Distributed energy management for the multi-microgrid system based on ADMM

In this paper, a distributed energy management method for a multi-microgrid (multi-MG) system is developed. Internally, each MG cooperatively coordinates with one another to minimize the aggregated operational cost, while externally, the multi-MG system derives profit via energy arbitrage with the main grid. To this end, the energy management is formulated as a convex optimization, and an alternating direction method of multipliers (ADMM) based distributed algorithm is introduced. Within this algorithm, each MG energy management system (MG-EMS) iteratively exchanges a small amount of information with its neighboring MG-EMSs, and locally optimizes the schedule of the corresponding MG. The proposed method is scalable, center-free, privacy-preserving, and reliable in communication. Numerical results of a 3-MG system demonstrate the effectiveness of the proposed method.

[1]  M. Verbrugge,et al.  Cycle-life model for graphite-LiFePO 4 cells , 2011 .

[2]  Yasser Abdel-Rady I. Mohamed,et al.  Optimized Multiple Microgrid-Based Clustering of Active Distribution Systems Considering Communication and Control Requirements , 2015, IEEE Transactions on Industrial Electronics.

[3]  Stephen P. Boyd,et al.  Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..

[4]  Tomaso Erseghe,et al.  Distributed Optimal Power Flow Using ADMM , 2014, IEEE Transactions on Power Systems.

[5]  Chris J. Dent,et al.  Investigation of Maximum Possible OPF Problem Decomposition Degree for Decentralized Energy Markets , 2015, IEEE Transactions on Power Systems.

[6]  C. Dent,et al.  Decentralized Multi-Period Economic Dispatch for Real-Time Flexible Demand Management , 2016, IEEE Transactions on Power Systems.

[7]  Tomaso Erseghe,et al.  A Distributed and Scalable Processing Method Based Upon ADMM , 2012, IEEE Signal Processing Letters.

[8]  Wotao Yin,et al.  On the Global and Linear Convergence of the Generalized Alternating Direction Method of Multipliers , 2016, J. Sci. Comput..

[9]  Marija D. Ilic,et al.  From Hierarchical to Open Access Electric Power Systems , 2007, Proceedings of the IEEE.

[10]  Mehdi Savaghebi,et al.  Distributed Smart Decision-Making for a Multimicrogrid System Based on a Hierarchical Interactive Architecture , 2016, IEEE Transactions on Energy Conversion.

[11]  Hoay Beng Gooi,et al.  Robust Electric Vehicle Aggregation for Ancillary Service Provision Considering Battery Aging , 2018, IEEE Transactions on Smart Grid.

[12]  Vahid Esfahanian,et al.  Optimum sizing and optimum energy management of a hybrid energy storage system for lithium battery life improvement , 2013 .