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Journal articles on the topic 'Smarth energy'

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Author: Grafiati

Published: 14 March 2023

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1

Babu, A. Narendra, Ch V. L. D. Kavya, A. Praneetha, T. T. Sai Dhanush, T. V. Ramanaiah, K. Nidheesh, and P. S. Brahmanandam. "Smart Energy Meter." Indian Journal Of Science And Technology 15, no. 29 (August 5, 2022): 1451–57. http://dx.doi.org/10.17485/ijst/v15i29.1241.

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Ryu, Sung Uk, Hwang Bae, Jin Hwa Yang, Byong Guk Jeon, Eun Koo Yun, Jaemin Kim, Yoon Gon Bang, Myung Joon Kim, Sung-Jae Yi, and Hyun-Sik Park. "An Experimental Study on Flow Distributor Performance with Single-Train Passive Safety System of SMART-ITL." Journal of Energy Engineering 25, no. 4 (December 30, 2016): 124–32. http://dx.doi.org/10.5855/energy.2016.25.4.124.

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3

Tharuka Lulbadda, Kushan, and K. T. M. U. Hemapala. "The additional functions of smart inverters." AIMS Energy 7, no. 6 (2019): 971–88. http://dx.doi.org/10.3934/energy.2019.6.971.

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4

Aleksandrovich, Panfilov Stepan. "Energy Efficient System "Smart House"." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (July 25, 2020): 260–62. http://dx.doi.org/10.5373/jardcs/v12sp7/20202106.

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5

Shinde, Mrs Sandhya, Mr Yogesh Yadav, and Miss Bharti Sontakke Miss Pratiksha Zapake. "IoT Based Smart Energy Meter." International Journal of Trend in Scientific Research and Development Volume-1, Issue-6 (October 31, 2017): 1151–53. http://dx.doi.org/10.31142/ijtsrd5761.

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6

Joshi, Dr Shreedhar A., Srijay Kolvekar, Y. Rahul Raj, and Shashank Singh Singh. "IoT Based Smart Energy Meter." Bonfring International Journal of Research in Communication Engineering 6, Special Issue (November 30, 2016): 89–91. http://dx.doi.org/10.9756/bijrce.8209.

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Kavousi-Fard, Abdollah, and Amin Khodaei. "Multi-objective optimal operation of smart reconfigurable distribution grids." AIMS Energy 4, no. 2 (2016): 206–21. http://dx.doi.org/10.3934/energy.2016.2.206.

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D’Alpaos, Chiara, and Michele Moretto. "Do Smart grids innovation affect real estate market values?" AIMS Energy 7, no. 2 (2019): 141–50. http://dx.doi.org/10.3934/energy.2019.2.141.

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K., Dr Shanthi. "IoT based Smart Energy Theft Detection System in Smart Home." Journal of Advanced Research in Dynamical and Control Systems 12, SP8 (July 30, 2020): 605–13. http://dx.doi.org/10.5373/jardcs/v12sp8/20202561.

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10

Solovey, V., V. Filenko, F. Tinti, A. Shevchenko, and M. Zipunnikov. "Smart PV-H2 grid energy complex." Journal of Mechanical Engineering 20, no. 3 (September 30, 2017): 49–53. http://dx.doi.org/10.15407/pmach2017.03.049.

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Collado, Edwin, Easton Li Xu, Hang Li, and Shuguang Cui. "Profit maximization with customer satisfaction control for electric vehicle charging in smart grids." AIMS Energy 5, no. 3 (2017): 529–56. http://dx.doi.org/10.3934/energy.2017.3.529.

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12

Pawar, Prakash, and Panduranga Vittal K. "Performance analysis of a smart meter node for congestion avoidance and LoS coverage." AIMS Energy 7, no. 3 (2019): 313–36. http://dx.doi.org/10.3934/energy.2019.3.313.

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Prasad, Hari, Lakshmipathi S, Nelson John Antony D, Vishwas C, and Subhashini S. "SMART POWER GENERATION WITH RENEWABLE ENERGY SOURCES." International Journal of Current Engineering and Scientific Research 6, no. 6 (June 2019): 126–38. http://dx.doi.org/10.21276/ijcesr.2019.6.6.22.

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14

Khan Khadem, Shafiuzzaman, Malabika Basu, and Michael F. Conlon. "Capacity enhancement and flexible operation of unified power quality conditioner in smart and microgrid network." AIMS Energy 6, no. 1 (2018): 49–69. http://dx.doi.org/10.3934/energy.2018.1.49.

