Research on Optimization Model of Medium-Long-Term Maintenance Schedule for New-Generation Power System

With the rapid expansion of new energy, including wind and solar energy, the volatility and randomness of new energy output are very strong, the uncertainty of generation supply and increasing abandonment of new energy are more and more serious. Those problems severely hindered further development of new-generation power system. The medium-long-term maintenance schedule of generator units is an important part of sequential production simulation for verifying power and energy balance, which is critical for generation expansion planning of new-generation power system. When formulating a medium-long-term maintenance schedule, how to consider the complementary characteristics of hydro-wind-photovoltaic power, how to make the best of pumped storage, and how to adapt to the regional load and new energy output characteristics to accommodate more new energy are all urgent problems. To solve these problems, this paper proposed an optimization model of medium-long-term maintenance schedule for new-generation power system. The optimization objective functions were constructed from three aspects, including hydro-wind-photovoltaic complementarity, the stability of power generation, the peak regulation capacity of system. The simplex method and discrete particle swarm optimization algorithm (DPSO) were used to solve the model. Taking a regional power system in central China as an example, the different cases were set, the comparation between different cases showed that maintenance schedule has a significant influence on the renewable energy accommodation, usable capacity and peak regulation capacity of system. The simulated results obtained by sequential production simulation further showed considering hydro-wind-photovoltaic complementarity can effectively improve the accommodation rate and utilization hours of wind power and photovoltaic power.