基于改进单纯形法和凝结水节流的超超临界机组协调优化
摘要：风能、太阳等新能源的规模化并网对电网的安全稳定性造成较大影响。为提高新能源的消纳能力，电网对燃煤机组的运行灵活性、负荷快速响应能力、深度调峰能力等提出了很高的要求。采用先进的控制策略提升协调控制的品质，具有重要的现实意义。基于近年来发展起来的"凝结水节流"快速变负荷方法，采用人工神经网络建立了考虑凝结水节流特性的负荷预测模型及主汽压力预测模型。在此基础上，利用经典优化理论中的改进单纯形法，设计了协调系统智能优化控制策略，编制了实时优化程序。借助1000 MW超超临界机组仿真机开展了详细的优化控制仿真实验，结果表明文中方法可有效提高机组变工况负荷响应的快速性，减少主汽压力波动，提升协调控制品质。
Abstract:With large-scale wind and solar energy power units put into operation, it brings great influence on the stability and safety of the power network due to the high fluctuation and randomness features of the wind and solar resources. In order to absorb more new energy power, regional load dispatch center puts up very high requirement for the operation flexibility, load fast-following and deep peak load regulation ability. Therefore, it is very significant to adopt advanced control strategies to optimize the coordinated control system (CCS) to improve its control quality. In this work, the load prediction neural network model considering "condensate throttling" and the main steam pressure prediction model were developed by taking a 1000 MW ultra-supercritical power unit as the object investigated. Based on the established models, a classic optimization theory-improved simplex method was selected as the CCS optimization algorithm. An intelligent coordination optimization scheme with condensate throttling was designed, and the real-time optimization program was developed with MATLAB software. Detailed simulation tests were carried out in the full-scope simulator of the 1000 MW power unit. Simulation results indicate that the proposed scheme can effectively improve the coordinated control quality with faster load response, less main steam pressure fluctuation during dynamic load-changing process.
标题：基于改进单纯形法和凝结水节流的超超临界机组协调优化
title:Coordinated System Intelligent Optimization for an Ultra-Supercritical Power Unit Based on Improved Simplex Method and Condensate Throttling
作者：马良玉,李倩倩,李帆
authors:Liangyu MA,Qianqian LI,Fan LI
关键词：超超临界机组,协调系统,神经网络建模,单纯形法,预测优化控制,凝结水节流,
keywords:ultra-supercritical power unit,coordinated control system,neural network modelling,simplex method,predictive optimization control,condensate throttling,
发表日期：2018-12-31
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