| Accurate mathematic model of hydro turbine unit not only provides basis for hydro turbine system simulation, but also plays an important role in interconnected power system calculation and analysis, operation and plan, protection device and controller design. With great developing of the hydro-electric power, the built and building hydro power stations are with large capacity generators, long penstock, big water inertia, and complicated water diversion system, meanwhile, they also undertake the task of primary frequency modulation, peak load regulation and emergency reserve for accident. This causes great challenge for power system modeling and control. However, models of the hydraulic turbine governing system used in power system stability calculation nowadays in China usually cited simplified models, which is different from the field hydraulic turbine governing system (HTGS) in operation. Hence, it is very necessary to study of the identification method and control law for accurate modeling of hydro turbine unit not only for improving the simulation accuracy and the controller performance, but also for the hydro turbine operation with high efficient and interconnected power system operation safely.System modeling based on identification is an important way to provide accurate models of control systems. Conventionally, linear system model and linear identification theory was studied for parameters identification of hydro power unit. While, they neglected the nonlinear factor such as saturation, amplitude limitation in servomotor system and time-varying factor in turbine, which are hard to satisfied the need of power system dynamic analysis, mid-term and long-term voltage stability calculation, auto generation control and system frequency analysis. Focus on these problems and research on models of synchronous generator (SG) and its speed mover governor system (PMGS) of hydropower unit, the paper proposed the scientific problems of parameters identification and control law design of hydropower unit. Combing the multi-innovation identification theory, intelligent optimization method, dynamic system design method and sliding mode control law, the paper studied detailed parameters identification technology and control laws of hydropower unit, and built the frame of parameters identification and system control for hydropower unit. Main contribution and innovations of the paper is organized as follows:(1) Focus on the need of frequency regulation and control of power system, the paper studied and built models of HTGS under frequency regulations, opening regulations and power regulation. Meanwhile, nonlinear sets of the system are detailed described and a simulation platform for hydropower system is built in Simulink, which provide a basis for parameters estimation and control law design of hydropower system.(2) To get accurate models of SG and its PMGS, the paper introduced the multi-innovation least square (MILS) identification method. A linear regressive model of SG and its PMGS is derived from their transfer function model. Case study showed the effect of the multi-innovation least square method in parameters identification of hydropower unit.(3) To estimate parameters of HTGS, the paper introduced the Quantum Particle Swarm Optimization (QPSO) algorithm and converted the problem of parameters identification of HTGS into a constrained optimization problem with single object function. Focus on the characteristic of time-varing, non-minimum phase and complex nonlinearity of HTGS, an improved QPSO (IQPSO) with chaos mutation operator is proposed and is used to solve the problem of parameters estimate of nonlinear HTGS. Simulations under different operations show the effectiveness of IQPSO.(4) To identification parameters of nonlinear state space of SG, this paper presents an improved algorithm named Particle Swarm Optimization with Quantum Operation (PSO-QO) to solve both offline and online parameters estimation problem for SG. An illustrative example for parameters identification of SG is provided to confirm the validity. Meanwhile, PSO-QO is also improved with a sentry particle introduced into the swarm to detect and determine parameters variation. Simulation results confirm that the proposed algorithm is a viable alternative for online parameters detection of SG.(5) With reviewing the identification methods in literatures, this paper tried to provide a novel idea to deal with parameters estimation as a problem of dynamic system design. Principles for dynamic system design are proposed in this paper, and a specific dynamic system based on Hopfield Neural Networks (HNN) is listed in the paper. With the dynamic system based on HNN, the paper estimated parameters of the nonlinear SG model formulated by third order differential equations and feasibility of the method is verified by simulation test.(6) Focus on conventional PID controller can not satisfied the need of HTGS with multi-condition and time-varying parameters, this paper introduced Bacterial Foraging Optimization (BFO) into PID parameter optimization tuning. Considering the slow convergence of BFO algorithm and the good convergence of particle swarm optimization (PSO) algorithm, a novel method named BFO-PSO algorithm was proposed. A new performance index integrated with ITAE and the Jcc index which can reflect the effect of bacterial swarm's mutual attraction, mutual repellence and mutual learning was proposed. Thus, the paper constructed the frame of PID parameter optimization tuning based on intelligent optimization method and provides an alternative for PID parameter optimization tuning of HTGS in any conditions.(7) Considering that the PID control law is not suitable for HTGS with multiple conditions and parameter time-varying, the sliding mode control (SMC) law was illustrated in this paper. With control input of unit reference speed neglected, the no-load disturbance can not be simulated in conventional state space model of HTGS and steady speed error exists in this state space model under linear optimal control theory. To overcome these problems, the paper proposed an improved state space model of HTGS with three control inputs. With the steady error of the improved state space model analyzed, the paper display reason of the steady error and supplied a technique to eliminate the steady error of the improved model of HTGS. Meanwhile, a sliding mode controller for HTGS is designed based on the improved state space model of HTGS with three control inputs. |
