Coordinated energy management using agents in neighborhood areas with RES and storage
This study proposes a novel coordination mechanism for smart homes in a small-scale neighborhood. This mechanism deploys a price and incentive-based energy management algorithm that considers renewable energy sources and battery storage. The objective of the proposed coordination algorithm is to decrease the electricity bills of the smart homes by increasing renewable energy usage inside the neighborhood, and enabling electricity trading among smart homes. The neighborhood is modeled using multi-agent systems, and heuristic problem solving is used by deploying a genetic optimization and rolling-horizon technique for day-ahead scheduling of the electricity appliances. Simulation results show…
Autonomy estimation for EV based on road planning software
A methodology to estimate the energy consumption of an electric vehicle is presented. An approach to create a driving cycle based on data extracted from road planning software is developped; it is used to forecast the total cycle energy consumption. Results are compared to the ones obtained from the corresponding actual driving cycle. The influence of road elevation is taken into. Results match with regard to vehicle velocities, power demand and estimated energy consumption, with a maximum error of 10%. It can thus be concluded that road planning-based energy consumption estimation can be a useful tool by providing accurate information to drivers.