摘要
电蓄能技术是转移高峰电力、开发低谷用电、优化资源配置和保护生态环境的一项重要技术措施。受到分时电价政策的鼓励,蓄热式电锅炉供热技术已逐步得到推广应用。在蓄热式电锅炉供热系统中,直接向热用户供热的是蓄热器,电锅炉则应尽可能在低电价时段启动向蓄热器供热,而在高电价时段停运。
当前运行的蓄热式电锅炉供热系统中电锅炉的启停控制一般有两种方式:一种是根据分时电价和用户热负荷由人工启停,另一种是根据蓄热器的水位或水温信号由自动控制装置启停。这两种方式都不能充分利用分时电价,实现最优化运行(即运行费用最低)。
实际上,在已知逐时电价曲线和用户热负荷曲线的情况下,应存在一条最优的供热曲线(或电锅炉启停曲线),这条曲线可利用最优化理论和适当的优化方法来找到。问题是,其中的用户热负荷与诸多因素有关,难以预先确定。
考虑到影响供热采暖需求负荷的因素复杂且具有随机性和非线形性,在对预测理论进行研究和对各种预测方法进行比较后,本文首次将基于人工神经网络的负荷预测与基于动态规划原理的优化方法相结合,用于蓄热式电锅炉系统的经济运行策略研究。作为尝试,通过“CWL(气候-星期-负荷)”模型预测用户的热负荷需求,并以此为基础,结合当前及着眼未来的分时电价发展趋势,利用优化方法对该系统的经济运行做出决策。
本文还讨论了神经网络模型中隐含层神经元个数的选取问题及输入输出矢量的归一化处理问题,介绍了根据问题特点建立动态规划的优化模型及采用改进单纯形法求解的思路,并给出了具体的算法原理及实现步骤。
最后,介绍了应用Visual Basic、Access和MATLAB等工具进行编程实现的方法,并展示了研究结果在运行控制和经济分析上的应用。本文的研究成果对于蓄热式电锅炉系统的运行优化和电蓄能技术的推广应用,具有较为实际的参考和工程应用意义。
The electric power storage technology is an important technical measure that can remove peak load and fill valley load, optimize resource allotment and protect ecological environment. As a concrete realization of this technology, the electric boiler system with heat accumulator has been extensively used due to the stimulus of time-of-use electricity price policy. During the heat accumulator supplying to users, the electric boiler usually try to make heat by starting at low price of electric and stopping at high.
In general, the system of electric boiler with heat accumulator runs according to experience to utilize the time-of-use electricity price or controlled by the signals of water level or temperature. But the two ways are not ideal to realize the economical operation without full use of the policy of time-of-use electricity price.
Actually, known the distribution of electric price and demand of heat load versus time, an optimizing supply curve can be drawn, that is, the concrete economically running policy can be made. But it is difficult to define the heat load in advance.
After studying the prediction method and considering the complex, random and nonlinear factors that affect the demand load of heating, the ANN technology is adopted. Different from the general analysis in technology and economy, it is for the first time to combine the prediction in method of artificial neutral network with optimization in use of dynamic planning principle for the running analysis of the electric boiler. This paper tries to establish a CWL (climate-weekday-load) model to predict the heat demand load of users. Based on this and associated with the policy of time-of-use electricity price at present time and its future tendency, a much more economical decision can be made for this system using the optimization method. This paper tries to establish a CWL (climate-weekday-load) model to predict the heat demand load of users. Based on this and associated with the policy of time-sharing charge at present time and its future tendency, a much more economical decision can be made for this system using the
optimization method.
In addition, the problem of selecting the neuron number of implicit layer in the network model and the problem of normalization of input-output vectors are discussed. During the operation optimization, the model of dynamic planning is established according to the feature of this problem and the advanced simplex method is used for resolution with the concrete algorithm provided.
Finally, Application program design is realized by hybrid programming with the tools of Visual Basic, Access and MATLAB. It is also showed the result helpful for operating control and economical analysis. The result is helpful for the operation optimization of the system of electric boiler with heat accumulator and the popularization of the electric power storage technology, which will bring the achievement of comprehensive profit.
引文
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