Real time demand response using renewable energy resources and energy storage in smart consumers

There is a pressing need to accelerate the development of low-carbon energy technologies in order to address the global challenges of energy safety, climate changes and economic growth. Smart grids are particularly important as they enable several other low-carbon energy technologies, including electric vehicles, variable renewable energy sources and demand response. This paper describes an optimization model to adjust the hourly load level of a given consumer in response to hourly electricity prices with consideration of renewable energy resources and energy storage. The objective of the model is to minimize the energy cost of the consumer. Price uncertainty and uncertainties in making prediction about solar PV and wind power generation are modeled through robust optimization techniques. The model materializes into a simple linear programming algorithm that can be easily integrated in the Energy Management System of a household or a small business. A simple bidirectional communication device between the power supplier and the consumer enables the implementation of the proposed model. Simulations results confirm the performance of the proposed model.