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QUASI REAL-TIME ECONOMICAL OPERATION OF HYDROPOWER PLANT

机译：水电站的准实时经济运行

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Optimum regulation can improve the economic benefits for hydropower plant. Economical Operation of Hydropower Plant (EOHP) is one type of optimum regulation in a day, which can improve the economic results at least 1%. It aims at dispatch the load among the units of hydropower plant. As the time-interval being 1 hour in load diagram supplied by power system, EOHP always selects 1 hour as calculating time-interval in the past. That means EOHP calculates at the beginning of every hour to dispatch load for this hour. In this way, the real-time system of EOHP cannot be obtained. With the development of power system and monitoring and controlling technique of hydropower plant, the load can be forecasted in a shorter period and real-time EOPH can be realized step by step. So a quasi real-time EOHP is proposed, which is close to real-time EOHP. Two improvements are made to realize quasi real-time EOHP, one is to improve accuracy of EOHP, and the other is to increase the speed of calculation. EOHP distributes load according to the load requirement of the electrical network and state of water level as well as situation of each hydroelectric power unit. The accuracy of EOHP is affected by unit state and calculation speed greatly. In order to gain the correct state of each water turbine generator units, in this paper a radial basis function (RBF) network is proposed to forecast the flow consumption. Efficiency test data for typical water heads is used to train the network. Then groups of water heads and generator output data are used as input vector of the network, with the flow consumption as outputs vector, to train the RBF network. After the network being trained, the proper weights and biases are obtained, with which the flow consumption of water turbine generator unit can be forecasted by the network. In practice, the weights and biases of the RBF network can be modified by the last period water head and generator unit output. According to the change of water heads and electrical loads, optimal calculation of EOHP is realized by dynamic programming in this paper. If the changes reach the computational condition, optimal calculation of EOHP will begin to dispatch the load for each unit; else the operating states of units in last period will be continued. Improvements in these two respects can increase accuracy and calculation speed of EOHP. In a case study, the speed of calculation exceeds the speed of necessary changes of the controlled hardware. Thus quasi real-time economic hydropower plant operation is achieved.
机译：最佳规定可以提高水电站的经济效益。水电站（EOHP）的经济运行是一天的一种最佳调节，可以提高经济结果至少1％。它旨在调度水电站单位之间的负荷。随着电力系统提供的负载图中的时间间隔为1小时，EOHP始终选择过去的时间间隔1小时。这意味着EOHP在每小时开始时计算此时派遣负载。以这种方式，无法获得EOHP的实时系统。随着电力系统的发展和水电站的监测和控制技术，可以在较短的时间内预测负载，并且可以通过步骤实现实时EOPH。因此提出了一种准确的EOHP，其接近实时EOHP。进行了两种改进来实现准实时EOHP，是提高EOHP的准确性，另一个是提高计算速度。 EOHP根据电网的负载要求和水平状态的负载要求以及每个水力发电单元的情况分配负载。 EOHP的准确性受到单位状态和计算速度的影响。为了获得每个水轮机发生器单元的正确状态，本文提出了一种径向基函数（RBF）网络来预测流量消耗。典型水头的效率测试数据用于培训网络。然后，水头和发电机输出数据被用作网络的输入向量，流量消耗作为输出向量，训练RBF网络。在培训网络之后，获得了适当的权重和偏置，可以通过该重量和偏置来预测水轮机发生器单元的流量消耗。在实践中，RBF网络的权重和偏置可以通过最后一段水头和发电机单元输出来修改。根据水头和电荷的变化，通过本文的动态编程实现了EOHP的最佳计算。如果变化达到计算条件，EOHP的最佳计算将开始分派每个单元的负载;否则将继续在上一段时间内的单位经营状态。这两个方面的改进可以提高EOHP的精度和计算速度。在一个案例研究中，计算速度超过受控硬件的必要变化的速度。因此，实现了准实时经济水电站运行。

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