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  • Open Access

    ARTICLE

    Analysis and Modeling of Time Output Characteristics for Distributed Photovoltaic and Energy Storage

    Kaicheng Liu1,3,*, Chen Liang2, Xiaoyang Dong2, Liping Liu1

    Energy Engineering, Vol.121, No.4, pp. 933-949, 2024, DOI:10.32604/ee.2023.043658

    Abstract Due to the unpredictable output characteristics of distributed photovoltaics, their integration into the grid can lead to voltage fluctuations within the regional power grid. Therefore, the development of spatial-temporal coordination and optimization control methods for distributed photovoltaics and energy storage systems is of utmost importance in various scenarios. This paper approaches the issue from the perspective of spatiotemporal forecasting of distributed photovoltaic (PV) generation and proposes a Temporal Convolutional-Long Short-Term Memory prediction model that combines Temporal Convolutional Networks (TCN) and Long Short-Term Memory (LSTM). To begin with, an analysis of the spatiotemporal distribution patterns of PV generation is conducted, and… More >

  • Open Access

    ARTICLE

    Research on the MPPT of Photovoltaic Power Generation Based on Improved WOA and P&O under Partial Shading Conditions

    Jian Zhong, Lei Zhang*, Ling Qin

    Energy Engineering, Vol.121, No.4, pp. 951-971, 2024, DOI:10.32604/ee.2023.041433

    Abstract Partial shading conditions (PSCs) caused by uneven illumination become one of the most common problems in photovoltaic (PV) systems, which can make the PV power-voltage (P-V) characteristics curve show multi-peaks. Traditional maximum power point tracking (MPPT) methods have shortcomings in tracking to the global maximum power point (GMPP), resulting in a dramatic decrease in output power. In order to solve the above problems, intelligent algorithms are used in MPPT. However, the existing intelligent algorithms have some disadvantages, such as slow convergence speed and large search oscillation. Therefore, an improved whale algorithm (IWOA) combined with the P&O (IWOA-P&O) is proposed for… More >

  • Open Access

    ARTICLE

    Short-Term Prediction of Photovoltaic Power Generation Based on LMD Permutation Entropy and Singular Spectrum Analysis

    Wenchao Ma*

    Energy Engineering, Vol.120, No.7, pp. 1685-1699, 2023, DOI:10.32604/ee.2023.025404

    Abstract The power output state of photovoltaic power generation is affected by the earth's rotation and solar radiation intensity. On the one hand, its output sequence has daily periodicity; on the other hand, it has discrete randomness. With the development of new energy economy, the proportion of photovoltaic energy increased accordingly. In order to solve the problem of improving the energy conversion efficiency in the grid-connected optical network and ensure the stability of photovoltaic power generation, this paper proposes the short-term prediction of photovoltaic power generation based on the improved multi-scale permutation entropy, local mean decomposition and singular spectrum analysis algorithm.… More >

  • Open Access

    ARTICLE

    Research on the MPPT of Photovoltaic Power Generation Based on the CSA-INC Algorithm

    Tao Hou1, Shan Wang1,2,*

    Energy Engineering, Vol.120, No.1, pp. 87-106, 2023, DOI:10.32604/ee.2022.022122

    Abstract The existing Maximum Power Point Tracking (MPPT) method has low tracking efficiency and poor stability. It is easy to fall into the Local Maximum Power Point (LMPP) in Partial Shading Condition (PSC), resulting in the degradation of output power quality and efficiency. It was found that various bio-inspired MPPT based optimization algorithms employ different mechanisms, and their performance in tracking the Global Maximum Power Point (GMPP) varies. Thus, a Cuckoo search algorithm (CSA) combined with the Incremental conductance Algorithm (INC) is proposed (CSA-INC) is put forward for the MPPT method of photovoltaic power generation. The method can improve the tracking… More > Graphic Abstract

    Research on the MPPT of Photovoltaic Power Generation Based on the CSA-INC Algorithm

  • Open Access

    ARTICLE

    Dust Deposition’s Effect on Solar Photovoltaic Module Performance: An Experimental Study in India’s Tropical Region

    K. R. Chairma Lakshmi*, Geetha Ramadas

    Journal of Renewable Materials, Vol.10, No.8, pp. 2133-2153, 2022, DOI:10.32604/jrm.2022.019649

    Abstract A solar PV panel works with maximum efficiency only when it is operated around its optimum operating point or maximum power point. Unfortunately, the performance of the solar cell is affected by several factors like sun direction, solar irradiance, dust accumulation, module temperature, as well as the load on the system. Dust deposition is one of the most prominent factors that influence the performance of solar panels. Because the solar panel is exposed to the atmosphere, dust will accumulate on its surface, reducing the quantity of sunlight reaching the solar cell and diminishing output. In the proposed work, a detailed… More >

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