Research On Optimal Operation Of Power System Including Wind Farms

The energy issue is an important issue of concern all over the world and it also affects China’s economic development.However,fossil energy has become increasingly scarce,and the ecological environment is also deteriorating.The energy situation in China is not optimistic and has become a major issue.In this context,various renewable clean energy sources have received attention,such as:wind energy,tidal energy,and solar energy.Nowadays,wind power generation has been strongly supported by national policies with its rapid technological development and superior cost performance.It has become one of the major energy sources in the power system and will be applied in larger scale in the future.However,while protecting ecological environment and improving people’s quality of life,wind power also brings a lot of trouble to the optimal operation of power systems because of its randomness,volatility and intermittent characteristics.In the face of these problems,we need to find some effective countermeasures when wind power is connected to the grid to participate in the dispatch of power systems.This paper first analyzes the characteristics of wind power output,studies the estimation method of wind power forecast error,and establishes the probability model of wind power output.Since wind power is connected to the grid,its volatility will adversely affect the scheduling of the system.Therefore,the method of power interval prediction is used to describe the uncertainty of wind power and the prediction interval is solved.Secondly,this paper establishes two kinds of power system optimization scheduling models with wind farms.The first model takes into account the volatility of wind power.To reflect the impact of wind power on the system’s economy and reserve capacity,wind power forecasting intervals and other information are added to the model.The second model uses the invocation of demand-side resources as a scheduling method,taking into account the access of interruptible loads,and based on the characteristics of the interruptible load and various factors that affect its cost,Established an optimal scheduling model that takes into account the interruptable load.Finally,an IEEE-10 machine system example is used to solve the above two models using an improved particle swarm algorithm.The results of the example show the feasibility of the two models and the algorithm:For a scheduling model based on wind power interval prediction,Firstly,the confidence probability is selected.When the value is large,although the economical efficiency is reduced,the proper amount of backup ensures the safe and reliable operation of the system.For models that take into account interruptible loads,access to interruptible loads not only improves the economics of the system,but also effectively responds to the effects of wind power fluctuations.