Coordinated consensus for smart grid economic environmental power dispatch with dynamic communication network

Hamdi, Mounira; Chaoui, Mondher; Idoumghar, Lhassane; Kachouri, Abdennaceur

doi:10.1049/iet-gtd.2017.1197

Cited by 32 publications

(15 citation statements)

References 38 publications

(30 reference statements)

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“…The proposed approach utilized a robust consensus model to counter the communication uncertainties. A study of consensus-based ED model under dynamic communication network is evaluated by M. Hamdi et al in [81]. T. Yang et al [82] explored a distributed ED model for a system with potentially timevarying topologies and network delays.…”

Section: Economic Dispatchmentioning

confidence: 99%

Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

Nair

Hossen

Campion

et al. 2018

Technol Econ Smart Grids Sustain Energy

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With the increasing integration of Distributed Energy Resources (DER) in the power grid, a decentralized approach becomes essential for scheduling and allocation of resources in a smart grid. Economic Dispatch (ED) and Unit Commitment (UC) are the two major resource allocation problems that play critical role in the safe and stable operation of a grid system. The uncertainty associated with renewable energy sources have made the resource allocation problems even more challenging for grid operators. The future grid will have a higher generation mix of renewable energy sources and a large load of Electrical vehicles, with the possibility of bi-directional power flow. This complex smart grid system necessitates the development of a decentralized approach to resource allocation problem, which allows inter-node communication and decision making. Multi-agent systems (MAS) is a promising platform to decentralize the traditional centralized resource allocation aspects of smart grid. This paper presents a comprehensive literature review on the application of MAS to Economic Dispatch (ED) and Unit Commitment (UC) in smart grids.

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Section: Economic Dispatchmentioning

confidence: 99%

Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

Nair

Hossen

Campion

et al. 2018

Technol Econ Smart Grids Sustain Energy

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“…Computing time larger than GA GA [76][77][78][79][80][81][82][83][84] the evolutionary computation-based method provides global optimisation for the system regardless of historical data and system constraints. Iterative time-consuming process to achieve its optimal condition consensus algorithm [95][96][97][98][99][100][101][102][103][104][105][106][107][108][109][110][111][112] the precise computation method quickly converges all the agents to a common value with less data requirement. preferred at the primary level because of advantages over the other two control techniques mainly in terms of adaptive towards local variables, no communication requirement, significantly better voltage and current regulation along with easy implementation.…”

Section: Resultsmentioning

confidence: 99%

“…The Laplacian consensus dynamics memorandum can be used to recapitulate all potential inputs so that the desired system performance can be achieved. Here the undirected communication topology is used to distribute the dynamics of each agent and the information sharing is only between the neighbours [104][105][106].…”

Section: Consensus Algorithmmentioning

confidence: 99%

Review of hierarchical control strategies for DC microgrid

Abhishek

Ranjan

Devassy

et al. 2020

IET Renewable Power Generation

104

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This work presents an extensive review of hierarchical control strategies that provide effective and robust control for a DC microgrid. DC microgrid is an efficient, scalable and reliable solution for electrification in remote areas and needs a reliable control scheme such as hierarchical control. The hierarchical control strategy is divided into three layers namely primary, secondary and tertiary based on their functionality. In this study, different methods of primary control for current and voltage regulation, secondary control for error-correction in voltage and current, power sharing in a microgrid and microgrid clusters and tertiary control for power and energy management with a primary focus on minimal power loss and operational cost in a DC microgrid system are reviewed in-depth. Along with this, the advantages and limitations of various control structures like centralised, decentralised, distributed are discussed in this study. After a comparative study of all control strategies, the optimum control schemes from the author's point of view are also presented.

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“…Reference [36] uses the Metropolis criterion to construct a double stochastic matrix A. Metropolis weight can ensure the stability of the algorithm and ability to adapt to the changing of topological structure.…”

Section: Diffusion Strategy For Microgrid a Economic Dispatch Omentioning

confidence: 99%

Multi-Agent Based Fully Distributed Economic Dispatch in Microgrid Using Exact Diffusion Strategy

Wang

2020

IEEE Access

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To solve the economic dispatch (ED) problem of multiple distributed generations in the microgrid, this paper proposes a fully distributed method by using the exact diffusion strategy which can achieve exact convergence under sparse communication network. Firstly, a multi-agent hierarchical control architecture for the microgrid is designed. The microgrid central controller (MGCC) agent does not act as centralized control but instead participates in the distributed optimization between the bottom layer agents. Furthermore, an economic dispatch optimization model is established which aims at minimizing the operation cost, optimizing the active power of all dispatchable agents including distributed generators and flexible loads on demand side, and realizing the economic utilization of resources. A modified diffusion algorithm supporting full distributed optimization is proposed to solve it, which does not depend on the ''leader unit'' and is applicable to the actual problem. The modified algorithm has faster convergence speed, higher stability and stronger expansibility than consensus algorithm. Six scenarios are adopted to verify the proposed method. The result shows that the agent framework and the algorithm can cope with changing of communication topology and realize the ''plug and play''. The output will converge to the optimal dispatch solution even if communication fails. INDEX TERMS Consensus, diffusion algorithm, economic dispatch problem, fully distributed control, multi-agent system.

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Coordinated consensus for smart grid economic environmental power dispatch with dynamic communication network

Cited by 32 publications

References 38 publications

Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid

Review of hierarchical control strategies for DC microgrid

Multi-Agent Based Fully Distributed Economic Dispatch in Microgrid Using Exact Diffusion Strategy

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