TY - JOUR
T1 - A hybrid Harris Hawks optimizer for economic load dispatch problems
AU - Al-Betar, Mohammed Azmi
AU - Awadallah, Mohammed A.
AU - Makhadmeh, Sharif Naser
AU - Doush, Iyad Abu
AU - Zitar, Raed Abu
AU - Alshathri, Samah
AU - Abd Elaziz, Mohamed
N1 - Funding Information:
Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2022R197), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
Publisher Copyright:
© 2022
PY - 2023/2/1
Y1 - 2023/2/1
N2 - This paper proposes a hybridized version of the Harris Hawks Optimizer (HHO) with adaptive-hill-climbing optimizer to tackle economic load dispatch (ELD) problems. ELD is an important problem in power systems that is tackled by finding the optimal schedule of the generation units that minimize fuel conceptions under a set of constraints. Due to the complexity of ELD search space, as it is rigid and deep, the exploitation of HHO is improved by hybridizing it with a recent local search method called adaptive-hill climbing. The HHO can navigate several potential search space regions, while adaptive-hill climbing is used to deeply search for the local optimal solution in each potential region. To evaluate the proposed approach, six versions of ELD cases with various complexities and constraints have been used which are the 6 generation units with 1263 MW of load demand, 13 generation units with 1800 MW of load demand, 13 generation units with 2520 MW of load demand, 15 generation units with 2630 MW of load demand, 40 generation units with 10500 MW of load demand, and 140 generation units with 49342 MW of load demand. Furthermore, the proposed algorithm is evaluated on two ELD real-world cases which are 6 units-1263 MW and 15units-2630 MW. The results show that the proposed algorithm can achieve a significant performance for the majority of the experimented cases. It can achieve the best-reported solution for the ELD case with 15 generation units when compared to 15 well-established methods. Additionally, it obtains the second-best for the ELD case with 140 generation units when compared to 10 well-established methods. In conclusion, the proposed method can be an alternative to solve ELD problems which is efficient.
AB - This paper proposes a hybridized version of the Harris Hawks Optimizer (HHO) with adaptive-hill-climbing optimizer to tackle economic load dispatch (ELD) problems. ELD is an important problem in power systems that is tackled by finding the optimal schedule of the generation units that minimize fuel conceptions under a set of constraints. Due to the complexity of ELD search space, as it is rigid and deep, the exploitation of HHO is improved by hybridizing it with a recent local search method called adaptive-hill climbing. The HHO can navigate several potential search space regions, while adaptive-hill climbing is used to deeply search for the local optimal solution in each potential region. To evaluate the proposed approach, six versions of ELD cases with various complexities and constraints have been used which are the 6 generation units with 1263 MW of load demand, 13 generation units with 1800 MW of load demand, 13 generation units with 2520 MW of load demand, 15 generation units with 2630 MW of load demand, 40 generation units with 10500 MW of load demand, and 140 generation units with 49342 MW of load demand. Furthermore, the proposed algorithm is evaluated on two ELD real-world cases which are 6 units-1263 MW and 15units-2630 MW. The results show that the proposed algorithm can achieve a significant performance for the majority of the experimented cases. It can achieve the best-reported solution for the ELD case with 15 generation units when compared to 15 well-established methods. Additionally, it obtains the second-best for the ELD case with 140 generation units when compared to 10 well-established methods. In conclusion, the proposed method can be an alternative to solve ELD problems which is efficient.
KW - Economic load dispatch
KW - Harris Hawks Optimizer
KW - Power Systems
KW - Swarm intelligence
KW - β-hill climbing
UR - http://www.scopus.com/inward/record.url?scp=85138802584&partnerID=8YFLogxK
U2 - 10.1016/j.aej.2022.09.010
DO - 10.1016/j.aej.2022.09.010
M3 - Article
SN - 1110-0168
VL - 64
SP - 365
EP - 389
JO - AEJ - Alexandria Engineering Journal
JF - AEJ - Alexandria Engineering Journal
ER -