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Echeverri-Martínez, Ricardo, Wilfredo Alfonso-Morales, and Eduardo F. Caicedo-Bravo. "A methodological Decision-Making support for the planning, design and operation of smart grid projects." AIMS Energy 8, no. 4 (2020): 627–51. http://dx.doi.org/10.3934/energy.2020.4.627.

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Rizzo, Santi Agatino. "Editorial to the 'Special Issue—Distribution network reliability in Smart Grids and Microgrids' of AIMS Energy." AIMS Energy 10, no. 3 (2022): 533–34. http://dx.doi.org/10.3934/energy.2022026.

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17

Mansour,, Atef M., Khaled N. Faris,, and Essam El-Din Aboul Zahab. "Smart Energy Management controller for a Micro Grid." International Journal of Engineering Research 4, no. 8 (August 1, 2015): 456–64. http://dx.doi.org/10.17950/ijer/v4s8/811.

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18

Lund, Henrik, Poul Alberg Østergaard, David Connolly, and Brian Vad Mathiesen. "Smart energy and smart energy systems." Energy 137 (October 2017): 556–65. http://dx.doi.org/10.1016/j.energy.2017.05.123.

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19

Shigenobu, Ryuto, Oludamilare Bode Adewuyi, Atsushi Yona, and Tomonobu Senjyu. "Demand response strategy management with active and reactive power incentive in the smart grid: a two-level optimization approach." AIMS Energy 5, no. 3 (2017): 482–505. http://dx.doi.org/10.3934/energy.2017.3.482.

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20

M.S, Mr Muneshwara, Dr Anil G.N, and Dr Thungamani M. "Reducing Energy Consumption in Smart System through Mobilouds Framework." International Journal of Trend in Scientific Research and Development Volume-2, Issue-1 (December 31, 2017): 627–35. http://dx.doi.org/10.31142/ijtsrd6998.

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21

Nadia, Awatif, Md Sanwar Hossain, Md Mehedi Hasan, Sinthia Afrin, Md Shafiullah, Md Biplob Hossain, and Khondoker Ziaul Islam. "Determination of transmission reliability margin for brownout." AIMS Energy 9, no. 5 (2021): 1009–26. http://dx.doi.org/10.3934/energy.2021046.

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<abstract> <p>Power shortage is a severe problem in developing countries that are rolling to blackout, but today smart grids have the scope to avoid entire blackouts by transforming them into brownouts. A brownout is an under-voltage condition where the AC supply drops below the nominal value (120 V or 220 V) by about 10%. In a power system network, power shortages or disturbances can occur at any time, and the reliability margin analysis is essential to maintain the stability of the system. Transmission reliability margin (TRM) is a margin that keeps the network secure during any occurrence of disturbance. This paper presents a new approach to compute TRM in the case of brownout. The detailed assessment of TRM largely depends on the estimation of the available transfer power (ATC). In this method, the ATC of the system is calculated considering the effect of alternating current (AC) and direct current (DC) reactive power (Q) flow (DCQF). The entire procedure is carried out for the multi-transaction IEEE-6 bus system, and the results are compared to the current efficiency justification method. Numerical results demonstrate that the proposed technique is an effective alternative for calculating the TRM and is valid compared to the existing technique.</p> </abstract>

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22

Nareshkumar, R., B. J. Naveenkumar, and R. Sivasankari. "IoT - Internet of Things Based Energy Management for Smart Home." International Journal of Trend in Scientific Research and Development Volume-2, Issue-2 (February 28, 2018): 1539–42. http://dx.doi.org/10.31142/ijtsrd10764.

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23

Arthur, Emmanuel. "Energy development: A global perspective and advances in Ghana." AIMS Energy 10, no. 2 (2022): 306–39. http://dx.doi.org/10.3934/energy.2022017.

