Multistage Bounded Evolutionary Algorithm to Optimize the Design of Sustainable Photovoltaic (PV) Pumping Irrigation Systems with Storage

Monís, Julián Ignacio; López-Luque, R.; Reca, Juan; Martínez, J.A.

doi:10.3390/su12031026

Cited by 15 publications

(9 citation statements)

References 34 publications

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“…The deficit water required for irrigation during peak months can be compensated through irrigation scheduling. The findings are in agreement with those achieved by Rafael and Reca (2020). The hydraulic energy requirement for different pumping configurations shown in Table 6 were used to obtain the technical parameter for the complete pumping system as indicated in Table 7.…”

Section: Hydraulic Power Requirement For Communal Pumping System Conf...supporting

confidence: 83%

“…The prerequisite is to minimize system failure during the entire irrigation season. The approach is evaluated according to the pump use efficiency and energy use efficiency (Rafael and Reca, 2020).…”

Section: Technical Optimization Approachmentioning

confidence: 99%

“…Whereas, the energy use efficiency (EUE), is the fraction of the maximum energy potentially generated by the PV system that is effectively used. The higher the value of EUE, the more efficient use of solar energy generated (Rafael and Reca, 2020).…”

Section: Technical Optimization Approachmentioning

confidence: 99%

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Design optimization of communal solar powered irrigation system

Isaac¹,

Wanyama²

2023

Afr. J. Agric. Res.

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Communal solar-powered irrigation systems (SPIS) have the potential for sharing the upfront costs hence encouraging farmers to adopt irrigation. Conventional methods of sizing photovoltaic water pumping (PVWP) system for irrigation consider the hydraulic energy requirement by the pump and PV generator capacity separately from the available water source capacity. As a result, the potential of the technology is not optimized, leading to over or under-sizing of the system. Consequently, there is a negative impact on acquisition cost and system performance. The study aimed to determine the optimal PVWP system configuration for communal irrigation. A comparative techno-economic and environmental performance assessment was conducted on different pumping system configurations and a multi-criteria decision analysis approach was used to select the optimal configuration. The findings show a PVWP system with storage tank as the optimal configuration for the communal irrigation. Although the initial capital cost for standalone PVWP system configurations is almost two times that of the conventional diesel pumping systems (CPS), its operation and maintenance (O&M) and lifecycle cost are respectively three times and about four times lower than the CPS cost. Furthermore, the PVWP system for communal irrigation is feasible for irrigation projects that exceed 3 years due to their high acquisition costs. Therefore, promotion of solar-powered irrigation should also focus on the communal approach as a way of improving technology adoption and upscaling.

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Section: Hydraulic Power Requirement For Communal Pumping System Conf...supporting

confidence: 83%

Section: Technical Optimization Approachmentioning

confidence: 99%

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Design optimization of communal solar powered irrigation system

Isaac¹,

Wanyama²

2023

Afr. J. Agric. Res.

View full text Add to dashboard Cite

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“…A review of the studies of systems with a water tank as storage is proposed in [35], which highlights the advantages of this configuration. A sizing methodology of a PV system with a water tank, based on genetic algorithms, is presented in [36]. The results for Spain show a higher influence of the PV generator rated power and the pump type, while the influence of the pipe system's parameters and the water tank capacity is lower.…”

Section: Systems With One Renewable Generator For Irrigationmentioning

confidence: 99%

Multivariate Analysis of a Wind–PV-Based Water Pumping Hybrid System for Irrigation Purposes

et al. 2021

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The Green Deal and increased nutritional needs are driving factors in human activities nowadays. Agriculture is an essential economic sector that can profit from the application of renewable energy sources by the assimilation of off-grid, arid and barren terrains. Power supplied by hybrid systems for water pumping is a solution for overcoming the stochastic character of the renewable energy sources. This paper presents a sizing methodology for a hybrid system with wind and PV generation and water tank storage, based on the consideration of the entire energy conversion chain with energy models and a one-year operation simulation. The PV generator is modeled using a reduced Durisch’s model, while for the wind generator a piecewise interpolation is used. The methodology is applied for sites in Bulgaria with specific agricultural crops and meteorological data. Combinations of PV (different technologies) and wind (different types) generators and water tank capacities are considered and discussed. The combinations are compared on the basis of three criteria: the investment cost, the satisfaction of crop requirements and system oversizing. The possibility for the introduction of battery storage is also examined. The results show some trends in the hybrid system sizing and the possibility to apply the proposed methodology for various sites, generators and crops.

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“…If we focus on fuzzy logic approach, it has been used with meteorological parameters [14] and for short-term energy forecasting [15]. Finally, we can find genetic algorithms used in order to achieve the self-sustainability of a pump [16] and finally, the use of artificial neural networks (ANN).…”

Section: Related Workmentioning

confidence: 99%

Solar Energy Prediction Model Based on Artificial Neural Networks and Open Data

et al. 2020

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With climate change driving an increasingly stronger influence over governments and municipalities, sustainable development, and renewable energy are gaining traction across the globe. This is reflected within the EU 2030 agenda, that envisions a future where there is universal access to affordable, reliable and sustainable energy. One of the challenges to achieve this vision lies on the low reliability of certain renewable sources. While both particulars and public entities try to reach self-sufficiency through sustainable energy generation, it is unclear how much investment is needed to mitigate the unreliability introduced by natural factors such as varying wind speed and daylight across the year. In this sense, a tool that aids predicting the energy output of sustainable sources across the year for a particular location can aid greatly in making sustainable energy investments more efficient. In this paper, we make use of Open Data sources, Internet of Things (IoT) sensors and installations distributed across Europe to create such tool through the application of Artificial Neural Networks. We analyze how the different factors affect the prediction of energy production and how Open Data can be used to predict the expected output of sustainable sources. As a result, we facilitate users the necessary information to decide how much they wish to invest according to the desired energy output for their particular location. Compared to state-of-the-art proposals, our solution provides an abstraction layer focused on energy production, rather that radiation data, and can be trained and tailored for different locations using Open Data. Finally, our tests show that our proposal improves the accuracy of the forecasting, obtaining a lower mean squared error (MSE) of 0.040 compared to an MSE 0.055 from other proposals in the literature.

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Multistage Bounded Evolutionary Algorithm to Optimize the Design of Sustainable Photovoltaic (PV) Pumping Irrigation Systems with Storage

Cited by 15 publications

References 34 publications

Design optimization of communal solar powered irrigation system

Design optimization of communal solar powered irrigation system

Multivariate Analysis of a Wind–PV-Based Water Pumping Hybrid System for Irrigation Purposes

Solar Energy Prediction Model Based on Artificial Neural Networks and Open Data

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