Coordination control of multiple micro sources in islanded microgrid based on differential games theory

Zhang, Jing; Gao, Yuan; Yu, Peijia; Li, Bowen; Yang, Yan; Shi, Ya Bei; Zhao, Liangwei

doi:10.1016/j.ijepes.2017.10.028

Cited by 11 publications

(2 citation statements)

References 21 publications

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“…In [11], differential games are applied in power systems to solve the problem of coordination between primary and secondary frequency control. In [12], linear quadratic differential games theory is applied in the load frequency control (LFC) of an islanded microgrid system.…”

Section: Introductionmentioning

confidence: 99%

Load-Frequency Control of Multi-Area Power System Based on the Improved Weighted Fruit Fly Optimization Algorithm

Wang

Zhang

et al. 2020

Energies

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With the development and application of large-scale renewable energy sources, the electric power grid is becoming huge and complicated; one of the most concerning problems is how to ensure coordination between a large number of varied controllers. Differential games theory is used to solve the problem of collaborative control. However, it is difficult to solve the differential game problem with constraints by using conventional algorithm. Furthermore, simulation models established by existing research are almost linear, which is not conducive to practical engineering application. To solve the above problem, we propose a co-evolutionary algorithm based on the improved weighted fruit fly optimization algorithm (IWFOA) to solve a multi-area frequency collaborative control model with non-linear constraints. Simulation results show that the control strategy can achieve system control targets, and fully utilize the various characteristics of each generator to balance the interests of different areas. Compared with a co-evolutionary genetic algorithm and a collaborative multi-objective particle swarm optimization algorithm, the co-evolutionary algorithm based on the IWFOA has a better suppression effect on the frequency deviation and tie-line power deviation caused by the disturbance and has a shorter adjustment time.

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Section: Introductionmentioning

confidence: 99%

Load-Frequency Control of Multi-Area Power System Based on the Improved Weighted Fruit Fly Optimization Algorithm

Wang

Zhang

et al. 2020

Energies

Self Cite

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“…A virtual droop control method, as proposed in [20], results in improved performance vis-à-vis the droop control methods, in different operating modes of microgrid in respect of maintaining both the frequency and voltage constant. Authors in [21] made use of the linear quadratic differential game theory for frequency regulation in an islanded microgrid having multiple DGs.…”

Section: Introductionmentioning

confidence: 99%

Frequency Regulation in AC Microgrid with and without Electric Vehicle Using Multiverse-Optimized Fractional Order- PID controller

Singh¹,

Suhag²

2019

IJCDS

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This paper presents the design and implementation of a novel control scheme for frequency regulation in an AC microgrid, subjected to varying operating conditions, using fractional order proportional integral derivative (FOPID) controller with its parameters optimized employing multi-verse optimizer (MVO) evolutionary algorithm. For the comparative analysis, proportional integral derivative (PID) and fractional order proportional integral (FOPI) controllers, both optimally tuned using MVO, are also implemented. Further, the impact of electric vehicle (EV) on system performance is analyzed. Integral of time multiplied absolute error (ITAE) is considered as the cost function in the optimization process whereas, the settling time and peak undershoot serve as the performance indices and a step change in load is taken as the perturbation. The proposed control scheme is tested for robustness against system parametric changes in the range of ± 25 besides random step load varying both in magnitude and time scale. The proposed MVO optimized FOPID controller outperforms other control schemes implemented in this work and proves to be very effective in frequency regulation in the AC microgrid comprising the renewable energy sources (RESs), diesel engine generator (DEG), and the energy storage systems (ESS). System Modeling and simulations are performed in MATLAB/Simulink.

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Non-cooperative games to control learned inverter dynamics of distributed energy resources

Serna-Torre,

Shenoy,

Schoenwald

et al. 2024

Electric Power Systems Research

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Coordination control of multiple micro sources in islanded microgrid based on differential games theory

Cited by 11 publications

References 21 publications

Load-Frequency Control of Multi-Area Power System Based on the Improved Weighted Fruit Fly Optimization Algorithm

Load-Frequency Control of Multi-Area Power System Based on the Improved Weighted Fruit Fly Optimization Algorithm

Frequency Regulation in AC Microgrid with and without Electric Vehicle Using Multiverse-Optimized Fractional Order- PID controller

Non-cooperative games to control learned inverter dynamics of distributed energy resources

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