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A Novel Discounted Min-Consensus algorithm for Optimal Electrical Power Trading in Grid-Connected DC Microgrids

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2019年第11期66卷 8474-8484页

作者： Xu, Yinliang Sun, Hongbin Gu, Wei Tsinghua Berkeley Shenzhen Inst Shenzhen Environm Sci & New Energy Technol Engn L Shenzhen 518055 Peoples R China Tsinghua Berkeley Shenzhen Inst Shenzhen 518055 Peoples R China Tsinghua Univ Dept Elect Engn State Key Lab Power Syst Beijing 100084 Peoples R China Southeast Univ Sch Elect Engn Nanjing 210096 Jiangsu Peoples R China

Due to the private ownerships of various resource and equipment in a microgrid, it is essential to design a proper power trading strategy for a mutually satisfying partnership among suppliers and users. This paper proposes a novel discounted min-consensus algorithm to discover the optimal electrical power trading route with minimal power loss in dc microgrids. The proposed distributed algorithm only requires information exchange among neighbors based on a peer-to-peer communication protocol, which is robust to topology changes and enables parallel data processing to achieve fast decision-making. The convergence and optimality of the proposed discounted min-consensus algorithm are guaranteed by rigorous analysis. Simulation results of the 10-bus, 68-bus, and 1062-bus power systems demonstrate the effectiveness of the proposed distributed optimal routing strategy for electrical power trading. Moreover, the proposed novel distributed algorithm sheds light on applying distributed control and optimization approaches to solve problems arising in artificial intelligence.

关键词： DC microgrid discounted min-consensus distributed algorithm electrical power trading optimal routing algorithm

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Leader Tracking of Euler-Lagrange Agents on Directed Switching Networks Using a Model-Independent algorithm

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2019年第2期6卷 561-571页

作者： Ye, Mengbin Anderson, Brian D. O. Yu, Changbin Westlake Univ Inst Adv Technol Westlake Inst Adv Study Hangzhou 310024 Zhejiang Peoples R China Australian Natl Univ Res Sch Engn Canberra ACT 2601 Australia Univ Groningen ENTEG Fac Sci & Engn NL-9747 AG Groningen Netherlands Hangzhou Dianzi Univ Sch Automat Hangzhou 310000 Zhejiang Peoples R China Australian Natl Univ Canberra ACT 2601 Australia CSIRO Data61 Canberra ACT 2601 Australia

In this paper, we propose a discontinuous distributed model- independent algorithm for a directed network of Euler- Lagrange agents to track the trajectory of a leader with nonconstant velocity. We initially study a fixed network and show that the leader tracking objective is achieved semiglobally exponentially fast if the graph contains a directed spanning tree. By model independent, we mean that each agent executes its algorithm with no knowledge of the parameter values of any agent's dynamics. Certain bounds on the agent dynamics (including any disturbances) and network topology information are used to design the control gain. This fact, combined with the algorithm's model independence, results in robustness to disturbances and modeling uncertainties. Next, a continuous approximation of the algorithm is proposed, which achieves practical tracking with an adjustable tracking error. Last, we show that the algorithm is stable for networks that switch with an explicitly computable dwell time. Numerical simulations are given to show the algorithm's effectiveness.

关键词： Directed graph distributed algorithm Euler-Lagrange agent model independent switching network tracking

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Decentralized iterative approaches for community clustering in the networks

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JOURNAL OF SUPERCOMPUTING 2019年第8期75卷 4894-4917页

作者： Bhih, Amhmed Johnson, Princy Randles, Martin LJMU Dept Elect & Elect Engn Comp Sci Liverpool L3 3AF Merseyside England

