Improving Solar Power PV Plants Using Multivariate Design Optimization

Arefifar, Seyed Ali; Paz, Francisco; Ordonez, Martin

doi:10.1109/jestpe.2017.2670500

Cited by 45 publications

(24 citation statements)

References 23 publications

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“…In the planning of a photovoltaic power plant the electric power produced is strongly linked to the meteorological conditions (solar radiation and temperature) [13,14]. Due to the intermittent nature of solar energy, power forecasting is crucial for a correct interpretation of business profitability and payback time [15]. In the current market there is a great offer of manufacturers that, of course, have quite different technological production processes.…”

Section: Introductionmentioning

confidence: 99%

Simulation and Comparison of Mathematical Models of PV Cells with Growing Levels of Complexity

Rodrigues¹,

Godina

Marzband

et al. 2018

Energies

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The amount of energy generated from a photovoltaic installation depends mainly on two factors—the temperature and solar irradiance. Numerous maximum power point tracking (MPPT) techniques have been developed for photovoltaic systems. The challenge is what method to employ in order to obtain optimum operating points (voltage and current) automatically at the maximum photovoltaic output power in most conditions. This paper is focused on the structural analysis of mathematical models of PV cells with growing levels of complexity. The main objective is to simulate and compare the characteristic current-voltage (I-V) and power-voltage (P-V) curves of equivalent circuits of the ideal PV cell model and, with one and with two diodes, that is, equivalent circuits with five and seven parameters. The contribution of each parameter is analyzed in the particular context of a given model and then generalized through comparison to a more complex model. In this study the numerical simulation of the models is used intensively and extensively. The approach utilized to model the equivalent circuits permits an adequate simulation of the photovoltaic array systems by considering the compromise between the complexity and accuracy. By utilizing the Newton–Raphson method the studied models are then employed through the use of Matlab/Simulink. Finally, this study concludes with an analysis and comparison of the evolution of maximum power observed in the models.

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Section: Introductionmentioning

confidence: 99%

Simulation and Comparison of Mathematical Models of PV Cells with Growing Levels of Complexity

Rodrigues¹,

Godina

Marzband

et al. 2018

Energies

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“…As PV integration and PV power plants are becoming more popular, PV systems need to comply with more grid regulation standards, codes, and operational conditions [56]. Meeting grid standards requires special considerations in the design of PV systems as in [57]. Many times PV systems are oversized to meet load demand better and counteract the effects of low insolation, high temperature, pollution, and age degradation on the system [58].…”

Section: Discussionmentioning

confidence: 99%

An Adaptive Model Predictive Controller for Current Sensorless MPPT in PV Systems

Metry

Balog

2020

IEEE Open J. Power Electron.

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Finite control set model predictive control (MPC) is a model-based control method that can include multi-objective optimization, constrained control, adaptive control, and online auto-tuning of weighting factors all in a single controller that exhibits fast dynamic tracking. This paper utilizes the model-based framework of MPC to develop a sensorless current maximum power point tracking (MPPT) algorithm. Eliminating the current sensor can reduce the cost and improve the reliability of the photovoltaic system. This paper also utilizes constrained control and online auto-tuning of MPC to develop an adaptive perturbation MPPT to reduce steady-state oscillation and improve dynamic performance. This paper builds in a single framework the different layers of the MPPT problem: control, estimation, and MPPT. The proposed adaptive perturbation sensorless current mode MPPT (ASC-MPPT) technique performance is compared to the well-known incremental conductance (InCon) MPPT technique. The EN50530 European industrial test standards were used to demonstrate performance.

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“…The expression for determining the required ASPP battery capacity can be easily generalized for any number of changes in the steps of the load graph. 4. The method for calculating ASPP capacity allows excluding the unjustified overestimation of the power plant component capacities and the increase in ASPP cost.…”

Section: Discussionmentioning

confidence: 99%

“…Today, the electric energy production by solar power plants is used almost world-wide with a constant increase in solar cell application [1][2][3][4]. This is facilitated by many factors, and the main of them is the use of alternative (renewable) energy sources which have recently become increasingly important as well as a total absence of any moving parts, due to which their lifespan may be practically unlimited.…”

Section: Introductionmentioning

confidence: 99%

Method for Calculating the Capacity of Solar Power Plants and its Implementation in LabVIEW Environment

et al. 2019

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The paper presents the method for calculating the capacity of an autonomous solar power plant and its components. This method allows considering a load variation during the day as well as specifying the required capacity of the battery and excluding an unjustified overestimation of the power plant component capacities along with the increase in efficiency of the autonomous solar power plant. Formula for determining the required battery capacity of an autonomous solar power plant could be easily generalized for any number of changes in the load schedule steps. Virtual instruments (calculators) for calculating the capacity of an autonomous solar power plant and its components have been developed on the basis of this method in LabVIEW environment. These calculators may have a rather high visibility, ease of use and low memory requirements along with less computing time spent on calculations. The first calculator may allow recalculating capacities of loads on the power plant main supply bus as well as determining the energy consumption of loads per day. The second calculator may be used for determining the required capacity and number of batteries as well as the capacity of the charger, inverters, main supply bus and solar modules along with the solar power plant efficiency.

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Improving Solar Power PV Plants Using Multivariate Design Optimization

Cited by 45 publications

References 23 publications

Simulation and Comparison of Mathematical Models of PV Cells with Growing Levels of Complexity

Simulation and Comparison of Mathematical Models of PV Cells with Growing Levels of Complexity

An Adaptive Model Predictive Controller for Current Sensorless MPPT in PV Systems

Method for Calculating the Capacity of Solar Power Plants and its Implementation in LabVIEW Environment

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