A robust distributed system incremental cost estimation algorithm for smart grid economic dispatch with communications information losses

Zhang, Yuan; Rahbari-Asr, Navid; Chow, Mo-Yuen

doi:10.1016/j.jnca.2015.05.014

Cited by 55 publications

(16 citation statements)

References 24 publications

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“…Most of the papers discussed above assume a perfect communication between agents without any information loss, but in a realistic smart grid environment can have packet loss and communication failures. Y. Zhang et al [79] proposed a distributed ED model which remains robust under information loss among agents. A combination of two algorithms running in parallel, Robust distributed system Incremental Cost Estimation (RICE) algorithm, was introduced by authors to handle the issue.…”

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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“…3. Table 4 shows that the distributed algorithms proposed in [22,27] are vulnerable to dynamic time varying communication topology since they cannot achieve calculation and diverge, whereas the FDCP time convergence is smaller than that of the RCCA [29] which is partially distributed.…”

Section: Case 1: Convergence Of Fully Decentralised Consensus Protocomentioning

confidence: 99%

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

Hamdi

Chaoui

Idoumghar

et al. 2018

IET Generation, Transmission & Distribution

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“…Another scenario is communication packet loss. In one of our previous papers [6], we have used the gossip algorithm to handle the packet loss among the agents. More detailed study on the communication latency and packet loss will be presented in another paper.…”

Section: A 30-bus System: Normal Operationmentioning

confidence: 99%

Day-Ahead Smart Grid Cooperative Distributed Energy Scheduling With Renewable and Storage Integration

Zhang

Rahbari-Asr

Duan

et al. 2016

IEEE Trans. Sustain. Energy

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Day-ahead scheduling of generation units and storage devices is essential for the economic and efficient operation of a power system. Conventionally, a control center calculates the dispatch schedule by gathering information from all of the devices. However, this centralized control structure makes the system vulnerable to single point of failure and communication failures, and raises privacy concerns. In this paper, a fully distributed algorithm is proposed to find the optimal dispatch schedule for a smart grid with renewable and energy storage integration. The algorithm considers modified DC power flow constraints, branch energy losses, and energy storage charging and discharging efficiencies. In this algorithm, each bus of the system is modeled as an agent. By solely exchanging information with its neighbors, the optimal dispatch schedule of the conventional generators and energy storage can be achieved in an iterative manner. The effectiveness of the algorithm is demonstrated through several representative case studies.

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A robust distributed system incremental cost estimation algorithm for smart grid economic dispatch with communications information losses

Cited by 55 publications

References 24 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

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

Day-Ahead Smart Grid Cooperative Distributed Energy Scheduling With Renewable and Storage Integration

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