TY - GEN
T1 - Cost-Effective Microgrid Operation with Plug-In Hybrid Electric Vehicle Considering Demand Side Management
AU - Dey, Bishwajit
AU - Misra, Srikant
AU - Pal, Arnab
AU - Sharma, Gulshan
AU - Bokoro, Pitshou N.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Demand side management (DSM) lowers operating costs by dividing loads into shiftable and non-shiftable categories and rearranging the load demand model of a distribution system. Moving variable loads to hours with lower utility prices per unit allows for this. This work employs a bi-level optimization approach to lower the operational expenses of a low-voltage microgrid system that runs in grid-connected mode and uses fossil fuel generators, renewable energy sources, and plug-in hybrid electric vehicles (PHEVs). The load model is rearranged at the first optimization stage based on the DSM participation level. Subsequently, the reorganized load demand models are considered, and suggestions for distributed generator scheduling are brewed to lower the second-level microgrid system's producing expenses. The widely used differential evolution (DE) method, used for several power system optimization problems in the past, served as the study's optimization tool. The active power production cost was decreased while accounting for DSM and considering different grid participation and grid pricing systems. Like the grid, the PHEV implemented the G2V and V2G technology to charge and discharge itself which also played a vital role in decrement of the operational expense.
AB - Demand side management (DSM) lowers operating costs by dividing loads into shiftable and non-shiftable categories and rearranging the load demand model of a distribution system. Moving variable loads to hours with lower utility prices per unit allows for this. This work employs a bi-level optimization approach to lower the operational expenses of a low-voltage microgrid system that runs in grid-connected mode and uses fossil fuel generators, renewable energy sources, and plug-in hybrid electric vehicles (PHEVs). The load model is rearranged at the first optimization stage based on the DSM participation level. Subsequently, the reorganized load demand models are considered, and suggestions for distributed generator scheduling are brewed to lower the second-level microgrid system's producing expenses. The widely used differential evolution (DE) method, used for several power system optimization problems in the past, served as the study's optimization tool. The active power production cost was decreased while accounting for DSM and considering different grid participation and grid pricing systems. Like the grid, the PHEV implemented the G2V and V2G technology to charge and discharge itself which also played a vital role in decrement of the operational expense.
KW - Demand Side Management
KW - G2V
KW - Microgrid Energy Management
KW - PHEV
KW - V2G
UR - http://www.scopus.com/inward/record.url?scp=85217854796&partnerID=8YFLogxK
U2 - 10.1109/ICAST61769.2024.10856473
DO - 10.1109/ICAST61769.2024.10856473
M3 - Conference contribution
AN - SCOPUS:85217854796
T3 - IEEE International Conference on Adaptive Science and Technology, ICAST
BT - Proceedings of the 2024 IEEE 9th International Conference on Adaptive Science and Technology, ICAST 2024
PB - IEEE Computer Society
T2 - 9th IEEE International Conference on Adaptive Science and Technology, ICAST 2024
Y2 - 24 October 2024 through 26 October 2024
ER -