TY - JOUR
T1 - Efficient Load Control Based Demand Side Management Schemes Towards a Smart Energy Grid System
AU - Chakraborty, Nilotpal
AU - Mondal, Arijit
AU - Mondal, Samrat
N1 - Funding Information:
The work of A. Mondal and S. Mondal was supported in part by the IMPRINT-2 initiative undertaken by MHRD and DST through SERB, Govt. of India with sanction order no: IMP/2018/000323.
Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/8
Y1 - 2020/8
N2 - In this paper, we propose efficient load scheduling based demand side management schemes for the objective of peak load reduction. We propose two heuristic algorithms, named G-MinPeak and LevelMatch, which are based on the generalized two-dimensional strip packing problem, where each of the appliances has their specific timing requirements to be fulfilled. Furthermore, we have proposed some improvement schemes that try to modify the resulted schedule from the proposed heuristic algorithms to reduce the peak. All the proposed algorithms and improvement schemes are experimented using benchmark data sets for performance evaluation. Extensive simulation studies have been conducted using practical data to evaluate the performance of the algorithms in real life. The results obtained show that all the proposed methodologies are thoroughly effective in reducing peak load, resulting in smoother load profiles. Specifically, for the benchmark datasets, the deviation from the optimal values has been about 6% and 7% for LevelMatch and G-MinPeak algorithms respectively and by using the improvement schemes the deviations are further reduced up to 3% in many cases. For the practical datasets, the proposed improvement schemes reduce the peak by 5.21− 7.35 % on top of the peaks obtained by the two proposed heuristic algorithms without much computation overhead.
AB - In this paper, we propose efficient load scheduling based demand side management schemes for the objective of peak load reduction. We propose two heuristic algorithms, named G-MinPeak and LevelMatch, which are based on the generalized two-dimensional strip packing problem, where each of the appliances has their specific timing requirements to be fulfilled. Furthermore, we have proposed some improvement schemes that try to modify the resulted schedule from the proposed heuristic algorithms to reduce the peak. All the proposed algorithms and improvement schemes are experimented using benchmark data sets for performance evaluation. Extensive simulation studies have been conducted using practical data to evaluate the performance of the algorithms in real life. The results obtained show that all the proposed methodologies are thoroughly effective in reducing peak load, resulting in smoother load profiles. Specifically, for the benchmark datasets, the deviation from the optimal values has been about 6% and 7% for LevelMatch and G-MinPeak algorithms respectively and by using the improvement schemes the deviations are further reduced up to 3% in many cases. For the practical datasets, the proposed improvement schemes reduce the peak by 5.21− 7.35 % on top of the peaks obtained by the two proposed heuristic algorithms without much computation overhead.
KW - Demand side management
KW - Direct load control
KW - energy management
KW - heuristic algorithm
KW - scheduling
KW - smart grid
UR - http://www.scopus.com/inward/record.url?scp=85084051187&partnerID=8YFLogxK
U2 - 10.1016/j.scs.2020.102175
DO - 10.1016/j.scs.2020.102175
M3 - Journal article
AN - SCOPUS:85084051187
SN - 2210-6707
VL - 59
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
M1 - 102175
ER -