Decentralized energy management using consensus-based algorithm is a vibrant research field since it can promote the local accommodation of the renewable energy generation without raising privacy and scalability issue...
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Decentralized energy management using consensus-based algorithm is a vibrant research field since it can promote the local accommodation of the renewable energy generation without raising privacy and scalability issues. Most of the existing methods assume that the communication links are reliable, which might not be true in real-world implementations. This paper focuses on tackling the problem of random packet drops. We first formulate the models of the energy management problem in the microgrid and the information packet drop in the communication network. based on the models, we conclude that losing the information about incremental electricity cost estimation is tolerable, while losing the information about the power mismatch estimation is not. We propose a novel consensusalgorithm that tracks and exchanges the accumulated value of the power mismatch estimation so that the information loss can be recovered. An equivalent form of the proposed method is established by augmenting the communication links with virtual buffering nodes. based on the augmented communication topology, we theoretically prove the convergence of the proposed algorithm and the optimality of the solution. Several case studies are provided to validate the effectiveness of the proposed algorithm.
The existing event-triggered (ET) strategies for distributed multi-target filter commonly employ triggering conditions focusing on the instantaneous information discrepancy. Although this approach can save com-municat...
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The existing event-triggered (ET) strategies for distributed multi-target filter commonly employ triggering conditions focusing on the instantaneous information discrepancy. Although this approach can save com-munication resource, it suffers from its sensitivity to instantaneous disturbance and outliers that results in unnecessary communications. In this correspondence, an integral-type event-triggered mechanism is integrated with the consensus-based labeled multi-Bernoulli filter (LMB). The proposed algorithm provides a passivation effect that lowers the communication activities while preserving the tracking performance in the uncertain environment with disturbance. The theoretical analysis demonstrates that the integral-type event-triggered mechanism introduces bounded information discrepancy in the sense of Kullback-Leibler (KL) divergence. The proposed algorithm is also verified by numerical simulations in a target tracking scenario.
Economic dispatch problem(EDP)is a fundamental optimization problem in power system operation,which aims at minimizing the total generation *** fact,the power grid is becoming a cyber-physical power system(CPPS).There...
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Economic dispatch problem(EDP)is a fundamental optimization problem in power system operation,which aims at minimizing the total generation *** fact,the power grid is becoming a cyber-physical power system(CPPS).Therefore,the quality of communication is a key *** this paper,considering two important factors,i.e.,time delays and channel noises,a fully distributed consensusbasedalgorithm is proposed for solving *** critical maximum allowable upper bounds of heterogeneous communication delays and self-delays are *** should be pointed out that the proposed algorithm can be robust against the time-varying delays and channel noises considering generator *** addition,even with time-varying delays and channel noises,the power balance of supply and demand is not broken during the *** simulation studies are presented to validate the correctness and superiority of the developed results.
This paper discusses a distributed design for clustering based on the K-means algorithm in a switching multi-agent network, for the case when data are decentralized stored and unavailable to all agents. The authors pr...
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This paper discusses a distributed design for clustering based on the K-means algorithm in a switching multi-agent network, for the case when data are decentralized stored and unavailable to all agents. The authors propose a consensus-based algorithm in distributed case, that is, the double- clock consensus-based K-means algorithm (DCKA). With mild connectivity conditions, the authors show convergence of DCKA to guarantee a distributed solution to the clustering problem, even though the network topology is time-varying. Moreover, the authors provide experimental results on vari- ous clustering datasets to illustrate the effectiveness of the fully distributed algorithm DCKA, whose performance may be better than that of the centralized K-means algorithm.
For the microgrids to operate securely, distributed generators must be able to interact with one another without experiencing any communication delays or noise. To develop a more effective economic dispatch strategy, ...
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For the microgrids to operate securely, distributed generators must be able to interact with one another without experiencing any communication delays or noise. To develop a more effective economic dispatch strategy, this research focuses on noise's effect on the performance of an islanded microgrid. Three different strategies, Lagrange, firefly, and artificial bee colony algorithms, are compared for optimal solutions of economic dispatch. Their performance is compared based on stability during noise interference and faster response time with and without the virtual synchronous generator-STATCOM strategy. The virtual synchronous generator is used as a voltage source to regulate active power and reactive power with the grid. A STATCOM controller is introduced in the system for reactive power compensation. Reactive power compensation is the process of controlling reactive power to enhance the efficiency of alternating current power systems. By boosting the active power, reactive power compensation in the transmission system will increase the stability of microgrids. The voltage, output power, power factor, and phase angle of the microgrid benefit from the stability provided by the controller. As a result, the performance and resilience of the microgrid is improved.
The proper operation of microgrids depends on Economic Dispatch. It satisfies all requirements while lowering the microgrids' overall operating and generation costs. Since distributed generators constitute a large...
