid technologies and power systems related topics is presented, and intriguing research directions are also envisioned.展开更多
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...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.展开更多
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 comm...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.展开更多
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...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.展开更多
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. A...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.展开更多
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 allocati...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.展开更多
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 pr...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.展开更多
抽水蓄能作为电力系统中最为成熟的新能源储能技术,凭借其能调节电网负荷、平衡电力波动及提升系统稳定性的独特优势,已成为实现中国“双碳”目标的重要路径之一。因此,对抽水蓄能电站综合效益进行科学评估,是项目决策及政策制定中至关...抽水蓄能作为电力系统中最为成熟的新能源储能技术,凭借其能调节电网负荷、平衡电力波动及提升系统稳定性的独特优势,已成为实现中国“双碳”目标的重要路径之一。因此,对抽水蓄能电站综合效益进行科学评估,是项目决策及政策制定中至关重要的一环。为此,本文提出一种基于博弈论组合赋权‒云模型的综合效益评价模型。首先,运用社会网络分析法(SNA)筛选关键评价指标,构建包含财务评价、国民经济评价、技术效益、动态效益、静态效益、电网效益、综合可持续性效益和社会效益8个1级指标及其下属30个2级指标的评价指标体系。其次,采用序关系分析(G1)法和CRITIC(criteria importance through intercriteria correlation)法相结合的方式,对各评价指标进行主观与客观权重赋值。通过引入博弈论组合赋权方法,进一步优化各指标的权重分配。最终,基于云模型构建综合效益评价模型。利用博弈论组合赋权‒云模型对紫云山抽水蓄能电站进行实例分析,结果表明,该电站的综合效益评估等级为“好”,与实际情况相符,充分验证了所构建模型的有效性与准确性。该研究不仅为抽水蓄能电站的综合效益评估提供了科学的评估框架,并为类似项目的决策和实施提供了理论支持和实践依据。展开更多
当综合能源系统(integrated energy system,IES)的电、气、热系统分属不同的运营主体时,IES内部异质能之间的协调调度会导致各主体利益的严重冲突,不利于维系IES多能系统联合运行机制的稳定性,因此,需要解决IES内部多能系统协同运营定...当综合能源系统(integrated energy system,IES)的电、气、热系统分属不同的运营主体时,IES内部异质能之间的协调调度会导致各主体利益的严重冲突,不利于维系IES多能系统联合运行机制的稳定性,因此,需要解决IES内部多能系统协同运营定价机制、该机制下的IES内部多能系统协同优化调度,以及IES与配电网(active distribution network,ADN)联合运行优化调度等关键问题,以促进IES中高比例新能源的就地消纳,实现多主体利益共赢。为此,文中提出了IES内部多余电能有偿交易模式,即电力系统将剩余电能转化为气、热能,电力运营商据此制定售能价格,引导气、热公司优先购买,通过气、热时空迁移调节调度,促进新能源就地消纳。对此,文中构建了IES双层优化调度模型:外层,为ADN和IES之间的主从博弈模型,优化电网电价和IES电能交易量;内层,为电力运营商与气、热公司之间的主从博弈模型,优化电力运营商报价和气、热公司购能策略。采用粒子群优化(particle swarm optimization,PSO)算法和CPLEX求解器相结合求解,内、外双层模型交替迭代优化,获得ADN最优购售电价策略及电、气、热各主体最优能量调度策略,并通过多场景算例,对比验证了文中方法的有效性。展开更多
针对多虚拟电厂(virtual power plant,VPP)协同运行中的源荷不确定性与隐私保护难题,提出一种融合点对点(peer to peer,P2P)电能共享与分布式优化的创新框架。首先,建立含云储能租赁系统的电热型VPP模型,设计多VPP点对点电能互济框架;其...针对多虚拟电厂(virtual power plant,VPP)协同运行中的源荷不确定性与隐私保护难题,提出一种融合点对点(peer to peer,P2P)电能共享与分布式优化的创新框架。首先,建立含云储能租赁系统的电热型VPP模型,设计多VPP点对点电能互济框架;其次,为克服传统不确定性优化方法的计算复杂度高与保守性强缺陷,构建计及最恶劣源荷场景概率的四层三阶段随机鲁棒优化模型,同步处理源荷出力及场景概率分布双重不确定性,并提出支持并行计算的改进型列与约束生成(column and constraint generation,C&CG)算法提升求解效率;最后,基于纳什谈判理论建立多VPP利益分配模型,将其建模为合作成本最小化与个体收益最大化子问题,采用融合改进C&CG的交替方向乘子法(alternating direction multiplier method,ADMM)分布式算法实现隐私保护下的高效求解。算例表明,所提模型使不确定环境下系统经济性显著提升,该分布式求解方法能同时保证系统隐私性与求解效率,实现各虚拟电厂收益的公平分配。展开更多
