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distributed Optimization of Islanded Microgrids Integrating Multi-Type VSG Frequency Regulation and Integrated Economic Dispatch

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ENERGIES 2024年第7期17卷 1618页

作者： Xu, Huixin Sun, Jiahang Huang, Jingguang Lin, Xinyuan Ma, Chenghao China Three Gorges Univ Natl Virtual Simulat Expt Ctr Elect Engn Yichang 443002 Peoples R China

The question of how to simultaneously perform frequency regulation and integrated economic scheduling for microgrids with low-inertia islanding operation under communication constraints is a difficult problem that needs to be solved for many current applications. To this end, this paper establishes a microgrid scheduling control model containing a virtual synchronous generator (VSG) with multiple types of power sources and proposes a distributed optimization algorithm that integrates frequency regulation and comprehensive economic scheduling to simultaneously realize frequency regulation and economic scheduling in a microgrid. Firstly, a distributed economic dispatch problem is proposed based on a comprehensive consideration of the costs and benefits of various types of power VSGs, as well as the overall inertia and standby capacity requirements of the microgrid, which minimizes the integrated costs incurred by the participation of each type of VSG in the frequency regulation and improves the stable operation of the microgrid in terms of frequency under perturbation. Then, the optimal scheduling problem is solved by reconstructing the optimization problem based on considering the dynamic characteristics of microgrid inverters and using event-triggered communication to sense and compensate for the supply-demand imbalance online. The proposed method can avoid inter-layer coordination across time scales, improve the inertia, frequency regulation capability, and economy of the system, and enhance its robustness to short-term communication failures. Finally, simulation results are used to verify the effectiveness of the method.

关键词： virtual synchronization machine optimized scheduling frequency regulation distributed algorithms isolated island microgrid

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Comparative Study of distributed Consensus Gossip algorithms for Network Size Estimation in Multi-Agent Systems

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FUTURE INTERNET 2021年第5期13卷 134页

作者： Kenyeres, Martin Kenyeres, Jozef Slovak Acad Sci Inst Informat Dribravska Cesta 9 Bratislava 84507 Slovakia EBCONT Proconsult GmbH Millennium TowerHandelskai 94-96 A-1200 Vienna Austria

Determining the network size is a critical process in numerous areas (e.g., computer science, logistic, epidemiology, social networking services, mathematical modeling, demography, etc.). However, many modern real-world systems are so extensive that measuring their size poses a serious challenge. Therefore, the algorithms for determining/estimating this parameter in an effective manner have been gaining popularity over the past decades. In the paper, we analyze five frequently applied distributed consensus gossip-based algorithms for network size estimation in multi-agent systems (namely, the Randomized gossip algorithm, the Geographic gossip algorithm, the Broadcast gossip algorithm, the Push-Sum protocol, and the Push-Pull protocol). We examine the performance of the mentioned algorithms with bounded execution over random geometric graphs by applying two metrics: the number of sent messages required for consensus achievement and the estimation precision quantified as the median deviation from the real value of the network size. The experimental part consists of two scenarios-the consensus achievement is conditioned by either the values of the inner states or the network size estimates-and, in both scenarios, either the best-connected or the worst-connected agent is chosen as the leader. The goal of this paper is to identify whether all the examined algorithms are applicable to estimating the network size, which algorithm provides the best performance, how the leader selection can affect the performance of the algorithms, and how to most effectively configure the applied stopping criterion.

关键词： consensus algorithms count data aggregation distributed algorithms distributed computing gossip algorithms information fusion network size network size estimation sensor fusion

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distributed Optimal Assignment Algorithm for Collective Foraging

Distributed Optimal Assignment Algorithm for Collective Fora...

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American Control Conference (ACC)

作者： Miyano, Tatsuya Romberg, Justin Egerstedt, Magnus Toyota Motor North Amer Inc 1555 Woodridge Ave Ann Arbor MI 48105 USA Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA Univ Calif Irvine Samueli Sch Engn Irvine CA 92697 USA

ISBN: (数字)9781665451963

ISBN: (纸本)9781665451963

We consider the problem of collectively transporting multiple objects by multiple agents. The objective is to find the optimal matching between the objects and agents that minimizes the energy of the overall system. We show that combining a proximal gradient method with continuous relaxation yields a distributed algorithm which converges to a near-optimal solution for the associated optimization problem. Furthermore, by using this solution as an initial solution, a distributed negative-cycle canceling algorithm, which monotonically decreases the matching cost at each step, provides the globally optimal solution for the problem. Numerical simulations demonstrate the performance on practical problems.

