2015 IEEE 2nd International Future Energy Electronics Conference (IFEEC) 2015
DOI: 10.1109/ifeec.2015.7361470
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Optimal scheduling of real-time pricing electrical power market considering participation rate of demand response

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“…To obtain the value of participation ratio at a given incentive price, the concept of price sensitivity of consumers is adopted to model the correlation between participation ratio and incentive price [32, 33]. Although there is no unified mathematical expression of price‐sensitivity function [32–35], there still exists a general character that the function should be a non‐decreasing function according to microeconomic theory. In reality, the back propagation neural network can be utilised to fit the price‐sensitivity function if historical sample data is sufficient ϑkffalse(pkfalse)=netfalse(pkfalse) where pk=false[p1,k,,pN,kfalse]T denotes a vector whose entries are incentive prices to consumers.…”
Section: Mathematical Formulation Of the Stochastic Programming Modelmentioning
confidence: 99%
“…To obtain the value of participation ratio at a given incentive price, the concept of price sensitivity of consumers is adopted to model the correlation between participation ratio and incentive price [32, 33]. Although there is no unified mathematical expression of price‐sensitivity function [32–35], there still exists a general character that the function should be a non‐decreasing function according to microeconomic theory. In reality, the back propagation neural network can be utilised to fit the price‐sensitivity function if historical sample data is sufficient ϑkffalse(pkfalse)=netfalse(pkfalse) where pk=false[p1,k,,pN,kfalse]T denotes a vector whose entries are incentive prices to consumers.…”
Section: Mathematical Formulation Of the Stochastic Programming Modelmentioning
confidence: 99%