Efficient integration of demand response and plug-in electrical vehicle in microgrid: Environmental and economic assessment

Abstract

The microgrid has become a promising area to mitigate multiple challenges of the power system, resulting from renewable energy integration, climate change, as well as economic issues. However, the integration of flexible emerging technologies in microgrid operation to enhance the efficiency of energy supply, as well as environmental and economic challenges are urgently needed. Motivated by these challenges, this paper elaborates on the two-stage multi-objective optimization model for optimal scheduling of microgrid. The demand response program based on the time of use model, and plug-in electric vehicles have been integrated into the microgrid to contribute in economic and environmental goals. The proposed model extends the realistic EVs model based on the Wohler curve and AC-power flow equations. The proposed model is exposed to a wide range of random parameters, including wind output, load, price, and EVs’ behaviours. To handle the uncertainties, and solving problem, scenario-based stochastic and weighted sum based on fuzzy decision-making strategies are respectively applied. The proposed model is tested on the 33-bus microgrid and examined for different cases. Results prove the impacts of the efficient integration of demand response, and a plug-in electric vehicle in the reducing of operational cost, and emission by 3.57% and 3.4%, respectively. • Proposing a realistic model for EV based on DoD and battery degradation. • Providing high-level flexibility for MG with the integration of PEV and DR. • Emission-economic assessment of renewable-based MG with flexible resources. • Proposing a two-stage stochastic programming model to capture uncertainties.