Quantifying energy flexibility of commuter plug-in electric vehicles within a residence–office coupling virtual microgrid. Part I: System configuration, quantification framework, and optimization model

Abstract

China’s decarbonization goals have accelerated its transition from a fossil-fuel-based power system to one with a high penetration level of renewable energy, thereby stimulating a massive demand for flexible grid services. Plug-in electric vehicles (PEVs) could offer a huge potential for energy flexibility in future power systems, especially in terms of mitigating high power peaks and power ramps. This work focuses on the flexibility assessment and optimal dispatch of commuter PEVs within a microgrid system. First, a virtual microgrid system including residential buildings, an office, distributed generation, and commuter PEVs was established. Second, a generic framework was proposed to quantify the flexibility potential of PEVs for reshaping the net load profile, along with several indicators to identify the flexibility characteristics in multiple dimensions. Third, a mixed-integer linear programming model was developed to schedule the charging and discharging processes of PEVs and calculate the flexibility indicators. This paper aims to explain the system configuration of the microgrid and the quantification framework and formulation of the optimization model. As such, it serves as the basis of a case study involving scenario and sensitivity analyses of PEV flexibility, presented in the companion paper (Part II).