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The proper operation of microgrids depends on Economic Dispatch. It satisfies all requirements while lowering the microgrids' overall operating and generation costs. Since distributed generators constitute a large portion of microgrids, seamless communication between generators is essential. While guaranteeing a reliable microgrid operation, this should be achieved with the fewest losses as possible. The distributed generator technology introduces noise into the system by design. To find the best economic dispatch strategy, noise was considered in this research as a limitation in grid-connected microgrids. The microgrid's performance was improved, and the proposed technique also showed increased resilience. A virtual synchronous generator (VSG) control approach is proposed with a noiseless consensus-based algorithm to improve the power quality of microgrids. Voltage and frequency regulation modules are the foundation of the VSG paradigm. The synchronous generator's second-order equation (hidden-pole configuration) was also used to represent the voltage of the stator and rotor motion. This study compared changes in power, frequency, and voltage for the microgrid by utilizing the described control approach using MATLAB. According to the findings, this method aids in controlling load and noise variations and offers distributed generators an efficient control strategy.
This paper aims at the distributed computation for semi-definite programming (SDP) problems over multi-agent networks. Two SDP problems, including a non-sparse case and a sparse case, are transformed into distributed ...
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This paper aims at the distributed computation for semi-definite programming (SDP) problems over multi-agent networks. Two SDP problems, including a non-sparse case and a sparse case, are transformed into distributed optimization problems, respectively, by fully exploiting their structures and introducing consensus constraints. Inspired by primal-dual and consensus methods, we propose two distributed algorithms for the two cases with the help of projection and derivative feedback techniques. Furthermore, we prove that the algorithms converge to their optimal solutions, and moreover, their convergences rates are evaluated by the duality gap. (C) 2021 Elsevier Ltd. All rights reserved.
This article proposes a secondary level control technique for dc microgrids, which achieves accurate power sharing through a distributed strategy while performing dc bus voltage restoration in a decentralized fashion....
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This article proposes a secondary level control technique for dc microgrids, which achieves accurate power sharing through a distributed strategy while performing dc bus voltage restoration in a decentralized fashion. In order to attain proper power sharing, each power converter exchanges its output power information with neighboring converters through a low-bandwidth network at defined time intervals. A consensus-based algorithm is employed to process this information and modify the converter's droop coefficient, compensating droop mismatches and cable resistances and enabling power sharing. Restoration of the average dc bus voltage is realized locally with each converter compensating its own output voltage drop through an integrator. A comprehensive design procedure and performance and stability analysis, including communication loss and substantial time delays, are also provided. The strategy has shown to be robust to some communication failure scenarios and moderate communication delays. The proposed method is evaluated through simulation in the software PLECS and it is experimentally validated in a 4.5-kW dc microgrid setup.
This paper tries to develop a multiagent consensus-based algorithm to handle the energy management problem (EMP) in the smart grids in the presence of dispatchable loads and distributed generators. To this end, the ne...
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This paper tries to develop a multiagent consensus-based algorithm to handle the energy management problem (EMP) in the smart grids in the presence of dispatchable loads and distributed generators. To this end, the neighbor virtualization concept is employed to improve the system performance by introducing a novel communication structure for distributed algorithms. Accuracy, quickness, and scalability are the most important benefits of this algorithm that make it applicable in real power systems. The increasing penetration of wind turbines and the stochastic nature of load demand can inject much uncertainty in our problem. In order to deal with this issue, unscented transform as a powerful tool is used to model the problem uncertainties. The proposed problem is formulated in the form of a single-objective stochastic optimization framework maximizing the generators and consumers welfare. The feasibility and high performance of the proposed framework are examined on two test systems, including the IEEE 39-bus test system and a large grid with 1305 agents in MATLAB simulation. The simulation results advocate the high capability and effectiveness of the proposed framework for EMP of smart grids.
Distributed, consensus-based algorithms constitute a promising approach for the coordination of distributed energy resources (DER) due to their practical advantages over centralized approaches. However, state-of-the-a...
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ISBN:
(纸本)9781728111568
Distributed, consensus-based algorithms constitute a promising approach for the coordination of distributed energy resources (DER) due to their practical advantages over centralized approaches. However, state-of-the-art consensus-based algorithms address the coordination problem in independent time periods and therefore are inherently unable to capture the time-shifting flexibility of the demand side. This paper demonstrates that state-of-the-art algorithms fail to converge when time-shiftable flexible demands (TSFD) are present. In order to address this fundamental limitation, a relative maximum power restriction is introduced, which effectively mitigates the concentration of the TSFD responses at the same time periods and steers the consensus-based algorithm towards a feasible and near-optimal solution.
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