Probabilistic day-ahead simultaneous active/reactive power management in active distribution systems

Abstract

Distributed generations (DGs) are main components for active distribution networks (ADNs). Owing to the large number of DGs integrated into distribution levels, it will be essential to schedule active and reactive power resources in ADNs. Generally, energy and reactive power scheduling problems are separately managed in ADNs. However, the separate scheduling cannot attain a global optimum scheme in the operation of ADNs. In this paper, a probabilistic simultaneous active/reactive scheduling framework is presented for ADNs. In order to handle the uncertainties of power generations of renewable-based DGs and upstream grid prices in an efficient framework, a stochastic programming technique is proposed. The stochastic programming can help distribution system operators (DSOs) to make operation decisions in front of existing uncertainties. The proposed coordinated model considers the minimization of the energy and reactive power costs of all distributed resources along with the upstream grid. Meanwhile, a new payment index as loss profit value for DG units is introduced and embedded in the model. Numerical results based on the 22-bus and IEEE 33-bus ADNs validate the effectiveness of the proposed method. The obtained results verify that through the proposed stochastic-based power management system, the DSO can effectively schedule all DGs along with its economic targets while considering severe uncertainties.