TY - GEN
T1 - Investigating Demand-Side Management (DSM) Opportunities Using Load Profiling
T2 - 11th International Conference on Innovative Smart Grid Technologies - Asia, ISGT-Asia 2022
AU - Monawwar, Haya
AU - Abedrabboh, Khaled
AU - Almarri, Omar
AU - Al-Fagih, Luluwah
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - High penetration of renewable energy is fundamental to the sustainable development of the electricity grid. It offers great environmental, economic, and social benefits. However, due to the intermittent nature of renewable energy resources, maintaining the supply-demand balance will be a key challenge. Demand-Side Management (DSM) is a prominent solution. Identifying the best DSM policy to adopt is not an easy task. Thus, awareness of consumer behavior and smart grid applications is necessary. This may be achieved through load profiling and load clustering. In this paper, we analyze residential consumer behavior in Qatar using unpublished smart meter data to understand the relationship between electricity usage and weather patterns and to be able to differentiate between paying and non-paying customers. Our study uses a sample size of 20 customers, 10 paying and 10 non-paying. First, the recent advances in load profiling and load clustering are reviewed. Then, we identify the residential demand trends in Qatar. The study also investigates the challenges of applying DSM techniques in the region and suggests policy recommendations. Additionally, we discuss possible future research directions in load profiling and load clustering.
AB - High penetration of renewable energy is fundamental to the sustainable development of the electricity grid. It offers great environmental, economic, and social benefits. However, due to the intermittent nature of renewable energy resources, maintaining the supply-demand balance will be a key challenge. Demand-Side Management (DSM) is a prominent solution. Identifying the best DSM policy to adopt is not an easy task. Thus, awareness of consumer behavior and smart grid applications is necessary. This may be achieved through load profiling and load clustering. In this paper, we analyze residential consumer behavior in Qatar using unpublished smart meter data to understand the relationship between electricity usage and weather patterns and to be able to differentiate between paying and non-paying customers. Our study uses a sample size of 20 customers, 10 paying and 10 non-paying. First, the recent advances in load profiling and load clustering are reviewed. Then, we identify the residential demand trends in Qatar. The study also investigates the challenges of applying DSM techniques in the region and suggests policy recommendations. Additionally, we discuss possible future research directions in load profiling and load clustering.
KW - consumer behavior
KW - demand response
KW - demand-side management
KW - load clustering
KW - load profiling
KW - smart grid
UR - https://www.scopus.com/pages/publications/85146894024
U2 - 10.1109/ISGTAsia54193.2022.10003591
DO - 10.1109/ISGTAsia54193.2022.10003591
M3 - Conference contribution
AN - SCOPUS:85146894024
T3 - Proceedings of the 11th International Conference on Innovative Smart Grid Technologies - Asia, ISGT-Asia 2022
SP - 399
EP - 403
BT - Proceedings of the 11th International Conference on Innovative Smart Grid Technologies - Asia, ISGT-Asia 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 1 November 2022 through 5 November 2022
ER -