Research On Hierarchical Multi-Objective Optimization Dispatching Of Renewable Power Generation Systems With Concentrating Solar Power Plants

In recent years,renewable power generation such as wind power and photovoltaics have increased in China.Still,with it,the problems of wasting wind power and photovoltaics have become increasingly prominent.Affected by factors such as the robust renewable energy construction and the limited power transmission capacity of the power grid,the northwest regions are still the hardest-hit areas for the abandonment use of wind and solar energy in China.Clean power sources and solar thermal power generation have high expectations for developing large-scale new energy bases.The concentrating solar power plant accompanied by the thermal energy storage system has good peak regulation and frequency regulation ability,which can replace thermal power units to a certain extent,stabilize power output,smooth power curve,and improve power quality.The State Grid’s "carbon peaking and carbon neutrality" action plan lists solar concentrating solar power generation as a peak-shaving power source.It takes the development of concentrating solar power generation as an essential means to improve system regulation capabilities.Therefore,the analysis of dispatching characteristics of renewable energy power systems with concentrating solar power plants is a subject worthy of study.Firstly,establishes a solar thermal power station scheduling model with a heat storage system according to the operation mechanism of solar thermal power stations.It then adds a solar thermal power station model to the energy generation day-ahead scheduling model.Using the energy storage characteristics and flexible dispatching characteristics of solar thermal power stations,the new energy generation curve can be stabilized,the new energy generation consumption rate can be improved,the number of thermal powers starts and stops,and costs can be reduced.At the same time,on the load side,the load curve is optimized by utilizing the price-based demand response model.Secondly,this paper establishes a real-time feedback dispatching system for new energy power generation based on grid-connected guidelines,given the intraday fluctuation of new energy power stations.Firstly,the output range of the station is calculated in real-time through the daily output,short-term forecast data,and energy storage status of the new energy station.Then,through mathematical optimization calculation,the objectives of the minimum number of limit violations,the maximum new energy consumption,and the optimal state of the energy storage system are optimized in turn.Finally,the minute-level scheduling results in the day are output.Finally,to realize the multi-objective optimization requirements of the renewable energy power generation system,this thesis constructs a two-layer hierarchical optimization scheduling system based on the multi-time scales of day-ahead and day-ahead.Firstly,through the dayahead scheduling system,considering each subsystem’s system-level constraints and power generation constraints,the system-level day-ahead optimal cost scheduling optimization is carried out with the optimal cost as the goal.Then,the system-level scheduling optimization results are transmitted to the station layer as a constraint condition.The station layer uses the real-time feedback scheduling system to achieve the maximum consumption target of new energy power generation.The simulation results showed that the double-layer hierarchical optimal scheduling proposed in this paper could effectively reduce the cost of new energy power generation,improve the absorption rate of wind and solar power generation,and reduce system fluctuations.