Intelligent data-driven modelling and optimization in power and energy applications/ edited by B Rajanarayan Prusty, Neeraj Gupta, Kishore Bingi, and Rakesh Sehgal.

Includes index.

Chapter 1 - Preprocessing approaches for data-driven modellingKishore Bingi, B. Rajanarayan Prusty, and Neeraj GuptaChapter 2 - Power system planning using data-driven modelsB. Rajanarayan Prusty, Sujith Jacob, and Kishore BingiChapter 3 - Data-driven analytics for power system stability assessmentPurna Prakash Kasaraneni, Yellapragada Venkata Pavan Kumar, and Ramani KannanChapter 4 - Data-driven machine learning models for load power forecasting in photovoltaic systemsPrem Prakash Vuppuluri, K. Pritam Satsangi, Pihu Agarwal, and Tania AroraChapter 5 - Forecasting of renewable energy using fractional-order neural networksBhukya Ramadevi, Venkata Ramana Kasi, Kishore Bingi, B. Rajanarayan Prusty, and Madiah OmarChapter 6 - Data-driven photovoltaic system characteristic determination using non-linear system identificationYellapragada Venkata Pavan Kumar, Challa Pradeep Reddy, Ramani Kannan, and Purna Prakash KasaraneniChapter 7 - Fractional feed-forward neural network-based smart grid stability prediction modelBhukya Ramadevi, Venkata Ramana Kasi, Kishore Bingi, Rosdiazli Ibrahim, and B. Rajanarayan PrustyChapter 8 - Data-driven optimization framework for microgrid energy managementMohamed Atef, Moslem Uddin, Md Masud Rana, Md Rasel Sarkar, and G.M. ShafiullahChapter 9 - Optimization of controllers for sustained buildingGaurav KumarChapter 10 - Intelligent data-driven approach for fractional-order wireless power transfer systemArshaque Ali, Ashneel Kumar, Utkal Mehta, and Maurizio Cirrincione