Artificial Intelligence and Machine Learning Based: Advances in Demand-Side Response of Renewable Energy-Integrated Smart Grid
Author:
Chaurasia KiranORCID, Kamath H. RavishankarORCID
Publisher
Springer Singapore
Reference42 articles.
1. Hafeez, G., Javaid, N., Zahoor, S., Fatima, I., Ali Khan, Z., Safeerullah: energy efficient integration of renewable energy sources in smart grid. In: Barolli, L., Zhang, M., Wang, X. (eds) Advances in Internetworking, Data and Web Technologies. EIDWT 2017. Lecture Notes on Data Engineering and Communications Technologies, vol. 6. Springer, Cham (2018). 2. Ahmadiahangar, R., Rosin, A., Palu, I., Azizi, A.: Challenges of Smart Grids Implementation. In: Demand-side Flexibility in Smart Grid. SpringerBriefs in Applied Sciences and Technology. Springer, Singapore (2020) 3. Yesilbudak, M., Colak, A.: Integration challenges and solutions for renewable energy sources, electric vehicles and demand-side initiatives in smart grids. In: 2018 7th International Conference on Renewable Energy Research and Applications (ICRERA), Paris, pp. 1407–1412 (2018) 4. Malik, A., Ravishankar, J.: A review of demand response techniques in smart grids. In: 2016 IEEE Electrical Power and Energy Conference (EPEC), Ottawa, ON, pp. 1–6 (2016) 5. Diahovchenko, I., Kolcun, M., Čonka, Z., Savkiv, V., Mykhailyshyn, R.: Progress and challenges in smart grids: distributed generation, smart metering, energy storage and smart loads. . Iran. J. Sci. Technol. Trans. Electr. Eng. 44, 1319–1333 (2020)
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
|
|