A Review on Optimal Energy Management of Multimicrogrid System Considering Uncertainties

Abstract

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.

New Horizons for Microgrids: From Rural Electrification to Space Applications

“…The transition from large, centralized distribution networks into interconnected microgrid clusters with distributed generation can result in significant benefits to the reliability, resilience and energy security of the local energy networks. The literature to date has focused on multiple aspects related to microgrid clusters including possible architectures, communication frameworks, energy management strategies, operation, protection, and resilience strategies [7][8][9]. Typically, the hierarchical control architectures defined in Section 2.1 are employed by all the microgrids forming the clusters.…”

“…The tertiary layer algorithms respond to dispatch commands to regulate the energy flows amongst the interconnected microgrids. However, due to the complexities involved in setting up and coordinating the operation of the microgrid clusters, there are still significant challenges that arise from uncertainties (such as the randomness of the load demand, energy market fluctuations and intermittency of the renewable power generation) [7].…”

“…In recent dec ades, microgrid technologies, architectures and control strategies have been extensively researched to increase their reliability and scalability. These ongoing research efforts can be grouped into the following categories: hierarchical control loops and architectures [1][2][3][4][5][6], microgrid clusters and multi-microgrids [7][8][9], integration and management of energy storage systems [10][11][12][13][14][15] and peer-to-peer energy trading and new roles for prosumers [16,17].…”

Distributed Optimization of Multi-Microgrid Integrated Energy System with Coordinated Control of Energy Storage and Carbon Emissions

“…The mainstream distributed algorithms used are based on the Lagrangian relaxation (LR) method, including optimal condition decomposition (OCD) [5][6][7] and generalized benders decomposition (GBD) [8,9], which can realize a completely distributed solution for multi-region scheduling problems. Other distributed algorithms in use are based on the augmented relaxation description (ALD) method, including the auxiliary problem principle (APP) [10][11][12] and analytical target cascading (ATC) [13][14][15], which can improve the convergence performance of the high standard LR method [16].…”

Optimized Performance and Economic Assessment for Hybrid Island Microgrid System Considering Uncertainties

“…However, expenditure on installation components of RES with microgrid distribution networks has gradually reduced after the 2021 26 th United Nations Climate Change Conference (COP26), held in Glasgow, Scotland, United Kingdom. Besides optimized performance considering various power system-related uncertainties of island hybrid microgrid systems is another issue, which also needs broad area research for controlling and removing those uncertainties [4].…”