Factors Hindering Solar Photovoltaic System Implementation in Buildings and Infrastructure Projects: Analysis through a Multiple Linear Regression Model and Rule-Based Decision Support System

被引:3
|
作者
Mustafa, Mansoor [1 ]
Malik, Muhammad Omer Farooq [1 ]
机构
[1] Sir Syed Ctr Adv Studies Engn CASE, Islamabad 444000, Pakistan
关键词
renewable energy; buildings; infrastructure solar PV; barriers; multiple linear regression model (MLRM); rule-based decision support system (RBDSS); ENERGY DEVELOPMENT; DEVELOPING-COUNTRIES; WIND ENERGY; BARRIERS; PV; POWER; ELECTRICITY; ISSUES; OPPORTUNITIES; CHALLENGES;
D O I
10.3390/buildings13071786
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Energy plays a predominant role in the development of society. With advancements in technology and the growth of society (buildings and infrastructures), the demand for energy is rapidly increasing. Developing countries typically rely on the import of fossil fuels and capital investments in infrastructure development to meet their energy needs. The execution of solar PV projects in developing countries is currently not being implemented promisingly. Therefore, the determination of the critical success factors hindering the implementation of solar PV projects is the need of the hour. The aim of this study is to determine the factors that hinder the implementation of solar PV projects through the use of a multiple linear regression model (MLRM) and a rule-based decision support system (RBDSS). Seven categories of factors were identified through a detailed literature review and interviews with energy experts. Four hundred and twenty-nine complete responses were collected in total through a questionnaire, and they were analyzed using relative importance indexing (RII) and MLRM and RBDSS approaches. A comparison was carried out against both methodologies to determine the most critical barriers to the implementation of solar PV projects. The findings regarding the MLRM approach showed that the top seven critical factors were economic conditions, encouraging policies, technological knowledge, organizational support, social awareness, market stability, and miscellaneous aspects. Similarly, the results for the RBDSS approach identified that the top seven critical factors were encouraging policies, economic conditions, organizational support, technological knowledge, market stability, social awareness, and miscellaneous aspects. The application of MLRM and RBDSS will help stakeholders in making timely decisions and corrections during the implementation phase, providing a systematic way to support the performance and execution of solar projects.
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页数:19
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  • [2] A Rule-Based Decision Support System for Critical Infrastructure Management
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    [J]. BEYOND EXPERIENCE IN RISK ANALYSIS AND CRISIS RESPONSE, 2011, 16 : 263 - 269
  • [3] A rule-based decision support system for evaluating and selecting IS projects
    Deng, Hepu
    Wibowo, Santoso
    [J]. IMECS 2008: INTERNATIONAL MULTICONFERENCE OF ENGINEERS AND COMPUTER SCIENTISTS, VOLS I AND II, 2008, : 1962 - 1968
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    de Castro, Joel T.
    Salistre, Gabriel M., Jr.
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    Gerardo, Bobby D.
    [J]. WORLD CONGRESS ON ENGINEERING AND COMPUTER SCIENCE, WCECS 2013, VOL II, 2013, Ao, : 802 - +
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    Ocampo-Melgar, Anahi
    Valls, Aida
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  • [7] UNIFICATION OF LINEAR-PROGRAMMING WITH A RULE-BASED SYSTEM BY THE POST-MODEL ANALYSIS APPROACH
    LEE, JK
    SONG, YU
    [J]. MANAGEMENT SCIENCE, 1995, 41 (05) : 835 - 847
  • [8] Enhancing the Efficiency of a Decision Support System through the Clustering of Complex Rule-Based Knowledge Bases and Modification of the Inference Algorithm
    Nowak-Brzezinska, Agnieszka
    [J]. COMPLEXITY, 2018,
  • [9] An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming
    da Silva, CG
    Figueira, J
    Lisboa, J
    Barman, S
    [J]. OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2006, 34 (02): : 167 - 177
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    Zhang, Kai
    [J]. JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2019, 9 (03) : 408 - 417