Improving A Grid-Based Energy Efficiency by Using Service Sharing Strategies.

One of most important concerns in electrical power markets and distribution network is supplying the customer demands. It is necessary to forecast the usage of electrical power in distribution network. The pattern of electrical power usage depends on many different parameters such as the density of population in those areas, the week days, weather condition and etc. However, the electric utilities and regulators face difficult challenges evaluating new energy efficiency and smart grid programs prompted by recent state. In this paper, it is tried to forecast the electrical power usage according to above parameters by using artificial neural network base on service sharing strategies regarding that can help meet their energy efficiency policy goals. It is tried to find out the pattern of electrical power usage with the dataset which is prepared by real data. Therefore, it has been used here is useful in all kind of power forecasting such as short term, middle term, and long term. It can be helpful to manage the distributed generators production schedule and also correction of electrical power usage. [ABSTRACT FROM AUTHOR]