Distributed Economic Dispatch Control via Saddle Point Dynamics and Consensus Algorithms

Bai, Liang; Ye, Maojiao; Sun, Chao; Hu, Guoqiang

doi:10.1109/tcst.2017.2776222

Cited by 66 publications

(25 citation statements)

References 29 publications

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“…结合不等式 (25), 于是, 2 3 0 0 1 3 0 0 0 0 0 0 2 3 0 0 0 0 1 3 0 0 0 0 2 3 0 0 0 0 0 1 3 1 3 0 0 0 1 3 1 3 0 0 0 0 0 0 1 3 1 3 0 1 3 0 0 0 0 0 1 3 0 1 3 0 0 1 3 0 1 3 0 0 1 3 0 0 1 3 0 0 0 0 0 0 0 1 3 1 3 1 3 0 0 1 3 0 0 1 3 0 1 3 为进一步验证所提出的分布式算法的可扩展性, 采用 IEEE 39 母线系统 [19] 进行了仿真分析. IEEE 39 母线系统由 10 个发电机 (分别位于母线 30∼39) 和 19 个负荷组成.…”

Section: 收敛性分析unclassified

Distributed algorithm for economic dispatch based on gradient descent and consensus in power grid

Ma¹,

Yu²,

Zhu³

et al. 2018

Sci. Sin.-Inf.

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This study aims to propose, a distributed optimization algorithm to solve the economic dispatch problem encountered in power grids with the ultimate objective of minimizing the total generation cost. The proposed approach is based on the gradient descent method and the consensus protocol. No central unit was required to broadcast the global information to each bus, and only local information was exchanged between the neighboring buses to balance power supply and demand. Theoretical analysis revealed that the proposed algorithm can converge to the optimal solution of the primal problem by selecting the appropriate step size and initial values. Simulation studies on the IEEE 9-bus system were conducted to show the validity of the proposed algorithm.

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Section: 收敛性分析unclassified

Distributed algorithm for economic dispatch based on gradient descent and consensus in power grid

Ma¹,

Yu²,

Zhu³

et al. 2018

Sci. Sin.-Inf.

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show abstract

“…In [25], a novel, distributed approach for the economic dispatch problem was proposed; a flooding-based consensus approach was applied. A consensus algorithm was utilized in [26] to estimate local information in a distributed way; the saddle point method was also combined with it to dynamically seek the optimal solution to the ED problem, and the algorithm's stability was analyzed by Lyapunov stability theory. In [27], an improved power flow control strategy of the BMC based on VSM for the hybrid AC/DC microgrid was proposed.…”

Section: Introductionmentioning

confidence: 99%

Distributed Dynamic Economic Dispatch of an Isolated AC/DC Hybrid Microgrid Based on a Finite-Step Consensus Algorithm

Zong

et al. 2019

Energies

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The AC/DC hybrid microgrid is the main trend of microgrids’ development, and the dynamic economic dispatch is regarded as an important way to ensure the economic and safe operation of a microgrid system. In this paper, a dynamic economic dispatch model of the isolated AC/DC hybrid microgrid is developed with the objective of minimizing the daily operation cost of controllable units. Furthermore, a distributed algorithm based on the finite-step consensus algorithm is proposed, in which the incremental cost of each distributed generation unit is set as a consensus variable, and all units obtain the optimal values by exchanging information only with their neighbors. In addition, the algorithm converges to the optimal solutions in finite steps, and the efficiency is improved significantly. The effectiveness of the proposed model and the algorithm were verified by simulation.

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“…As the size of the network increases, it is important to develop fast and efficient distributed methods where agents can perform local computations to collectively find the global optimal solution. This scenario arises in, for example, distributed learning problems [1], economic dispatch problems [2], and multi-agent coordination problems [3].…”

Section: Introductionmentioning

confidence: 99%

A Chebyshev-Accelerated Primal-Dual Method for Distributed Optimization

Seidman

Fazlyab

Pappas

et al. 2018

2018 IEEE Conference on Decision and Control (CDC)

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We consider a distributed optimization problem over a network of agents aiming to minimize a global objective function that is the sum of local convex and composite cost functions. To this end, we propose a distributed Chebyshevaccelerated primal-dual algorithm to achieve faster ergodic convergence rates. In standard distributed primal-dual algorithms, the speed of convergence towards a global optimum (i.e., a saddle point in the corresponding Lagrangian function) is directly influenced by the eigenvalues of the Laplacian matrix representing the communication graph. In this paper, we use Chebyshev matrix polynomials to generate gossip matrices whose spectral properties result in faster convergence speeds, while allowing for a fully distributed implementation. As a result, the proposed algorithm requires fewer gradient updates at the cost of additional rounds of communications between agents. We illustrate the performance of the proposed algorithm in a distributed signal recovery problem. Our simulations show how the use of Chebyshev matrix polynomials can be used to improve the convergence speed of a primal-dual algorithm over communication networks, especially in networks with poor spectral properties, by trading local computation by communication rounds.

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Distributed Economic Dispatch Control via Saddle Point Dynamics and Consensus Algorithms

Cited by 66 publications

References 29 publications

Distributed algorithm for economic dispatch based on gradient descent and consensus in power grid

Distributed algorithm for economic dispatch based on gradient descent and consensus in power grid

Distributed Dynamic Economic Dispatch of an Isolated AC/DC Hybrid Microgrid Based on a Finite-Step Consensus Algorithm

A Chebyshev-Accelerated Primal-Dual Method for Distributed Optimization

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