The UK electricity demand side response: Carbon savings analysis

Author(s):  
EngTseng Lau ◽  
Qingping Yang ◽  
Gareth Taylor ◽  
Lee Stokes ◽  
Alistair Forbes ◽  
...  
2015 ◽  
Vol 159 ◽  
pp. 478-489 ◽  
Author(s):  
E.T. Lau ◽  
Q. Yang ◽  
L. Stokes ◽  
G.A. Taylor ◽  
A.B. Forbes ◽  
...  

2014 ◽  
Vol 26 (10) ◽  
pp. 1118-1130 ◽  
Author(s):  
Michael J. Fell ◽  
David Shipworth ◽  
Gesche M. Huebner ◽  
Clifford A. Elwell

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 287
Author(s):  
Jerzy Andruszkiewicz ◽  
Józef Lorenc ◽  
Agnieszka Weychan

Demand side response is becoming an increasingly significant issue for reliable power systems’ operation. Therefore, it is desirable to ensure high effectiveness of such programs, including electricity tariffs. The purpose of the study is developing a method for analysing electricity tariff’s effectiveness in terms of demand side response purposes based on statistical data concerning tariffs’ use by the consumers and price elasticity of their electricity demand. A case-study analysis is presented for residential electricity consumers, shifting the settlement and consequently the profile of electricity use from a flat to a time-of-use tariff, based on the comparison of the considered tariff groups. Additionally, a correlation analysis is suggested to verify tariffs’ influence of the power system’s peak load based on residential electricity tariffs in Poland. The presented analysis proves that large residential consumers aggregated by tariff incentives may have a significant impact on the power system’s load and this impact changes substantially for particular hours of a day or season. Such efficiency assessment may be used by both energy suppliers to optimize their market purchases and by distribution system operators in order to ensure adequate generation during peak load periods.


Author(s):  
Jacopo Torriti

AbstractDuring peak electricity demand periods, prices in wholesale markets can be up to nine times higher than during off-peak periods. This is because if a vast number of users is consuming electricity at the same time, power plants with higher greenhouse gas emissions and higher system costs are typically activated. In the UK, the residential sector is responsible for about one third of overall electricity demand and up to 60% of peak demand. This paper presents an analysis of the 2014–2015 Office for National Statistics National Time Use Survey with a view to derive an intrinsic flexibility index based on timing of residential electricity demand. It analyses how the intrinsic flexibility varies compared with wholesale electricity market prices. Findings show that spot prices and intrinsic flexibility to shift activities vary harmoniously throughout the day. Reflections are also drawn on the application of this research to work on demand side flexibility.


Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4398
Author(s):  
Yiqi Li ◽  
Jing Zhang ◽  
Zhoujun Ma ◽  
Yang Peng ◽  
Shuwen Zhao

With the development of integrated energy systems (IES), the traditional demand response technologies for single energy that do not take customer satisfaction into account have been unable to meet actual needs. Therefore, it is urgent to study the integrated demand response (IDR) technology for integrated energy, which considers consumers’ willingness to participate in IDR. This paper proposes an energy management optimization method for community IES based on user dominated demand side response (UDDSR). Firstly, the responsive power loads and thermal loads are modeled, and aggregated using UDDSR bidding optimization. Next, the community IES is modeled and an aggregated building thermal model is introduced to measure the temperature requirements of the entire community of users for heating. Then, a day-ahead scheduling model is proposed to realize the energy management optimization. Finally, a penalty mechanism is introduced to punish the participants causing imbalance response against the day-ahead IDR bids, and the conditional value-at-risk (CVaR) theory is introduced to enhance the robustness of the scheduling model under different prediction accuracies. The case study demonstrates that the proposed method can reduce the operating cost of the community under the premise of fully considering users’ willingness, and can complete the IDR request initiated by the power grid operator or the dispatching department.


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