Load forecasting on demand side by multi-regression model for operation of battery energy storage system

The load forecasting of the electric power has been studied extensively in the world. In many cases, the load forecast of the electric power systems is studied in the electric power company rather than demand side. The load forecast in the demand side is affected by some specific factors that are not measured and expected in advance. Although the factors/parameters are limited, it was difficult to build standard models that are applicable to various demand sides. In the era of deregulation, however, the management of customers' load became more important. Moreover, the demand forecast with high accuracy is necessary for the proper operation of BESS (battery energy storage system) such as NAS battery. In this paper a load forecasting technique using multi-regression model is proposed. Based on five years' records of the load in a university campus, the load for tomorrow can be forecasted. Numerical tests demonstrate the robustness and accuracy of the proposed technique.