Big Data Management of Smart City Energy Conservation and Emission Reduction

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

Chapter Chapter 7 in Big Data in Energy Economics, 2022, pp 169-195 from Springer

Abstract: Abstract Smart city is the inevitable direction of urban development. As an important part of healthy and green urban development, energy conservation and emission reduction are closely related to the sustainable development of the urban economy. Load identification technology is one of the core technical difficulties to be solved in realizing the overall layout planning of the smart power grid. Statistics show that with the information provided by the non-intrusive load monitoring system, the energy costs can be cut down by 10–15%. This chapter introduces the load identification methods mainly around three methods. Besides, smart grid construction is a necessary means of urban power consumption behavior management, energy conservation, and emission reduction implementation. It is a general trend to apply the construction technology of smart grid to smart city planning, which is conducive to the transparency of the intelligent target of distribution network and more guarantee of urban power supply. The implementation of smart grid technology helps to improve the overall operational efficiency of the distribution network, achieve the effect of all-around monitoring, and improve the quality of voltage acquisition. This chapter gives feasible suggestions from two aspects of urban power consumption behavior planning, energy conservation, and emission reduction efficiency, to promote urban smart grid construction.

Keywords: Energy saving; Load identification; Smart city electricity behavior; Emission reduction (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/978-981-16-8965-9_7

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