随着电动汽车和分布式电源接入电网的比例不断提升,虚拟电厂(virtual power plant,VPP)为有效解决电动汽车、分布式电源并网提供了新思路。针对VPP独立运行时面临的运行成本高、电价和源荷不确定性大等挑战,文中提出了一种基于纳什三阶...随着电动汽车和分布式电源接入电网的比例不断提升,虚拟电厂(virtual power plant,VPP)为有效解决电动汽车、分布式电源并网提供了新思路。针对VPP独立运行时面临的运行成本高、电价和源荷不确定性大等挑战,文中提出了一种基于纳什三阶段鲁棒优化的多VPP协同运行的优化方法。为协调VPP运营商与电动汽车用户的经济利益冲突,采用主从博弈理论刻画VPP运营商和电动汽车上下层之间的互动关系,上层VPP运营商充分考虑到电力市场购售电价以及源荷功率波动带来的不确定性影响,由三阶段鲁棒优化模型构造上层主体,三阶段鲁棒优化模型较以往的传统模型不同,文中采用了min-maxmin-maxmin的构造刻画模型内部关系;构建了基于纳什谈判理论的多VPP协同优化模型,为解决复杂非凸非线性优化的求解问题,将模型等效转化为多VPP合作成本最小化和电能谈判支付两个子问题;考虑到各VPP间信息隐私安全,采用交替方向乘子法(alternating direction method of multipliers,ADMM)对上述两个子问题进行分布式求解。算例验证表明,所提方法不仅在多重不确定性影响的情况下为参与合作的各VPP提供了可行且鲁棒性强的调度方案,而且为各VPP制定了合理的能源交互策略和利益分配方案,参与合作的各VPP均实现了经济效益的提升。展开更多
文摘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.
基金This work was supported by National Natural Science Foundation of China （No. 51621065）.
文摘Due to its capability of solving decision-making problems involving multiple entities and objectives, as well as complex action sequences, game theory has been a basic mathematical tool of economists, politicians, and sociologists for decades. It helps them understand how strategic interactions impact rational decisions of individual players in competitive and uncertain environment, if each player aims to get the best payoff. This situation is ubiquitous in engineering practices. This paper streamlines the foundations of engineering game theory, which uses concepts, theories and methodologies to guide the resolution of engineering design, operation, and control problems in a more canonical and systematic way. An overview of its application in smart grid technologies and power systems related topics is presented, and intriguing research directions are also envisioned.
基金supported by National Natural Science Foundation of China (No. 60972059)Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)+3 种基金Fundamental Research Funds for the Central Universities of China (Nos. 2010QNA27 and 2011QNB26)China Postdoctoral Science Foundation (No. 20100481185)the Ph. D. Programs Foundation of Ministry of Education of China (Nos. 20090095120013 and 20110095120006)Talent Introduction Program, and Young Teacher Sailing Program of China University of Mining and Technology
文摘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.
基金Supported by the National Natural Science Foundation of China(60774064,61305133)the National Research Foundation for the Doctoral Program of Higher Education of China(20116102110026)+1 种基金the Aerospace Technology Support Foundation(2013-HT-XGD)the Aeronautical Science Foundation of China(2013zc53037)
文摘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.
基金supported by the National Natural Science Foundation of China (7070102571071105)+2 种基金the Program for New Century Excellent Talents in Universities of China (NCET-08-0396)the National Science Fund for Distinguished Young Scholars of China (70925005)the Program for Changjiang Scholars and Innovative Research Team in University (IRT/028)
文摘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.
基金supported by the Beijing Natural Science Foundation (4142049)863 project No. 2014AA01A701the Fundamental Research Funds for Central Universities of China No. 2015XS07
文摘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.
文摘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.
文摘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.
