Abstract
Electric power load forecasting is not only the sticking point of the safely, operation of whole system, but also the key part of the economical and healthy development of electric power system. The intrinsic single models have shortage, so the synthesis forecasting model making better use of all information will be pursued. It combines those single models property to take full advantage of their information to improve the precision. The most important part of the combination forecasting model is how to confirm the weight. In AIS, antigen and antibody are the parallelism of aim function and doable result. The appetency between antigen and antibody is regarded as the matching degree between feasible result and the objective function. Because of its good property on global searching, it can find the optimal solutions, some synthetic forecasting models based on AIS are set up in this paper, which combine AIS and load forecasting. The attempter average synthetic model and power geometry average synthetical model proposed in this paper, has been applied to a certain area mid-long term load forecasting. It is showed that the synthetic forecasting model based on AIS could provide high forecasting precision.
Highlights
In today's unprecedented development of China's electric power industry, power management is moving towards the market, and power load forecasting has become an important and arduous task we are facing [1]
Prediction accuracy is affected, in the past decade, there has been a rise in the combination of different prediction methods, making full use of the useful information contained in each single prediction model, to improve the prediction accuracy of the comprehensive prediction research [2]
The basic idea of the model is that the optimal weights of each single power load forecasting model in the comprehensive model of power load forecasting are used as antigens, the solution of weights is used as antibodies, and the working principle of biological immune system is simulated to search for the optimal weights, i.e. through the initialization of antibodies, the calculation of objective functions, the immune genetic evaluation and the immune genetic evaluation
Summary
In today's unprecedented development of China's electric power industry, power management is moving towards the market, and power load forecasting has become an important and arduous task we are facing [1]. Prediction accuracy is affected, in the past decade, there has been a rise in the combination of different prediction methods, making full use of the useful information contained in each single prediction model, to improve the prediction accuracy of the comprehensive prediction research [2]. Artificial immune algorithm is a random search method based on the working mechanism of simulated biological immune system. It combines the two characteristics of prior knowledge and adaptive ability of biological immune system, so it has strong and robust information processing ability, and is similar to other intelligent algorithms. We hope that the artificial immune algorithm can be applied to the comprehensive forecasting of power load in order to establish a highprecision forecasting model and make a useful attempt to the application of artificial immune algorithm
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