With the increasing penetration of distributed generators, distributed algorithms have become essential for efficient power system operations. However, these algorithms are often vulnerable to noise and communication ...
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ISBN:
(数字)9798350373929
ISBN:
(纸本)9798350373936
With the increasing penetration of distributed generators, distributed algorithms have become essential for efficient power system operations. However, these algorithms are often vulnerable to noise and communication delays due to their dependence on communication infrastructures. A consensus-based decentralized method is presented in this paper to solve economic dispatch in microgrids, accounting for practical communication challenges such as dynamically switching topologies, communication delays, and noise. A proportional-integral (PI) consensus protocol is proposed to address these issues, which includes an integral term to mitigate the harmful effects of noise and delays. The multi-agent system (MAS) model is used to describe the microgrid. A distributed PI consensus approach with two primary consensus variables—the global power imbalance (∆P ) and the incremental cost (λ)—is employed to solve the economic dispatch problem. A key benefit of this method is that it allows generating units to maintain the confidentiality of their cost characteristics. The effectiveness of the presented approach is demonstrated by simulation results on a microgrid with five buses.
This paper presents a fully distributed algorithm for scheduling electric vehicle (EV) charging and discharging to flatten the total load of the grid, while considering constraints on grid transmission capacity. As a ...
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ISBN:
(数字)9798350316339
ISBN:
(纸本)9798350316346
This paper presents a fully distributed algorithm for scheduling electric vehicle (EV) charging and discharging to flatten the total load of the grid, while considering constraints on grid transmission capacity. As a fully distributed solution, the proposed algorithm operates without the need for a central unit. Instead, each agent only communicates a single dual variable with its neighboring agents based on a communication graph, and thus no private information is shared. In particular, the algorithm does not rely on initial conditions, ensuring robustness in online changes of operational conditions. Simulation results verify the effectiveness of the proposed algorithm.
In this paper, we study distributed prime-dual flows for multi-agent optimization with spatio-temporal compressions. The central aim of multi-agent optimization is for a network of agents to collaboratively solve a sy...
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ISBN:
(数字)9798350316339
ISBN:
(纸本)9798350316346
In this paper, we study distributed prime-dual flows for multi-agent optimization with spatio-temporal compressions. The central aim of multi-agent optimization is for a network of agents to collaboratively solve a system-level optimization problem with local objective functions and node-to-node communication by distributed algorithms. The scalability of such algorithms crucially depends on the complexity of the communication messages, and a number of communication compressors for distributed optimization have recently been proposed in the literature. First of all, we introduce a general spatio-temporal compressor characterized by the stability of the resulting dynamical system along the vector field of the compressor. We show that several important distributed optimization compressors such as the greedy sparsifier, the uniform quantizer, and the scalarizer all fall into the category of this spatio-temporal compressor. Next, we propose two distributed prime-dual flows with the spatio-temporal compressors being applied to local node states and local error states, respectively, and prove (exponential) convergence of the node trajectories to the global optimizer for (strongly) convex cost functions. Finally, a few numerical examples are present to illustrate our theoretical results.
This paper presents a distributed algorithm based on mutual feedback mechanism for economic dispatch problem of power system. In such a mutual feedback mechanism, the average of the load demand and power generated are...
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ISBN:
(数字)9798350366204
ISBN:
(纸本)9798350366211
This paper presents a distributed algorithm based on mutual feedback mechanism for economic dispatch problem of power system. In such a mutual feedback mechanism, the average of the load demand and power generated are estimated, respectively. Simulation results on standard test cases show the convergence and effectiveness of the proposed algorithm.
This paper investigates the Nash equilibrium seeking problem for aggregative games, where some players are under Byzantine attacks. Since the previous distributed algorithms might be seriously affected by Byzantine at...
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ISBN:
(数字)9798350382655
ISBN:
(纸本)9798350382662
This paper investigates the Nash equilibrium seeking problem for aggregative games, where some players are under Byzantine attacks. Since the previous distributed algorithms might be seriously affected by Byzantine attacks that inject malicious information to the system, we propose a resilient distributed geometric-median based method to improve the robustness of the algorithm. When less than half of the players are Byzantine attackers and under strongly monotone assumption on the pseudo-gradient mapping, we show that the algorithm converges linearly to a neighborhood of the Nash Equilibrium with an error bound related to the ratio of Byzantine attackers. Finally, numerical examples are implemented to demonstrate the robustness of the proposed algorithm under various types of Byzantine attacks.
To reduce the environmental impact of port carbon emissions and promote the sustainable development of ports, this paper proposes a port distributed energy management strategy considering the charging and discharging ...
