Optimal Placement and Sizing of Reactive Power Sources in Active Distribution Networks: A Model Predictive Control Approach

Abstract

Reactive power sources have the potential for active distribution network (ADN) loss reduction and voltage profile improvement. However, the effective operation of reactive power sources depends upon their proper placement and sizing. To address this issue, this paper presents an optimal reactive power source allocation strategy in ADN. The salient feature of this strategy is that, by incorporating the ADN control scheme into the allocation process, it achieves the optimal allocation in a dynamic context. Specifically, smart transformer is considered as a particular realization of reactive power source, and the allocation problem is formulated as linear programming, which aims to minimize the investment cost of smart transformers. Meanwhile, the ADN control scheme is designed via model predictive control (MPC), with objectives of voltage regulation and loss reduction. Subsequently, the MPC formulation is embedded into the allocation problem, thus forming an integrated optimization problem, which links the control domain with the planning domain. By using the generalized Benders decomposition, this integrated problem is decomposed into a master problem and a set of subproblems, which can be solved alternately and iteratively. Simulation results verify the effectiveness of the proposed strategy.