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<abstract> <p>Climate change, population increase, and urbanisation present severe threats to energy security throughout the world. As a result, governments all over the world have made significant investments in diversifying and developing local energy systems, notably in the renewable energy sector. In this light, this review was conducted to analyse the production trends of fossil energy, renewable energy and nuclear energy, as well as the impact of renewable energy production on fossil energy production, between 2000 and 2021. Using correlation and regression analysis, the relationship between these energy sources and the impact of renewable energy on fossil energy production were studied and then measured against similar studies in the literature. The findings showed an increasing trend in fossil energy and renewable energy production and a slightly decreasing trend in nuclear energy production from 2000 to 2021. In addition, there was a significant impact of renewable energy production on fossil energy production in the last two decades. In Ghana, it was found that the addition of solar energy generation to the national grid significantly influenced thermal energy generation. On the whole, renewable energy production has significantly increased over the last decades, and it has the potential to reduce the dependence on fossil energy if effectively developed and managed.</p> <p>Therefore, future energy development should focus on more research and development in the area of smart and efficient renewable energy technologies.</p> </abstract>

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24

Nasiakou, Antonia, Manolis Vavalis, and Dimitris Zimeris. "Smart energy for smart irrigation." Computers and Electronics in Agriculture 129 (November 2016): 74–83. http://dx.doi.org/10.1016/j.compag.2016.09.008.

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25

Lizar, Nickolaus Reinaldy. "PENERAPAN KONSEP BANGUNAN CERDAS PADA DESAIN HUNIAN PADAT DI KAPUK." Jurnal Sains, Teknologi, Urban, Perancangan, Arsitektur (Stupa) 3, no. 1 (May 30, 2021): 455. http://dx.doi.org/10.24912/stupa.v3i1.10910.

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The project is located in the Kapuk area, Cengkareng District, West Jakarta. This project was motivated by population density problems which created a land and energy crisis in this area. So, with that, this smart building project was created with the aim of forming a compact residential unit that can accommodate many residents and creating a smart building system that can make energy independently for residential needs. In designing this project a contextual method was used to position the building so that it was in harmony with the existing environmental conditions. Where the original site and environmental conditions will form the basis of the concept in building the project. The smart building design strategy uses the concept of compact units to maximize efficient land use. And in answering the energy crisis problem, a building with a smart building concept is needed, which is needed to ease the use of natural resources with self-recycled energy in the project. So that the project does not depend on energy from outside, but can create its own energy through recycling systems, such as water filtration systems, solar power systems, and biogas systems. Keywords : Compact Residential Unit; Smart Building; Smart Energy System AbstrakProyek berada di kawasan Kapuk, Kecamatan Cengkareng, Jakarta Barat. Proyek ini dilatarbelakangi oleh permasalahan kepadatan penduduk yang menciptakan krisis lahan dan energi di kawasan tersebut. Proyek bangunan cerdas ini bertujuan untuk membentuk sebuah hunian unit padat yang dapat menampung banyak penghuni dan menciptakan sistem bangunan cerdas yang dapat membuat energi mandiri untuk kebutuhan berhuni. Dalam merancang proyek ini metode kontekstual digunakan untuk memposisikan bangunan agar selaras dengan kondisi lingkungan yang sudah lebih dulu ada. Dimana kondisi asal tapak dan lingkungan akan menjadi dasar konsep dalam membangun proyek. Strategi desain bangunan cerdas menggunakan konsep unit padat untuk memaksimalkan penggunaan lahan hunian secara efisien. Dalam menjawab masalah krisis energi digunakan konsep bangunan cerdas untuk meringankan penggunaan sumber daya alam dengan energi daur ulang mandiri di dalam proyek. Sehingga bangunan tidak bergantung terhadap energi dari luar, melainkan dapat menciptakan energinya sendiri melalui sistem-sistem daur ulang, seperti sistem filtrasi air, sistem tenaga surya, dan sistem biogas.

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26

Musau, Stephen K., Kathrin Stahl, Kevin Volkmer, Nicholas Kaufmann, and Thomas H. Carolus. "A design and performance prediction method for small horizontal axis wind turbines and its application." AIMS Energy 9, no. 5 (2021): 1043–66. http://dx.doi.org/10.3934/energy.2021048.

