Comprehensive overview of meta-heuristic algorithm applications on PV cell parameter identification

Yang, Bo; Wang, Jingbo; Zhang, Xiaoshun; Yu, Tao; Yao, Wei; Shu, Hongchun; Zeng, Fang; Sun, Liming

doi:10.1016/j.enconman.2020.112595

Cited by 260 publications

(100 citation statements)

References 147 publications

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“…With the rapid development and wide application of renewable energy [1], new materials [2], and advanced power electronics [3], requirements for higher power supply quality, reliability, and operation efficiency are ever-increasing in the past decade. High voltage direct current (HVDC) transmission technology owns elegant merits of flexible operation [4], fast power regulation [5], high reliability [6], and improved system transient stability [7]. It has achieved wide application in long-distance power transmission [8], asynchronous interconnection [9], and submarine power transmission [10].…”

Section: Introductionmentioning

confidence: 99%

Optimal coordinated control of hybrid AC/VSC-HVDC system integrated with DFIG via cooperative beetle antennae search algorithm

Jiang¹,

Huang²,

Zhang³

et al. 2020

PLoS ONE

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Nowadays, with the significant integration of various renewable energy, hybrid alternating current/ voltage source converter based high voltage direct current (AC/VSC-HVDC) system integrated with doubly-fed induction generator (DFIG) has achieved rapidly development in smart grid. A proper control system design for hybrid AC/VSC-HVDC system plays a very crucial role for a reliable and effective power transmission. Hence, this paper designs a novel cooperative beetle antenna search (CBAS) algorithm for optimal coordinated control of hybrid AC/VSC-HVDC system integrated with DFIG. Compared with original beetle antennae search (BAS) algorithm, CBAS algorithm can significantly improve searching efficiency via an efficient cooperation with a group of multiple beetles instead of a single beetle. Particularly, CBAS algorithm can effectively escape from local optimums thanks to its dynamic balance mechanism, which can maintain appropriate trade-off between global exploration and local exploitation. Moreover, three case studies are undertaken to validate the effectiveness and superiorities and effectiveness of CBAS algorithm compared against that of other traditional meta-heuristic algorithms. Especially, the average results of fitness function acquired by CBAS algorithm is merely 46.05%, 41.18%, and 47.82% of that of PSO, GA, and BAS algorithm, respectively.

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Section: Introductionmentioning

confidence: 99%

Optimal coordinated control of hybrid AC/VSC-HVDC system integrated with DFIG via cooperative beetle antennae search algorithm

Jiang¹,

Huang²,

Zhang³

et al. 2020

PLoS ONE

Self Cite

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“…This model not only considers the power deficiency of the power grid, the ramp rate constraint for units [11], the frequency quality constraint [12] that need to be considered in regular AGC systems, but also unit generation cost [13] and the security constraint of regular optimal power flow models that need to be considered in economical scheduling [14]. The model adopts the power flow formula that considers static characteristics to represent the relationship between power/frequency change [15] and the power flow as well as security constraint [16][17].…”

Section: Figure 2 Diagram Of Sectional Agc Dispatch Systemmentioning

confidence: 99%

Multi-Agent Deep Reinforcement Learning for Sectional AGC Dispatch

Zhu

et al. 2020

IEEE Access

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Aiming at the problem of coordinating system economy, security and control performance in secondary frequency regulation of the power grid, a sectional automatic generation control (AGC) dispatch framework is proposed. The dispatch of AGC is classified as three sections with the sectional dispatch method. Besides, a hierarchical multi-agent deep deterministic policy gradient (HMA-DDPG) algorithm is proposed for the framework in this paper. This algorithm, considering economy and security of the system in AGC dispatch, can ensure the control performance of AGC. Furthermore, through simulation, the control effect of the sectional dispatch method and several AGC dispatch methods on the Guangdong province power grid system and the IEEE 39 bus system is compared. The result shows that the best effect can be achieved with the sectional dispatch method. INDEX TERMS automatic generation control; hierarchical multi-agent deep deterministic policy gradient; sectional AGC dispatch; reinforcement learning.

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“…Improved ant lion optimization algorithm augmented with particle swarm optimization [17], and modified GSA [18] were also proposed for parameter identification of hydraulic turbine governing systems. Various optimization algorithms have been introduced and implemented to identify the photovoltaic (PV) parameters [19]- [24]. To name a few, modified cat swarm optimization algorithm [22], improved JAYA optimization algorithm [23], and flexible particle swarm optimization algorithm with an elimination phase [20] for parameters estimation of one-diode and two-diode PV models, as well as sunflower optimization for three-diode PV model [24].…”

Section: Introductionmentioning

confidence: 99%

Enhanced Fractional Chaotic Whale Optimization Algorithm for Parameter Identification of Isolated Wind-Diesel Power Systems

2020

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Parameters identification of isolated wind-diesel power systems (WDPS) is a significant issue in stability analysis of the power system as well as guaranteeing the power generation through the control system. In this paper, enhanced whale optimization algorithms (EWOA) are proposed to deal with the parameter identification problem of a WDPS system. The proposed EWOA effectively tackles the premature convergence problem of WOA by splitting the population into two subpopulations and updating the position of each whale according to the position of the best agent in its current subpopulation, the position of the other subpopulation's best agent, and the position of the best neighboring agent. Furthermore, fractional chaotic maps are embedded in the search process of EWOA to increase its performance in terms of accuracy. For validation purposes, the proposed algorithms are applied to identify the unknown parameters of WDPS, where different statistical analyzes and comparisons are carried out with other recent state-of-the-art algorithms. Simulation results confirm that the algorithms have less deviation in parameter estimation, more convergence speed, and higher precision in comparison with other algorithms. INDEX TERMS Optimization, parameter identification, whale optimization algorithm, wind-diesel power system.

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Comprehensive overview of meta-heuristic algorithm applications on PV cell parameter identification

Cited by 260 publications

References 147 publications

Optimal coordinated control of hybrid AC/VSC-HVDC system integrated with DFIG via cooperative beetle antennae search algorithm

Optimal coordinated control of hybrid AC/VSC-HVDC system integrated with DFIG via cooperative beetle antennae search algorithm

Multi-Agent Deep Reinforcement Learning for Sectional AGC Dispatch

Enhanced Fractional Chaotic Whale Optimization Algorithm for Parameter Identification of Isolated Wind-Diesel Power Systems

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