A framework of service-oriented operation model of China׳s power system

Zhou, Kaile; Yang, Shanlin

doi:10.1016/j.rser.2015.05.041

Cited by 17 publications

(6 citation statements)

References 46 publications

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“…Also, business systems like smart home, smart building and smart community are widely connected. With the deep penetration of advanced sensing, metering, communication and computing technologies, energy systems are digitalized [127][128][129][130]. Thus, the available energy big data become an important kind of resource, which can better support energy product and service providers to understand the requirements and needs of customers and to develop targeted marketing strategies [11,49].…”

Section: Business Model and Service Model Innovations Of Energy Internetmentioning

confidence: 99%

Energy Internet: The business perspective

2016

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Section: Business Model and Service Model Innovations Of Energy Internetmentioning

confidence: 99%

Energy Internet: The business perspective

2016

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“…Cloud computing is another important aspect of SG. This even produced the term 'cloud grid' in China, which integrates the nation's power system with big data analysis facilities, IoT, information and communication technologies, and of course, cloud computing [225]. Security concerns regarding cloud based infrastructure have been addressed previously in [226] and [227].…”

Section: B Counter-measures For Cyber-threatsmentioning

confidence: 99%

Application of Big Data and Machine Learning in Smart Grid, and Associated Security Concerns: A Review

et al. 2019

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This paper conducts a comprehensive study on the application of big data and machine learning in the electrical power grid introduced through the emergence of the next-generation power system-the smart grid (SG). Connectivity lies at the core of this new grid infrastructure, which is provided by the Internet of Things (IoT). This connectivity, and constant communication required in this system, also introduced a massive data volume that demands techniques far superior to conventional methods for proper analysis and decision-making. The IoT-integrated SG system can provide efficient load forecasting and data acquisition technique along with cost-effectiveness. Big data analysis and machine learning techniques are essential to reaping these benefits. In the complex connected system of SG, cyber security becomes a critical issue; IoT devices and their data turning into major targets of attacks. Such security concerns and their solutions are also included in this paper. Key information obtained through literature review is tabulated in the corresponding sections to provide a clear synopsis; and the findings of this rigorous review are listed to give a concise picture of this area of study and promising future fields of academic and industrial research, with current limitations with viable solutions along with their effectiveness.

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“…In this section, a serial of evaluation indices for the cloud computing applications of ESMS is proposed from three aspects of switching capability of network architecture A 11 , fast response capability of memory architecture A 12 , and virtual ability A 13 . The indices are summarized in Table 1.…”

Section: Evaluation Index Of a Cp Based Esmsmentioning

confidence: 99%

“…The contemporaneous research involves in the definition [9], data storage [10,11], and load evaluation [12]. K. Zhou [13] proposes a new cloud-based power system operation model. In power systems, especially in the application of ESMS, it is critical to improve the performance and service level through cloud computing [14].…”

Section: Introductionmentioning

confidence: 99%

An Improved Interval AHP Method for Assessment of Cloud Platform-based Electrical Safety Monitoring System

Ge¹,

Wang²,

Cai³

et al. 2017

Journal of Electrical Engineering and Technology

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-Electrical safety monitoring System (ESMS) is a critical component in modern power systems, which is characterized by large-scale access points, massive users and versatile requirements. For convenience of the information integration and analysis, the software development, maintenance, and application in the system, the cloud platform based ESMS is established and assessed in this paper. Firstly the framework of the system is proposed, and then the assessment scheme with a set of evaluation indices are presented, by which the appropriate cloud product can be chosen to meet the requirements of a specific application. Moreover, to calculate the weights of the evaluation indices under uncertainty, an improved interval AHP method is adopted to take into consideration of the fuzziness of expert scoring, the qualitative consistency test, and the two normalizations in the process of eigenvectors. Case studies have been made to verify the feasibility of the assessment approach for ESMS.

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A framework of service-oriented operation model of China׳s power system

Cited by 17 publications

References 46 publications

Energy Internet: The business perspective

Energy Internet: The business perspective

Application of Big Data and Machine Learning in Smart Grid, and Associated Security Concerns: A Review

An Improved Interval AHP Method for Assessment of Cloud Platform-based Electrical Safety Monitoring System

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