An Innovative Model-Based Algorithm for Power Control Strategy of Photovoltaic Panels

Cristaldi, L.; Faifer, Marco; Laurano, Christian; Petkovski, Emil; Toscani, Sergio; Ottoboni, R.

doi:10.1109/i2mtc48687.2022.9806605

Cited by 5 publications

(3 citation statements)

References 16 publications

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Section: Rl-based Methodsmentioning

confidence: 99%

“…To prepare the best course of action and arrive at an optimal solution in particular situations, the operator must have access to the model [152]. However, due to the following drawbacks, it is incompatible with several very complicated applications, including power management [153]: The complexity and difficulty of creating an environment model. Due to the sensitive nature of the solution, a model error is almost unavoidable. An anticipated decrease in computational efficiency when a basic application is used with a highly complex model. …”

Section: Energy Management Strategies For Hevsmentioning

confidence: 99%

See 1 more Smart Citation

Energy management strategies of hybrid electric vehicles: A comparative review

Azim Mohseni,

Bayati,

Ebel

2023

IET Smart Grid

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With increasing environmental problems, including air pollution, rising greenhouse gases and global warming, the need to use clean energy resources seems essential. Therefore, the usage of clean and renewable energy sources is suggested as a suitable solution to overcome the mentioned concerns. The transportation section contributes to a huge percentage of energy consumption. Hybrid electric vehicles (HEVs), by combining several energy resources, are considered as a crucial solution to decrease fossil fuel consumption and improve the environmental challenges. The existence of an alternative energy resource and the internal combustion engine together provides optimal power distribution among them to maximise power usage and minimise fuel consumption. Energy management strategy (EMS) is an essential challenge in HEV's design procedure to deal with the power distribution in multiple power source systems to improve the performance of the HEVs. A review of various EMSs for HEVs, followed by an analysis of each type, including its benefits and drawbacks, is presented by the authors. In addition to this, the major challenges in EMSs for HEVs are described and a comprehensive review is presented for strategies addressing these issues.

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Section: Rl-based Methodsmentioning

confidence: 99%

Section: Energy Management Strategies For Hevsmentioning

confidence: 99%

Energy management strategies of hybrid electric vehicles: A comparative review

Azim Mohseni,

Bayati,

Ebel

2023

IET Smart Grid

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“…This article is a technical extension of a previously published work, in which the MPP model was adapted to the tracking of a predefined RP [23]. The proposed MB strategy in this article enables working at RP as a percentage of the maximum available power, therefore maintaining accurate MPP estimation even while working at RP point (RPP).…”

Section: Introductionmentioning

confidence: 99%

Power Generation Control Algorithm for the Participation of Photovoltaic Panels in Network Stability

Cristaldi

Faifer

Laurano

et al. 2023

IEEE Trans. Instrum. Meas.

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The push for renewable energy and sustainable development has led to an ever-increasing integration of grid-tied photovoltaic (PV) systems. To maximize revenue, this resource generally operates in maximum power point trackers (MPPT) mode. However, to ensure grid stability and reliability, system operators will continue to introduce new requirements, eventually forcing PV plants to adhere to primary frequency regulation. To perform this task, PV plants will have to be capable of operating outside the MPP and varying their power production, to maintain an active power reserve, according to grid request. This article presents an innovative model-based (MB) tracking algorithm devoted to supporting power network regulation. Due to the updated formulation, the algorithm can vary the power curtailment according to a reduction factor given by the power system operators. Results show the remarkable performance and accuracy of the new algorithm, providing power regulation capability in the range 20%-100% of the maximum available power. Moreover, the impact of the employment of constant reduction coefficients on the algorithm performances has been evaluated. Validation has been performed based on the data collected over an observation interval of more than six months. Due to its flexibility, this could be the basis for the participation of PV systems to frequency regulation.

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