摘要:电力系统发展到今天，已成为国名经济建设和人民生活中必不可少的重要环节。电力系统的作用是对各类用户尽可能经济地提供可靠持续并且具有良好质量的电能。用电力系统部门术语来说，就是要可靠、安全、经济的供电，满足负荷的要求。因此就要对电力系统进行准确的负荷预测，负荷的大小与特征，无论是对于电力系统规划或者运行研究而言，都是极为重要的因素。
电力负荷的特点是经常变化的，有自身负荷的原因，也有外部因素导致负荷变化的因素。本文介绍了短期电力负荷预测的目的和意义，并对国内外短期负荷预测的现状进行介绍，通过介绍人工神经网络和模糊理论的相关概念和原理进行分析，并介绍神经网络的类型和训练算法。在本文的最后，详细介绍了预测模型建立的全过程，综合考虑温度、日期类型对日最大负荷预测的影响进而选择合适的模型输入建立相应的模糊神经网络预测模型，并取得了较为理想的预测结果，充分说明了模糊神经网络在短期电力负荷预测中有着巨大潜力。也说明研究电力负荷预测对电力系统能更好的服务于社会有着重要的意义。
关键词:短期负荷预测，人工神经网络，模糊理论，模糊神经网络
Abstract:Up to today, the development of power system has become an essential part in the construction of the national economy and in people’s life. The function of the power system is providing the continually reliable and good quality electricity for all types of users as economically as possible. For the sector terminology of the power systems, it is a reliable, safe and economical power supply, and it can meet the requirements of the load. Therefore, it is necessary to accurate the load forecasting of the power system. Whether it is a study for the power system planning or the operation, the load sizes and characteristics are extremely important factors.
The characteristics of the electrical load are constantly changing. The reasons for that situation are including the load factors and the external factors. This paper describes the purpose and significance of the short-term electrical load forecasting, introduces the current situation of the domestic and foreign short-term load forecasting. This paper analyzes the relevant concepts and principles of the artificial neural networks and fuzzy theory, and then introduces the type and training algorithms of neural network. At the end of this paper, details the whole process of the forecasting model. Considering the effect of the temperature, date type to the daily maximum load forecasting, and then select the appropriate model input fuzzy neural network prediction model. This study has achieved a more perfect prediction result and full explains the fuzzy neural network has a great potential in the short-term load forecasting. It also shows that the study of the electrical load forecasting has an important significance for the power system better serve the society.
Key words: short-term load forecasting, artificial neural networks, fuzzy theory, fuzzy neural network
