Collaboration model between Distribution System Operator and flexible prosumers based on a unique dynamic price for electricity and flexibility

Abstract

The paper presents an innovative coordination model between flexible final customers and an aggregator in providing flexibility service to the Distribution System Operator called Coordination Via Aggregator (CVA). The problem is formulated as a stochastic two-stage bilevel model in which the leader acts as both the aggregator and the supplier, and maximizes its profit by determining the price signal for flexible final customers composed of energy-based component and the incentive for service provision. Final users, modeled as followers in the lower level of the model, minimize their costs following the price signal from the upper level. The aggregator in this model is a non-zero-profit market entity, i.e., the price determined by the aggregator covers the balancing costs, the energy supply costs and at the same time incentivizes flexible customers to adequately change their consumption patterns. The CVA results are compared with the Direct Service Activation (DSA) approach in which final customers have a predefined two-tariff pricing option and receive a fixed amount of annual network charges discount for participating in the direct load control program. Based on the small-scaled and medium-scaled MV network results, customers with Renewable Energy Sources (RES) face lower electricity costs when providing flexibility service under the CVA approach compared to DSA (15% lower costs in small-scaled network). However, the results show that prosumers with high PV capacity (inject more energy in the grid than withdraw on an annual level) if not involved in providing flexibility, are more prone to signing up for a contract with the aggregator achieving lower electricity cost compared to two-tariff pricing option, however if they are providing flexibility services, direct load control results in 14% lower costs. In contrast, providing flexibility service under DSA with reduced network charges results in 9% lower cost in small-scaled and 16% in medium-scaled networks for final users without RES.