scholarly journals Optimal day‐ahead scheduling of multiple integrated energy systems considering integrated demand response, cooperative game and virtual energy storage

Author(s):  
Changming Chen ◽  
Xin Deng ◽  
Zhi Zhang ◽  
Shengyuan Liu ◽  
Muhammad Waseem ◽  
...  
Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4332
Author(s):  
Morteza Vahid-Ghavidel ◽  
Mohammad Sadegh Javadi ◽  
Matthew Gough ◽  
Sérgio F. Santos ◽  
Miadreza Shafie-khah ◽  
...  

A key challenge for future energy systems is how to minimize the effects of employing demand response (DR) programs on the consumer. There exists a diverse range of consumers with a variety of types of loads, such as must-run loads, and this can reduce the impact of consumer participation in DR programs. Multi-energy systems (MES) can solve this issue and have the capability to reduce any discomfort faced by all types of consumers who are willing to participate in the DRPs. In this paper, the most recent implementations of DR frameworks in the MESs are comprehensively reviewed. The DR modelling approach in such energy systems is investigated and the main contributions of each of these works are included. Notably, the amount of research in MES has rapidly increased in recent years. The majority of the reviewed works consider power, heat and gas systems within the MES. Over three-quarters of the papers investigated consider some form of energy storage system, which shows how important having efficient, cost-effective and reliable energy storage systems will be in the future. In addition, a vast majority of the works also considered some form of demand response programs in their model. This points to the need to make participating in the energy market easier for consumers, as well as the importance of good communication between generators, system operators, and consumers. Moreover, the emerging topics within the area of MES are investigated using a bibliometric analysis to provide insight to other researchers in this area.


Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 883 ◽  
Author(s):  
Jeseok Ryu ◽  
Jinho Kim

This work focuses on the demand response (DR) participation using the energy storage system (ESS). A probabilistic Gaussian mixture model based on market operating results Monte, Carlo Simulation (MCS), is required to respond to an urgent DR signal. However, there is considerable uncertainty in DR forecasting, which occasionally fails to predict DR events. Because this failure is attributable to the intermittency of the DR signals, a non-cooperative game model that is useful for decision-making on DR participation is proposed. The game is conducted with each player holding a surplus of energy but incomplete information. Consequently, each player can share unused electricity during DR events, engaging in indirect energy trading (IET) under a non-cooperative game framework. The results of the game, the Nash equilibrium (N.E.), are verified using a case study with relevant analytical data from the campus of Gwangju Institute of Science and Technology (GIST) in Korea. The results of the case study show that IET is useful in mitigating the uncertainty of the DR program.


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