A Decentralized Framework to Improve Resilience in Microgrids Based on Peer to Peer Transactions, Considering Independence and Privacy

Subject Areas : Renewable energy

Mohammad Doostizadeh ¹ (Department of Electrical Engineering- Khomein Branch, Islamic Azad University, Khomein, Iran)
Hassan Jalili ² (Department of Electrical Engineering- Roudehen Branch, Islamic Azad University, Roudehen, Iran)
Abbas Babaei ³ (Department of Electrical Engineering- Roudehen Branch, Islamic Azad University, Roudehen, Iran)

Received: 2022-05-10 Accepted : 2022-07-28 Published : 2022-07-28

Keywords: Microgrid, resilience, Peer to peer energy transactions, Decentralized scheduling,

Abstract :

Severe events such as floods, earthquakes and hurricanes cause disruption in the operation of distribution networks and lead to their islanding. In such cases, if the distribution networks have microgrids, these microgrids are able to separate from the main network and exchange energy with each other to reduce the operation and outage costs. Therefore, the energy management in a multi-microgrid network requires a decentralized operating framework to encourage microgrids to have transactions with each other by providing the necessary incentives. This paper developes a completely decentralized framework to improve the resilience of microgrids based on the organization of peer-to-peer energy transactions, taking into account the appropriate financial incentives for the participation of microgrids. The developed model protects the private data of each microgrid, such as load information and distributed generation resources, during market settlement. Using the developed decentralized model, microgrids can increase network resilience in the context of peer-to-peer energy exchanges, in addition to reducing their operating costs compared to the island mode. The proposed decentralized approach does not require a central controller and has a high convergence speed. Simulations are performed on a system with fourteen microgrids and the results are compared with the island approach to evaluate the performance of the proposed method. The simulations are performed in MATLAB R2020b environment using YALMIP toolbox. CPLEX 12.9 is also used to solve the optimization problem. The results show the efficiency of the proposed method in increasing the resilience and reducing the operating costs.

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