Techno-economic and environmental analysis of hybrid energy systems for a university in Australia

Saiprasad, Nithya; Kalam, Akhtar; Zayegh, Aladin

doi:10.1080/1448837x.2018.1546792

Cited by 5 publications

(4 citation statements)

References 6 publications

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“…In our previous work [4], in the literature review, comprehensive analysis was done for contributions that covers wide range of applications revealing the use of HES to overcome the stochastic nature of Renewable Energy Sources (RES), and reduce overall energy consumption and CO2 emissions [23,24]. The summary also included contributions that employed modern approaches for the optimum planning of electric power systems which includes Analytic Hierarchy Process [25], the use of multi-criteria decision making methods [26], scenario-based comparative analysis and techno-economic analysis of grid-connected hybrid systems [27][28][29]. Numerous scholars have employed a range of tools for integrating renewable energy sources, such as the Holistic Grid Resource Integration and Development (HiGRID) tool [32] and the HOMER simulator [33].…”

Section: Previous Researchmentioning

confidence: 99%

An Agile Approach for Adopting Sustainable and Environmentally Friendly Energy Solutions with Advanced Computational Techniques

Konneh,

Howlader,

Elkholy

et al. 2024

Preprint

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In the face of the burgeoning electricity demands and the imperative for sustainable development amidst rapid industrialization, this study introduces a dynamic and adaptable framework suitable for policy-makers and renewable energy experts working on integrating and optimizing renewable energy solutions. While using a case study representative model for Sub-Saharan Africa (SSA) to demonstrate the challenges and opportunities present in introducing optimization methods to bridge power supply deficits and the scalability of the model to other regions, this study presents an agile multi-criteria decision tool that pivots on four key development phases, advancing upon established methodologies and pioneering refined computational techniques, to select optimal configurations from a set of Policy Decision Making Metrics (PDM-DPS). Central to this investigation lies a rigorous comparative analysis of variants of three advanced algorithmic approaches: Swarm-Based Multi-objective Particle Swarm Optimization (MOPSO), Decomposition-Based Multi-objective Evolutionary Algorithm (MOEA/D), and Evolutionary-Based Strength Pareto Evolutionary Algorithm (SPEA2). These are applied to a grid-connected hybrid system, evaluated through a comprehensive 8760-hour simulation over a 20-year planning horizon. The evaluation is further enhanced by a set of refined Algorithm Performance Evaluation Metrics (AL-PEM) tailored to the specific constraints. The findings not only underscore the robustness and consistency of the SPEA2 variant over 15 runs of 200 generations each, which ranks first on the AL-PEM scale but also validate the strategic merit of combining multiple technologies and empowering policymakers with a versatile toolkit for informed decision-making.

show abstract

Section: Previous Researchmentioning

confidence: 99%

An Agile Approach for Adopting Sustainable and Environmentally Friendly Energy Solutions with Advanced Computational Techniques

Konneh,

Howlader,

Elkholy

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…In the literature review in our previous work [7], a comprehensive analysis was performed on a wide range of applications, revealing the use of HES in overcoming the stochastic nature of Renewable Energy Sources (RES) and reduce overall energy consumption and CO 2 emissions [8,9]. The summary also highlighted contributions that utilized modern approaches for optimal electric power system planning, including the Analytic Hierarchy Process [10], multi-criteria decision-making methods [11,12], scenario-based comparative analysis, and techno-economic analysis of grid-connected hybrid systems [13][14][15][16][17]. Numerous researchers have employed various tools for integrating renewable energy sources, such as the Holistic Grid Resource Integration and Development (HiGRID) tool [18] and the HOMER simulator [19].…”

Section: Previous Researchmentioning

confidence: 99%

An Agile Approach for Adopting Sustainable Energy Solutions with Advanced Computational Techniques

Konneh,

Howlader,

Elkholy

et al. 2024

Energies

View full text Add to dashboard Cite

In the face of the burgeoning electricity demands and the imperative for sustainable development amidst rapid industrialization, this study introduces a dynamic and adaptable framework suitable for policymakers and renewable energy experts working on integrating and optimizing renewable energy solutions. While using a case study representative model for Sub-Saharan Africa (SSA) to demonstrate the challenges and opportunities present in introducing optimization methods to bridge power supply deficits and the scalability of the model to other regions, this study presents an agile multi-criteria decision tool that pivots on four key development phases, advancing established methodologies and pioneering refined computational techniques, to select optimal configurations from a set of Policy Decision-Making Metrics (PDM-DPS). Central to this investigation lies a rigorous comparative analysis of variants of three advanced algorithmic approaches: Swarm-Based Multi-objective Particle Swarm Optimization (MOPSO), Decomposition-Based Multi-objective Evolutionary Algorithm (MOEA/D), and Evolutionary-Based Strength Pareto Evolutionary Algorithm (SPEA2). These are applied to a grid-connected hybrid system, evaluated through a comprehensive 8760-hour simulation over a 20-year planning horizon. The evaluation is further enhanced by a set of refined Algorithm Performance Evaluation Metrics (AL-PEM) tailored to the specific constraints. The findings not only underscore the robustness and consistency of the SPEA2 variant over 15 runs of 200 generations each, which ranks first on the AL-PEM scale, but the findings also validate the strategic merit of combining multiple technologies and empowering policymakers with a versatile toolkit for informed decision-making.

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“…Related operation models were used in previous studies. Saiprasad et al [23] and Perez et al [24] analyzed grid-connected photovoltaic technology for a case in Australia. Ahmet and Aktas [25] conducted operational decisions of a hybrid energy system by considering profit obtained from system operations and the renewable energy utilization ratio in load demand satisfaction.…”

Section: Introductionmentioning

confidence: 99%

Electricity Curtailment Cost Coupled to Operation Model Facilitates Clean Energy Accommodation in Grid-Connected System

Zhao

et al. 2021

Energies

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Electricity transmission in a grid-connected system provides an effective solution to promoting clean energy accommodation. However, with arbitrary determination in current operation models, the clean energy utilization ratio (CEUR) is not satisfactory largely due to the lack of electricity curtailment (the electricity equivalent of clean energy curtailment) cost-dependent optimization. In this study, a curtailment cost-dependent multi-objective operation (CCMO) model was proposed to complementarily operate a grid-connected hybrid energy system, identify optimal CEUR, and thus maximally reduce electricity curtailment. The CCMO model centers on coupling the punishment cost of electricity curtailment with the multi-objective function defined as the total cost of each grid component. The CCMO model was solved to derive the optimal equilibrium solution determined based on multiple non-dominated solutions. A grid-connected hybrid energy system including the Yunnan, Guangdong, and Guangxi Power Grids was used to test the model performance. The results showed that the CCMO model’s CEUR was up to 100% at hourly scale and 96.9% on daily average, which were both significantly higher than those in the current operation models. Furthermore, the CCMO’s optimal equilibrium solution, i.e., respective minimum total cost of each grid component, can also identify optimal transmission schemes of the daily channel utilization to make the peak utilization hours largest.

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Techno-economic and environmental analysis of hybrid energy systems for a university in Australia

Cited by 5 publications

References 6 publications

An Agile Approach for Adopting Sustainable and Environmentally Friendly Energy Solutions with Advanced Computational Techniques

An Agile Approach for Adopting Sustainable and Environmentally Friendly Energy Solutions with Advanced Computational Techniques

An Agile Approach for Adopting Sustainable Energy Solutions with Advanced Computational Techniques

Electricity Curtailment Cost Coupled to Operation Model Facilitates Clean Energy Accommodation in Grid-Connected System

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