Frequency Control Technology Of AC/DC Power System Based On Online Load Modeling

The obsequent distribution characteristic of energy resource and load center in China have significantly promoted the development of UHVAC/DC transmission technology.Meanwhile,the risk of large-capacity power shortage in power system is increasing correspondingly.The load control strategy represented by under frequency load shedding(UFLS)can effectively respond to frequency dips.Accurate load models and efficient control strategies are the basis for frequency control.With continuous development of energy internet and smart grid,the scale of power system is becoming larger.The penetration of new loads and equipments have intensified the load complexity and randomness.Traditional load modeling approaches are inadequate to reveal the real-time dynamic characteristics of load components.The rise of data analysis represented by machine learning,the maturity of power communication and sensing technologies have brought new opportunities for load modeling.By mining users’ power consumption data,it is helpful to carry out online accurate load modeling applications.Accurate and real-time load models are helpful to quickly analyze the frequency response characteristics and provide auxiliary decisions for operation dispatchers to make frequency control strategies.Based on above analysis,the work of this paper is organized mainly from two aspects.On the one hand,an online load modeling approach based on real-time measurement information is studies.On the other hand,the system frequency control strategy considering load frequency characteristics is researched.Concretely,they are arranged as follows.Firstly,a user clustering approach based on the pattern indexes dimensions reduction of daily load curve is proposed by utilizing users’ big data.The weights of load pattern indexs are configured by clustering validity checking,which improved the clustering effectiveness.Moreover,a load intelligent terminal is introduced,which is used to capture load information for online accurate load modeling.Secondly,an online load modeling approach based on the measurement information of intelligent terminal is proposed.Based on the user clustering results,several typical users in each cluster are selected to carry out real-time load information measurement and load modeling by configuring intelligent terminals,the load model of other users in each cluster are substituted by typical ones.Finally,the composite load model are built by bottom-up hierarchical aggregation and stepwise equivalent.Then,on the basis of analyzing the influencing factors of power system frequency response,the load frequency characteristics are studied.And the influence of load model parameters on the frequency characteristics are studied by perturbation method.When the power shortage occurred in power system,the impacts of cutting different type of loads on frequency recovery process are comparatively analyzed.Finally,a UFLS strategy considering both load frequency characteristics and adaptive load shedding is proposed.The loads are classified based on the frequency sensitivity and importance.By considering the frequency regulation characteristics of power system during UFLS process,a dynamic optimization scheme of adaptive load shedding is proposed,which dynamically optimizes the load shedding in each round.Proposed approach can maximize the load utilization,and further improve the frequency recovery effect.