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access icon free Stochastic assessment of distributed generation hosting capacity and energy efficiency in active distribution networks

© The Institution of Engineering and Technology
Received 09/04/2017, Accepted 20/07/2017, Revised 05/07/2017, Published 24/07/2017

Active network management (ANM) aims to increase the capacity of variable distributed generation (DG), which can be connected to existing distribution networks. In this study, it is proposed to simultaneously consider the efficient use of energy resources when high shares of DG are procured through the ANM approach. To that end, a multi-period and multiobjective optimisation algorithm, based on the linearised optimal power flow, is formulated. The algorithm seeks to maximise the installed capacity of DG while minimising the energy losses and consumption of voltage-dependent loads. The objectives are optimised considering the coordinated operation of voltage regulators and on-load tap changers, and the management of DG generation curtailment and reactive power compensation from DG. Additionally, the effects of load and generation uncertainties are addressed through a two-stage stochastic programming formulation of the multiobjective problem. The result is a set of non-inferior solutions, which allows exploring the degree of conflict among the objectives. The proposed approach was tested on two IEEE test feeders and the solutions show a significant improvement in the system's energy efficiency with a low impact on the amount of connected DG.

Inspec keywords: distribution networks; stochastic processes; voltage regulators; stochastic programming; compensation; load flow; on load tap changers; energy conservation; power system management; distributed power generation; reactive power; power consumption

Other keywords: DG generation curtailment; active network management; on-load tap changer; stochastic assessment; energy resource; energy loss minimization; ANM approach; active distribution network; distributed generation hosting capacity; multiperiod multiobjective optimisation algorithm; energy efficiency; voltage regulator; voltage-dependent load consumption; reactive power compensation; linearised optimal power flow; IEEE test feeder; two-stage stochastic programming formulation

Subjects: Transformers and reactors; Optimisation techniques; Distributed power generation; Power system management, operation and economics; Distribution networks; Other topics in statistics

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