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<abstract> <p>The paper deals with small wind turbines for grid-independent or small smart grid wind turbine systems. Not all small turbine manufacturers worldwide have access to the engineering capacity for designing an efficient turbine. The objective of this work is to provide an easy-to-handle integrated design and performance prediction method for wind turbines and to show exemplary applications.</p> <p>The underlying model for the design and performance prediction method is based on an advanced version of the well-established blade-element-momentum theory, encoded in MATLAB™. Results are (i) the full geometry of the aerodynamically profiled and twisted blades which are designed to yield maximum power output at a given wind speed and (ii) the non-dimensional performance characteristics of the turbine in terms of power, torque and thrust coefficient as a function of tip speed ratio. The non-dimensional performance characteristics are the basis for the dimensional characteristics and the synthesis of the rotor to the electric generator with its load.</p> <p>Two parametric studies illustrate typical outcomes of the design and performance prediction method: A variation of the design tip speed ratio and a variation of the number of blades. The predicted impact of those parameters on the non-dimensional performance characteristics agrees well with common knowledge and experience.</p> <p>Eventually, an interplay of various designed turbine rotors and the given drive train/battery charger is simulated. Criterions for selection of the rotor are the annual energy output, the rotor speed at design wind speed as well as high winds, and the axial thrust exerted on the rotor by the wind. The complete rotor/drive train//battery charger assembly is tested successfully in the University of Siegen wind tunnel.</p> </abstract>

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27

Umer, Saher, Yasuo Tan, and Azman Osman Lim. "Stability Analysis for Smart Homes Energy Management System with Delay Consideration." Journal of Clean Energy Technologies 2, no. 4 (2014): 332–38. http://dx.doi.org/10.7763/jocet.2014.v2.150.

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28

Denysiuk, S. P., D. H. Derevianko, and H. S. Bielokha. "Improving the Quality of Electricity Supply in the Energy Smart Community with Sources of Distributed Generation." Visnyk of Vinnytsia Politechnical Institute 158, no. 5 (2021): 64–70. http://dx.doi.org/10.31649/1997-9266-2021-158-5-64-70.

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29

Limpraptono, F. Yudi, Eko Nurcahyo, and M. Ibrahim Ashari. "Design Smart Panel to Support Energy Conservation with Active Approach Methods." International Journal of Electrical Energy 7, no. 1 (June 2019): 36–39. http://dx.doi.org/10.18178/ijoee.7.1.36-39.

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30

S, Senthil, and Ravi K. "Simulation of Integration of Smart Power Grids Using Distributed Energy Sources." Journal of Advanced Research in Dynamical and Control Systems 11, no. 0009-SPECIAL ISSUE (September 25, 2019): 644–52. http://dx.doi.org/10.5373/jardcs/v11/20192617.

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31

Matei, Lucian, Ilie Dumitru, and Laurentiu Racila. "Smart Signalization and Public Transport Priority, a First Step to Smart Mobility in a Smart City." Applied Mechanics and Materials 880 (March 2018): 383–88. http://dx.doi.org/10.4028/www.scientific.net/amm.880.383.

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Smarty city is a current topic, growing very fast in the last years. This concept is linked as a winning strategy to solve some major problems of big cities, like pollution, traffic jams, energy consumption, etc. Smart city is the next level, a more complex concept of the much restrictive green city, being an extension of this one, involving a better urban zone, a smaller environmental footprint, a higher penetration of ICT in the city life. A very important component of a smart city is the urban mobility, a smart mobility in a smart city. The aim of the paper is the presentation of the first step in this direction, because a smart mobility involve a smart signalization first. To reduce the traffic jam in an cross junction, an adaptive signal master plan of the intersection are used, with the help of a dedicated software.

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32

Akare, Ujawal Rajhans, Adit Dilip Keole, Nikhil Santosh Bahakar, and Rohit Manohan Paunikar. "Smart Energy Meter." International Journal of Innovations in Engineering and Science 6, no. 7 (June 15, 2021): 01–03. http://dx.doi.org/10.46335/ijies.2021.6.7.1.

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33

Yoshida, Tsukasa, He Sun, and Ajit Khosla. "Smart energy systems." Semiconductor physics, quantum electronics and optoelectronics 22, no. 4 (November 8, 2019): 452–56. http://dx.doi.org/10.15407/spqeo22.04.452.

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34

Schmeck, Hartmut. "Smart Energy Systems." it - Information Technology 55, no. 2 (April 2013): 43–44. http://dx.doi.org/10.1524/itit.2013.9002.

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35

Amft, Oliver, Richard Medland, Marcus Foth, Petromil Petkov, Joana Abreu, Francisco Camara Pereira, Philip Johnson, Robert Brewer, James Pierce, and Eric Paulos. "Smart Energy Systems." IEEE Pervasive Computing 10, no. 1 (January 2011): 63–65. http://dx.doi.org/10.1109/mprv.2011.10.

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36

Titus, Elby. "Smart energy materials." International Journal of Hydrogen Energy 45, no. 17 (March 2020): 10269. http://dx.doi.org/10.1016/j.ijhydene.2020.02.047.

