Smart supply-side management of optimal hydro reservoirs using the water/energy nexus concept: A hydropower pinch analysis

Charmchi, Amir Saman Tayerani; Ifaei, Pouya

doi:10.1016/j.apenergy.2020.116136

Cited by 28 publications

(4 citation statements)

References 58 publications

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“…Moreover, the application of multi-step ahead (MSA) multivariate not only increases complexity but also intricates the curse of dimensionality prediction, thereby exacerbating the situation. The predictability of MSA multivariate prediction against MSA univariate prediction has been discussed in several studies [16,26]. MSA multivariate prediction is a complex forecasting approach that considers multiple data series, with each series representing a different variable or feature [16,17,27].…”

Section: Research Background and Motivationmentioning

confidence: 99%

Feature Extraction from Satellite-Derived Hydroclimate Data: Assessing Impacts on Various Neural Networks for Multi-Step Ahead Streamflow Prediction

Ghobadi,

Tayerani Charmchi,

Kang

2023

Sustainability

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Enhancing the generalization capability of time-series models for streamflow prediction using dimensionality reduction (DR) techniques remains a major challenge in water resources management (WRM). In this study, we investigated eight DR techniques and their effectiveness in mitigating the curse of dimensionality, which hinders the performance of machine learning (ML) algorithms in the field of WRM. Our study delves into the most non-linear unsupervised representative DR techniques, including principal component analysis (PCA), kernel PCA (KPCA), multi-dimensional scaling (MDS), isometric mapping (ISOMAP), locally linear embedding (LLE), t-distributed stochastic neighbor embedding (t-SNE), Laplacian eigenmaps (LE), and autoencoder (AE), examining their effectiveness in multi-step ahead (MSA) streamflow prediction. In this study, we conducted a conceptual comparison of these techniques. Subsequently, we focused on their performance in four different case studies in the USA. Moreover, we assessed the quality of the transformed feature spaces in terms of the MSA streamflow prediction improvement. Through our investigation, we gained valuable insights into the performance of different DR techniques within linear/dense/convolutional neural network (CNN)/long short-term memory neural network (LSTM) and autoregressive LSTM (AR-LSTM) architectures. This study contributes to a deeper understanding of suitable feature extraction techniques for enhancing the capabilities of the LSTM model in tackling high-dimensional datasets in the realm of WRM.

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Section: Research Background and Motivationmentioning

confidence: 99%

Feature Extraction from Satellite-Derived Hydroclimate Data: Assessing Impacts on Various Neural Networks for Multi-Step Ahead Streamflow Prediction

Ghobadi,

Tayerani Charmchi,

Kang

2023

Sustainability

Self Cite

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“…However, current studies that employed the SDM in the WE nexus still have some limitations. On the one hand, scholars are inclined to observe the nexus from either the supply side or demand/end-use side [34,35] and seldom integrate these two sides together at urban scale. On the other hand, though the policy scenarios are generally embedded in SDM simulation, they largely ignore the process of policymaking that various stakeholders are involved in.…”

Section: Literature Reviewmentioning

confidence: 99%

Systematic Modeling and Policy Analysis on the Urban Water–Energy Nexus for Sustainable Resources Management

2022

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Urbanization in developing countries has imposed great pressure on the availability of water and energy (WE) resources, while single-sector strategies may cause several unanticipated consequences. To find sustainable solutions for resource management, this study develops an integrated approach to assess urban WE from a nexus perspective. With the city Shenzhen as a case study, the existing WE nexus on the supply and demand sides of urban areas is first quantified. Subsequently, a system dynamics model (SDM) is constructed to reveal the complex interactions in the urban nexus, and the trends of WE supply and demand by 2035 are simulated. To narrow the potential resources gap, a policy analysis considering the interest and influence of various stakeholders is conducted to formulate policy scenarios. As revealed from the results, the resources gap will expand continuously by 2035, especially for water resources. Compared to the demand side, the policies implemented on the supply side exhibit a better performance, and the scenario of import expansion could independently achieve the desirable result. Moreover, as the demand side displayed more complexities, the implementation of future policies should rigorously weigh the priorities and difficulties of a range of stakeholders’ involvements.

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“…In [19], the authors introduce the integration of water desalination within security-constrained unit commitment (SCUC), which significantly minimizes the system's operational cost, especially with the enormous desalination size. As the water-energy nexus concept is mainly applied at the supply side, in [20], the work considers the interconnections between water and energy demands in a reservoir to propose new supply-side management of optimal and smart hydro reservoirs and uses advanced neural networks to predict two different scenarios that simulate the annual operation and remote monitoring situations.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Integrated Water and Electrical Networks through a Holistic Water–Energy Nexus Approach

Elbalki,

Shaaban,

Osman

et al. 2024

Sustainability

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As water and electrical networks cannot be entirely independent, a more integrated approach, the water–energy nexus (WEN), is developed. A WEN is the basis of a smart city where water and electrical networks are interconnected and integrated by implementing efficient management strategies. Accordingly, this study develops a dynamic co-optimization model for designing and operating an integrated power and water system. The proposed co-optimization model minimizes the total annual and operational costs of a micro-WEN system while capturing its optimum design values and operating conditions and meeting the demands of the electrical and water networks. Furthermore, this work presents a plan for transitioning from thermal desalination to reverse osmosis (RO) desalination in the United Arab Emirates (UAE). The key objective is to decouple electricity and water production, effectively tackling the issue of operating the UAE’s power plants at low efficiency during the winter while ensuring an adequate water supply to meet the growing demand. The results show that the co-optimization model provides a significant reduction in the total operational cost with the integration of photovoltaic energy and shifting to RO. Most importantly, the micro-WEN system is optimized over multiple timescales to reduce the computation effort and memory requirements.

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Smart supply-side management of optimal hydro reservoirs using the water/energy nexus concept: A hydropower pinch analysis

Cited by 28 publications

References 58 publications

Feature Extraction from Satellite-Derived Hydroclimate Data: Assessing Impacts on Various Neural Networks for Multi-Step Ahead Streamflow Prediction

Feature Extraction from Satellite-Derived Hydroclimate Data: Assessing Impacts on Various Neural Networks for Multi-Step Ahead Streamflow Prediction

Systematic Modeling and Policy Analysis on the Urban Water–Energy Nexus for Sustainable Resources Management

Optimizing Integrated Water and Electrical Networks through a Holistic Water–Energy Nexus Approach

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