An integrated multiple layer perceptron-genetic algorithm decision support system for photovoltaic power plant site selection

Malemnganbi, Rajkumari; Shimray, Benjamin A.

doi:10.11591/ijece.v12i2.pp1965-1972

Cited by 5 publications

(4 citation statements)

References 20 publications

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“…The unavailability of resources disturbs the efficiency of production, the optimization of the objectives must be implemented by a method of multi-objective optimization and which allows more flexibility for key decisions. We consider the problem of production and losses of 131 turbines over 3 zones, the objective function defines the goal to maximize the production while taking into account various constraints [4]: Max=(Production-Losses). In Figure 1, the wind trubines are represented by (i,j) coordinates system for better modelisation.…”

Section: Methods 21 Modeling the Problemmentioning

confidence: 99%

Optimization of the operations and maintenancefor wind farm using genetic algorithms

Mkhaitari,

Mir,

Zazoui

2023

IJEECS

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In Morocco, with the growing wind installed capacity it becomes crucial to perform further the O&M process, the wind assets are exposed to several constraints and raindom of maintenances for incidents. The target of this work is to optimize the gross and net production while simultaneously adhering to the minimum turbine unavailability and minimizing all contractual power curtailments due to unforeseeable factors. The proposed system is modeled using technical and mathematical formulas composed of the main function and the associated constraints. The project's modularization ends with a complex mathematical system that is non-linear, non-differentiable and requires the genetic algorithm for optimal resolution. Using Matlab to determine the optimized solution that represents the number of operational turbines per day, allowing for maximum production, minimizing curtailment, and reducing the unavailability of turbines. The 365-vector containing the numbers of turbines per day will opimally define the long-term O&M strategy.

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Section: Methods 21 Modeling the Problemmentioning

confidence: 99%

Optimization of the operations and maintenancefor wind farm using genetic algorithms

Mkhaitari,

Mir,

Zazoui

2023

IJEECS

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“…Ultimately, they used the three life cycle stages to examine solar power, demonstrating an increase in the profitability of the renewable energy cycle. Malemnganbi and Shimray [27] conducted a study on selecting optimal solar power plant (SPP) sites. The article presents a detailed analysis of the optimal ranking of SPP sites using the analytical hierarchy process (AHP) of MCDM, a multiple-layer perceptron neural network trained with the backpropagation (MLP-BP) algorithm, and a genetic algorithm (MLP-GA).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The literature mentioned above [23][24][25][26][27] shows that the primary focus of building SPPS is site selection, with particular consideration for factors such as sunshine duration and energy quality. This is the pursuit of maximizing clean energy output.…”

Section: Literature Reviewmentioning

confidence: 99%

The Road to Sustainable Logistics: Using the Fuzzy Nonlinear Multi-Objective Optimization Model to Build Photovoltaic Stations in Taiwan’s Logistics Centers

Wang,

Chiang,

Pan

et al. 2023

Sustainability

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In Taiwan, numerous company logistics centers have embraced installing solar photovoltaic power stations (SPPSs) on their rooftops. The primary objective of this study is to expedite the generation of green electricity for sale, bolstering the logistics center’s income and enhancing its environmental, social, and governance (ESG) profile. How can we secure solar photovoltaic power station (SPPS) projects with expedited construction timelines, reduced investment costs, and heightened quality aligned with the long-term ESG objectives? The study applies the critical path method (CPM) to determine the item’s path. Next, the mothed leverages Zimmermann’s mathematical models for nonlinear multi-objectives and Yager’s fuzzy sets to enhance project efficiency, minimizing completion time and cost while maximizing the quality ratio. Subsequently, the project uses Liou and Wang’s defuzzification values and incorporates Dong’s fuzzy to accelerate calculations. In this case, Project HP’s item J, the construction time is reduced from 24.3 to 3.2 days, ensuring that construction quality meets an 85% standard. Item J necessitates expanding the fuzzy cost interval (4549.90, 15,416.65, 26,283.41) (it refers to a scope of possible costs). It becomes evident that construction time plays a pivotal role in controlling costs. For Project HP’s item H, the unit time quality decision ranges from TWD 238,000 to 240,000, to turn into a cost interval of TWD 215,100, 239,000, and 262,900. Consequently, cost transformation transitions from an active to a more passive role, with quality and construction time becoming the driving components. This study uses a fuzzy nonlinear multi-objective model to guide the decision analysis of SPPSs within logistics centers. This strategy enables decision-makers to streamline logistics center operations, ensuring time, cost, and quality (TCQ) alignment during SPPS installation, thereby advancing ESG sustainability goals.

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“…The semi-empirical V-I equation is expressed by (2). The hard drive's composition is made up of two components: magnetite and carbon.…”

Section: Steinmetz Modelmentioning

confidence: 99%

Photovoltaic system DC series arc fault: a case study

Omran

Said

Hussin

et al. 2022

IJEECS

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<p>Photovoltaic (PV) systems are becoming increasingly popular; however, arc faults on the direct current (DC) side are becoming more widespread as a result of the effects of aging as well as the trend toward higher DC voltage levels, posing severe risk to human safety and system stability. The parallel arc faults present higher level of current as compared with the series arc faults, making it more difficult to spot the series arc. In this paper and for the aim of condition monitoring, the features of a DC series arc fault are analyzed by analysing the arc features, performing model’s simulation in PSCAD, and carrying out experimental studies. Various arc models are simulated and investigated; for low current arcs, the heuristic model is used where a set of parameters established. Moreover, the heuristic model’s simulated arc has been shown to be compatible with the experimental data. The features of arc noise in the electrode separation region and steady-arcing states with varied gap widths are investigated. It has been discovered that after an arc fault occurs, arc noise increases, notably in the frequency range below 50 kHz; where this property is useful for detecting DC series arc faults. Besides that, variations in air gap width are more sensitive to frequencies under 5 kHz.</p>

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An integrated multiple layer perceptron-genetic algorithm decision support system for photovoltaic power plant site selection

Cited by 5 publications

References 20 publications

Optimization of the operations and maintenancefor wind farm using genetic algorithms

Optimization of the operations and maintenancefor wind farm using genetic algorithms

The Road to Sustainable Logistics: Using the Fuzzy Nonlinear Multi-Objective Optimization Model to Build Photovoltaic Stations in Taiwan’s Logistics Centers

Photovoltaic system DC series arc fault: a case study

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