Dynamic mathematical model design of photovoltaic water pumping systems for horticultural crops irrigation: A guide to electrical energy potential assessment for increase access to electrical energy

Chilundo, Rosa Jacob; Maure, Genito; Mahanjane, Urânio Stefane

doi:10.1016/j.jclepro.2019.117878

Cited by 22 publications

(13 citation statements)

References 23 publications

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“…10 Over the last decades, several mathematical models have been developed aiming improvement of planning process, mainly to determining optimal operational, tactical and strategic planning in many sectors of the Horticultural, such a land preparation, planting, crop cultivation, irrigation and drainage, use of machinery, diseases control, harvesting, etc. [11][12][13][14] Currently, these mathematical applications have not been related only to the plants cultivation, they have been very wide, being applied throughout the horticultural supply chain. 15 including to internal structure (financial situation, production and management) and external structure (technological developments, potential of species and cultivars, market, economy and environmental condition) of the horticulture, besides attending the environmental issues through sustainable cultivation 16,17 and use of waste.…”

Section: Contribution Of Mathematical Model For the Horticulturementioning

confidence: 99%

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2020

HIJ

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Mathematical modelling is a relevant knowledge area that studies simulation of real systems in order to predict and understand its behavior. Simulations are developed from computational implementations of the mathematical description of the phenomena involved in the real system, i.e., from mathematical model. Mathematical models are extensively used in Engineering and science, such as Agriculture, Medicine, Physics, Chemistry, Biology, Economics, and others.

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Section: Contribution Of Mathematical Model For the Horticulturementioning

confidence: 99%

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2020

HIJ

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“…Socioeconomic forecasting refers to scientifically based predictions of the main trends in socioeconomic, innovative, environmental and territorial development in the long term, the identification of factors that determine the trends in order to justify the strategic and tactical decisions made at the state and corporate levels, allowing uniting social and economic components of the system and considering them in interaction. Economic and mathematical modeling is an effective analysis tool [1].…”

Section: The Relevance Of the Study Of Socio-economic Systemsmentioning

confidence: 99%

Structural modeling of a forest cluster using discrete mathematics

et al. 2020

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Economic modeling allows studying the development trends of clusters and planning the introduction of control actions in this socio-economic system to achieve the necessary stabilization and development trends. The cluster can be described as a set of information about its elements and the relationships between them and can be represented as a graph, where the vertices are the agents, and the directed edges are connections between them. Cluster structural formations can be considered as social graphs containing information about heterogeneous factors and the relations between them. Complex structural modeling of the forest cluster allows creating a formal representation of the tasks of identifying the objects (socio-economic systems), analyzing their complexity, coherence, stability, and development scenarios. To do this, we applied the apparatus of discrete mathematics. Signed graphs make it possible to formally make forecasts of the development or trajectory of the simulated system in the phase space of its variables (factors) based on information about its structure and development programs by means of approximating them with pieces of trajectories of impulse processes in signed digraphs. Modeling with the help of the graph theory makes it possible to remove uncertainty associated with predicting the development of a complex system and to propose the option of controlling a stochastic process.

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“…Many studies analysed how to convert direct-drive pumping devices powered by electricity grids into standalone SPWS (Mérida García et al 2018;Chilundo et al 2019). Dursun and Özden (2014) developed software to avoid unnecessary water delivery to plots-reducing water and energy consumption by 38%-and other approaches released an algorithm to forecast water demand (Xiangmei et al 2021) or energy demand (Perea et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Economic assessment of converting a pressurised water distribution network into an off-grid system supplied with solar photovoltaic energy

Chabour

Picazo

Riquelme

2022

Clean Techn Environ Policy

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Converting a water pressurised distribution network into an off-grid pumping station supplied by solar photovoltaics represents a challenge for utility managers, user demand assessments evaluate the energy generated in a solar-powered systems to establish energy consumption. This work includes quantifying potential investments and economic savings that could be achieved, as well as the payback period which results as an indicator of the suitability of adapting to a power supply utilising solar panels. A tool (UAsolar) to aid practitioners has been developed, it requires a calibrated hydraulic model to account for the energy requirements in the water delivery process of pressurised networks. The authors encourage students, professionals, and decision-makers to use this tool to identify potential efficiency gains (e.g., delivery schedule, reduction of water use) and to synchronise energy production and consumption. Users can get results with low computational time using the software on six pressurised distribution networks. Practitioners should note that the irrigation networks have sized installations with a few photovoltaic modules, while in urban pressurised networks the results show larger installations are required. In addition, irrigation network managers can match energy demand with energy production by changing consumption over time, this could reduce the quantity of modules required and remove the need for energy storage. The payback period ranges from 6.08 to 13 years for the cases where the investment is recovered—(values that show that this investment yields a high return as the lifetime of the PV modules is 25 years). However, one municipality among those studied shows that in some scenarios it is not viable to convert networks into a standalone system. Graphical abstract

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Dynamic mathematical model design of photovoltaic water pumping systems for horticultural crops irrigation: A guide to electrical energy potential assessment for increase access to electrical energy

Cited by 22 publications

References 23 publications

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Structural modeling of a forest cluster using discrete mathematics

Economic assessment of converting a pressurised water distribution network into an off-grid system supplied with solar photovoltaic energy

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