Day Ahead Optimal Dispatch Schedule in a Smart Grid Containing Distributed Energy Resources and Electric Vehicles.

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Smart Grid Technology

Background:

• Smart grids require efficient energy management to integrate diverse distributed energy resources (DERs).
• Minimizing reliance on fossil fuel-based energy imports is crucial for grid sustainability.
• Electric vehicles (EVs) offer potential as distributed storage through vehicle-to-grid (V2G) technology.

Purpose of the Study:

• To develop and evaluate a day-ahead optimal dispatch strategy for smart grids.
• To minimize the import of fuel-based energy from the main grid.
• To maximize the utilization of renewable energy sources and storage systems.

Main Methods:

• A day-ahead optimal dispatch model was formulated for smart grids.
• The model incorporates two-axis tracking photovoltaic (PV) panels, wind turbines (WT), battery energy storage systems (BESS), and EVs in V2G mode.
• The method relies on data from smart grid communication networks, including sensors and metering devices.

Main Results:

• The proposed method effectively minimizes fuel-based energy imported from the main grid.
• Demonstrated full exploitation of DER production, including PV and WT.
• Showcased the capability of EVs to act as prosumers, contributing to grid stability and energy management.

Conclusions:

• The day-ahead optimal dispatch method enhances smart grid sustainability and efficiency.
• Integrating BESS and V2G-enabled EVs significantly improves DER utilization.
• The communication infrastructure of smart grids is vital for the successful implementation of advanced energy dispatch strategies.