In this era of big data, as the data size is scaling up, the need for computing power is exponentially increasing. However, most of the community detection algorithms in the literature are classified as global algorithms, which require access to the entire information of the network. These algorithms designed to work on a single machine cannot be directly parallelized. Hence, it is impossible for such algorithms working in stand-alone machines to find communities in large-scale networks and also the required processing power far exceeds the processing capabilities of single machines. In this paper, a set of novel Decentralized Iterative Community Clustering Approaches to extract an efficient community structure for large networks are proposed and devalued using the LFR benchmark model. The approaches have the ability to identify the community clusters from the entire network without global knowledge of the network topology and will work with a range of computer architecture platforms (e.g., cluster of PCs, multi-core distributed memory servers, GPUs). Detecting and characterizing such community structures is one of the fundamental topics in network systems' analysis, and it has many important applications in different branches of science including computer science, physics, mathematics and biology ranging from visualization, exploratory and data mining to building prediction models.

关键词： Community detection Connectivity-based graph clustering distributed algorithm

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CSDGP: cluster switched data gathering protocol for mobile wireless sensor networks

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IET COMMUNICATIONS 2019年第18期13卷 2973-2985页

作者： Karunanithy, Kalaivanan Velusamy, Bhanumathi Anna Univ Reg Campus Dept ECE Coimbatore 641046 Tamil Nadu India

Nowadays, most of the research focuses on the distributed algorithm to form the clusters in wireless sensor networks, in which the sensor nodes act autonomously to self-configure themselves with the help of the local information. However, the issues in such distributed mechanisms are (i) how to assign the time division multiple access (TDMA) schedule to collect the data from the cluster member (CM), (ii) how to distribute and balance the overall energy consumption of the cluster heads (CHs) under the circumstance of node's mobility. To overcome these problems, a cluster switched data gathering protocol (CSDGP) is proposed which ensures a uniform distribution of CHs by utilising a waiting time-based CH selection and an effective cluster switch based TDMA scheduling mechanism. The salient feature observed in the proposed CSDGP is that the migrated node has a chance to transmit the sensed data to the CH, whenever the CH has a free time slot. From the simulation results, it is proved that CSDGP provides a good performance under three different scenarios in comparison with existing protocols in terms of average energy consumption, average end-to-end delay, packet delivery ratio, and control overhead.

关键词： protocols wireless sensor networks mobile radio time division multiple access distributed algorithms telecommunication scheduling CSDGP mobile wireless sensor networks distributed algorithm sensor nodes local information distributed mechanisms time division multiple access schedule cluster heads cluster switched data gathering protocol uniform distribution waiting time-based CH selection effective cluster switch TDMA scheduling mechanism free time slot energy consumption node mobility end-to-end delay packet delivery ratio control overhead

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Dynamic Multi-Tenant Coordination for Sustainable Colocation Data Centers

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IEEE TRANSACTIONS ON CLOUD COMPUTING 2019年第3期7卷 733-743页

作者： Guo, Yuanxiong Pan, Miao Gong, Yanmin Fang, Yuguang Oklahoma State Univ Sch Elect & Comp Engn Stillwater OK 74078 USA Univ Houston Dept Elect & Comp Engn Houston TX 77204 USA Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

Colocation data centers are an important type of data centers that have some unique challenges in managing their energy consumption. Tenants in a colocation data center usually manage their servers independently without coordination, leading to inefficiency. To address this issue, we propose a formulation of coordinated energy management for colocation data centers. Considering the randomness of workload arrival and electricity cost function, we formulate it as a stochastic optimization problem, and then develop an online algorithm to solve it efficiently. Our algorithm is based on Lyapunov optimization, which only needs to track the instantaneous values of the underlying random factors without requiring any knowledge of the statistics or future information. Moreover, alternating direction method of multipliers (ADMM) is utilized to implement our algorithm in a decentralized way, making it easy to be implemented in practice. We analyze the performance of our online algorithm, proving that it is asymptotically optimal and robust to the statistics of the involved random factors. Moreover, extensive trace-based simulations are conducted to illustrate the effectiveness of our approach.