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ISBN:
(数字)9798350353334
ISBN:
(纸本)9798350353341
To reduce the environmental impact of port carbon emissions and promote the sustainable development of ports, this paper proposes a port distributed energy management strategy considering the charging and discharging of unmanned surface vehicles (USVs) under the polymorphic network. Firstly, taking into account the trend of continuous automation of ports, data centers are used to meet the ports' growing computing power needs. A data center power consumption calculation model considering data processing delay constraints is proposed. Secondly, taking the port microgrid operating cost, the main grid electricity purchase or sales cost, carbon cost, data center operating cost and USVs charging and discharging cost as objective functions, a port distributed energy management model considering USVs charging and discharging is established. Then, a distributed algorithm based on mixed integer linear programming is proposed to solve the problem. Finally, simulation results demonstrate the effectiveness of the proposed method.
A distributed approach is proposed in this work to solve large-scale optimization problems, called L-DATR, under the master/worker communication model. L-DATR is a distributed limited-memory trust-region method that a...
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ISBN:
(数字)9798350376647
ISBN:
(纸本)9798350376654
A distributed approach is proposed in this work to solve large-scale optimization problems, called L-DATR, under the master/worker communication model. L-DATR is a distributed limited-memory trust-region method that allows worker nodes to perform asynchronous computations. Our method dynamically adjusts the step size and direction using trust-region strategies to improve stability and convergence. To our knowledge, this is the first implementation of a distributed trust-region limited memory quasi-Newton method with robust handling of asynchronous updates and non-uniform delays between nodes. Our method is communication-efficient because it communicates only vectors of the dimension of the decision variable. Our numerical experiments match our theoretical results and showcase significant stability improvements compared to state-of-the-art distributed algorithms.
A critical edge is an edge whose removal results in the associated undirected network becoming disconnected. Identifying these critical edges and enhancing the corresponding edge connectivity is critical for achieving...
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ISBN:
(数字)9798350316339
ISBN:
(纸本)9798350316346
A critical edge is an edge whose removal results in the associated undirected network becoming disconnected. Identifying these critical edges and enhancing the corresponding edge connectivity is critical for achieving robustness in network connectivity. While existing methodologies are effective, they are centralized and rely on global information, which makes them not scalable with respect to the network size or its implementation. To address these shortcomings, a fully distributed approach is introduced in this paper to identify all the critical edges within an undirected network without requiring a central coordinating authority. Computationally, the proposed method has a complexity of ${\mathcal{O}}(n)$, where n is the number of nodes, which is more efficient when compared to the centralized approaches. Furthermore, the proposed method can be used to incrementally increase the network’s edge connectivity to 2, thus addressing the network’s most vulnerable edges.
To meet the development needs of new-type distribution networks, this paper proposes a distributed hierarchical control strategy based on honeycomb-like distribution network topology. Initially, we define the relevant...
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ISBN:
(数字)9798331505905
ISBN:
(纸本)9798331505912
To meet the development needs of new-type distribution networks, this paper proposes a distributed hierarchical control strategy based on honeycomb-like distribution network topology. Initially, we define the relevant concepts of microgrids (MGs) and establish a multi-layer control architecture based on the honeycomb-shaped distribution network. Subsequently, the paper designs methods for autonomous operation and hierarchical running of each MG area: each MG formulates day-ahead operation plans according to its own source-load characteristics; MGs achieve interaction of energy and information through base stations, while the distribution network operation center adopts the alternating direction method of multipliers (ADMM) as a distributed algorithm to realize power allocation among MGs; MGs connect with the distribution network via connection points to satisfy their energy balance. Finally, through case studies, the proposed control strategy is verified to alleviate the control burden of distribution network operators.
In this paper, we consider the problem of distributed average consensus in multi-agent systems, where each agent can come in or move out of the system, possibly multiple times. In the literature, such systems are refe...
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ISBN:
(数字)9798350316339
ISBN:
(纸本)9798350316346
In this paper, we consider the problem of distributed average consensus in multi-agent systems, where each agent can come in or move out of the system, possibly multiple times. In the literature, such systems are referred to as open multi-agent systems. A typical goal in such settings is to use an iterative distributed algorithm to calculate the average of some quantities of interest each agent possesses, which can be crucial in many estimation, control, or optimization applications. We consider an open multi-agent setting and propose a distributed algorithm that allows the participating agents to track their average. More specifically, if the set of agents remaining in the computation eventually settles to a certain subset of agents, then the proposed algorithm allows them (under some mild connectivity conditions) to asymptotically reach consensus to the average of the quantities of interest these remaining agents hold. Analysis and numerical examples to illustrate the operation of the proposed algorithm are also provided.
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