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Feasibility Model Of Solar Energy Plants By Ann And Mcdm Techniques

W.B. Yeats

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Published in Feasibility Model Of Solar Energy Plants By ANN And MCDM Techniques (SpringerBriefs In Energy)

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Harnessing the power of the sun to generate clean and renewable energy is a crucial step towards a sustainable future. Solar energy plants have emerged as a promising solution for addressing the world's growing energy demands while mitigating climate change. However, determining the feasibility of solar energy plants requires careful planning and evaluation. The "Feasibility Model of Solar Energy Plants by ANN and MCDM Techniques" provides a comprehensive roadmap for assessing the viability of solar energy projects.

Artificial Neural Networks (ANN) for Solar Power Forecasting

Accurate forecasting of solar power generation is essential for planning and optimizing solar energy plants. Artificial neural networks (ANNs) have gained wide recognition for their ability to learn complex patterns and make predictions. In the context of solar energy, ANNs can be trained on historical data to forecast future solar power output. This information is vital for grid integration, load balancing, and maximizing energy production.

Feasibility Model of Solar Energy Plants by ANN and MCDM Techniques (SpringerBriefs in Energy)

by Mrinmoy Majumder

5 out of 5

Language	:	English
File size	:	4335 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
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Print length	:	59 pages

Artificial Neural Network (ANN) For Solar Power Forecasting Feasibility Model Of Solar Energy Plants By ANN And MCDM Techniques (SpringerBriefs In Energy)

Multi-Criteria Decision Making (MCDM) for Solar Plant Siting

Choosing the optimal location for a solar energy plant involves considering multiple factors, such as land availability, solar insolation, environmental impact, and grid connectivity. Multi-criteria decision making (MCDM) techniques enable the systematic evaluation of these factors and help decision-makers identify the most suitable site for a solar energy plant. Techniques like the Analytic Hierarchy Process (AHP) and Technique for Free Download Preference by Similarity to Ideal Solution (TOPSIS) provide structured frameworks for comparing and ranking potential sites based on their performance against specified criteria.

Integrated Feasibility Model for Solar Energy Plants

The "Feasibility Model of Solar Energy Plants by ANN and MCDM Techniques" combines the strengths of ANNs and MCDM to provide a comprehensive framework for assessing the feasibility of solar energy projects. This hybrid approach leverages the predictive capabilities of ANNs to forecast solar power generation and the robust decision-making capabilities of MCDM to evaluate potential plant locations. The model considers key aspects such as:

Solar resource assessment
Land availability and suitability
Environmental impact assessment
Grid connectivity and infrastructure requirements
Financial and economic analysis

Benefits of the Feasibility Model

The "Feasibility Model of Solar Energy Plants by ANN and MCDM Techniques" offers numerous benefits for stakeholders involved in solar energy development:

Improved project planning: Accurate solar power forecasting and site selection enhance the planning and design of solar energy plants, ensuring optimal performance and maximizing energy yield.
Reduced investment risk: Comprehensive feasibility analysis minimizes uncertainty and risk associated with solar energy investments, providing investors with confidence in the project's potential.
Accelerated project development: The structured and efficient approach of the model streamlines project development timelines, reducing delays and bringing solar energy projects to fruition faster.
Increased stakeholder engagement: The transparent and inclusive nature of the model fosters collaboration and buy-in from stakeholders, ensuring project success.
Contribution to sustainable development: By promoting the feasibility of solar energy plants, the model contributes to the transition to a clean energy future and the achievement of sustainability goals.

The "Feasibility Model of Solar Energy Plants by ANN and MCDM Techniques" is an indispensable tool for developers, investors, and policymakers seeking to harness the potential of solar energy. By integrating advanced forecasting and decision-making techniques, this model provides a comprehensive approach to evaluating the feasibility of solar energy projects, enabling informed decision-making and the successful deployment of renewable energy solutions. As the world transitions to a low-carbon future, the adoption of this model will contribute significantly to the acceleration of solar energy development and the realization of a sustainable energy landscape.

Feasibility Model of Solar Energy Plants by ANN and MCDM Techniques (SpringerBriefs in Energy)

by Mrinmoy Majumder

5 out of 5