Photovoltaic parameter estimation using Grey Wolf Optimization

Darmansyah,; Robandi, Imam

doi:10.1109/iccar.2017.7942766

“…For instance, BESS facilitates peak shifting and load levelling to support the system during peak demand periods and maintain the power quality of the system [17]. The study in [18] confirmed that fuel consumption in MG could be reduced by up to 75% if the ESS is combined with renewable energy sources. Numerous storage technologies and their potential applications is comprehensively presented in [19][20][21].…”

Section: Introductionmentioning

confidence: 79%

Techno-Economic Assessment and Operational Planning of Wind-Battery Distributed Renewable Generation System

Salman

¹

,

Khan

²

,

Al–Ismail

³

et al. 2021

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Electrical energy and power demand will experience exponential increase with the rise of the global population. Power demand is predictable and can be estimated based on population and available historical data. However, renewable energy sources (RES) are intermittent, unpredictable, and environment-dependent. Interestingly, microgrids are becoming smarter but require adequate and an appropriate energy storage system (ESS) to support their smooth and optimal operation. The deep discharge caused by the charging–discharging operation of the ESS affects its state of health, depth of discharge (DOD), and life cycle, and inadvertently reduces its lifetime. Additionally, these parameters of the ESS are directly affected by the varying demand and intermittency of RES. This study presents an assessment of battery energy storage in wind-penetrated microgrids considering the DOD of the ESS. The study investigates two scenarios: a standalone microgrid, and a grid-connected microgrid. The problem is formulated based on the operation cost of the microgrid considering the DOD and the lifetime of the battery. The optimization problem is solved using non-linear programming. The scheduled operation cost of the microgrid, the daily scheduling cost of ESS, the power dispatch by distributed generators, and the DOD of the battery storage at any point in time are reported. Performance analysis showed that a power loss probability of less than 10% is achievable in all scenarios, demonstrating the effectiveness of the study.

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“…This paper explain MPPT using GWO and QZSI for the AC loads. The GWO technique inspired by hunting mechanism of grey wolves and their leadership hierarchy in nature [14]- [16]. GWO algorithm has three main steps of hunting process: tracking, pursuing and attacking.…”

Section: Mppt Design Using Grey Wolf Techniquementioning

confidence: 99%

Quasi Z-Source Inverter as MPPT on Renewable Energy using Grey Wolf Technique

Sias¹,

Fadlika²,

Wahyono³

et al. 2019

EECSI

0

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Z-Source Inverter (ZSI) is famous power converter who has capability to deal with voltage sags, improved power factor and wide voltage range of output. Quasi Z Source Inverter (QZSI) is the modern ZSI who has continuous current of input and can reduce stress of the passive component. This paper proposes simple boost QZSI circuit as Maximum Power Point Tracking (MPPT) using Grey Wolf Optimization (GWO) algorithm in photovoltaic system. Grey Wolf algorithm has been compared with the Perturb and Observed (P&O) technique for gaining the maximum power from the sun. Both techniques can get the optimum power of solar panel not only at constant sun light condition but also under varying irradiance levels. The value of average power obtained from GWO technique is greater than P&O. Although the value of solar radiation changes, the output voltage remains stable and both algorithms carry on obtaining optimal power of the sun.

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“…Grey Wolf algorithm, optimizer published on 2014, has good competitive results compared to the other algorithms for solving 29 benchmarked test functions [15]. It can also be used to solve the real problem such as in PV modeling because of the limited information from the manufacturer datasheet [16]. GWO can also be used as MPPT compared to Improved-PSO (IPSO) method in DC system [14].…”

Section: Mppt Design Using Grey Wolf Techniquementioning

confidence: 99%

Quasi Z-Source Inverter as MPPT on Renewable Energy using Grey Wolf Technique

Sias¹,

Fadlika²,

Wahyono³

et al. 2019

EECSI

0

View full text Add to dashboard Cite

Z-Source Inverter (ZSI) is famous power converter who has capability to deal with voltage sags, improved power factor and wide voltage range of output. Quasi Z Source Inverter (QZSI) is the modern ZSI who has continuous current of input and can reduce stress of the passive component. This paper proposes simple boost QZSI circuit as Maximum Power Point Tracking (MPPT) using Grey Wolf Optimization (GWO) algorithm in photovoltaic system. Grey Wolf algorithm has been compared with the Perturb and Observed (P&O) technique for gaining the maximum power from the sun. Both techniques can get the optimum power of solar panel not only at constant sun light condition but also under varying irradiance levels. The value of average power obtained from GWO technique is greater than P&O. Although the value of solar radiation changes, the output voltage remains stable and both algorithms carry on obtaining optimal power of the sun.

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Photovoltaic parameter estimation using Grey Wolf Optimization

Cited by 18 publications

References 6 publications

Techno-Economic Assessment and Operational Planning of Wind-Battery Distributed Renewable Generation System

Techno-Economic Assessment and Operational Planning of Wind-Battery Distributed Renewable Generation System

Quasi Z-Source Inverter as MPPT on Renewable Energy using Grey Wolf Technique

Quasi Z-Source Inverter as MPPT on Renewable Energy using Grey Wolf Technique

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