A LOW CARBON ECONOMIC OPTIMAL DISPATCHING MODEL FOR COMPREHENSIVE ENERGY SYSTEM BASED ON IMPROVED WHALE ALGORITHM, 1-12.

Lin Jin and Qian Sun

References

  1. [1] Z. Yu, L. Shen, C. Shuai, Y. Tan, Y. Ren, and Y. Wu, Is the low-carbon economy efficient in terms of sustainable development?A global perspective, Sustainable Development, 27(1), 2019,130–152.
  2. [2] L.Y. Zhang, M.L. Tseng, C.H. Wang, C. Xiao, and T. Fei, Low-carbon cold chain logistics using ribonucleic acid-ant colonyoptimization algorithm, Journal of Cleaner Production, 233,2019, 169–180.
  3. [3] K. Jain and A. Saxena, Simulation on supplier sidebidding strategy at day-ahead electricity market using antlion optimizer, Journal of Computational and CognitiveEngineering, 2(1), 2023, 17–27.
  4. [4] G.N. Sakalis, G.J. Tzortzis, and C.A. Frangopoulos, Synthesis,design and operation optimization of a combined cycleintegrated energy system including optimization of the seasonalspeed of a VLCC, Proceedings of the Institution of MechanicalEngineers, Part M: Journal of Engineering for the MaritimeEnvironment, 235(1), 2021, 41–67.
  5. [5] J. Yuan, Y. Li, X. Luo, L. Li, and C. Li, Regional integratedenergy system schemes selection based on risk expectation andMahalanobis-Taguchi system, Journal of Intelligent and FuzzySystems, 40(6), 2021, 1–18.
  6. [6] X. Gao and W. Liu, Optimal device capacity planningand strategy determination in an integrated energy systemto promoting IES integration considering reliability value,IET Generation Transmission & Distribution, 15(6), 2021,2356–2370.
  7. [7] J. Su, H.D. Chiang, Y. Zeng, and N Zhou, Toward completecharacterization of the steady-state security region for theelectricity-gas integrated energy system, IEEE Transactionson Smart Grid, 12(4), 2021, 3004–3015.
  8. [8] H. Liu, S. Tian, X. Wang, Y. Cao, and Y. Li, Optimalplanning design of a district-level integrated energy systemconsidering the impacts of multi-dimensional uncertainties: Amulti-objective interval optimization method, IEEE Access,9(1), 2021, 26278–26289.
  9. [9] Q. Guo, L. Gao, X. Chu, and H. Sun, Parameter identificationfor static var compensator model using sensitivity analysisand improved whale optimization algorithm, CSEE Journal ofPower and Energy Systems, 8(2), 2022, 535–547.
  10. [10] O.O. Obadina, M.A. Thaha, K. Althoefer, and M.H. Shaheed,Dynamic characterization of a master-slave robotic manipulatorusing a hybrid grey wolf –whale optimization algorithm, Journalof Vibration and Control, 28(15/16), 2021, 1992–2003.
  11. [11] R. Gupta, M.A. Alam, and P. Agarwal, Whale optimizationalgorithm fused with SVM to detect stress in EEG signals,Intelligent Decision Technologies, 15(1), 2021, 87–97.
  12. [12] M.A. Kahya, S.A. Altamir, and Z.Y. Algamal, Improving whaleoptimization algorithm for feature selection with a time-varyingtransfer function, Numerical Algebra, Control, Optimization,11(1), 2021, 87–98.
  13. [13] K. Heraguemi, Whale optimization algorithm for solvingassociation rule mining issue, IJCDS Journal, 10(1), 2021,332–342.
  14. [14] R. Wang, S. Cheng, X. Zuo, and Y. Liu, Optimal managementof multi stakeholder integrated energy system considering dualincentive demand response and carbon trading mechanism,International Journal of Energy Research, 46(5), 2022,6246–6263.
  15. [15] J. Jia, G. Zang, and M.C. Paul, Energy, exergy, and economic(3E) evaluation of a CCHP system with biomass gasifier,solid oxide fuel cells, micro-gas turbine, and absorptionchiller, International Journal of Energy Research, 45(10), 2021,15182–15199.
  16. [16] Y. Wang, L. Wang, R.F. Hu, L.X. Kong, and J. Cheng, Effectsof sampling frequency on the proper orthogonal decompositionbased reconstruction of a wind turbine wake, IET RenewablePower Generation, 15(13), 2021, 2956–2970.
  17. [17] L. Xiong, X. Zhang, and Y. Chen, Experimental verification ofvolt-ampere characteristic curve for a memristor-based chaoticcircuit, Circuit World, 46(1), 2019, 13–24.
  18. [18] A. Mohammadbeigi, A. Maroosi, and M. Hemmati, Optimalchiller loading for energy conservation using a hybridwhale optimization algorithm based on population membranesystems, International Journal of Modelling & Simulation,42(1/2), 2022, 101–116.
  19. [19] A. Qi, D. Zhao, F. Yu, A.A. Heidari, H. Chen, and L. Xiao,Directional mutation and crossover for immature performanceof whale algorithm with application to engineering optimiza-tion, Journal of Computational Design and Engineering, 9(2),2022, 519–563.
  20. [20] K. Asghari, M. Masdari, F.S. Gharehchopogh, and R.Saneifard, A chaotic and hybrid gray wolf-whale algorithm forsolving continuous optimization problems, Progress in ArtificialIntelligence, 10(3), 2021, 349–374.
  21. [21] F. Jiang, L. Wang, and L. Bai, An improved whale algorithmand its application in truss optimization, Journal of BionicEngineering, 18, 2021, 721–732.
  22. [22] J. Luo, F. He, H. Li, X.T. Zeng, and Y. Liang, A novel whaleoptimisation algorithm with filtering disturbance and nonlinearstep, International Journal of Bio-Inspired Computation,20(2), 2022, 71–81.
  23. [23] S.R. Valayapalayam Kittusamy, M. Elhoseny, and S. Kathire-san, An enhanced whale optimization algorithm for vehicularcommunication networks, International Journal of Communi-cation Systems, 35(12), 2022, e3953.
  24. [24] M. Li, G. Xu, Q. Lai, and J. Chen, A chaotic strategy-basedquadratic opposition-based learning adaptive variable-speedwhale optimization algorithm, Mathematics and Computers inSimulation, 193, 2022, 71–99.

Important Links:

Go Back