Renewable energy system paradigm change from trending technology: a review

被引：10

作者：

Khare, Vikas ^{[1
]}

Khare, Cheshta ^{[2
]}

Nema, Savita ^{[3
]}

Baredar, Prashant ^{[4
]}

机构：

[1] NMIMS, Sch Technol Management & Engn, Indore, Madhya Pradesh, India

[2] SGSITS, Dept Elect Engn, Indore, Madhya Pradesh, India

[3] MANIT, Dept Elect, Bhopal, India

[4] MANIT, Energy Ctr, Bhopal, India

来源：

INTERNATIONAL JOURNAL OF SUSTAINABLE ENERGY | 2021年 / 40卷 / 07期

关键词：

Renewable energy; artificial intelligence; internet of things; cloud computing; big data; game theory; ARTIFICIAL-INTELLIGENCE METHODS; BIG DATA; SOCIAL ACCEPTANCE; SOLAR-RADIATION; ECONOMIC-GROWTH; SMART CONTRACT; HYBRID SYSTEM; MANAGEMENT; PREDICTION; OPTIMIZATION;

D O I：

10.1080/14786451.2020.1860043

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Green technology or renewable energy system (RES) is an advancement of the electricity generation which creates pollution free environment. Since last 15-20 years, renewable power plant works in the traditional way over the world and needs technology enhancement. This paper presents a complete review of application of recent advanced technology in the field of RES. The paper analyses and discusses the potential application of artificial intelligence, the internet of things, cloud computing, big data, blockchain and game theory in the area of RESs such as solar energy, wind energy, biomass energy, etc. At the end of this paper, the ordinal assessment of application of recent technology for different objectives of RES is presented.

引用

页码：697 / 718

页数：22

共 89 条

[1]

Abdullah A. H., 2019, IEEE IND APPL SOC AN

[2]

Al-Ali A.R., 2019, J. Electr. Sci. Technol., V17, DOI [10.1016/j.jnlest.2020.100017, DOI 10.1016/J.JNLEST.2020.100017]

[3] A computational workflow to analyse material properties and solar radiation of existing contexts from attribute information of point cloud data [J].

Alkadri, Miktha Farid ;

Turrin, Michela ;

Sariyildiz, Sevil .

BUILDING AND ENVIRONMENT, 2019, 155 :268-282

[4] Blockchain technology in the energy sector: A systematic review of challenges and opportunities [J].

Andoni, Merlinda ;

Robu, Valentin ;

Flynn, David ;

Abram, Simone ;

Geach, Dale ;

Jenkins, David ;

McCallum, Peter ;

Peacock, Andrew .

RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2019, 100 :143-174

[5] Renewable energy sources: Using PROMETHEE II for ranking websites to support market opportunities [J].

Andreopoulou, Zacharoula ;

Koliouska, Christiana ;

Galariotis, Emilios ;

Zopounidis, Constantin .

TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2018, 131 :31-37

[6]

[Anonymous], 2011, 2011 IEEE Trondheim PowerTech

[7] Designing local renewable energy communities to increase social acceptance: Evidence from a choice experiment in Austria, Germany, Italy, and Switzerland [J].

Azarova, Valeriya ;

Cohen, Jed ;

Friedl, Christina ;

Reichl, Johannes .

ENERGY POLICY, 2019, 132 :1176-1183

[8] A Hybrid Intelligent System to forecast solar energy production [J].

Basurto, Nuno ;

Arroyo, Angel ;

Vega, Rafael ;

Quintian, Hector ;

Luis Calvo-Rolle, Jose ;

Herrero, Alvaro .

COMPUTERS & ELECTRICAL ENGINEERING, 2019, 78 :373-387

[9] Research on the social acceptance of renewable energy technologies: Past, present and future [J].

Batel, Susana .

ENERGY RESEARCH & SOCIAL SCIENCE, 2020, 68

[10]

Bayens E., 2011, IEEE T POWER SYST, V28

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