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Selection of optimum green energy sources by considering environmental constructs and their technical criteria: a case study

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Abstract

Optimum green energy sources selection needs a strategic decision for reducing the use of conventional resources. In the selection of optimum green resources, constraints like technical and customer requirements play an important role. The proposed integrated AHP-QFD approach has been applied to a specific northeastern region, India, to select the optimal green energy sources addressing the technical and customer requirements. AHP is used to calculate the intensity of relative priority for customer requirements. The main reason behind choosing AHP methodology is its reliability and consistency in decision-making process. The prime idea of QFD is to translate typical customer requirements into a significant technical requirement by means of transformation for every stage of development and selection. The relative priority and normalized priority of each technical requirement are computed using QFD transformation. An overall score for each green energy sources alternative is then calculated to select the optimum green energy sources based on conflicting multiple criteria. The proposed integrated methodology reveals that the solar energy is the optimum choice for future green energy investment projects followed by other sources likely hydropower, biomass and biogas, and it also suggests that exhausted source is replaced by the available sources for future clean energy planning. Based on the study findings, this research also provides guidelines for Tripura’s green energy expansion policy for practice. The uniqueness of the present research is to ascertain the relationship between needs and strategies by taking opinions from experts as well as residents.

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Abbreviations

GES:

Green energy sources

AHP:

Analytical Hierarchy Process

OWA:

Ordered Weighted Averaging

VIKOR:

Vlsekriterijuska Optimizacija I Komoromisno Resenje (Multi-criteria Optimization and Comoros Solution)

ANP:

Analytic Network Process

TOPSIS:

Technique for Order of Preference by Similarity to Ideal Solution

PROMETHEE:

Preference Ranking Organisation Method for Enrichment Evaluations

GHG:

Greenhouse gas

MCGP:

Multi-Choice Goal Programming

MCA:

Multi-Criteria Analysis

O&M:

Operation & maintenance

MAVT:

Multi-Attribute Value Theory

MULTIMOORA:

Multi-Objective Optimization by Ratio Analysis plus the full multiplicative form

COPRAS:

Complex Proportional Assessment

ELECTRE:

Elimination and Choice Expressing Reality

WLC:

Weighted Linear Combination

DEMATEL:

Decision Making Trial and Evaluation Laboratory

SWARA:

Stepwise Weight Assessment Ratio Analysis

WASPAS:

Weighted Aggregated Sum Product Assessment

EVAMIX:

Evaluation of Mixed Data

SWOT:

Strength, Weakness, Opportunities, Threats

WSM:

Weight Sum Model

MOOSRA:

Multi-Objective Optimization on The Basis of Simple Ratio Analysis

ARAS:

Additive Ratio Assessment

BOCR:

Benefits, Opportunities, Costs and Risks

TRs:

Technical Requirements

CRs:

Customer Requirements

QFD:

Quality Function Deployment

HOQ:

House of Quality

TREDA:

Tripura Renewable Energy Development Organization

PC:

Pairwise Comparison

PV:

Priority Values

CSI:

Customer Satisfaction Index

CO2 :

Carbon dioxide

MNRE:

Ministry of New and Renewable Energy

AFM:

Attribute Factor Measure

AFD:

Attribute Factor Dimensions

NWFM:

Normalized Weight Factor Measure Missing

\({A}_{1}\) :

Consumption

\({A}_{2}\) :

Consumption

\({A}_{3}\) :

Acceptability

\({A}_{4}\) :

Energy autarky

\({A}_{5}\) :

Cost effectiveness

\({A}_{6}\) :

Use of green energy

\({C}_{1}\) :

Energy needs

\({C}_{2}\) :

Management

\({C}_{3}\) :

Energy production

\({C}_{4}\) :

Emission reduction

\({C}_{5}\) :

Scope of fossil resources and firewood

\({C}_{6}\) :

Soundness in the face of external changes

\({M}_{1}\) :

Solar

\({M}_{2}\) :

Hydropower

\({M}_{3}\) :

Biogas

\({M}_{4}\) :

Biomass

\(k\) :

Perception of the decision maker

\(n\) :

Number of energy source alternatives

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Acknowledgement

The authors would like to thank Department of Science, Technology and Environment Government of Tripura, and Tripura Renewable Energy Development Agency (TREDA) for their insightful help to collect the data. The authors also would like to thank the anonymous reviewers and the editor for their insightful comments and suggestions.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Faculty of Engineering & Technology, Parul Institute of Engineering & Technology, Parul University, Vadodara, Gujarat, 391760, India

    Chiranjib Bhowmik

  2. Department of Mechanical Engineering, National Institute of Technology, Silchar, Assam, 788010, India

    Sumit Bhowmik

  3. Department of Mechanical Engineering, Jalpaiguri Government Engineering College, Jalpaiguri, West Bengal, 735102, India

    Amitava Ray

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Bhowmik, C., Bhowmik, S. & Ray, A. Selection of optimum green energy sources by considering environmental constructs and their technical criteria: a case study. Environ Dev Sustain 23, 13890–13918 (2021). https://doi.org/10.1007/s10668-021-01244-z

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