Optimal Operation of Self-Healing Networked Microgrids

What is it about?

This paper presents an approach for optimal operation of self-healing networked microgrids (NMGs) under both normal operation and emergency conditions using the pufferfish optimization algorithm (POA). The proposed methodology is based on an energy management system (EMS) with two levels and independent functions. The lower-level is designed for normal operation, where the local controller of each microgrid (MG) performs the optimal dispatch of power from the dispatchable sources. During emergency case in any MG, the higher-level EMS is activated, and the global controller is brought into operation. Physically, the NMGs are connected by tie-lines, while cyber links are established to exchange information and control signals for coordinated operation. Each MG operates to supply its local demand during normal operation conditions, resulting in no electrical power exchange between MGs. İn case of generation deficiency or a fault leading to generation outage electrical power can be exchanged through the existing interconnections, enabling the affected microgrid to receive support from neighbouring MGs. The main objective of the POA is to minimize both total generation cost and energy losses. Simulation studies are conducted using MATLAB and DIgSILENT software over one day. The proposed algorithm reduces the operation cost and energy losses for both normal operation and emergency conditions.

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Photo by Kevin Gilleard on Unsplash

Photo by Kevin Gilleard on Unsplash

Why is it important?

The simulation studies described in this paper have shown that the proposed POA can be effectively applied to NMGs to achieve optimal operation with minimal generation cost and reduced losses in both normal and emergency conditions. In normal operation, each MG operates to minimize the operation cost and maintain self-sufficiency. The considered emergency cases leading to generation outage are generation deficiency and line fault. The MG affected by emergency will receive power support from the neighbouring MGs. A two-level of energy management system is designed. The lower-level EMS operates during normal conditions, while the higher-level EMS is activated during emergency conditions. Additionally, the network energy losses are considered in the optimal operation of networked microgrids in both normal and emergency conditions. The results demonstrate the effectiveness of the proposed POA algorithm in improving the performance of NMGs. In normal operation, the operating cost is reduced by 7.42%, 5.05%, and 2.15%, while energy losses are reduced by 12.26%, 6.32%, and 7.41% for MG-1, MG-2, and MG-3, respectively, compared with the case without optimization. During emergency conditions, the algorithm reduces the operating cost by 2.98%, 9.31%, and 3.74%, while reducing the energy losses by 9.41%, 9.22%, and 12.51% for cases 2-a, 2-b, and 2-c, respectively. These results highlight the capability of NMGs to enhance system resilience while simultaneously improving economic performance.

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