ARTIFICIAL NEURAL NETWORK FOR LOAD FORECASTING IN SMART GRID HAO-TIAN ZHANG, FANG-YUAN XU, LONG ZHOU Energy System Group,City University London,Northampton Square ,London,UK E-MAIL:************.uk,***************.uk,*******************.ukAbstract: It is an irresistible trend of the electric power improvement for developing the smart grid, which applies a large amount of new technologies in power generation, transmission, distribution and utilization to achieve optimization of the power configuration and energy saving. As one of the key links to make a grid smarter, load forecast plays a significant role in planning and operation in power system. Many ways such as Expert Systems, Grey System Theory, and Artificial Neural Network (ANN) and so on are employed into load forecast to do the simulation. This paper intends to illustrate the representation of the ANN applied in load forecast based on practical situation in Ontario Province, Canada. Keywords:Load forecast; Artificial Neuron Network; back propagation training; Matlab 1. Introduction Load forecasting is vitally beneficial to the power system industries in many aspects. As an essential part in the smart grid, high accuracy of the load forecasting is required to give the exact information about the power purchasing and generation in electricity market, prevent more energy from wasting and abusing and making the electricity price in a reasonable range and so on. Factors such as season differences, climate changes, weekends and holidays, disasters and political reasons, operation scenarios of the power plants and faults occurring on the network lead to changes of the load demand and generations. Since 1990, the artificial neural network (ANN) has been researched t...
