Location mapping for constructing biomass power plant using multi-criteria decision-making method

Zhao, Baosheng; Wang, Han; Huang, Zhihao; Sun, Qianqian

doi:10.1016/j.seta.2021.101707

“…The algorithm for the quantum enhanced process for MCDM [5] approach for site selection of solar plant has been illustrated.…”

Section: Methodsmentioning

confidence: 99%

Quantum-Enhanced SOLAR Site Selection: A Novel MCDM Approach

Gunjan Mukherjee

2024

jes

0

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In the pursuit of optimizing renewable energy sources, the selection of solar plant installation sites presents a complex decision-making challenge that involves multiple criteria. This research introduces a groundbreaking algorithm, leveraging quantum computing techniques to enhance Multi-Criteria Decision Making (MCDM) for solar plant site selection. The proposed algorithm harnesses the superposition and entanglement properties of quantum bits to evaluate extensive datasets and criteria with unprecedented speed and accuracy. By integrating quantum versions of established MCDM methods such as the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the algorithm provides a sophisticated tool for decision-makers. The research demonstrates the algorithm’s superiority over classical methods through rigorous simulation and validation processes. The findings suggest that quantum-enhanced MCDM can significantly streamline the solar plant site selection, paving the way for a more efficient deployment of solar energy infrastructure and contributing to a sustainable energy future.

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“…IV METHODOLOGY The algorithm for the quantum enhanced process for MCDM [5] approach for site selection of solar plant has been illustrated.…”

Section: Author Namementioning

confidence: 99%

Quantum-Enhanced Solar Site Selection: A Novel McDm Approach

Gunjan Mukherjee

2024

jes

0

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In the pursuit of optimizing renewable energy sources, the selection of solar plant installation sites presents a complex decision-making challenge that involves multiple criteria. This research introduces a groundbreaking algorithm, leveraging quantum computing techniques to enhance Multi-Criteria Decision Making (MCDM) for solar plant site selection. The proposed algorithm harnesses the superposition and entanglement properties of quantum bits to evaluate extensive datasets and criteria with unprecedented speed and accuracy. By integrating quantum versions of established MCDM methods such as the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the algorithm provides a sophisticated tool for decision-makers. The research demonstrates the algorithm’s superiority over classical methods through rigorous simulation and validation processes. The findings suggest that quantum-enhanced MCDM can significantly streamline the solar plant site selection, paving the way for a more efficient deployment of solar energy infrastructure and contributing to a sustainable energy future.

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“…Due to their complexity, most DSSs are designed for a very specific area of interest. In recent years, DSSs have been used in exploring the design aspects of green hydrogen [90] and selecting sites for solar [91] and biomass power plants [92]. DSS-aided multi-objective methods are utilized in designing central heating plants [93] and in improving buildings' environmental performance [94].…”

Section: Literature Reviewmentioning

confidence: 99%

City-Level Transition to Low-Carbon Economy

Višković

¹

,

Franki

²

,

Bašić-Šiško

³

2022

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In recent years climate change has emerged as a global issue directly related to quality of life. In this context, one of the key goals in the next few decades will be to transition the global economy to a sustainable system. The nature of the energy planning process dictates the application of complex models. There is no universal solution to the energy planning problem. Each territory requires a bespoke strategy aimed at utilising its specific potential. The research presented in this paper explores reaching a zero-carbon energy system at the city level. It establishes a step-by-step decarbonisation method and proposes an energy transition index (ETI). The index presented is used to evaluate different renewable energy sources (RES) deployment scenarios in the context of affordability, self-reliance, and sustainability. The main aspects and barriers of deploying sustainable energy solutions are also explored. Some of the key challenges of RES deployment are identified as capital intensity, output variability, and the regulatory framework. The approach applied in the paper focuses on a city-level strategy in line with the goal of satisfying demand through local energy sources. The presented analysis offers two basic conclusions: (1) each territory requires a bespoke strategy that can optimally utilise its energy potential and (2) building a local zero-carbon system can be feasible only by implementing energy storage technologies.

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Location mapping for constructing biomass power plant using multi-criteria decision-making method

Cited by 9 publications

References 34 publications

Quantum-Enhanced SOLAR Site Selection: A Novel MCDM Approach

Quantum-Enhanced SOLAR Site Selection: A Novel MCDM Approach

Quantum-Enhanced Solar Site Selection: A Novel McDm Approach

City-Level Transition to Low-Carbon Economy

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