Next Article in Journal
A Stochastic Inexact Robust Model for Regional Energy System Management and Emission Reduction Potential Analysis—A Case Study of Zibo City, China
Previous Article in Journal
Sequence Planning for Selective Disassembly Aiming at Reducing Energy Consumption Using a Constraints Relation Graph and Improved Ant Colony Optimization Algorithm
Open AccessArticle

Optimal P-Q Control of Grid-Connected Inverters in a Microgrid Based on Adaptive Population Extremal Optimization

1
School of Computer, South China Normal University, Guangzhou 510631, China
2
National-Local Joint Engineering Laboratory of Digitalize Electrical Design Technology, Wenzhou University, Wenzhou 325035, China
3
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
4
State Key Laboratory of Power Systems and Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
*
Author to whom correspondence should be addressed.
Energies 2018, 11(8), 2107; https://doi.org/10.3390/en11082107
Received: 24 July 2018 / Revised: 6 August 2018 / Accepted: 9 August 2018 / Published: 13 August 2018
(This article belongs to the Section Electrical Power and Energy System)
The optimal P-Q control issue of the active and reactive power for a microgrid in the grid-connected mode has attracted increasing interests recently. In this paper, an optimal active and reactive power control is developed for a three-phase grid-connected inverter in a microgrid by using an adaptive population-based extremal optimization algorithm (APEO). Firstly, the optimal P-Q control issue of grid-connected inverters in a microgrid is formulated as a constrained optimization problem, where six parameters of three decoupled PI controllers are real-coded as the decision variables, and the integral time absolute error (ITAE) between the output and referenced active power and the ITAE between the output and referenced reactive power are weighted as the objective function. Then, an effective and efficient APEO algorithm with an adaptive mutation operation is proposed for solving this constrained optimization problem. The simulation and experiments for a 3 kW three-phase grid-connected inverter under both nominal and variable reference active power values have shown that the proposed APEO-based P-Q control method outperforms the traditional Z-N empirical method, the adaptive genetic algorithm-based, and particle swarm optimization-based P-Q control methods. View Full-Text
Keywords: power control; grid-connected inverter; extremal optimization; design optimization; evolutionary algorithms power control; grid-connected inverter; extremal optimization; design optimization; evolutionary algorithms
Show Figures

Figure 1

MDPI and ACS Style

Chen, M.-R.; Wang, H.; Zeng, G.-Q.; Dai, Y.-X.; Bi, D.-Q. Optimal P-Q Control of Grid-Connected Inverters in a Microgrid Based on Adaptive Population Extremal Optimization. Energies 2018, 11, 2107.

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.

Article Access Map by Country/Region

1
Back to TopTop