Distributed Solution of Stochastic Volt/VAr Control in Radial Networks

Abstract

This paper presents a fully distributed algorithm for the stochastic Volt/VAr control (VVC) problem in active distribution networks. Exact convexification of the VVC problem is achieved through the use of second-order cones on the continuous relaxation of the original optimization structure. The global optimum solution of the relaxed problem is obtained through the application of the alternating direction method of multipliers (ADMM). In order to minimize the effect of rounding off on the final solution, an adaptive threshold discretization technique is used. A two-stage control strategy is adopted where the discrete controllers, like load tap changers and switched capacitors, are dispatched at the beginning of the optimization interval and the continuous controllers, like distributed generation (DG) inverters, are adjusted in real time according to an optimized decision rule. The superiority of the proposed algorithm is demonstrated through numerical simulations on the UKGDS-95 and the IEEE-123 bus systems.

Affinely Adjustable Robust Volt/VAr Control Without Centralized Computations

“…This leads to the problem of the coordinated voltage control between the legacy VCDs and the PV inverters, which has been a subject of recent research. Many research works adopt a control law for adjusting the smart inverter reactive power in response to fluctuations in either the voltage magnitude [6]- [8] or active power [1], [9]- [12] at their terminals, thereby effectively allowing the legacy VCDs to run at a slower time scale.…”

“…In practice, both the parameters of the control law and the settings of the legacy VCDs are computed simultaneously at the beginning of the optimization horizon. The Q(V ) control law, adopted in [6] - [8], suffers from the main problem of restrictive convergence conditions and can lead to undesirable oscillatory behaviour, whereas the Q(P ) control law has shown stable performance to maintain the voltages in an acceptable region [1], [9]- [12]. Furthermore, the German Grid Code also proposes such Q(P ) characteristics to support the network voltage profile [13].…”

Affinely Adjustable Robust Volt/VAr Control without Centralized Computations

“…This leads to the problem of the coordinated voltage control between the legacy VCDs and the PV inverters, which has been a subject of recent research. Many research works adopt a control law for adjusting the smart inverter reactive power in response to fluctuations in either the voltage magnitude [6]- [8] or active power [1], [9]- [12] at their terminals, thereby effectively allowing the legacy VCDs to run at a slower time scale.…”

“…In practice, both the parameters of the control law and the settings of the legacy VCDs are computed simultaneously at the beginning of the optimization horizon. The Q(V ) control law, adopted in [6] - [8], suffers from the main problem of restrictive convergence conditions and can lead to undesirable oscillatory behaviour, whereas the Q(P ) control law has shown stable performance to maintain the voltages in an acceptable region [1], [9]- [12]. Furthermore, the German Grid Code also proposes such Q(P ) characteristics to support the network voltage profile [13].…”

“…Furthermore, the German Grid Code also proposes such Q(P ) characteristics to support the network voltage profile [13]. These Q(P ) characteristics are mostly decided based on affine policies [1], [11], [12] whereas quadratic decision rules have been used in [9], [10]. Although the quadratic decision rules allow finer control, their use is limited by the tractability of the underlying optimization framework.…”