Monitoring and checking of performance in photovoltaic plants: A tool for design, installation and maintenance of grid-connected systems

Spertino, Filippo; Corona, Fabio

doi:10.1016/j.renene.2013.06.011

Cited by 54 publications

(25 citation statements)

References 14 publications

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“…Monitoring a PV system is a well-known and widespread practice around world [21][22][23][24][25][26][27][28][29][30][31][32]. Monitoring all operational parameters of a PV solar plant (e.g., DC-AC voltages, currents, power, solar radiation, etc.)…”

Section: Monitoring Of Pv Power Plant-method Results and Discussionmentioning

confidence: 99%

One-Year Monitoring PV Power Plant Installed on Rooftop of Mineirão Fifa World Cup/Olympics Football Stadium

et al. 2017

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This paper presents results of one-year monitoring of AC side electrical parameters and the characterization of local solar radiation at the biggest rooftop PV Power Plant, with an installed capacity of 1.42 MWp, mounted at Mineirão Football Stadium in Brazil. This stadium is one of the sport facilities that hosted 2014 FIFA World Cup and Rio 2016 Summer Olympics Games in the country. Results showed how it is important to study and characterize the solar resource in the region of interest, based on historic data, to provide the understanding of solar radiation and thus project PV power plants with better performance. Furthermore, AC electrical data show the behavior of active, reactive and apparent powers and the influence of the PV system on the power factor at the local grid utility connection point. Finally, PV power plant performance data (as annual final yield, performance ratio and capacity factor) are also presented and compared with data from PVsyst software simulations. The results over the monitoring period were good considering the specificities of the stadium.

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Section: Monitoring Of Pv Power Plant-method Results and Discussionmentioning

confidence: 99%

One-Year Monitoring PV Power Plant Installed on Rooftop of Mineirão Fifa World Cup/Olympics Football Stadium

et al. 2017

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“…By inserting the previous expression into Equation (8), the predictive values of active and reactive power can be obtained by the following predictive model:…”

Section: Of 26mentioning

confidence: 99%

Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm

Krama

Zellouma²,

Rabhi

et al. 2018

Energies

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This paper proposes a high performance control scheme for a double function grid-tied double-stage PV system. It is based on model predictive power control with space vector modulation. This strategy uses a discrete model of the system based on the time domain to generate the average voltage vector at each sampling period, with the aim of canceling the errors between the estimated active and reactive power values and their references. Also, it imposes a sinusoidal waveform of the current at the grid side, which allows active power filtering without a harmonic currents identification phase. The latter attempts to reduce the size and cost of the system as well as providing better performance. In addition, it can be implemented in a low-cost control platform due to its simplicity. A double-stage PV system is selected due to its flexibility in control, unlike single-stage strategies. Sliding mode control-based particle swarm optimization (PSO) is used to track the maximum power of the PV system. It offers high accuracy and good robustness. Concerning DC bus voltage of the inverter, the anti-windup PI controller is tuned offline using the particle swarm optimization algorithm to deliver optimal performance in DC bus voltage regulation. The overall system has been designed and validated in an experimental prototype; the obtained results in different phases demonstrate the higher performance and the better efficiency of the proposed system in terms of power quality enhancement and PV power injection.Energies 2018, 11, 3516 2 of 26 and in the center of a big city [6], because sunlight is available almost everywhere. Photovoltaic electricity can be produced as close as possible to its place of consumption in a decentralized way [7], directly to the user, which makes it accessible to a large part of the world's population.Much research and development are conducted about the critical elements of photovoltaic energy; starting with energy generation [6], conversion, then injection into the network [8], as well as energy management [9]. The key problem with photovoltaic energy generation is the difficulty of achieving the highest energy yield for PV panels. The voltage of a PV panel strongly depends on the connected load due to the non-linear behavior of the PV cell [10]. Therefore, various Maximum Power Point Tracking (MPPT) algorithms have been established to allow panels operate in optimal conditions, and thus, to track the maximum power point [6,11]. Among these algorithms are "Perturbation & Observation (P&O)" [12] and "incremental conductance (InCon)" [13] which are the most used due to the simplicity of their implementation. However, the abovementioned methods are constrained by the amplitude of the injected perturbations, which determines the importance of the oscillations around the Maximum power point (MPP) as well as the convergence time. To overcome this problem, several algorithms have been developed based on techniques derived from artificial intelligence such as Fuzzy Logic [14], Neural Network [15], Neuro-Fuz...

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“…Actually, mutual distances between meteorological station and PV plant higher than 5-10 km and/or the lack of the radiation data for the year under study can cause noticeable errors in the calculation of the performance ratio [13].…”

Section: B Identification Of the Irradiance Sensorsmentioning

confidence: 99%

A power and energy procedure in operating photovoltaic systems to quantify the losses according to the causes

et al. 2015

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Recently, after high feed-in tariffs in Italy, retroactive cuts in the energy payments have generated economic concern about several grid-connected photovoltaic (PV) systems with poor performance. In this paper the proposed procedure suggests some rules for determining the sources of losses and thus minimizing poor performance in the energy production. The on-site field inspection, the identification of the irradiance sensors, as close as possible the PV system, and the assessment of energy production are three preliminary steps which do not require experimental tests. The fourth step is to test the arrays of PV modules on-site. The fifth step is to test only the PV strings or single modules belonging to arrays with poor performance (e.g., I-V mismatch). The sixth step is to use the thermo-graphic camera and the electroluminescence at the PV-module level. The seventh step is to monitor the DC racks of each inverter or the individual inverter, if equipped with only one Maximum Power Point Tracker (MPPT). Experimental results on real PV systems show the effectiveness of this procedure.

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Monitoring and checking of performance in photovoltaic plants: A tool for design, installation and maintenance of grid-connected systems

Cited by 54 publications

References 14 publications

One-Year Monitoring PV Power Plant Installed on Rooftop of Mineirão Fifa World Cup/Olympics Football Stadium

One-Year Monitoring PV Power Plant Installed on Rooftop of Mineirão Fifa World Cup/Olympics Football Stadium

Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm

A power and energy procedure in operating photovoltaic systems to quantify the losses according to the causes

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