Generator preventive maintenance scheduling in large power systems with high penetration of renewable energy resources

Refereed/Peer-reviewed This paper proposes an optimization model to address the generator preventive maintenance scheduling (GPMS) in large power systems with high penetration of renewable energy resources (RERs). The dynamic programming (DP) technique is modified to reduce the required computational effort. A step for system inertia calculation and a constraint of minimum system inertia requirement are integrated into the GPMS model to address the inertia reduction issue linked with the proliferation of RERs in power networks. This study also considers the energy reserve requirement of the power system. The efficacy of the developed model is evaluated based on the operational data of an actual large power system including 41GW of conventional generators (400 units), and 14GW of wind and solar photovoltaics (PVs). The proposed algorithm is validated against the original DP method and the GPMS technique currently used by the Vietnamese system operator (SO). It is shown that the proposed simplified DP, while being much faster than the full DP, still guarantees an optimal solution as good as the full DP's solution. The proposed method outperforms the technique currently used by the Vietnamese SO, generating significant improvements in the system capacity reserve profile and reliability indexes with less adjustment effort required. The proposed algorithm is validated against the original DP method and the GPMS technique currently used by the Vietnamese system operator (SO). It is shown that the proposed simplified DP, while being much faster than the full DP, still guarantees an optimal solution as good as the full DP's solution. The proposed method outperforms the technique currently used by the Vietnamese SO, generating significant improvements in the system capacity reserve profile and reliability indexes with less adjustment effort required.