Wind Power, Hydropower and Thermal Power Combined Low-Carbon Maintenance Optimization Based on Continuous Hidden Markov Model

Abstract

[Introduction] In the context of the new power system, low-carbon maintenance of wind turbines and coordinated maintenance with conventional wind turbine generator systems (WTGS) need to be solved urgently. In this paper, taking into account the impact of multi-attribute meteorological factors and low carbon and economic needs, an optimization model for wind power, hydropower and thermal power combined low-carbon maintenance based on continuous hidden Markov model is established. [Method] Firstly, dynamic tracking of wind farm maintenance capacity was realized by taking rainfall, wind speed and lightning hazard degree as the observation sequence, taking maintenance capacity as hidden state sequence, and using continuous hidden Markov model (CHMM) process. Then, an optimization model for wind power, hydropower and thermal power combined low-carbon maintenance was constructed by taking the optimal maintenance capacity as the decision-making basis, taking the minimum total cost as the optimization objective, and taking the maintenance constraints and system control constraints into consideration. Finally, took the IEEE30-node system as an example. [Result] The results show that the proposed model has more significant economic benefits and low carbon characteristics. [Conclusion] The research in this paper has high theoretical value for the operation and maintenance of WTGS, and has strong engineering applicability.

Keywords

• wind power operation and maintenance
• continuous hidden markov
• wind power hydropower and thermal power combined
• low-carbon maintenance
• economic benefit