Two-stage flexible power sales optimization for electricity retailers considering demand response strategies of multi-type users

Author(s):  
Qingyou Yan ◽  
Hongyu Lin ◽  
Meijuan Zhang ◽  
Xingbei Ai ◽  
De Gejirifu ◽  
...  
Energy ◽  
2021 ◽  
pp. 121283
Author(s):  
Lina Montuori ◽  
Manuel Alcázar-Ortega ◽  
Carlos Álvarez-Bel

Author(s):  
Ruiguang Ma ◽  
Chao Cheng ◽  
Chuan Long ◽  
Da Li ◽  
Liyang Liu ◽  
...  
Keyword(s):  

2018 ◽  
Vol 30 (1) ◽  
pp. 63-80 ◽  
Author(s):  
Paraskevas Panagiotidis ◽  
Andrew Effraimis ◽  
George A Xydis

The main aim of this work is to reduce electricity consumption for consumers with an emphasis on the residential sector in periods of increased demand. Efforts are focused on creating a methodology in order to statistically analyse energy demand data and come up with forecasting methodology/pattern that will allow end-users to organize their consumption. This research presents an evaluation of potential Demand Response programmes in Greek households, in a real-time pricing market model through the use of a forecasting methodology. Long-term Demand Side Management programs or Demand Response strategies allow end-users to control their consumption based on the bidirectional communication with the system operator, improving not only the efficiency of the system but more importantly, the residential sector-associated costs from the end-users’ side. The demand load data were analysed and categorised in order to form profiles and better understand the consumption patterns. Different methods were tested in order to come up with the optimal result. The Auto Regressive Integrated Moving Average modelling methodology was selected in order to ensure forecasts production on load demand with the maximum accuracy.


2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yuling Li ◽  
Xiaoying Wang ◽  
Peicong Luo

Modern smart grids have proposed a series of demand response (DR) programs and encourage users to participate in them with the purpose of maintaining reliability and efficiency so as to respond to the sustainable development of demand-side management. As a large load of the smart grid, a datacenter could be regarded as a potential demand response participant. Encouraging datacenters to participate in demand response programs can help the grid to achieve better load balancing effect, while the datacenter can also reduce its own power consumption so as to save electricity costs. In this paper, we designed a demand response participation strategy based on two-stage decisions to reduce the total cost of the datacenter while considering the DR requirements of the grid. The first stage determines whether to participate in demand response by predicting real-time electricity prices of the power grid and incentive information will be sent to encourage users to participate in the program to help shave the peak load. In the second stage, the datacenter interacts with its users by allowing users to submit bid information by reverse auction. Then, the datacenter selects the tasks of the winning users to postpone processing them with awards. Experimental results show that the proposed strategy could help the datacenter to reduce its cost and effectively meet the demand response requirements of the smart grid at the same time.


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