关键词： Colocation data centers energy-efficiency green computing Lyapunov optimization distributed algorithm

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On the Convergence of Message Passing Computation of Harmonic Influence in Social Networks

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2019年第2期6卷 116-129页

作者： Rossi, Wilbert Samuel Frasca, Paolo Univ Twente Dept Appl Math NL-7500 AE Enschede Netherlands Univ Grenoble Alpes CNRS INRIA Grenoble INPGIPSA Lab F-38000 Grenoble France

The harmonic influence is a measure of node influence in social networks that quantifies the ability of a leader node to alter the average opinion of the network, acting against an adversary field node. The definition of harmonic influence assumes linear interactions between the nodes described by an undirected weighted graph;its computation is equivalent to solve a discrete Dirichlet problem associated to a grounded Laplacian for every node. This measure has been recently studied, under slightly more restrictive assumptions, by Vassio et al., IEEE Trans. Control Netw. Syst., 2014, who proposed a distributed message passing algorithm that concurrently computes the harmonic influence of all nodes. In this paper, we provide a convergence analysis for this algorithm, which largely extends upon previous results: we prove that the algorithm converges asymptotically, under the only assumption of the interaction Laplacian being symmetric. However, the convergence value does not in general coincide with the harmonic influence: by simulations, we show that when the network has a larger number of cycles, the algorithm becomes slower and less accurate, but nevertheless provides a useful approximation. Simulations also indicate that the symmetry condition is not necessary for convergence and that performance scales very well in the number of nodes of the graph.

关键词： distributed algorithm message passing opinion dynamics social networks

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Bearing-only circumnavigation control of the multi-agent system around a moving target

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IET CONTROL THEORY AND APPLICATIONS 2019年第17期13卷 2747-2757页

作者： Yu, Yangguang Li, Zhongkui Wang, Xiangke Shen, Lincheng Natl Univ Def Technol Coll Mechatron & Automat Changsha 410073 Hunan Peoples R China Peking Univ Coll Engn Dept Mech & Aerosp Engn State Key Lab Turbulence & Complex Syst Beijing 100871 Peoples R China

The bearing-based coordinated circumnavigation control for networked multi-agent systems with only bearing measurements in the presence of moving target is studied. First, a distributed algorithm is proposed to estimate the target's velocity and the distances between the agents and the target, based on the velocity and the bearing information of the local network. Then, a distributed circumnavigation algorithm is designed to drive the agents to circumnavigate around a moving target at a desired distance. The stability of the proposed control algorithm is proven by employing the newly developed bearing rigidity theory. Finally, the simulation experiment is performed based on the Gazebo simulator to illustrate the effectiveness of the proposed circumnavigation control law.

关键词： mobile robots aerospace control multi-robot systems multi-agent systems control engineering computing numerical analysis mathematical analysis motion control space vehicles bearing-only multiagent system moving target bearing-based networked multiagent systems bearing measurements distributed algorithm bearing information local network distributed circumnavigation algorithm control algorithm circumnavigation control law

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Planning While Flying: A Measurement-Aided Dynamic Planning of Drone Small Cells

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IEEE INTERNET OF THINGS JOURNAL 2019年第2期6卷 2693-2705页

作者： Lu, Ning Zhou, Yi Shi, Chenhao Cheng, Nan Cai, Lin Li, Bin Thompson Rivers Univ Dept Comp Sci Kamloops BC V2C 0C8 Canada Henan Univ Sch Comp & Informat Engn Kaifeng 475001 Peoples R China Xidian Univ Sch Telecommun Engn Xian 710071 Shaanxi Peoples R China Univ Victoria Dept Elect & Comp Engn Victoria BC V8W 3P6 Canada Univ Rhode Isl Dept Elect Comp & Biomed Engn South Kingstown RI 02881 USA

