2022
DOI: 10.3389/fenrg.2022.762931
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Energy Efficient Photovoltaic-Electric Spring for Real and Reactive Power Control in Demand-Side Management

Abstract: Photovoltaic-electric spring (PV-ES) is a promising topology to utilize widespread residential roof-top photovoltaic systems in demand-side management. Power control for an integrated configuration of photovoltaic-electric spring system to achieve dynamic supply-demand balance in power distribution networks is presented. Extraction of maximum power from PV panel using Perturb and Observe algorithm along with boost converter are designed. This power is given as input to the DC link of the Electric Spring. The m… Show more

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Cited by 2 publications
(2 citation statements)
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“…Alternatively, in LV systems with RESs, ESs were coupled in series with nonessential loads to deliver V stabilization via essential loads [77]. In addition, ESs reduce the need for communication tools in DCM [77,79,80]. The configuration created by the ES and the nonessential load is usually denoted as a smart load (SL) [81][82][83].…”
Section: Difficulties With Pq In 1ø-µgsmentioning
confidence: 99%
“…Alternatively, in LV systems with RESs, ESs were coupled in series with nonessential loads to deliver V stabilization via essential loads [77]. In addition, ESs reduce the need for communication tools in DCM [77,79,80]. The configuration created by the ES and the nonessential load is usually denoted as a smart load (SL) [81][82][83].…”
Section: Difficulties With Pq In 1ø-µgsmentioning
confidence: 99%
“…Machine learning methods, such as deep neural networks, can effectively extract high-dimensional complex nonlinear features and directly map them to the output, making them a commonly used method for PV power prediction Kollipara et al (2022); Voyant et al (2017). Deep neural networks include models such as convolutional neural networks (CNN), deep belief networks (DBN), superposition denoising autoencoders (SDAE), and longterm memory (LSTM).…”
Section: Introductionmentioning
confidence: 99%