Next Article in Journal
H Robust Control of an LCL-Type Grid-Connected Inverter with Large-Scale Grid Impedance Perturbation
Previous Article in Journal
Rotor Position Self-Sensing of SRM Using PSO-RVM
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Energies 2018, 11(1), 76; https://doi.org/10.3390/en11010076

Improved Krill Herd Algorithm with Novel Constraint Handling Method for Solving Optimal Power Flow Problems

1
Key Laboratory of Network Control & Intelligent Instrument, Chongqing University of Posts and Telecommunications, Ministry of Education, Chongqing 400065, China
2
Research Center on Complex Power System Analysis and Control, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
3
Key Laboratory of Communication Network and Testing Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
*
Author to whom correspondence should be addressed.
Received: 17 October 2017 / Revised: 6 December 2017 / Accepted: 22 December 2017 / Published: 1 January 2018
(This article belongs to the Section Electrical Power and Energy System)
Full-Text   |   PDF [5614 KB, uploaded 1 January 2018]   |  

Abstract

As one of the most important tools used in operation and planning of power systems, the optimal power flow (OPF) problem considering the economy and security is large-scale, complex and hard to solve. In this paper, an improved krill herd algorithm (IKHA) has been proposed. In IKHA, the onlooker search mechanism is introduced to reduce the probability of falling into local optimum; and the parameter values of the proposed algorithm including inertia weight and step-length scale factor are varied according to the iteration of evolutionary process, which improves the exploration and exploitation capabilities. Moreover, a novel constraint handling method is proposed to guide the individual to the feasible space and ensure that the optimal solution satisfies the security constraints. Then, IKHA is combined with the novel constraint handling method to solve the multi-constrained OPF problem, and its performance is tested on the IEEE 30 bus, IEEE 57 bus and IEEE 118 bus systems for 10 different simulation cases containing linear and non-linear objective functions. The simulation results demonstrate that the proposed method can solve the OPF problem successfully and obtain better solutions compared with other methods reported in the recent literatures, which prove the feasibility and effectiveness of the improvements in this work. View Full-Text
Keywords: optimal power flow; power systems; improved krill herd algorithm; novel constraint handling method optimal power flow; power systems; improved krill herd algorithm; novel constraint handling method
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

Share & Cite This Article

MDPI and ACS Style

Chen, G.; Lu, Z.; Zhang, Z. Improved Krill Herd Algorithm with Novel Constraint Handling Method for Solving Optimal Power Flow Problems. Energies 2018, 11, 76.

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