The traditional droop control is usually used to share real and reactive power without communication for fully decentralization power system. Because of that the traditional droop control has its inherent limitations,...
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ISBN:
(纸本)9784886864055
The traditional droop control is usually used to share real and reactive power without communication for fully decentralization power system. Because of that the traditional droop control has its inherent limitations, this paper presents a modified droop controller based on Kalman filter to reduce load effect, and then utilizes a distributed consensus algorithm to transmit error voltage to other distributed generation (DG) with sparse communication network, and last make use of distributed model predictive control (MPC) to achieve accurately load power sharing between multi-parallel inverters. Simulation results is verified the reliability of the proposed algorithm in realizing load sharing and the voltage-frequency restoration.
The increasing number of electric vehicles (EVs) on highways calls for the installment of adequate charging infrastructure. Since charging infrastructure has limited capacity, EVs need to wait at a charging station to...
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The increasing number of electric vehicles (EVs) on highways calls for the installment of adequate charging infrastructure. Since charging infrastructure has limited capacity, EVs need to wait at a charging station to get charged, and their waiting times may differ significantly from one location to another. This paper aims at developing a strategy to coordinate the queues among the charging stations, with only local information about traffic flows and the status of EV charging stations along a bidirectional highway, so that excessively long waiting times can be avoided. Specifically, a distributedalgorithm is presented to schedule EV flows into neighboring charging stations, so that EVs are all appropriately served along the highway and that all the charging resources are uniformly utilized. In addition, a distributed decision making policy is developed to influence the aggregate number of EVs entering any given service station, so that each EV makes an appropriate decision (i.e., whether or not it should enter the next charging station) by contributing positively to meeting the desired queue length at service stations and by considering its own battery constraint. Performance improvement of the proposed strategy is illustrated via one of the highways in the United States, namely the Florida Turnpike.
Due to beneficial insights on PDEs, recently, the reverse of this approach is implemented where a spatially discrete system is approximated by a spatially continuous one, governed by linear PDEs forming diffusion equa...
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Due to beneficial insights on PDEs, recently, the reverse of this approach is implemented where a spatially discrete system is approximated by a spatially continuous one, governed by linear PDEs forming diffusion equations. In the case of distributed consensus algorithms, this approach is adapted to enhance its convergence rate to the equilibrium. In previous studies within this context, constant diffusion coefficient is considered for obtaining the diffusion equations. This is equivalent to assigning a constant weight to all edges of the underlying graph in the consensusalgorithm. Here, by relaxing this restricting assumption, a spatially variable diffusion coefficient is considered and by optimizing the obtained system, it is shown that significant improvements are achievable in terms of the convergence rate of the obtained spatially continuous system. As a result of approximation, the system is divided into two sections, namely, the spatially continuous path branches and the lattice core which connects these branches at one end. The optimized weights and diffusion coefficient for each of these sections are optimal individually, but considering the whole system, they are suboptimal. It is shown that the symmetric star topology is an exception and the obtained results for this topology are globally optimal. Furthermore, through a variational method, the results obtained for the symmetric star topology are validated and it is shown that the variable diffusion coefficient improves the robustness of the system too.
In a low-voltage microgrid system, the line impedances between power sources are resistive. The accuracy of reactive power sharing provided by droop controllers is affected by output impedances of the distributed gene...
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In a low-voltage microgrid system, the line impedances between power sources are resistive. The accuracy of reactive power sharing provided by droop controllers is affected by output impedances of the distributed generations (DGs) and line impedances. To improve the power sharing accuracy, a distributed secondary control approach is proposed in this paper. Based on the communication technology and hierarchical control theory, a novel distributed hierarchical control scheme is presented for the DSC of micro-grids (MGs), which consists of primary control layer and secondary control layer. The primary control layer includes droop control, voltage and current control as well as virtual impedance control to achieve power sharing. In the secondary control, distributed consensus algorithm is applied to designing the observer so as to get global average values, restoring the voltage deviation and improving the accuracy of reactive power sharing;meanwhile the proposed approach reduces the high bandwidth requirements, and improves the reliability and flexibility of microgrids. Finally, the simulation and experimental platform are built based on Matlab/Simulink software and dSPACE1103 device. Real-time simulation and experimental results are presented in order to evaluate the feasibility and effectiveness by the proposed distributed secondary control (DSC). The results indicate that the distributed consensus algorithm is very robust with respect to communication impairments, such as packet delays and random packet losses.
In this paper, a dynamic economic dispatch problem (DEDP) which considers the benefit function, environmental cost function and fuel cost function is studied by the distributed strategy. We propose a distributed algor...