关键词： Gradient methods Costs Numerical simulation Optimal matching distributed algorithms Optimization

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SRSSIS: Super-Resolution Screen Space Irradiance Sampling for Lightweight Collaborative Web3D Rendering Architecture 18th

SRSSIS: Super-Resolution Screen Space Irradiance Sampling fo...

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18th International Conference on Computer-Aided Design and Computer Graphics (CAD/Graphics)

作者： Long, Huzhiyuan Yang, Yufan Liu, Chang Jia, Jinyuan Tongji Univ 1239 Siping Rd Shanghai Peoples R China Nanchang Hangkong Univ 696 Fenghe South Ave Nanchang Jiangxi Peoples R China

ISBN: (纸本)9789819996650;9789819996667

traditional collaborative rendering architecture, the front-end computes direct lighting, which imposes certain performance requirements on the front-end devices. To further reduce the front-end load in complex 3D scenes, we propose a Super-resolution Screen Space Irradiance Sampling technique (SRSSIS), which is applied to our designed architecture, a lightweight collaborative rendering system built on Web3D. In our system, the back-end samples low-resolution screen-space irradiance, while the front-end implements our SRSSIS technique to reconstruct high-resolution and high-quality images. We also introduce frame interpolation in the architecture to further reduce the backend load and the transmission frequency. Moreover, we propose a self-adaptive sampling strategy to improve the robustness of super-resolution. Our experiments show that, under ideal conditions, our reconstruction performance is comparable to DLSS and FSR real-time super-resolution technology. The bandwidth consumption of our system ranges from 8% to 66% of pixel streaming at different super-resolution rates, while the back-end's computational cost is approximately 33% to 46% of pixel streaming at different super-resolution rates.

关键词： Collaborative rendering Web3D Super resolution distributed algorithms

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distributed Algorithm Design for Resource Allocation Problems of Second-Order Multi-Agent Systems 41

Distributed Algorithm Design for Resource Allocation Problem...

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第41届中国控制会议

作者： Tao Chen Jin Luo Zhenhua Deng Xiaolon Zuo Xuepeng Zhou Yong-min Liu School of Automation Central South University College of Computer and Information Engineering Central South University of Forestry and Technology Research Center of Smart Forestry Cloud Central South University of Forestry and Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,we investigate distributed resource allocation problems of second-order multi-agent systems,where the decisions of agents are subjected to inequality network resource *** contrast to well-known resource allocation problems,the second-order dynamics of agents and the coupling inequality constraints are considered in our problem at the same *** order to optimally allocate the network resource,a distributed algorithm is developed via state feedback and gradient ***,the convergence of the algorithm is analyzed with the help of convex analysis and Lyapunov stability *** the algorithm,the second-order agents globally asymptotically converge to the optimal ***,the effectiveness of our method is verified by the numerical example.

关键词： Resource allocation inequality constraints second-order multi-agent systems distributed algorithms cyberphysical systems

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On observability and optimal gain design for distributed linear filtering and prediction 30

On observability and optimal gain design for distributed lin...

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30th European Signal Processing Conference (EUSIPCO)

作者： Das, Subhro IBM Res MIT IBM Watson AI Lab Cambridge MA 02142 USA

ISBN: (纸本)9789082797091

This paper presents a new approach to distributed linear filtering and prediction. The problem under consideration consists of a random dynamical system observed by a multi-agent network of sensors where the network is sparse. Inspired by the consensus+innovations type of distributed estimation approaches, this paper proposes a novel algorithm that fuses the concepts of consensus and innovations. The paper introduces a definition of distributed observability, required by the proposed algorithm, which is a weaker assumption than that of global observability and connected network assumptions combined together. Following first principles, the optimal gain matrices are designed such that the mean-squared error of estimation is minimized at each agent and the distributed version of the algebraic Riccati equation is derived for computing the gains.

关键词： Kalman filter distributed estimation multiagent networks distributed algorithms consensus

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Path Computation in Multi-switching Multi-layer Networks

Path Computation in Multi-switching Multi-layer Networks

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International Conference on Computing, Networking and Communications (ICNC)

作者： Yi, Zihe Chen, Lin Sun Yat Sen Univ Sch Comp Sci & Engn Guangzhou Peoples R China

ISBN: (纸本)9798350371000;9798350370997

In this paper, we study the problem of path computation in multi-layer multi-switching networks. Compared to the standard shortest path problem, path computation in this context needs to take into account the heterogeneous switching capabilities of nodes. We develop a routing algorithm by adapting the Floyd-Warshall algorithm to take into account the switching technology conversion. Our algorithm solves the all-pair min-cost continuous path problem by building routing tables for each node to allows hop-to-hop routing. We then extend our efforts by developing a distributed routing algorithm to construct the routing tables based on local information and interactions with direct neighbors. We complete our algorithmic analysis with extensive simulations to demonstrate the effectiveness of the developed routing algorithms.

