An Optimal Power Allocation Scheme of Microgrid Using Grey Wolf Optimizer

Jiancheng Zhang,Lingyu Ma,Xinsheng Wang

doi:10.1109/access.2019.2942352

Jiancheng Zhang, Lingyu Ma + Show 1 more

Open Access

https://doi.org/10.1109/access.2019.2942352

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Abstract

There are some existing power management methods considering economic factors, but these methods are limited by fixed structure of microgrid (MG) and mathematical model, which will be out of effect once the structure changes. In order to obtain the optimal power allocation scheme, this paper proposed the grey wolf optimization (GWO) for the distributed hierarchical control structure of MG, considering the economic dispatching problem. Firstly, the distributed generators (DGs) of MG are considered as multi-agent system, and the secondary controller is constructed. Secondly, the objective function and constraints of GWO are established. Thirdly, the calculation results of GWO are taken as the input of secondary controller, which are called virtual rated power (VRP). Finally, by adjusting VRP dynamically, the on-line real-time optimal power distribution of MG is achieved, and the system stability is proved by multi-agent consensus theory. This power allocation scheme is more flexible to realize the plug-and-play capability. The simulation model is established in Matlab/Simulink environment, and the simulation results show that the method is effective.

Highlights

Microgrid (MG) is a distributed system composed of multiple distributed generators (DGs), energy storage and loads
With the intensification of global climate change and the depletion of traditional energy, more and more people are concerned about the use of unconventional and renewable energy for distributed generator (DG), which usually includes wind, solar and nuclear energy etc
To mathematically model the social hierarchy of grey wolves, firstly, the objective function is constructed according to the problems and the best solution is regarded as alpha, the second and third best solutions are considered as beta and delta, while the rests of the solutions are regarded as omega

Summary

INTRODUCTION

Microgrid (MG) is a distributed system composed of multiple distributed generators (DGs), energy storage and loads. Zhang et al.: Optimal Power Allocation Scheme of Microgrid Using Grey Wolf Optimizer topology of MG, the system can adjust the active power dynamically and achieve the power-sharing state again Inspired by this method, if the multi-agent consistency control algorithm is used to realize active and reactive power sharing, the power of each DG is dynamically managed by adjusting the virtual rated power (VRP as the intermediate variable to regulate the energy, by replacing the rated power of DG in the adjustment process). Utilizing the nature of consistency, realizes the real-time and dynamic energy management of MG by adjusting VRP This method considers the rated power of each DG, and takes into account the generation cost of every DG.

SYSTEM STRUCTURE

SECONDARY CONTROL

OVERVIEW OF GREY WOLF OPTIMIZATION

SIMULATION VALIDATION

VARIABLE COST COEFFICIENT

CONCLUSION