Next Article in Journal
Exergoeconomic Performance Comparison and Optimization of Single-Stage Absorption Heat Transformers
Next Article in Special Issue
Validation of the Measurement Characteristics in an Instrument for Power Quality Estimation—A Case Study
Previous Article in Journal
Developing an Input-Output Based Method to Estimate a National-Level Energy Return on Investment (EROI)
Previous Article in Special Issue
Modelling and Optimization in Microgrids
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle
Energies 2017, 10(4), 535; doi:10.3390/en10040535

A Framework for Real-Time Optimal Power Flow under Wind Energy Penetration

Department of Simulation and Optimal Processes, Institute of Automation and Systems Engineering, Ilmenau University of Technology, Ilmenau 98693, Germany
*
Author to whom correspondence should be addressed.
Received: 9 February 2017 / Revised: 27 March 2017 / Accepted: 6 April 2017 / Published: 14 April 2017
View Full-Text   |   Download PDF [3835 KB, uploaded 18 April 2017]   |  

Abstract

Developing a suitable framework for real-time optimal power flow (RT-OPF) is of utmost importance for ensuring both optimality and feasibility in the operation of energy distribution networks (DNs) under intermittent wind energy penetration. The most challenging issue thereby is that a large-scale complex optimization problem has to be solved in real-time. Online simultaneous optimization of the wind power curtailments of wind stations and the discrete reference values of the slack bus voltage which leads to a mixed-integer nonlinear programming (MINLP) problem, in addition to considering variable reverse power flow, make the optimization problem even much more complicated. To address these difficulties, a two-phase solution approach to RT-OPF is proposed in this paper. In the prediction phase, a number of MINLP OPF problems corresponding to the most probable scenarios of the wind energy penetration in the prediction horizon, by taking its forecasted value and stochastic distribution into account, are solved in parallel. The solution provides a lookup table for optional control strategies for the current prediction horizon which is further divided into a certain number of short time intervals. In the realization phase, one of the control strategies is selected from the lookup table based on the actual wind power and realized to the grid in the current time interval, which will proceed from one interval to the next, till the end of the current prediction horizon. Then, the prediction phase for the next prediction horizon will be activated. A 41-bus medium-voltage DN is taken as a case study to demonstrate the proposed RT-OPF approach. View Full-Text
Keywords: real-time optimal power flow (RT-OPF); mixed-integer nonlinear programming (MINLP) OPF; prediction and realization approach; wind power curtailment; variable reverse power flow real-time optimal power flow (RT-OPF); mixed-integer nonlinear programming (MINLP) OPF; prediction and realization approach; wind power curtailment; variable reverse power flow
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Mohagheghi, E.; Gabash, A.; Li, P. A Framework for Real-Time Optimal Power Flow under Wind Energy Penetration. Energies 2017, 10, 535.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top