Reactive DLMP for Hierarchical Energy Management and Optimal Reactive Power Response from EVs

Abstract

The aggregated demand-side flexibility has become a promising pathway to provide grid support services. Several management studies focusing on active demand response through Electric Vehicle Aggregator (EVA) and active price signal design are presented but the provision of reactive response and pricing is neglected. This paper presents a hierarchical energy management strategy for Distribution System Operator (DSO) and Electric Vehicle Aggregator (EVA) in an Active Distribution Network (ADN). Bilevel programming approach is adopted, where the EVA provides reactive demand response to the distribution grid. The EVA is motivated by reactive Distribution Location Marginal Price (DLMP) provided by the DSO. The lower-level aims to minimize the operational cost of ADN considering system security, and the upper-level aims to reduce the total payment of EVA. The Karush-Kuhn-Tucker (KKT) optimality conditions are used to convert the bilevel model into a single-level optimization problem, and active/reactive DLMPs are computed using the lagrangian function’s derivation. A case study of IEEE 33-bus radial distribution system is considered to illustrate the proposed hierarchical optimization problem. The results are analyzed in terms of nodal voltages, impact of reactive pricing on the system economics and, on active DLMPs. The analysis of the case study indicates the proposed approach can improve the economic and physical system performance due to the introduction of reactive power pricing at the distribution level.