Research On Stochastic Economic Dispatch Model And Method Of Renewable Energy And Thermal Power Coupling System

With the promotion of the strategy about energy structure adjustment,China actively develops renewable energy including wind,photovoltaic and hydro.With the increase of their grid-connection ratio,the uncertainty of their power output poses a new challenge to power system.Meanwhile,the high proportion of these renewable energy sources increases the stress of power system.On the one hand,since the capacity for thermal power plant(TPP)in China is too large,it has become normal for thermal power units(TPUs)to undertake the task of deep peak-regulating operation(DPRO).However,the increase of operating costs under the DPRO makes the survival for a large number of TPPs very difficult.On the other hand,the coal market in China is facing a new situation of increasing coal sources and large differences in coal quality,so mixed coal-blending combustion technology is gradually and widely used in TPPs.Furthermore,according to the current compensation mechanism based on dispatch in China,it is difficult for TPPs to reasonably compensate for the economic losses caused by providing DPRO,which leads to the low enthusiasm of peak regulation.Consequently,considering the randomness of wind power output,this paper studies the stochastic economic dispatch(SED)model and the peak-regulating cost allocation model for the coupling system of renewable energy and TPUs from the perspectives of mixed coal-blending combustion(MCBC)technology and the initiative of DPRO for TPUs.The main contents are summarized as follows:Firstly,aiming at the modeling problem of renewable energy power output represented by wind power,this paper introduces the stochastic modeling and stochastic expectation model of wind power output based on scenario analysis.The stochastic model of wind power based on scenario analysis mainly includes the establishment of wind speed probability distribution model,the generation and reduction of wind speed scenarios,and the conversion of "wind speed to wind power".In order to consider the accuracy of target scenario fitting,the difference degree of probability distribution is introduced as an indicator of the accuracy of scenario fitting.On this basis,the stochastic optimization model is introduced,and the stochastic expectation model based on the scenario analysis can be given.Secondly,in view of the problem of cascading hydropower optimal dispatch,the Wujiang River Basin in Guizhou Province is investigated.The basic characteristics of seven hydropower stations along the Wujiang River and the mathematical model of cascading hydropower generation dispatch are introduced in detail.The principle of Monarch Butterfly Optimization(MBO)including its migration operator and butterfly adjustment operator is described.Subsequently,taking the minimum water consumption as the objective function,this paper uses MBO algorithm to solve the scheduling problem of cascading hydropower stations.Furthermore,the comparison among Particle Swarm Optimization(PSO)and Sine and Cosine Algorithm(SCA)proves the superiority of this algorithm in finding better adaptability.Thirdly,aiming at the SED problem of renewable energy and TPUs coupling power system,the scenario analysis method described above can be introduced to describe the randomness of wind power from the perspective of DPRO for TPUs,and the coupling of power system could be reduced by the two-stage strategy with the help of the MBO algorithm mentioned above.Therefore,a SED model of hydro-thermalwind-photovoltaic coupling system with MCBC is established.A simplified provincial power system is taken as an example to study the effects of MCBC on the cost-reduction and efficiency increase of TPUs in DPRO.The relevant discussions and conclusions can provide references for the research and practice of power generation planning under the scenario of TPUs participating in DPRO.Finally,aiming at the problem of cost allocation for TPUs with DPRO in the electricity market environment and from the perspective of motivating TPUs to actively participate in DPRO,a cost allocation model considering the impact coefficient of peak regulation is constructed based on the on-grid quantity of market entities and the peakvalley difference of different power sources.An example analysis is carried out on a simplified provincial power grid system.The results of comparison with the costsharing model demonstrate the effectiveness of the proposed model.Furthermore,the relevant discussion and conclusions are of certain reference value for the government to make the cost allocation scheme of TPUs.