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37

Jose K, Jithin, Leneesh Mohan, Nijeesh U K, and Tony C Benny. "Smart Energy Meter." International Journal of Engineering Trends and Technology 22, no. 4 (April 25, 2015): 179–82. http://dx.doi.org/10.14445/22315381/ijett-v22p238.

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38

Dr. Ananth.J P and Premnath.S P, Dr Belsam Jeba Ananth M. "Smart Energy Meter." International Journal for Modern Trends in Science and Technology 6, no. 12 (December 4, 2020): 125–28. http://dx.doi.org/10.46501/ijmtst061224.

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In present time Electricity is the necessary thing in the world for human life. Today every home, offices, companies, industries have electricity connection. So here this project is building only for interfacing electricity energy meter with microcontrollers. The main aim of the project is identifying the current meter reading and intimating the user when they are crossing the certain limit. It also identifies the power theft and auto tripping will be done.Here, Arduino is used for interfacing and the main aim of this project is to know, how much unit is obtained and the total amount of rupees has to be paid. That will be sent to the EB office for billing. Excess power usage can also be monitored. Hence, power theft can be avoided. If bill is not paid in time, then it will automatically turn off the power.

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39

Nižetić, Sandro. "Smart energy technologies." International Journal of Energy Research 45, no. 1 (September 14, 2020): 5. http://dx.doi.org/10.1002/er.5952.

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40

Dincer, Ibrahim. "Smart energy solutions." International Journal of Energy Research 40, no. 13 (August 9, 2016): 1741–42. http://dx.doi.org/10.1002/er.3621.

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41

hadapad, Rahul basappa, Dr H. Ghanashyam Shenoy, Pruthvi H. M, and Sagar S. "DESIGN AND DEVELOPMENT OF ENERGY EFFICIENT DOMESTIC WATER HEATER USING SMART MATERIALS." International Journal of Current Engineering and Scientific Research 6, no. 6 (June 2019): 26–28. http://dx.doi.org/10.21276/ijcesr.2019.6.6.5.

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42

Nabati, Ali, Sayyed Majid Mazinani, and Iman Sariri Ajili. "A Novel Energy-Efficient Architecture Based on QoS for the Smart Grid." Journal of Clean Energy Technologies 3, no. 4 (2015): 247–53. http://dx.doi.org/10.7763/jocet.2015.v3.203.

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43

Joãozinho Sguarezi Filho, Alfeu, Carlos Eduardo Capovilla, Ivan R. S. Casella, Rogério Vani Jacomini, José Luis Azcue Puma, and Ernesto Ruppert Filho. "A Smart Grid Wireless Neuro-fuzzy Power Control For Wind Energy Systems." Eletrônica de Potência 18, no. 3 (August 1, 2013): 1022–29. http://dx.doi.org/10.18618/rep.2013.3.10221029.

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44

Alghamdi, Noof Awad, Israa Mohammed Budayr, Samar Mohammed Aljehani, and Majed Mohammed Aborokbah. "A Scheme for Predicting Energy Consumption in Smart Cities Using Machine Learning." Webology 19, no. 1 (January 20, 2022): 3481–99. http://dx.doi.org/10.14704/web/v19i1/web19230.

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Fluctuating result on weather condition throughout several decades became a global concern due to the direct or indirect effect on energy consumption, and that was well-defined in several sector. Research investigates the use of technology and the speed of obtaining information ، which helps in decision-making. This paper Emphasize the role of data science and their application to monitoring energy consumption, also, explain the importance used and challenges of Internet of Things (IoT). Thus, there is a global concern on data transformation from IoT devices when taking into account deferent weather variations. Cities are a critical part when of energy management, it presents the effect of urbanization and some of the success achievement in several cities around the world. Our Analysis indicate that three dissimilar types of sensors can detect massive amount of information up to four hundred thousand rows, compared to traditional methods for collecting data. The results depict the resilient of IOT performance which provide an aggregate of measures reach around 405,184 rows in a record time, with achieved accuracy up to 99% when implementing the decision tree algorithm, the outcome after applying the algorithm was vary 27.60 per-cent recorded by the first device while the other devices scored 26.14%,46.26% respectively, throughout different circumstances with continuous reading in a short period of times around 8 days.

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45

John, M. Mohammed. "Smart Energy Meter for Energy Conservation." International Journal for Research in Applied Science and Engineering Technology 7, no. 3 (March 31, 2019): 2456–57. http://dx.doi.org/10.22214/ijraset.2019.3450.

