skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Stochastic assessment of distributed generation hosting capacity and energy efficiency in active distribution networks

Abstract

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.

Authors:
; ; ;
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
Sao Paulo Research Foundation (FAPESP)
OSTI Identifier:
1466342
DOE Contract Number:  
AC02-06CH11357
Resource Type:
Journal Article
Journal Name:
IET Generation, Transmission, & Distribution
Additional Journal Information:
Journal Volume: 11; Journal Issue: 18; Journal ID: ISSN 1751-8687
Publisher:
Institution of Engineering and Technology
Country of Publication:
United States
Language:
English

Citation Formats

Quijano, Darwin Alexis, Wang, Jianhui, Sarker, Mushfiqur R., and Padilha-Feltrin, Antonio. Stochastic assessment of distributed generation hosting capacity and energy efficiency in active distribution networks. United States: N. p., 2017. Web. doi:10.1049/iet-gtd.2017.0557.
Quijano, Darwin Alexis, Wang, Jianhui, Sarker, Mushfiqur R., & Padilha-Feltrin, Antonio. Stochastic assessment of distributed generation hosting capacity and energy efficiency in active distribution networks. United States. doi:10.1049/iet-gtd.2017.0557.
Quijano, Darwin Alexis, Wang, Jianhui, Sarker, Mushfiqur R., and Padilha-Feltrin, Antonio. Thu . "Stochastic assessment of distributed generation hosting capacity and energy efficiency in active distribution networks". United States. doi:10.1049/iet-gtd.2017.0557.
@article{osti_1466342,
title = {Stochastic assessment of distributed generation hosting capacity and energy efficiency in active distribution networks},
author = {Quijano, Darwin Alexis and Wang, Jianhui and Sarker, Mushfiqur R. and Padilha-Feltrin, Antonio},
abstractNote = {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.},
doi = {10.1049/iet-gtd.2017.0557},
journal = {IET Generation, Transmission, & Distribution},
issn = {1751-8687},
number = 18,
volume = 11,
place = {United States},
year = {2017},
month = {12}
}