Adaptive condition predictive-fuzzy PID optimal control of start-up process for pumped storage unit at low head area

Xu, Yanhe; Zheng, Yuan; Du, Yi; Yang, Wen; Peng, Xuyi; Li, Chaoshun

doi:10.1016/j.enconman.2018.10.004

Cited by 83 publications

(37 citation statements)

References 27 publications

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“…(3) Generator. The common first-order model [6,16,18] is adopted in this study to balance the pump turbine torque and the generator torque. The transfer function of the first-order model is as follows:…”

Section: Description Of the Ptgs Systemmentioning

confidence: 99%

“…Pump turbine governing system is the core control system of the pumped storage power station which is responsible for stabilizing the unit frequency and regulating the unit power [4,5]. Due to the huge flow inertia of the long-distance water pipeline and the existence of the unstable "S" characteristic area, the optimal control of PTGS is highly complex [6]. Therefore, it is of great theoretical value and practical significance to explore optimization methods for PTGS and research new control laws.…”

Section: Introductionmentioning

confidence: 99%

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Multiobjective Optimization of a Fractional‐Order PID Controller for Pumped Turbine Governing System Using an Improved NSGA‐III Algorithm under Multiworking Conditions

Zhang

Tian

et al. 2019

Complexity

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In order to make the pump turbine governing system (PTGS) adaptable to the change of working conditions and suppress the frequency oscillation caused by the “S” characteristic area running at middle or low working water heads, the traditional single-objective optimization for fractional-order PID (FOPID) controller under single working conditions is extended to a multiobjective framework in this study. To establish the multiobjective FOPID controller optimization (MO-FOPID) problem under multiworking conditions, the integral of the time multiplied absolute error (ITAE) index of PTGS running at low and high working water heads is adopted as objective functions. An improved nondominated sorting genetic algorithm III based on Latin hypercube sampling and chaos theory (LCNSGA-III) is proposed to solve the optimization problem. The Latin hypercube sampling is adopted to generate well-distributed initial population and take full of the feasible domain while the chaos theory is introduced to enhance the global search and local exploration ability of the NSGA-III algorithm. The experimental results on eight test functions and a real-world PTGS have shown that the proposed multiobjective framework can improve the Pumped storage units’ adaptability to changeable working conditions and the proposed LCNSGA-III algorithm is able to solve the MO-FOPID problem effectively.

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Section: Description Of the Ptgs Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multiobjective Optimization of a Fractional‐Order PID Controller for Pumped Turbine Governing System Using an Improved NSGA‐III Algorithm under Multiworking Conditions

Zhang

Tian

et al. 2019

Complexity

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“…Compared with traditional PID controller, the FOPID controller has two more adjustable parameters, which improve its control performance. However, at the same time, additional two adjustable parameters also make the optimal setting of fractional PID controller parameters more difficult [25].…”

Section: Introductionmentioning

confidence: 99%

Characteristic Analysis and Optimal Regulation of Primary Frequency Regulation Condition in Low Water Head Area Based on Hydraulic-Mechanical-Electrical Coupling Model of Pumped Storage Unit

et al. 2020

Complexity

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Pumped storage power station is an important regulating tool for peak load regulation and frequency regulation of the power grid, especially its primary frequency regulation function, which is of profound significance for the safety and stability of the power grid. As the core equipment of the pumped storage power station, the reversible design of the pump turbine makes it easy to have hydraulic fluctuation and mechanical instability when the unit runs to the “S” characteristic area, which will cause the frequency oscillation of the generator under the condition of primary frequency regulation. Therefore, some innovative work is studied in this paper: (1) an accurate hydraulic-mechanical-electrical coupling system mathematical model of pumped storage unit regulation system (PSURS) is established based on full characteristic curve of the pump turbine and seventh-order synchronous generator and excitation system; (2) the dynamic response characteristics of primary frequency regulation of pumped storage unit (PSU) under different water heads and different frequency disturbances are analyzed by numerical simulation; (3) in view of the unstable condition of the unit under the large frequency disturbance when it operates in the low head and small load area, the objective optimization function considering the ITAE index of hydraulic, mechanical, and electrical factors is proposed; and (4) fractional-order PID controller and the bacterial-foraging chemotaxis gravitational search algorithm (BCGSA) combined optimization strategy is used for PSURS optimization regulation and parameter optimization. The results show that the joint optimization strategy proposed in this paper has smaller objective function value, and makes the PSURS pass through the unbalanced area quickly, with better primary frequency regulation speed and smaller regulation depth.

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“…Although SVM possesses superior ability in pattern recognition, its performance is affected by parameters. In view of this, various optimization algorithms have been developed and applied to search the best parameters, such as particle swarm optimization (PSO) [23], bacterial foraging algorithm (BFA) [24], artificial sheep algorithm (ASA) [25] and sine cosine algorithm (SCA) [26]. As a novel optimization approach, the effectiveness of SCA in parameter optimization has been proved in many previous studies [27,28].…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis for Rolling Bearings Based on Fine-Sorted Dispersion Entropy and SVM Optimized with Mutation SCA-PSO

Tan

et al. 2019

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Rolling bearings are a vital and widely used component in modern industry, relating to the production efficiency and remaining life of a device. An effective and robust fault diagnosis method for rolling bearings can reduce the downtime caused by unexpected failures. Thus, a novel fault diagnosis method for rolling bearings by fine-sorted dispersion entropy and mutation sine cosine algorithm and particle swarm optimization (SCA-PSO) optimized support vector machine (SVM) is presented to diagnose a fault of various sizes, locations and motor loads. Vibration signals collected from different types of faults are firstly decomposed by variational mode decomposition (VMD) into sets of intrinsic mode functions (IMFs), where the decomposing mode number K is determined by the central frequency observation method, thus, to weaken the non-stationarity of original signals. Later, the improved fine-sorted dispersion entropy (FSDE) is proposed to enhance the perception for relationship information between neighboring elements and then employed to construct the feature vectors of different fault samples. Afterward, a hybrid optimization strategy combining advantages of mutation operator, sine cosine algorithm and particle swarm optimization (MSCAPSO) is proposed to optimize the SVM model. The optimal SVM model is subsequently applied to realize the pattern recognition for different fault samples. The superiority of the proposed method is assessed through multiple contrastive experiments. Result analysis indicates that the proposed method achieves better precision and stability over some relevant methods, whereupon it is promising in the field of fault diagnosis for rolling bearings.

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Adaptive condition predictive-fuzzy PID optimal control of start-up process for pumped storage unit at low head area

Cited by 83 publications

References 27 publications

Multiobjective Optimization of a Fractional‐Order PID Controller for Pumped Turbine Governing System Using an Improved NSGA‐III Algorithm under Multiworking Conditions

Multiobjective Optimization of a Fractional‐Order PID Controller for Pumped Turbine Governing System Using an Improved NSGA‐III Algorithm under Multiworking Conditions

Characteristic Analysis and Optimal Regulation of Primary Frequency Regulation Condition in Low Water Head Area Based on Hydraulic-Mechanical-Electrical Coupling Model of Pumped Storage Unit

Fault Diagnosis for Rolling Bearings Based on Fine-Sorted Dispersion Entropy and SVM Optimized with Mutation SCA-PSO

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