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46

G. Rajakumar. "Smart Home Energy Monitoring and Energy Reduction Technique." Journal of Electrical Engineering and Automation 4, no. 3 (October 15, 2022): 209–19. http://dx.doi.org/10.36548/jeea.2022.3.008.

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The concept of Home Energy Management System (HEMS) is emerged from the development of smart homes, which connect humans and things to automate the manual operations. The smart homes users enjoy secured, pleasant, and autonomously managed lifestyle. Additionally, smart homes have the potential to generate revenue by vending clean and sustainable energy to the grid, thereby saving both energy and money. The proposed method efficiently reschedules and arranges the power flow among grid electricity, storage devices, and photovoltaic models to manage the energy requirements of smart home. Energy-management systems is highly preferred to economic benefits of smart homes while maintaining a comfortable living, maximizing connectivity and developing optimized operation of loads. The proposed system is finally implemented in a simulation environment, and further the obtained outcomes demonstrate the efficiency of the proposed method in terms of energy management from various sources.

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47

Tantau, Adrian, and Ana-Maria Iulia Şanta. "New Energy Policy Directions in the European Union Developing the Concept of Smart Cities." Smart Cities 4, no. 1 (February 9, 2021): 241–52. http://dx.doi.org/10.3390/smartcities4010015.

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In the context of the European Union promoting clean energy, sustainability and better living conditions for its citizens, the development of smarts cities is an initiative supported at the European Union level, in line with the new energy policies of the European Union promoted by the package “Clean Energy for All Europeans”. The concept of smart cities gains increasing importance in the European Union, a fact that is reflected in the project “European Innovation Partnership on Smart Cities and Communities” of the European Commission. Smart cities are a practical example of how the new energy policies shape the lives of the European Union citizens, trying to improve it. As a consequence, new business models arise in big cities, involving the use of technology for better living conditions. These new, technology-based business models are important, as they improve the life quality of the inhabitants, they reduce the climate change impact, and they contribute as well to job creation in the IT-industry, promoting innovation. They have as well a social impact, as they bring experts from energy policies, business, economics, legal and IT together in order to project a new type of city—the smart city. The research hypothesis of the present article is that there is a high acceptance towards the concept of smart cities at the European Union level and that this concept could be implemented with the help of information technology and of artificial intelligence. This way, legal provisions, economic measures and IT-tools work together in order to create synergy effects for better life quality of the citizens of the European Union. The research hypothesis is analyzed by means of the questionnaire as a qualitative research method and is as well assessed by using case studies (e.g., Austria, Finland, Romania). The novelty of the case studies is that the development of smart cities is analyzed due to the new trend towards sustainability in two countries with different living conditions in the European Union.

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48

Sun, Mengxuan, Jinglin Zhao, and Heidan Shang. "Building Energy Consumption Prediction with Principal Component Analysis and Artificial Neural Network." International Journal of Electronics and Electrical Engineering 8, no. 2 (June 2020): 36–39. http://dx.doi.org/10.18178/ijeee.8.2.36-39.

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The implementation of the smart grid will greatly improve the efficiency of energy supply by detecting, predicting, and reacting to real-time local changes of energy uses. To this end, energy usage prediction of household buildings is critically important to facilitate the implementation of smart grid. This study used a single house as a prototype, employed different observed features, advanced data analysis approach, and artificial neural network model to predict real-time dynamics of house energy usage. Data analysis revealed that among the 26 observed features, only the top ten most important features were helpful and could maximize the neural network model performance. The resultant model has the great predictive capability on energy usage, thus provided a promising framework to improve the smart grid implementation.

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49

V, Prema, Amita Amita, Kruthishree T.R, and Pallavi C.S. "ENHANCEMENT OF POWER QUALITY IN WIND ENERGY SYSTEM AND IMPLEMENTATION OF SMART CURTAIN." International Journal of Current Engineering and Scientific Research 6, no. 6 (June 2019): 139–42. http://dx.doi.org/10.21276/ijcesr.2019.6.6.23.

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Banari, Ehsan, Sayyed Majid Mazinani, and Iman Sariri Ajili. "An Energy-Efficient and Low-Latency MAC Protocol in Smart Grid (SG-MAC)." Journal of Clean Energy Technologies 3, no. 4 (2015): 242–46. http://dx.doi.org/10.7763/jocet.2015.v3.202.

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