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ISBN:
(纸本)9781538611272
In this paper, a dynamic economic dispatch problem (DEDP) which considers the benefit function, environmental cost function and fuel cost function is studied by the distributed strategy. We propose a distributedalgorithm based on undirected graphs and alternating direction method of multipliers (ADMM). Firstly, the DEDP is decomposed into three minimization steps to solve according to ADMM. Secondly, in the first minimization iterative step, with the E exponential term introduced into the environmental cost function and coupling constraint of all generators, we proposed a distributed consensus algorithm with Lambert W function to acquire the values of first minimization iterative step;in the second minimization iterative step, we use ADMM based on parallel projection and distributedconsensus strategy to gain the values of it. Based on the above designed, our algorithm is distributed, i.e., all the generators only communicate with their neighbors. Simulation results tested on IEEE14-bus system show that the proposed algorithm is capable of converging to the optimal solution of DEDP.
Spectrum Sensing (SS) is a crucial task of Cognitive Radio (CR) to avoid the destructive interference of the unlicensed users to the licensed users of the spectrum and to find the accessible spectrum for improving the...
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ISBN:
(纸本)9781538638644
Spectrum Sensing (SS) is a crucial task of Cognitive Radio (CR) to avoid the destructive interference of the unlicensed users to the licensed users of the spectrum and to find the accessible spectrum for improving the spectrum utilization. But detection of licensed users is often compromised due to issues such as multipath fading, shadowing, and receiver uncertainty. So to deal with these issues, Cooperative Spectrum Sensing (CSS) has been proposed. There are two classes in CSS: centralized and decentralized or distributed. In this paper, we compare a fully distributed CSS technique using consensusalgorithms with the existing OR fusion rule based CSS scheme under AWGN, Rayleigh and correlated log-normal shadowing environments. We also compare existing OR rule with a distributed coalition sensing scheme and study the effect of error in reporting channel. Simulation results show that distributedconsensus scheme outperforms OR fusion rule, thus showing the importance of distributed schemes. But in the case of distributed coalition sensing and OR fusion rule, both show somewhat same performance. We found that, with increasing probability of error in reporting channel, the probability of false alarm increases drastically showing a degradation in detection performance.
This paper addresses the economic operation of multiple plug-in electric vehicle parking decks using novel distributed cooperative control methods. In this paper, we proposes a consensus-based distributed cooperative ...
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This paper addresses the economic operation of multiple plug-in electric vehicle parking decks using novel distributed cooperative control methods. In this paper, we proposes a consensus-based distributed cooperative control algorithm to determine the best operation strategy for the operator/owner of multiple parking decks. The proposed distributed control approach completely eliminates the reliance on a central controller to make an optimal decision while still satisfying a variety of global and local constraints. Case studies demonstrate the accuracy, robustness, effectiveness, and scalability of the proposed distributed cooperative control method for solving the economic operation problem of multiple plug-in electric vehicle parking decks under various operating conditions. The distributed control ideas contained here can apply to many other smart grid applications.
The traditional droop control is usually used to share real and reactive power without communication for fully decentralization power system. Because of that the traditional droop control has its inherent limitations,...
详细信息
The traditional droop control is usually used to share real and reactive power without communication for fully decentralization power system. Because of that the traditional droop control has its inherent limitations, this paper presents a modified droop controller based on Kalman filter to reduce load effect, and then utilizes a distributed consensus algorithm to transmit error voltage to other distributed generation (DG) with sparse communication network, and last make use of distributed model predictive control (MPC) to achieve accurately load power sharing between multi-parallel inverters. Simulation results is verified the reliability of the proposed algorithm in realizing load sharing and the voltage-frequency restoration.
This paper deals with an output consensus problem of multiple agents and first presents a centralized algorithm for solving it by a model predictive control method based on linear matrix inequalities. It can be shown ...
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ISBN:
(纸本)9781424453634
This paper deals with an output consensus problem of multiple agents and first presents a centralized algorithm for solving it by a model predictive control method based on linear matrix inequalities. It can be shown that the outputs of all the agents controlled by the presented method asymptotically converge to a common point, i.e., consensus point. Then two kinds of algorithms for solving the consensus problem in a decentralized way are presented by using primal and dual decomposition methods. In general, these algorithms require a large number of iterations, i.e., a large number of communications between agents. To cope with this communication burden, a method that can reduce the number of iterations and guarantee the convergence to a consensus point is proposed by exploiting the property that the primal and dual decomposition methods can give upper and lower bounds of the optimal value of the optimization problem to be solved. The numerical example is given to illustrate the effectiveness of the proposed method.
This paper presents a distributedconsensus strategy that regulates the power outputs of dispersed energy storage systems ( DESS) in power distribution network, which can be used to smooth the renewable power fluctuat...
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ISBN:
(纸本)9781467371063
This paper presents a distributedconsensus strategy that regulates the power outputs of dispersed energy storage systems ( DESS) in power distribution network, which can be used to smooth the renewable power fluctuations. The algorithm is based on the consensusalgorithm in graph theory and it satisfies both the smooth of the renewable power fluctuations and the equity allocation among DESS. The most distinct feature of the algorithm is that there is no "dispatch center" or "leader" to collect the global information in real-time power allocation process, each DESS obtains the global information and allocates its power outputs and realizes the target of smoothing the global renewable power fluctuations according to the local information interaction among DESS. Simulation on the IEEE 34-bus distribution system demonstrates the effectiveness of the proposed algorithm.
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