The deployment of drone small cells has emerged as a promising solution to agile provisioning of Internet backbone access for Internet of Things devices, and many other types of users/devices. In this paper, we consider the problem of deploying a set of drone cells operating on multiple channels in a target area to provide access to the backbone/core network, which is formulated as a combinatorial network utility maximization problem. Since an offline and centralized solution to such a problem is not feasible, a low-complexity and distributed online algorithm is highly desired. Therefore, we propose a measurement-aided dynamic planning (MAD-P) algorithm, where the dispatched drones perform position and channel configurations autonomously on the fly based on the real-time measurement of network throughput to solve the problem in a distributed fashion during flight with minimal centralized control. We prove that the proposed MAD-P algorithm is asymptotically optimal, and investigate how long it takes for the convergence to stationarity under the MAD-P algorithm by giving a mixing time analysis. We also derive an upper bound of the performance gap in presence of measurement errors. Simulation results are provided to validate our analytic results and demonstrate the effectiveness of our algorithm.

关键词： distributed algorithm drone small cell Internet of Things (IoT) Markov approximation optimal dynamic planning unmanned aerial vehicles (UAVs)

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A Generalized Nash Equilibrium Approach for Autonomous Energy Management of Residential Energy Hubs

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2019年第11期15卷 5892-5905页

作者： Liang, Yile Wei, Wei Wang, Cheng Alibaba Grp Beijing 100102 Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China North China Elect Power Univ Sch Elect & Elect Engn Beijing 102206 Peoples R China

The development of the cutting-edge technologies in cogeneration and trigeneration has led to a rapid transition toward integrated energy systems and the mushrooming of energy hubs, calling for effective energy management schemes. This paper proposes a distributed algorithm for autonomous energy management (AEM) of a cluster of residential energy hubs. Given the interactive behaviors of energy purchasing at the supply side, we treat each hub as a self-interested agent, and formulate the AEM problem of these hubs as a monotone generalized Nash game (MON-GNG). On one hand, there are global coupling constraints representing the supply limits of the input energy systems, which are imposed by the limited capacities of electrical feeders and natural gas pipelines, thus making it a GNG. On the other hand, the cost function of each hub is merely convex in its actions considering the input-to-output energy transformation inside and the impacts of the energy storage devices, which leads to an MON game. The existence of the generalized Nash equilibria (GNEs) of this MON-GNG can be theoretically guaranteed. Then, by reformulating the MON-GNG as a variational inequality problem with special decomposition structure, an efficient and single-loop distributed algorithm is then proposed for computing a GNE with clear economic interpretation based on an improved Tikhonov regularization technique. Principles of parameter selection that will guarantee convergence are suggested. Numeric simulations validate the convergence performance and effectiveness of the proposed algorithm.

关键词： distributed algorithms Games Energy management Resistance heating Turbines Optimization Nash equilibrium distributed algorithm energy hub generalized Nash equilibrium (GNE) integrated energy system (IES) variational inequality (VI)

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A Two-Stage Game Model for Combined Heat and Power Trading Market

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IEEE TRANSACTIONS ON POWER SYSTEMS 2019年第1期34卷 506-517页

作者： Wu, Chenyu Gu, Wei Bo, Rui Jiang, Ping Wu, Zhi Lu, Shuai Yao, Shuai Southeast Univ Sch Elect Engn Nanjing 210096 Jiangsu Peoples R China Missouri Univ Sci & Technol Dept Elect & Comp Engn Rolla MO 65409 USA

The proliferation of technologies such as combined heat and power systems and smart meters has accelerated the multi-energy trading. A two-stage game model is built in this paper to analyze the optimal strategy of each player and their interactions. Specifically, in consumer game model, we present an autonomous and distributed micro energy management system among users in which power and heat are traded at the same time. In supplier game model, integrated energy suppliers receive energy demand information and share the market according to the game result. In addition, we present a detailed proof of the existence and uniqueness of the Nash equilibrium, which lays the foundation for researchers to build an effective model using game theory. Further, a distributed algorithm specifically designed for this model is proposed. The players can retain a certain level of anonymity without revealing the details of their energy consumption or generation schedules to other players. Lastly, simulation results confirm the feasibility of two-stage game model and the effectiveness of the proposed distributed algorithm.

关键词： Demand side management distributed algorithm game theory micro energy management system

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