Efficiency dynamic optimizing operation closed-loop optimization control method based on optimum operating conditions of thermal generator set
A technology for thermal power generating units and optimal working conditions, which is applied in the direction of electrical program control, comprehensive factory control, etc., and can solve the problem of not realizing closed-loop optimization control of efficiency automatic control system.
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Embodiment 1
[0015] Such as figure 1 As shown, the present invention is based on the efficiency dynamic optimization operation flow chart of the closed-loop optimization control method of the optimal working condition of the thermal power generating set. The operating parameters of the thermal power generating set are read from the DCS to the intelligent plug-in system through the network, and in the smart plug-in system through Optimize the control algorithm to obtain the operating parameter guidance values to optimize the unit efficiency and achieve the best operating conditions, and then return some valuable optimization parameter operation guidance values to the DCS system through the network, and introduce these optimization parameters into the unit automatic In the control system DCS, as the given value (command) of each automatic control system, the unit operating parameters are consistent with the optimized parameters through the adjustment function of the automatic control syst...
Embodiment 2
[0028] Embodiment 2, optimize operation process
[0029] 2.1 Prediction of unit operating parameters
[0030] Some key parameters of thermal power units, such as steam turbine exhaust enthalpy, carbon content in fly ash, etc., are difficult to measure accurately, and these parameters are necessary for the calculation and optimization of unit operation economic performance. In recent years, soft sensor on-line monitoring technology has been greatly developed. This technology uses some variables that are easy to measure in real time and are closely related to the measured variable. The core is the soft sensor model. At present, soft sensor modeling methods can generally be divided into: mechanism modeling, regression analysis, state estimation, pattern recognition, artificial neural network, fuzzy mathematics, methods based on support vector machines and kernel functions, and modern nonlinear system information processing technology, etc. . Among them, support vector machine ...
Embodiment 3
[0112] 1 Self-optimization mode to determine the target value
[0113] 1.1 Fuzzy comprehensive evaluation decision
[0114] The fuzzy comprehensive evaluation decision is to apply the fuzzy set method to make a single decision on the factors involved in the object, and then synthesize all aspects of the situation to give an overall decision for the object.
[0115] The mathematical model of fuzzy comprehensive evaluation decision-making is composed of three elements, and its steps are divided into four steps:
[0116] (1) Factor set U={u 1 , u 2 ,...u n}, a set composed of various factors of the evaluated object;
[0117] (2) Judgment set (evaluation set or decision set) V={v 1 , v 2 ,…v m}, a set of comments;
[0118] (3) Single factor judgment, that is, for a single factor u i (i=1,...,n) evaluation, get the fuzzy set on V (r i1 , r i2 ,...r im ), so it is a fuzzy mapping from U to V
[0119] f : ...
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Abstract
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