**Electricity Consumption and Generation Forecasting with Artificial Neural Networks** Electricity Consumption and Generation Forecasting

DOI: 10.5772/intechopen.71239

Adela Bâra and Simona Vasilica Oprea

with Artificial Neural Networks

Additional information is available at the end of the chapter Adela Bâra and Simona Vasilica Oprea

http://dx.doi.org/10.5772/intechopen.71239 Additional information is available at the end of the chapter

## Abstract

Nowadays, smart meters, sensors and advanced electricity tariff mechanisms such as timeof-use tariff (ToUT), critical peak pricing tariff and real time tariff enable the electricity consumption optimization for residential consumers. Therefore, consumers will play an active role by shifting their peak consumption and change dynamically their behavior by scheduling home appliances, invest in small generation or storage devices (such as small wind turbines, photovoltaic (PV) panels and electrical vehicles). Thus, the current load profile curves for household consumers will become obsolete and electricity suppliers will require dynamical load profiles calculation and new advanced methods for consumption forecast. In this chapter, we aim to present some developments of artificial neural networks for energy demand side management system that determines consumers' profiles and patterns, consumption forecasting and also small generation estimations.

Keywords: forecast, renewable energy, smart metering, demand side management, consumers' profiles
