Big Data Analysis of Energy Economics in Photovoltaic Power Generation Market

Hui Liu (), Nikolaos Nikitas (), Yanfei Li () and Rui Yang ()
Additional contact information
Hui Liu: Central South University
Nikolaos Nikitas: University of Leeds
Yanfei Li: Hunan Agricultural University
Rui Yang: Central South University

Chapter Chapter 5 in Big Data in Energy Economics, 2022, pp 117-136 from Springer

Abstract: Abstract As a clean, renewable energy, photovoltaic power generation has a rapid growth in its application range and installed capacity, and has provided great help for alleviating the energy crisis. Developing photovoltaic power generation can exploit the untapped and abundant solar energy resources and contribute to regional economic development. However, photovoltaic power generation systems still face many challenges such as randomness, uncertainty, and intermittence. The fluctuations and instability can easily cause impact and affect stability. In addition, it will increase the difficulty of the economic dispatch of the power system. This chapter first introduces the photovoltaic power generation system, then discusses and summarizes the big data prediction technology in the system, and gives prediction examples. An economic dispatch model involving photovoltaic power generation is sequentially presented, and finally, the solving algorithm is discussed.

Keywords: Photovoltaic power generation; Power forecasting; Deep learning; Economic dispatch model; Multi-objective optimization (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:mgmchp:978-981-16-8965-9_5

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DOI: 10.1007/978-981-16-8965-9_5

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