Sustainable Energy Infrastructure Planning Framework: Transition to a Sustainable Electricity Generation System in Bangladesh

Khan, Imran

doi:10.1007/978-3-030-63654-8_7

Cited by 4 publications

(2 citation statements)

References 34 publications

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“…To resolve concerns about the possibility of the termination of support programs due to financial pressures on governments [15] and budget deficiencies resulting from the implementation of programs such as FIT [8,16], this study assumes that support programs with endogenous financial resources are sustainable, and evaluates their sustainability. Assuming a rational relationship between price changes and supply and demand, along with a competitive market, and inspired by a variety of support policies implemented in the world [7,30], this study evaluates the sustainability of the three following support policies and offers solutions to provide implementation costs:…”

Section: Modelmentioning

confidence: 99%

“…In studies such as [14], the amount of funding needed for decision-makers to achieve specific goals under different scenarios is analyzed, while issues such as how they are funded, the effects of their scarcity, and the prediction of the financial crises are not considered. For long-term development, in addition to considering the system's variables such as supply, demand, and pricing as endogenous, one should also think about financing new capacities and implementing these support programs [15]. If a decision-maker does not plan for covering these costs (e.g., as stated in [8]), the implementation of support plans (such as the FIT policy) with no feedback from the financial resources leads to the failure of the development plan despite the temporary satisfactory development effects.…”

Section: Introductionmentioning

confidence: 99%

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Sustainability Assessment of Electricity Generation Development under the Implementation of Support Policies with Endogenous Financial Resources Using a Hybrid Decision Support Model

Dianat

Khodakarami

Ganjavi

et al. 2022

Mathematical Problems in Engineering

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Sustainable electricity development is one of the requirements for achieving sustainable development in global communities. However, due to barriers, especially in less developed countries, there is little incentive to invest in the development of sustainable electricity technologies. Therefore, there should be a change in market mechanisms, and broad support policies have to be implemented for the sustainable development of electricity. In the long run, these policies must lead to the sustainable development of energy systems. To evaluate the efficiency and effects of the proposed support policies on the sustainability of electricity generation development, this study intends to analyze the multiple and complex dimensions of the problem using a hybrid decision support model. Moreover, by defining an indicator to assess the electricity generation expansion sustainability, this study assists policymakers in making logical decisions about sustainable support programs for the electricity development based on the characteristics of the electricity market of each country. Despite uncertainties in the electricity market, simulations show that the results of this hybrid model have approximately 88% conformance with historical data. Consequently, the model can evaluate the sustainability of the system under the implementation of the proposed support programs and compare them to select the most effective one. The results show that by assuming a competitive market and rational behavior and implementing support programs with endogenous financial resources, the installed renewable capacity can be improved by up to 70.4% compared with the direct subsidy policies. Regardless of the financial burden of policies (e.g., direct subsidies) and the possibility of facing a budget deficit, these programs can be up to 79.2% more effective in the sustainability of the energy system compared with the direct subsidy policy.

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Section: Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sustainability Assessment of Electricity Generation Development under the Implementation of Support Policies with Endogenous Financial Resources Using a Hybrid Decision Support Model

Dianat

Khodakarami

Ganjavi

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

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Intelligent characteristic objects method (INCOME): a data knowledge-based multi-criteria decision analysis

Kizielewicz,

Shekhovtsov,

Więckowski

et al. 2024

Artif Intell Rev

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Multi-criteria decision analysis (MCDA) methods are vital in assessing decision variants under multiple conditions. However, involving domain experts in developing decision models can be challenging and costly, necessitating more scalable and independent solutions. This paper introduces the intelligent characteristic objects method (INCOME), which combines the k-Nearest Neighbor (kNN) algorithm and the COMET method to create a theoretical decision-maker for comparing characteristic objects (COs). INCOME overcomes limitations of classical MCDA methods, such as the TOPSIS approach, which struggles with complex functions and non-monotonic modeling. INCOME influences data-based knowledge to provide a robust framework for assessing decision options. The integration of the COMET method and kNN algorithm enables improved modeling of decision functions based on evaluated data, increasing the flexibility and independence of the INCOME approach. A case study assessing gas power plants based on four criteria is presented to validate the performance of the INCOME method. The results demonstrate high correlations with the reference model and slightly higher classical approaches like TOPSIS and TOPSIS-COMET. However, INCOME exhibits greater stability and flexibility by utilizing all available data instead of relying on limited expert knowledge. The proposed INCOME approach offers several advantages, including creating a continuous decision model, resistance to the Rank-Reversal phenomenon, and the potential for replacing domain experts with artificial experts. This study highlights the effectiveness of INCOME in Multi-Criteria Decision Analysis. It suggests future research directions, such as parameter selection and testing in different decision-making problems.

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Multi-criteria decision analysis methods for energy sector's sustainability assessment: Robustness analysis through criteria weight change

Sahabuddin¹,

Khan²

2021

Sustainable Energy Technologies and Assessments

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Sustainable Energy Infrastructure Planning Framework: Transition to a Sustainable Electricity Generation System in Bangladesh

Cited by 4 publications

References 34 publications

Sustainability Assessment of Electricity Generation Development under the Implementation of Support Policies with Endogenous Financial Resources Using a Hybrid Decision Support Model

Sustainability Assessment of Electricity Generation Development under the Implementation of Support Policies with Endogenous Financial Resources Using a Hybrid Decision Support Model

Intelligent characteristic objects method (INCOME): a data knowledge-based multi-criteria decision analysis

Multi-criteria decision analysis methods for energy sector's sustainability assessment: Robustness analysis through criteria weight change

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