Multi-objective optimal scheduling of power system considering the coordinated operation of photovoltaic-wind-pumped storage hybrid power

Ma, Rui; Li, Xuan; Wu, Zhaoyu; Zhang, Qiang

doi:10.1109/drpt.2015.7432316

Cited by 6 publications

(2 citation statements)

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Section: Introductionmentioning

confidence: 99%

“…So the originality of work is that we propose a hybrid pumping system composed of these two sources of energy with storage about battery, which consists in the optimal exploitation of the coupling between them, our system is completely different from the structures adopted in literature. [8][9][10][11][12][13][14][15][16][17] The frame mainly studied is water pumping. Of course, from the point of view of renewable energy sources and the control of water optimization, the results appear quite convincing and interesting, but this does not exclude the fact that the combination of the two sources generates a pretty complex system.…”

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confidence: 99%

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Bond graph modelling and control enhancement of an off‐grid hybrid pumping system by frequency optimization

Mezghani

Mami

Dauphin-Tanguy

2020

Int J Numerical Modelling

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The climate's dependence requires a complex modelling and other optimization methods for the control of the hybrid system. Moreover, recently, and as for both the technological progression of the hardware and software, researchers may more and more optimize problems through the use of enabled platforms. The paper aims to discuss this issue. Our hybrid pumping installation contains a photovoltaic generator, a wind source, converters, and an induction motor‐pump group; it has a hybrid and complex character and requires a good modelling of the energetic point of view before passing the phase of design of control laws. So we use the graphical approach of modelling called dedicated graph for this type of system, and this tool showed very interesting results in the level of modelling, dimensioning, monitoring, and diagnosing. The numerical closed‐loop simulation of the complete model in an appropriate environment allows us to generate an optimization control in which the appropriate frequency depends on meteorological conditions. The simulations are made from the climatic conditions measured in a real system using a microcontroller ARDUINO board. These measurements are used to simulate the adopted control and to judge on the feasibility of our architecture adopted.

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Section: Introductionmentioning

confidence: 99%