Efficient Energy Management of Multi-Microgrids Systems Based on Distributed Cooperative Control in Autonomous Mode

Brahmia, Ibrahim; Zhao, Pingwei; Wang, Jingcheng

doi:10.1109/icpes47639.2019.9105376

Cited by 4 publications

(1 citation statement)

References 16 publications

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“…In the distributed strategy, each MG is locally interconnected through a certain connection mode and realizes energy and information interaction with the main grid respectively [53][54]. In particular, 1) when one of the MGs failures or energy supply and demand is unbalanced, this MG can communicate with the neighboring MGs and main grid through the internal energy management system, and then the networked MGs/main grid can supply energy support, so that it can operate stably again [24]; 2) when the main grid fails and all the MG are disconnected from main grid, that is, when multiple MGs are in an islanded mode, the MGs can also realize energy interaction through the interconnection between them [55]. A significant difference regarding the other strategy is that individual agents are allowed to discover or exchange other agent information through communication and coordination with their neighbors.…”

Section: Centralizedmentioning

confidence: 99%

A Review on Optimal Energy Management of Multimicrogrid System Considering Uncertainties

Zhang

2022

IEEE Access

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Microgrid (MG) is one of the most effective solution to integrate distributed renewable energy into power system. However, modern MG has several technical challenges such as migration to multi vector energy system, increasing renewable energy penetration, and the uncertainties that arise from the large-scale incorporation of renewable energy. Recent development of multi-microgrid (MMG) could potentially mitigate these challenges. MMG has obvious advantages in improving the system stability, reliability, economy, and energy efficiency of power grid operation through autonomous management and coordinated control among networked MGs. In the meantime, uncertainties from many elements and operators in the MMG system also pose huge challenges in modeling. This paper will present and review typical architecture of MMG, including physical layer, information layer and application layer. Moreover, this paper will critically review and analyze challenges in uncertainty modelling and solution in MMGs. Finally, the paper will also discuss future research areas and development trends of MMG.

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Section: Centralizedmentioning

confidence: 99%

A Review on Optimal Energy Management of Multimicrogrid System Considering Uncertainties

Zhang

2022

IEEE Access

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Hierarchical smart energy management strategy based on cooperative distributed economic model predictive control for multi‐microgrids systems

Brahmia

Wang

Oliveira

et al. 2020

Int Trans Electr Energ Syst

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Summary With the new edge of smart grids technology, the concept of efficient energy management among cooperative microgrids (MGs) distribution networks for the next generation of energy trading applications has become more and more challenging. This article presents smart energy dispatch for multi‐MGs (MMGs) systems based on the cooperative distributed economic model predictive control (DEMPC) within a hierarchical structure. The optimization framework consists of two levels. First, a DEMPC coordinator computes the optimal energy dispatch solution, taking into account the energy surplus with a power‐sharing policy, the retail electricity price based on the time of use (TOU), and the distributed generators units. For the second level, each local controller executes the energy scheduling reference from the first level. Thus, the MMGs system achieves a global supply‐demand balance. Moreover, the proposed approach improves the utilization of renewable power and demonstrates optimal energy dispatch while reducing operating costs. Finally, to validate the efficiency and resiliency of our proposed approach, two cases of study are presented based on three interconnected MGs system under a cooperative and non‐cooperative optimization. Simulation results show the advantage of the cooperative strategy with 28% for MG 1, and 20% for MG 2 in terms of daily operating costs savings.

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Smart Energy Dispatch for Networked Microgrids Systems Based on Distributed Control Within a Hierarchy Optimization

et al. 2020

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Efficient Energy Management of Multi-Microgrids Systems Based on Distributed Cooperative Control in Autonomous Mode

Cited by 4 publications

References 16 publications

A Review on Optimal Energy Management of Multimicrogrid System Considering Uncertainties

A Review on Optimal Energy Management of Multimicrogrid System Considering Uncertainties

Hierarchical smart energy management strategy based on cooperative distributed economic model predictive control for multi‐microgrids systems

Smart Energy Dispatch for Networked Microgrids Systems Based on Distributed Control Within a Hierarchy Optimization

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