Distribution Locational Marginal Price Driven Reactive Demand Response from Electric Vehicle Aggregator
Bhavana Jangid, Parul Mathuria, Vikas Gupta
Abstract
To maintain balance in renewable energy-rich grids, distribution system operators (DSOs) increasingly rely on local demand response (DR) flexibility. Electric vehicles (EVs) through an EV aggregator (EVA) can serve as a cost-effective source for DR flexibility. While EVs' active DR capabilities have received attention, their potential for providing reactive DR to support the grid remains underexplored. This study explores the potential of EVAs as active as well as reactive DR provider to DSO, enhancing the synergy across transmission-distribution (TD) interface. Spectral clustering algorithm-based aggregation is performed to obtain aggregated DR. The aggregated active & reactive DR potential is considered for hierarchical energy management framework, where DSO optimizes grid's operational cost under network constraints while considering DR from EVA, and EVA minimizes its energy payments driven by DSO's Distribution Locational Marginal Prices (DLMPs). The resulting bi-level model is transformed into a single-level optimization problem using KKT optimality conditions and strong duality theorem. Furthermore, the EVA decomposes the reference schedule provided by DSO to meet user constraints. A case study of the IEEE 33-bus radial distribution system demonstrates that reactive DR through EVA at the distribution level can significantly enhance economic and physical systems performance while maintaining balance at TD interface.