Eco-energetic feasibility study of using grid-connected photovoltaic system in wastewater treatment plant

Bey, Mohamed; Hamidat, A.; Nacer, T.

doi:10.1016/j.energy.2020.119217

Cited by 25 publications

(5 citation statements)

References 50 publications

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“…In addition, the signal is sampled at every h time increment, so that the whole signal y(t) is described by the vector Y ∈ R N that contains the N data points of the given signal, as shown in Equation (2).…”

Section: Regression-based Fourier Model Formulationmentioning

confidence: 99%

“…Solar energy has been widely adopted and integrated into various sectors, such as the gas and oil industries, where solar energy has evolved into a primary source for essential utilities, including applications in water treatment [1][2][3]. Accurate direct average irradiance data is necessary for commercial and residential solar panel installations.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Solar and Wind Data Recognition: Fourier Regression for Robust Recovery

Al-Aboosi,

Muñoz Vazquez,

Al-Aboosi

et al. 2024

BDCC

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Accurate prediction of renewable energy output is essential for integrating sustainable energy sources into the grid, facilitating a transition towards a more resilient energy infrastructure. Novel applications of machine learning and artificial intelligence are being leveraged to enhance forecasting methodologies, enabling more accurate predictions and optimized decision-making capabilities. Integrating these novel paradigms improves forecasting accuracy, fostering a more efficient and reliable energy grid. These advancements allow better demand management, optimize resource allocation, and improve robustness to potential disruptions. The data collected from solar intensity and wind speed is often recorded through sensor-equipped instruments, which may encounter intermittent or permanent faults. Hence, this paper proposes a novel Fourier network regression model to process solar irradiance and wind speed data. The proposed approach enables accurate prediction of the underlying smooth components, facilitating effective reconstruction of missing data and enhancing the overall forecasting performance. The present study focuses on Midland, Texas, as a case study to assess direct normal irradiance (DNI), diffuse horizontal irradiance (DHI), and wind speed. Remarkably, the model exhibits a correlation of 1 with a minimal RMSE (root mean square error) of 0.0007555. This study leverages Fourier analysis for renewable energy applications, with the aim of establishing a methodology that can be applied to a novel geographic context.

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Section: Regression-based Fourier Model Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Solar and Wind Data Recognition: Fourier Regression for Robust Recovery

Al-Aboosi,

Muñoz Vazquez,

Al-Aboosi

et al. 2024

BDCC

View full text Add to dashboard Cite

show abstract

“…No one doubts the necessity of wastewater treatment due to its high amount of physical, chemical, and biological pollution which is only reachable through treatment plants. However, the high costs of these large-scale projects have led experts Citation: Gheibi to fi nd the most appropriate process that, besides meeting quality parameters, optimally satisfi es the technical, economic, and environmental goals [12][13][14][15][16]. On the other hand, each of these treatment plants and related processes has special characteristics and attitudes.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity analysis of parameters affecting suspended growth in industrial wastewater treatment plants; with emphasis on economic performance criteria

Gheibi¹,

chahkandi²,

Kian³

et al. 2021

Ann Environ Sci Toxicol

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Industrial wastewater treatment is of high priority due to the presence of an extraordinary concentration of dangerous pollutants. Similar to urban wastewater treatment plants, there are plenty of options while designing industrial ones which need various analyses and researches to choose correctly. One of the most effi cient ways to solve this problem is to implement Economic and Sensitivity Analysis. This research has studied designing an industrial wastewater treatment plant utilizing three different biological treatment methods (including Sequential Batch Reactors (SBR), plug-fl ow activated sludge with a secondary clarifi er, and step aeration activated sludge with a secondary clarifi er). It also measures the sensitivity of performance cost parameters to factors affecting the suspended growth unit. The results of the economic analysis showed that using SBR has the highest construction cost of $ 70,200,000 and the highest total cost of 96,900,000. Sensitivity analysis showed that by adjusting design retention time and variance between heterotrophic microorganism decay rate and the reality, using activated carbon-based systems could signifi cantly reduce total annual costs.

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“…The optimization proposed by authors is based on: energy balance, installation surface area and levelized cost of energy (LCOE). Obtained results show that the grid-connected PV system can cover 53% of WWTP electrical load and can inject 510 MWh/year into the grid, representing 65% of the load [18].…”

Section: Introductionmentioning

confidence: 99%

Energetic-Environmental-Economic Feasibility and Impact Assessment of Grid-Connected Photovoltaic System in Wastewater Treatment Plant: Case Study

Andrei

Badea²,

Andrei

et al. 2020

Energies

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Wastewater treatment plants and power generation constitute inseparable parts of present society. So the growth of wastewater treatment plants is accompanied by an increase in the energy consumption, and a sustainable development implies the use of renewable energy sources on a large scale in the power generation. A case study of the synergy between wastewater treatment plants and photovoltaic systems, aiming to improve the energetic, environmental and economic impacts, is presented. Based on data acquisition, the energy consumption analysis of wastewater treatment plant reveals that the highest demand is during April, and the lowest is during November. The placement of photovoltaic modules is designed to maximize the use of free space on the technological area of wastewater treatment plant in order to obtain a power output as high as possible. The peak consumption of wastewater treatment plant occurs in April, however the peak production of the photovoltaic is in July, so electrochemical batteries can partly compensate for this mismatch. The impact of the photovoltaic system connectivity on power grid is assessed by means of the matching-index method and the storage battery significantly improves this parameter. Carbon credit and energy payback time are used to assess the environmental impact. The results prove that the photovoltaic system mitigates 12,118 tons of carbon and, respectively, the embedded energy is compensated by production in 8 ½ years. The economic impact of the photovoltaic system is analyzed by the levelized cost of energy, and the results show that the price of energy from the photovoltaic source is below the current market price of energy.

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Eco-energetic feasibility study of using grid-connected photovoltaic system in wastewater treatment plant

Cited by 25 publications

References 50 publications

Solar and Wind Data Recognition: Fourier Regression for Robust Recovery

Solar and Wind Data Recognition: Fourier Regression for Robust Recovery

Sensitivity analysis of parameters affecting suspended growth in industrial wastewater treatment plants; with emphasis on economic performance criteria

Energetic-Environmental-Economic Feasibility and Impact Assessment of Grid-Connected Photovoltaic System in Wastewater Treatment Plant: Case Study

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