Framework demonstrates reduced operational costs in microgrids with renewable energy and demand response, highlighting effective real-time pricing strategies.
Key Points
This research aims to optimize real-time dynamic pricing in microgrids using a stochastic approach to reduce operational costs.
Developed a framework for energy management in microgrids with renewable energy sources.
Used probabilistic modeling to address uncertainties in load demand, wind speed, solar irradiance, and market prices.
Employed a two-stage stochastic optimization combining mixed-integer linear programming and optimal power flow.
Analyzed three microgrid scenarios using historical data: grid-connected without DR, with 10% and 20% DR, and an islanded microgrid.
Incorporating demand response strategies significantly reduced operational costs and reliance on grid imports during peak demand.
The islanded microgrid scenario highlighted challenges of self-sufficiency, incurring higher operational costs despite autonomy.