The role of sodium-nickel chloride (Na-NiCl2) batteries in managing uncertainty and renewable sources for empowering hybrid energy systems using bi-level CONOPT-based optimization

In the realm of integrated energy systems, the allocation of energy storage capacity stands as a critical challenge. Renewable energy resources (RERs), with their inherent variability and intermittency, pose a threat to grid stability and reliability. Effective management of energy storage resources becomes imperative to counteract the impacts of this volatility, a task contingent upon various factors including the storage technology’s type and function. This paper introduces a novel bi-level methodology aimed at determining the optimal allocation of storage capacity across a hybrid energy network to improve its overall performance. The methodology leverages the CONOPT approach within the GAMS platform, which integrates sequential linear and quadratic programming algorithms with reduced gradients to address complex nonlinear optimization issues characterized by sparse and nonlinear constraints. The proposed approach takes into consideration uncertainties associated with RER generation, electrical load, and market prices. Fuzzy C-means clustering is used to generate uncertain scenarios for the output-generated power of the uncertain parameters and then employed to cluster their normally distributed scenarios into fewer representative scenarios. By incorporating these stochastic factors, the methodology aims to identify the most effective way to distribute storage resources to smooth out the variability of renewables-based power. As power systems increasingly rely on variable RERs, the integration of energy storage emerges as crucial for enhancing system stability, resilience, and reliability. This study provides a robust framework to assist in decision-making concerning storage investments and deployment strategies. Through a comparative analysis of three prominent energy storage systems—specifically pumped hydro storage (PHS), sodium-sulfur (NaS), and sodium-nickel chloride (Na-NiCl 2 )—using comprehensive data, distinct characteristics and trade-offs among these technologies are revealed, offering valuable insights for stakeholders. The results indicate that PHS achieves moderate savings, ranging from 2.12% to 4.68%. In comparison, NaS systems exhibit savings percentages between 3.93% and 4.39%. In contrast, Na-NiCl 2 demonstrates notably higher savings percentages, from 5.64% to 5.82%. These findings suggest that Na-NiCl 2 stands out as a more economically efficient option, offering enhanced savings potential. To validate the effectiveness of the proposed solution, this paper employs the GAMS platform and juxtaposes its outcomes with those attained through alternative optimization techniques. GAMS showed superior performance compared to other optimization techniques.

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Publication Details

Journal
Ain Shams Engineering Journal
Published
2024-11-26
DOI
https://doi.org/10.1016/j.asej.2024.103174
Citations
4
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.81

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article

The role of sodium-nickel chloride (Na-NiCl2) batteries in managing uncertainty and renewable sources for empowering hybrid energy systems using bi-level CONOPT-based optimization

Abdallah Aldosary
4 citations
Ain Shams Engineering Journal
Advanced Battery Technologies Research
0.81
article

The role of sodium-nickel chloride (Na-NiCl2) batteries in managing uncertainty and renewable sources for empowering hybrid energy systems using bi-level CONOPT-based optimization

Abdallah Aldosary
article en
4 citations

Abstract

In the realm of integrated energy systems, the allocation of energy storage capacity stands as a critical challenge. Renewable energy resources (RERs), with their inherent variability and intermittency, pose a threat to grid stability and reliability. Effective management of energy storage resources becomes imperative to counteract the impacts of this volatility, a task contingent upon various factors including the storage technology’s type and function. This paper introduces a novel bi-level methodology aimed at determining the optimal allocation of storage capacity across a hybrid energy network to improve its overall performance. The methodology leverages the CONOPT approach within the GAMS platform, which integrates sequential linear and quadratic programming algorithms with reduced gradients to address complex nonlinear optimization issues characterized by sparse and nonlinear constraints. The proposed approach takes into consideration uncertainties associated with RER generation, electrical load, and market prices. Fuzzy C-means clustering is used to generate uncertain scenarios for the output-generated power of the uncertain parameters and then employed to cluster their normally distributed scenarios into fewer representative scenarios. By incorporating these stochastic factors, the methodology aims to identify the most effective way to distribute storage resources to smooth out the variability of renewables-based power. As power systems increasingly rely on variable RERs, the integration of energy storage emerges as crucial for enhancing system stability, resilience, and reliability. This study provides a robust framework to assist in decision-making concerning storage investments and deployment strategies. Through a comparative analysis of three prominent energy storage systems—specifically pumped hydro storage (PHS), sodium-sulfur (NaS), and sodium-nickel chloride (Na-NiCl 2 )—using comprehensive data, distinct characteristics and trade-offs among these technologies are revealed, offering valuable insights for stakeholders. The results indicate that PHS achieves moderate savings, ranging from 2.12% to 4.68%. In comparison, NaS systems exhibit savings percentages between 3.93% and 4.39%. In contrast, Na-NiCl 2 demonstrates notably higher savings percentages, from 5.64% to 5.82%. These findings suggest that Na-NiCl 2 stands out as a more economically efficient option, offering enhanced savings potential. To validate the effectiveness of the proposed solution, this paper employs the GAMS platform and juxtaposes its outcomes with those attained through alternative optimization techniques. GAMS showed superior performance compared to other optimization techniques.

Ain Shams Engineering JournalVol. 16(1)
Prince Sattam Bin Abdulaziz University (SA)
Prince Sattam bin Abdulaziz University
Affordable and clean energy
Openalex Percentile: Top 28%
Advanced Battery Technologies Research
0.81
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