Primary Frequency Control Ability Evaluation of Valve Opening in Thermal Power Units Based on Artificial Neural Network

With the development of new energy,the primary frequency control(PFC)is becoming more and more important and complicated.To improve the reliability of the PFC,an evaluation method of primary frequency control ability(PFCA)was proposed.First,based on the coupling model of the coordinated control system(CCS)and digital electro-hydraulic control system(DEH),principle and control mode of the PFC were introduced in detail.The simulation results showed that the PFC of the CCS and DEH was the most effective control mode.Then,the analysis of the CCS model and variable condition revealed the internal relationship among main steam pressure,valve opening and power.In term of this,the radial basis function(RBF)neural network was established to estimate the PFCA.Because the simulation curves fit well with the actual curves,the accuracy of the coupling model was verified.On this basis,simulation data was produced by coupling model to verify the proposed evaluation method.The low predication error of main steam pressure,power and the PFCA indicated that the method was effective.In addition,the actual data obtained from historical operation data were used to estimate the PFCA accurately,which was the strongest evidence for this method.

Research on the Prediction of Load Regulation Capacity for Supercritical Thermal Power Unit

Both the modeling and the load regulation capacity prediction of a supercritical power plant are investigated in this paper. Firstly, an indirect identification method based on subspace identification method is proposed. The obtained identification model is verified by the actual operation data and the dynamic characteristics of the system are well reproduced. Secondly, the model is used to predict the load regulation capacity of thermal power unit. The power, main steam pressure, main steam temperature and other parameters are simulated respectively when the unit load is going up and down. Under the actual constraints, the load regulation capacity of thermal power unit can be predicted quickly.

Source-Load Coordinated Optimal Scheduling Considering the High Energy Load of Electrofused Magnesium and Wind Power Uncertainty

In fossil energy pollution is serious and the“double carbon”goal is being promoted,as a symbol of fresh energy in the electrical system,solar and wind power have an increasing installed capacity,only conventional units obviously can not solve the new energy as the main body of the scheduling problem.To enhance the systemscheduling ability,based on the participation of thermal power units,incorporate the high energy-carrying load of electro-melting magnesiuminto the regulation object,and consider the effects on the wind unpredictability of the power.Firstly,the operating characteristics of high energy load and wind power are analyzed,and the principle of the participation of electrofusedmagnesiumhigh energy-carrying loads in the elimination of obstructedwind power is studied.Second,a two-layer optimization model is suggested,with the objective function being the largest amount of wind power consumed and the lowest possible cost of system operation.In the upper model,the high energy-carrying load regulates the blocked wind power,and in the lower model,the second-order cone approximation algorithm is used to solve the optimizationmodelwithwind power uncertainty,so that a two-layer optimizationmodel that takes into account the regulation of the high energy-carrying load of the electrofused magnesium and the uncertainty of the wind power is established.Finally,the model is solved using Gurobi,and the results of the simulation demonstrate that the suggested model may successfully lower wind abandonment,lower system operation costs,increase the accuracy of day-ahead scheduling,and lower the final product error of the thermal electricity unit.

500 MW Unit Simulator for Panshan Thermal Power Plant Passed Acceptance

After a thorough demonstration in Panshan Thermal Power Plant, the 500 MW super critical pressure unit simulator developed by the Simulation & Control Institute under the North China University of Electric Power was accepted by experts from the North China Electric Power Group Company on 3rd August 1996.

Research and Demonstration of Direct Air-Cooling System for 600-MW Fossil-Fired Power Plants

Given the distribution feature of resources such as coal and water, the requirements for the development of Chinese power industry, and the fact of monopoly by foreign companies, it is very necessary and significant to independently research and develop air-cooling technologies. Through experimental research, simulative calculation, process and equipment development, field tests and a demonstration project, the design and operation technologies for air-cooling system are grasped and relevant key equipment is developed. The results of the demonstration project show that the technical indicators for the air-cooling system have met or exceeded the design requirements. Part of the research results have been incorporated into the relevant national design standards. The technologies developed have been applied to more than 23 sets of thermal power units of or above 600 MW in China.