文摘抽水蓄能作为电力系统中最为成熟的新能源储能技术,凭借其能调节电网负荷、平衡电力波动及提升系统稳定性的独特优势,已成为实现中国“双碳”目标的重要路径之一。因此,对抽水蓄能电站综合效益进行科学评估,是项目决策及政策制定中至关重要的一环。为此,本文提出一种基于博弈论组合赋权‒云模型的综合效益评价模型。首先,运用社会网络分析法(SNA)筛选关键评价指标,构建包含财务评价、国民经济评价、技术效益、动态效益、静态效益、电网效益、综合可持续性效益和社会效益8个1级指标及其下属30个2级指标的评价指标体系。其次,采用序关系分析(G1)法和CRITIC(criteria importance through intercriteria correlation)法相结合的方式,对各评价指标进行主观与客观权重赋值。通过引入博弈论组合赋权方法,进一步优化各指标的权重分配。最终,基于云模型构建综合效益评价模型。利用博弈论组合赋权‒云模型对紫云山抽水蓄能电站进行实例分析,结果表明,该电站的综合效益评估等级为“好”,与实际情况相符,充分验证了所构建模型的有效性与准确性。该研究不仅为抽水蓄能电站的综合效益评估提供了科学的评估框架,并为类似项目的决策和实施提供了理论支持和实践依据。
文摘当综合能源系统(integrated energy system,IES)的电、气、热系统分属不同的运营主体时,IES内部异质能之间的协调调度会导致各主体利益的严重冲突,不利于维系IES多能系统联合运行机制的稳定性,因此,需要解决IES内部多能系统协同运营定价机制、该机制下的IES内部多能系统协同优化调度,以及IES与配电网(active distribution network,ADN)联合运行优化调度等关键问题,以促进IES中高比例新能源的就地消纳,实现多主体利益共赢。为此,文中提出了IES内部多余电能有偿交易模式,即电力系统将剩余电能转化为气、热能,电力运营商据此制定售能价格,引导气、热公司优先购买,通过气、热时空迁移调节调度,促进新能源就地消纳。对此,文中构建了IES双层优化调度模型:外层,为ADN和IES之间的主从博弈模型,优化电网电价和IES电能交易量;内层,为电力运营商与气、热公司之间的主从博弈模型,优化电力运营商报价和气、热公司购能策略。采用粒子群优化(particle swarm optimization,PSO)算法和CPLEX求解器相结合求解,内、外双层模型交替迭代优化,获得ADN最优购售电价策略及电、气、热各主体最优能量调度策略,并通过多场景算例,对比验证了文中方法的有效性。
文摘针对多虚拟电厂(virtual power plant,VPP)协同运行中的源荷不确定性与隐私保护难题,提出一种融合点对点(peer to peer,P2P)电能共享与分布式优化的创新框架。首先,建立含云储能租赁系统的电热型VPP模型,设计多VPP点对点电能互济框架;其次,为克服传统不确定性优化方法的计算复杂度高与保守性强缺陷,构建计及最恶劣源荷场景概率的四层三阶段随机鲁棒优化模型,同步处理源荷出力及场景概率分布双重不确定性,并提出支持并行计算的改进型列与约束生成(column and constraint generation,C&CG)算法提升求解效率;最后,基于纳什谈判理论建立多VPP利益分配模型,将其建模为合作成本最小化与个体收益最大化子问题,采用融合改进C&CG的交替方向乘子法(alternating direction multiplier method,ADMM)分布式算法实现隐私保护下的高效求解。算例表明,所提模型使不确定环境下系统经济性显著提升,该分布式求解方法能同时保证系统隐私性与求解效率,实现各虚拟电厂收益的公平分配。
文摘随着电动汽车和分布式电源接入电网的比例不断提升,虚拟电厂(virtual power plant,VPP)为有效解决电动汽车、分布式电源并网提供了新思路。针对VPP独立运行时面临的运行成本高、电价和源荷不确定性大等挑战,文中提出了一种基于纳什三阶段鲁棒优化的多VPP协同运行的优化方法。为协调VPP运营商与电动汽车用户的经济利益冲突,采用主从博弈理论刻画VPP运营商和电动汽车上下层之间的互动关系,上层VPP运营商充分考虑到电力市场购售电价以及源荷功率波动带来的不确定性影响,由三阶段鲁棒优化模型构造上层主体,三阶段鲁棒优化模型较以往的传统模型不同,文中采用了min-maxmin-maxmin的构造刻画模型内部关系;构建了基于纳什谈判理论的多VPP协同优化模型,为解决复杂非凸非线性优化的求解问题,将模型等效转化为多VPP合作成本最小化和电能谈判支付两个子问题;考虑到各VPP间信息隐私安全,采用交替方向乘子法(alternating direction method of multipliers,ADMM)对上述两个子问题进行分布式求解。算例验证表明,所提方法不仅在多重不确定性影响的情况下为参与合作的各VPP提供了可行且鲁棒性强的调度方案,而且为各VPP制定了合理的能源交互策略和利益分配方案,参与合作的各VPP均实现了经济效益的提升。
