His primary areas of investigation include Electric power system, Reliability engineering, Mathematical optimization, Electricity and Reliability. The Electric power system study combines topics in areas such as Wind power, Operations management, Market clearing, Renewable energy and Operations research. His work on Failure rate as part of general Reliability engineering study is frequently connected to Evaluation algorithm, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Mathematical optimization research is multidisciplinary, incorporating elements of Reliability theory, System model, Fuzzy control system and Fuzzy set. The concepts of his Electricity study are interwoven with issues in Distributed generation, Stand-alone power system, Microeconomics and Smart grid. His biological study spans a wide range of topics, including Electrical network, Market structure, State and Fuzzy logic.
His primary scientific interests are in Electric power system, Reliability engineering, Electricity, Mathematical optimization and Reliability. His Electric power system research incorporates elements of Wind power, Demand response, Renewable energy and Air conditioning. The study incorporates disciplines such as Electricity generation, Monte Carlo method, Markov process and Reliability in addition to Reliability engineering.
His Electricity research incorporates themes from Production, Cogeneration and Reliability. His research in Mathematical optimization intersects with topics in Fuzzy logic, Convergence, Reliability theory and Electric power. His Reliability research is multidisciplinary, relying on both Probabilistic logic, State and Process.
His primary areas of study are Electric power system, Reliability engineering, Mathematical optimization, Electricity and Demand response. His work deals with themes such as Automatic frequency control, Renewable energy and Air conditioning, which intersect with Electric power system. His Reliability engineering research is multidisciplinary, incorporating perspectives in Operational reliability, Electricity generation, Reliability, Monte Carlo method and Reliability.
As part of one scientific family, he deals mainly with the area of Mathematical optimization, narrowing it down to issues related to the Electric power, and often Reliability theory. Yi Ding combines subjects such as Power usage, Cogeneration, Convolutional neural network and Data mining with his study of Electricity. His studies in Demand response integrate themes in fields like Distributed computing, Energy storage, Smart grid, Voltage and Scheduling.
Yi Ding mostly deals with Electric power system, Reliability engineering, Demand response, Smart grid and Distributed computing. His research on Electric power system often connects related topics like Air conditioning. His research integrates issues of Environmental economics, Electricity, Reliability and Renewable energy in his study of Air conditioning.
The various areas that Yi Ding examines in his Reliability engineering study include Electricity generation and Natural gas. His Demand response study integrates concerns from other disciplines, such as Photovoltaics, Telecommunications, Energy engineering and Tap changer. Yi Ding has included themes like Digitization, Key and Data analysis in his Smart grid study.
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Multi-state System Reliability Analysis and Optimization for Engineers and Industrial Managers
Anatoly Lisnianski;Ilia Frenkel;Yi Ding.
Review of real-time electricity markets for integrating Distributed Energy Resources and Demand Response
Qi Wang;Chunyu Zhang;Yi Ding;George Xydis.
Applied Energy (2015)
Fuzzy universal generating functions for multi-state system reliability assessment
Yi Ding;Anatoly Lisnianski.
Fuzzy Sets and Systems (2008)
Long-Term Reserve Expansion of Power Systems With High Wind Power Penetration Using Universal Generating Function Methods
Yi Ding;Peng Wang;L Goel;Poh Chiang Loh.
IEEE Transactions on Power Systems (2011)
Nodal market power assessment in electricity markets
Peng Wang;Yu Xiao;Yi Ding.
IEEE Transactions on Power Systems (2004)
Modeling and Integration of Flexible Demand in Heat and Electricity Integrated Energy System
Changzheng Shao;Yi Ding;Jianhui Wang;Yonghua Song.
IEEE Transactions on Sustainable Energy (2018)
Day-ahead tariffs for the alleviation of distribution grid congestion from electric vehicles
Niamh O’Connell;Qiuwei Wu;Jacob Østergaard;Arne Hejde Nielsen.
Electric Power Systems Research (2012)
Redundancy analysis for repairable multi-state system by using combined stochastic processes methods and universal generating function technique
Anatoly Lisnianski;Yi Ding.
Reliability Engineering & System Safety (2009)
A Convex Model of Risk-Based Unit Commitment for Day-Ahead Market Clearing Considering Wind Power Uncertainty
Ning Zhang;Chongqing Kang;Qing Xia;Yi Ding.
IEEE Transactions on Power Systems (2015)
5G network-based Internet of Things for demand response in smart grid: A survey on application potential
Hongxun Hui;Yi Ding;Qingxin Shi;Fangxing Li.
Applied Energy (2020)
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