Profit maximization through bid based dynamic power dispatch using symbiotic organism search
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@Article{JICS-12-003,
author = {Archana Tiwari, Manjaree Pandit and Hari Mohan Dubey},
title = {Profit maximization through bid based dynamic power dispatch using symbiotic organism search},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {12},
number = {1},
pages = {003--013},
abstract = { Deregulation of power system has created competition in the power market shifting the focus
from cost optimization to profit maximization, which has created different trading mechanisms. The power
companies and their customers submit their bids for each trading interval of the next day and the independent
system operator (ISO) conducts a bid based dynamic economic dispatch (BBDED) to allocate power to the
generating companies and customers in such a manner that the total profit is maximized while all constraints
such as power balance, operating limits and ramp rate limits are satisfied. Nature inspired (NI) optimization
techniques score over the classical numerical methods for solving such complex practical problems due to (i)
their population based random search mechanism and (ii) their non-dependence on initial solution. This paper
proposes a symbiotic organisms search (SOS) based solution for solving BBDED problem in the deregulated
electricity market. The SOS algorithm depicts the interaction between different species in nature, the three
symbiotic relationships. The performance of the proposed approach has been tested on standard power
system bench marks from literature having 10 generators, 6 customers and varying power demands over 12
dispatch periods. The results have been validated with published results and SOS is found to be more
effective than the other methods for solving the BBDED problem.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22492.html}
}
TY - JOUR
T1 - Profit maximization through bid based dynamic power dispatch using symbiotic organism search
AU - Archana Tiwari, Manjaree Pandit and Hari Mohan Dubey
JO - Journal of Information and Computing Science
VL - 1
SP - 003
EP - 013
PY - 2024
DA - 2024/01
SN - 12
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22492.html
KW - BBDED
KW - deregulated electricity market
KW - social profit
KW - SOS.
AB - Deregulation of power system has created competition in the power market shifting the focus
from cost optimization to profit maximization, which has created different trading mechanisms. The power
companies and their customers submit their bids for each trading interval of the next day and the independent
system operator (ISO) conducts a bid based dynamic economic dispatch (BBDED) to allocate power to the
generating companies and customers in such a manner that the total profit is maximized while all constraints
such as power balance, operating limits and ramp rate limits are satisfied. Nature inspired (NI) optimization
techniques score over the classical numerical methods for solving such complex practical problems due to (i)
their population based random search mechanism and (ii) their non-dependence on initial solution. This paper
proposes a symbiotic organisms search (SOS) based solution for solving BBDED problem in the deregulated
electricity market. The SOS algorithm depicts the interaction between different species in nature, the three
symbiotic relationships. The performance of the proposed approach has been tested on standard power
system bench marks from literature having 10 generators, 6 customers and varying power demands over 12
dispatch periods. The results have been validated with published results and SOS is found to be more
effective than the other methods for solving the BBDED problem.
Archana Tiwari, Manjaree Pandit and Hari Mohan Dubey. (2024). Profit maximization through bid based dynamic power dispatch using symbiotic organism search.
Journal of Information and Computing Science. 12 (1).
003-013.
doi:
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