Research On Grid-connected Control Technology For Custom Power Of Clean Energy

Under the dual pressures of energy and the environment,the development of clean energy has become the consensus of all countries in the world.Our country has a vast territory and abundant clean energy resources,but there are significant regional differences in china.Distributed generation(DG)can be used directly on load center,reduce dependence on large power grid transmission,and improve the economy of clean energy power generation.However,with the increasing penetration of DG in distribution network,many new challenges has been brought to the gird,among them,the influence to safe and economical operation and high power quality is especially serious in distribution network.According to the definition of the active power distribution network,clean energy system which has the function of regulating and optimizing the power network,is an important unit of the active power distribution network.Custom power grid connected technology includes two aspects: participate in power quality control of power grid and active distribution network optimization operation.In this paper,the specific research work includes: control technology of grid-connected inverter with the function of active control for power quality,terminal voltage control technology for solid oxide fuel cells,control strategy of photovoltaic and storage system participating in optimal operation scheduling control of active distribution network,and development of optical storage integrated customized power grid-connected prototype.First,based on the detailed analysis of the working principle of DC/AC inverter and the derivation of the nonlinear mathematical model of the inverter,a current tracking control algorithm based on general model control and a PID current tracking control algorithm based on neuro-fuzzy compensation are proposed separately.Among them,the control method based on general model is directly used the nonlinear process model of inverter,meanwhile,based on the design idea of the optimal control method,an explicit control law for the current tracking control is proposed,which has the characteristics of simple structure,strong robustness,and easy tuning of the control parameters;The PID control method based on neuro-fuzzy compensation combines the advantage of the PID controller and neuro-fuzzy controller.The effective combination of the two controllers can guarantee the system to be globally asymptotically stable in a certain range,and the system can obtain better performance than traditional PID controller.Then,aiming at the existence of different topology structure of inverter in practical engineering caused the problem that model-based control algorithm can not achieve the "plug and play",which is difficult to large-scale application,improved hysteresis control and model free adaptive control of IV inverter are separately proposed.Among them,improved hysteresis control method based on current prediction can effectively reduce the control errors of the hysteresis loop control,improve the sampling rate of the system equivalently,and enhance the control precision.Model free adaptive control method does not require mathematical model of inverter,depends only on the input and output data of the controlled system,which can guarantee the stability and convergence of the closed loop system.And the method does not need any iterative algorithm to determine the control input,so it has the advantage of high real time.Next,aiming at the control of the terminal voltage of the solid oxide fuel cell,an adaptive neural network control algorithm based on dynamic anti saturation is proposed.The method is constrained to the control input generated by the RBF controller.On the one hand,it can ensure that the SOFC control input is maintained within an acceptable range,which guarantee the performance and safety of SOFC battery,on the other hand,the problem of actuator saturation of fuel cell control system and fuel cell utilization constraints can be effectively solved,meanwhile,which can effectively avoid the problem of instability and divergence of the closed loop system due to the saturation problem.Simulation results show that the proposed control based on RBF neural network has a good effect on the response speed and tracking accuracy,and can ensure that the control input is kept within the scope of the constraints,at the same time,the utilization rate of the battery can be kept in the optimum range.Then,in order to ensure the clean energy consumption quota,node voltage control of full network,economical operation of “source-network”,photovoltaic and energy storage system participating in optimization operation strategy of the active distribution network has been proposed.Based on the principle of similar days,the proposed method selects the prediction samples of photovoltaic power and use the support vector machine algorithm to predict the average value of the power generation at each time period of photovoltaic power station.Based on this,the topological structure of optical storage system is given and the optical storage flexible grid connected model is established;With Photovoltaic MPPT combined with energy storage to achieve distributed energy consumption quota,with the minimum loss of the “source-network” with independent control of grid connected inverter P/Q to make the node voltage of full network to meet the security constraints to achieve the control of voltage exceeding specified limits.According to the sequential continuity of energy storage capacity in model and dual decision making for active and reactive power in optical storage,a multi-dimensional dynamic programming algorithm is used to solve the model.The simulation results show that the flexible photovoltaic and energy-storage system has a strong ability of power flow regulation and the mentioned objective is efficiently realized by proposed method.Last,based on the comprehensive analysis of the requirements and design goals of the grid connected system for clean energy,the design scheme of the system is proposed,a grid-connected controller based on hysteresis space vector of current prediction and no model adaptive control is developed,the experimental platform of active distribution network is constructed,the performance of grid-connected clean energy customized power has been verified.Under the trend of global energy interconnection,the research results of this paper will guide the innovation of clean energy power generation technology,optimize the allocation of resources efficiently,which response to the demand for high quality power supply of power grid at the technical level,have an active participation in regulation and optimization of power grid,achieve the “double-friendly” of clean energy power generation to the resource environment and grid operation,reflect development goals of the smart grid of “green,two-way,interactive,friendly”.