关键词： Path computation multi-switching multi-layer networks distributed algorithms

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distributed Online Learning for Joint Regret with Communication Constraints 33

Distributed Online Learning for Joint Regret with Communicat...

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33rd International Conference on Algorithmic Learning Theory (ALT)

作者： van der Hoeven, Dirk Hadiji, Hedi van Erven, Tim Univ Milan Dept Comp Sci Milan Italy Univ Amsterdam Korteweg de Vries Inst Math Amsterdam Netherlands

We consider distributed online learning for joint regret with communication constraints. In this setting, there are multiple agents that are connected in a graph. Each round, an adversary first activates one of the agents to issue a prediction and provides a corresponding gradient, and then the agents are allowed to send a b-bit message to their neighbors in the graph. All agents cooperate to control the joint regret, which is the sum of the losses of the activated agents minus the losses evaluated at the best fixed common comparator parameters u. We observe that it is suboptimal for agents to wait for gradients that take too long to arrive. Instead, the graph should be partitioned into local clusters that communicate among themselves. Our main result is a new method that can adapt to the optimal graph partition for the adversarial activations and gradients, where the graph partition is selected from a set of candidate partitions. A crucial building block along the way is a new algorithm for online convex optimization with delayed gradient information that is comparator-adaptive, meaning that its joint regret scales with the norm of the comparator parallel to u parallel to. We further provide near-optimal gradient compression schemes depending on the ratio of b and the dimension times the diameter of the graph.

关键词： Online convex optimization distributed algorithms

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distributed algorithm for social cost minimization with second-order nonlinear over-unbalanced

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SYSTEMS & CONTROL LETTERS 2024年 183卷

作者： Nian, Xiaohong Li, Fan Liu, Dongxin Cent South Univ Sch Automat Changsha 410075 Peoples R China

In this paper, the emerging social cost minimization framework of second -order nonlinear systems over weight -unbalanced digraphs is studied. It provides a general framework containing several important classes of problems. Therein each local cost function depends on a global decision variable consisting of all the agents' decisions not limited to the form of aggregative terms. Under the partial decision and cost function information setting, distributed algorithms are designed based on the state feedback and left eigenvector estimation mechanism to overcome the challenges posed by second -order nonlinear systems and weightunbalanced digraphs. The asymptotic convergence of the algorithm is demonstrated via the Lyapunov stability theory. Finally, numerical simulations of the vehicle monitoring problem are provided to support the algorithm design.

关键词： Social cost minimization distributed algorithms Weight-unbalanced digraphs Second-order nonlinear systems

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distributed strategy for constrained resource allocation problems of autonomous second-order nonlinear agents and its application to smart grids

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INFORMATION SCIENCES 2024年 652卷

作者： Deng, Zhenhua Luo, Jin Chen, Tao Cent South Univ Sch Automat Changsha 410075 Hunan Peoples R China Cent South Univ Room 3181 Comprehens BldgRailway Campus Changsha 410075 Hunan Peoples R China

This paper studies the constrained distributed resource allocation problems (DRAPs) of autonomous multi-agent systems (MASs). Unlike well-defined DRAPs, the disturbed second-order agents are taken into account. Moreover, all agents' decisions are subject to both coupling and local inequalities. Because of the coexistence of disturbed second-order nonlinear dynamics and inequality constraints, existing strategies are not applicable to tackle our problem. Also, they create challenges for the strategy design, because the inequality constraints must hold at the optimal allocation (OA), while these agents are not able to control their decisions directly. By gradient descent, state feedback and internal model (IM), we exploit a distributed strategy to control all agents to carry out the distributed resource allocation tasks (DRATs). Furthermore, the strategy is rigorously analyzed. Finally, our strategy is applied to the economic dispatch problems (EDPs). Under our approach, turbine-generators can autonomously achieve the optimal generation allocation by regulating their powers, in accordance with the load demand of smart grids.

关键词： Resource allocation Inequality constraints Second-order nonlinear multi-agent systems distributed algorithms Internal model Cyber-physical systems

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