Employing Input-Output Model to Assess the Water Footprint of Energy System

Chai, Li; Han, Aixi; Yan, Xi; Ma, Sai

doi:10.1007/978-981-33-4377-1_6

Cited by 5 publications

(3 citation statements)

References 26 publications

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“…Mathematical models known as I-O models provide a common method for modeling hydropower plant output and performance [7] [24]. The Glimn-Kirchmayer quadratic model is an advanced I-O model that effectively represents the non-linear relationship between water flow rate, head height, and turbine efficiency, enabling control over output and performance [24].…”

Section: Background To the Studymentioning

confidence: 99%

Enhancing Hydro Power Plant Efficiency through Hybrid-Optimization Approach

Enyiukwu, E. I. and Omeje, C. O.

2024

JCMPS

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The inclusion of hydroelectric power is crucial to Nigeria's overall energy mix, playing a significant role in electricity generation. However, the Shiroro hydro plant, one of the main facilities located on the Kaduna River, is currently facing operational obstacles due to deteriorating infrastructure and inadequate maintenance practices. To overcome these challenges and improve efficiency within Nigeria's hydroelectric power sector, a hybrid-optimization approach has been proposed. This study sought to enhance the efficiency of the Shiroro hydro plant by implementing this innovative method. To achieve our objectives and address pertinent research questions, a mixed research method combining primary and secondary data was employed. The analysis included hydropower modeling and hydro-turbine input-output modeling. Three optimizer models, namely the particle swarm optimizer (PSO), Ant colony optimizer (ACO), and Artificial bee colony optimizer (ABCO), were utilized to formulate objective functions and task representations. The study involved comparing the daily output and fitness response of the Shiroro hydro plant through swarm optimizer iterations. The findings revealed a clear correlation between the turbine's power output and the water flow rate and water column height, suggesting that altering these factors could significantly improve the plant's performance. The comparison of the PSO, ACO, and ABCO models demonstrated that PSO and ABCO generated optimal or near-optimal solutions, while ACO produced suboptimal results. Consequently, the study concluded that enhancing the Shiroro hydro plant's output was feasible by increasing the water flow rate and column height. Additionally, the utilization of PSO and ABCO models proved to be an effective means of accurately predicting the turbine's output. As a result, the study recommended the integration of hybrid optimization techniques to monitor and identify any deviations in the Shiroro hydro plant's daily power output. This approach would enable prompt maintenance to be carried out, preventing significant damage to the plant. Ultimately, this research contributes valuable insights into improving the efficiency and performance of Nigeria's Shiroro hydro plant.

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Section: Background To the Studymentioning

confidence: 99%

Enhancing Hydro Power Plant Efficiency through Hybrid-Optimization Approach

Enyiukwu, E. I. and Omeje, C. O.

2024

JCMPS

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“…While the water footprint of power generation based on fossil fuels has been widely analyzed [59,60], concerns have been raised regarding the water needs of the renewable energy development [61,62]. Several methodologies have been proposed to quantify the water footprint of these technologies, aiming to assess the real sustainability of renewable sources of energy [63][64][65][66], e.g., PV [67], biomass [68], hydropower [69,70] or wind ones [71]. Estimates indicate that the water footprint of renewable power technologies could be reduced by shifting to [5] and IEA (2019) Headline global energy data [47]).…”

Section: Overviewmentioning

confidence: 99%

Data-driven appraisal of renewable energy potentials for sustainable freshwater production in Africa

Angelis

Tuninetti

Bergamasco

et al. 2021

Renewable and Sustainable Energy Reviews

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“…Different impacts such as direct impact, indirect impact, and induced impact can be modeled in IO analysis. Several studies adapted the IO analysis in different fields such as circular economy modeling (Towa et al, 2021), the water footprint of the energy system (Chai et al, 2021), renewable energy consumption (Wang & Liu, 2021), EU bioeconomy (Cingiz et al, 2021), employment impact assessment (Henriques et al, 2016), ecological and water footprint accounting (Ewing et al, 2012), estimation of energy and carbon emission intensity (Chung et al, 2009). Although SRIO models are widely used on environmental policy making, it has several limitations such as uncertainties in raw data, time‐intensive continuous update of economic and environmental data, aggregation of sectoral data, coverage of a single region economic transaction, and lack of up‐to‐date time series data (Wiedmann et al, 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis

Bulak

Küçükvar

2021

Sustainable Development

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This paper presents an integrated approach combining the optimization‐based frontier model with a global multiregional input–output (MRIO) analysis for food consumption in Europe. The weighted and conventional data envelopment analysis models are coupled with production and consumption‐based environmental and economic footprint data obtained from the environmental footprint explorer database. Eco‐efficiency assessment is carried out using multiple undesirable environmental outputs such as carbon emission, total energy consumption, land use, material use, water use, and one desirable economic output, which is the gross value‐added (GVA). This assessment indicates an efficiency level of each economic activity associated with its environmental impacts and policies are made as a result of the efficiency level to propose an equilibrium between economic development and environmental impacts. Finally, a sensitivity analysis of each parameter, variability analysis between weighted and non‐weighted models, and performance improvement projections are presented. Based on the results, four countries become efficient when moving from production‐based accounting (PBA) to consumption‐based accounting (CBA). France, United Kingdom, Italy, and Sweden are efficient countries in both findings. Denmark caused the highest carbon emission from the production point of view. Germany is the largest importer in all environmental categories such as carbon emission, energy usage, material use, land use, and water use. Additionally, the weight‐restricted model indicated a noticeable difference concerning the eco‐efficiency scores under the PBA and CBA approach, where land use and material footprint categories were found to be the most sensitive parameters for eco‐efficiency scores. The authors believe that this integrated approach will aid in decision‐making and help build a composite eco‐efficiency score when comparing the performance of food consumption with multiple environmental and economic metrics.

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Employing Input-Output Model to Assess the Water Footprint of Energy System

Cited by 5 publications

References 26 publications

Enhancing Hydro Power Plant Efficiency through Hybrid-Optimization Approach

Enhancing Hydro Power Plant Efficiency through Hybrid-Optimization Approach

Data-driven appraisal of renewable energy potentials for sustainable freshwater production in Africa

How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis

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