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Yi Ding

Researcher at Zhejiang University

Publications -  320
Citations -  7102

Yi Ding is an academic researcher from Zhejiang University. The author has contributed to research in topics: Electric power system & Reliability (statistics). The author has an hindex of 33, co-authored 280 publications receiving 4670 citations. Previous affiliations of Yi Ding include University of Copenhagen & Nanyang Technological University.

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Multi-state System Reliability Analysis and Optimization for Engineers and Industrial Managers

TL;DR: In this article, the authors used UGF and stochastic process methods for MSS Reliability Assessment and Statistical Analysis of Reliability Data for Real-world MSS's Universal Generating Function (UGF) Models Combined UFG and Stochastic Process Technique Aging Multi-state Systems Reliability Associated Costs for Multi-State Systems and Optimal Management Decisions Fuzzy multi-state System
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Review of real-time electricity markets for integrating Distributed Energy Resources and Demand Response

TL;DR: In this article, a review of typical typical RTMs in North America, Australia and Europe, focusing on their market architectures and incentive policies for integrating distributed energy resources (DER) and demand response (DR) in electricity markets is presented.
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5G network-based Internet of Things for demand response in smart grid: A survey on application potential

TL;DR: This paper’s application survey of 5G on DR is carried out before 5G technology enters the large-scale commercial stage, so as to provide references and guidelines for developing future 5G networks in the smart grid paradigm.
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Fuzzy universal generating functions for multi-state system reliability assessment

TL;DR: A special technique for reliability assessment of multi-state MSSs where performance rates or/and corresponding state probabilities are presented as fuzzy values is developed.
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Modeling and Integration of Flexible Demand in Heat and Electricity Integrated Energy System

TL;DR: This paper is focused on utilizing customers’ flexible energy demand, including both heat demand and electricity demand, to provide balancing resources and relieve the difficulties of integrating variable wind power with the combined heat and power.