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Research Articles

An elitist cuckoo search algorithm for combined heat and power economic dispatch

ORCID Icon, , &
Pages 846-866 | Received 13 Jun 2022, Accepted 16 Jan 2023, Published online: 15 Feb 2023

References

  • Abed-alguni, Bilal H., Noor Aldeen Alawad, Malek Barhoush, and Rafat Hammad. 2021. “Exploratory Cuckoo Search for Solving Single-Objective Optimization Problems.” Soft Computing 25 (15): 10167–10180. doi:10.1007/s00500-021-05939-3.
  • Ali, Ahmed F., and Mohamed A. Tawhid. 2016. “A Hybrid Cuckoo Search Algorithm with Nelder Mead Method for Solving Global Optimization Problems.” Springerplus 5: Article 473. doi:10.1186/s40064-016-2064-1.
  • Alomoush, Muwaffaq I. 2020. “Optimal Combined Heat and Power Economic Dispatch Using Stochastic Fractal Search Algorithm.” Journal of Modern Power Systems and Clean Energy 8 (2): 276–286. doi:10.35833/mpce.2018.000753.
  • Awad, N. H., M. Z. Ali, P. N. Suganthan, J. J. Liang, and B. Y. Qu. 2016. “Problem Definitions and Evaluation Criteria for the CEC 2017 Special Session and Competition on Single Objective Real-Parameter Numerical Optimization.” In Technical Report. Singapore: Nanyang Technological University.
  • Basu, M. 2015a. “Combined Heat and Power Economic Dispatch Using Opposition-Based Group Search Optimization.” International Journal of Electrical Power & Energy Systems 73: 819–829. doi:10.1016/j.ijepes.2015.06.023.
  • Basu, Mousumi. 2015b. “Modified Particle Swarm Optimization for Non-Smooth Non-Convex Combined Heat and Power Economic Dispatch.” Electric Power Components and Systems 43 (19): 2146–2155. doi:10.1080/15325008.2015.1076906.
  • Basu, M. 2019. “Squirrel Search Algorithm for Multi-Region Combined Heat and Power Economic Dispatch Incorporating Renewable Energy Sources.” Energy 182: 296–305. doi:10.1016/j.energy.2019.06.087.
  • Basu, M., and A. Chowdhury. 2013. “Cuckoo Search Algorithm for Economic Dispatch.” Energy 60: 99–108. doi:10.1016/j.energy.2013.07.011.
  • Mohamad, Azizah Binti, Azlan Mohd Zain, and Nor Erne Nazira Bazin. 2014. “Cuckoo Search Algorithm for Optimization Problems—a Literature Review and its Applications.” Applied Artificial Intelligence 28 (5): 419–448. doi:10.1080/08839514.2014.904599.
  • Bolsi, Beatrice, Vinícius Loti de Lima, Thiago Alves de Queiroz, and Manuel Iori. 2022. “Heuristic Algorithms for Integrated Workforce Allocation and Scheduling of Perishable Products.” International Journal of Production Research. doi:10.1080/00207543.2022.2144525.
  • Cai, Jingcao, Deming Lei, Jing Wang, and Lei Wang. 2022. “A Novel Shuffled Frog-Leaping Algorithm with Reinforcement Learning for Distributed Assembly Hybrid Flow Shop Scheduling.” International Journal of Production Research. doi: 10.1080/00207543.2022.2031331.
  • Chen, Xu, and Kangji Li. 2022. “Collective Information-Based Particle Swarm Optimization for Multi-Fuel CHP Economic Dispatch Problem.” Knowledge-Based Systems 248: Article 10890. doi:10.1016/j.knosys.2022.108902.
  • Chen, Xu, Kangji Li, Bin Xu, and Zhile Yang. 2020. “Biogeography-based Learning Particle Swarm Optimization for Combined Heat and Power Economic Dispatch Problem.” Knowledge-Based Systems 208: Article 106463. doi:10.1016/j.knosys.2020.106463.
  • Chen, Xu, and Anning Shen. 2022. “Self-adaptive Differential Evolution with Gaussian–Cauchy Mutation for Large-Scale CHP Economic Dispatch Problem.” Neural Computing and Applications 34 (14): 11769–11787. doi:10.1007/s00521-022-07068-w.
  • Chen, Xu, and Kunjie Yu. 2019. “Hybridizing Cuckoo Search Algorithm with Biogeography-Based Optimization for Estimating Photovoltaic Model Parameters.” Solar Energy 180: 192–206. doi:10.1016/j.solener.2019.01.025.
  • Cheng, Jiatang, Lei Wang, Qiaoyong Jiang, Zijian Cao, and Yan Xiong. 2018. “Cuckoo Search Algorithm with Dynamic Feedback Information.” Future Generation Computer Systems 89: 317–334. doi:10.1016/j.future.2018.06.056.
  • de Melo, Vinícius Veloso, and Giovanni Iacca. 2014. “A Modified Covariance Matrix Adaptation Evolution Strategy with Adaptive Penalty Function and Restart for Constrained Optimization.” Expert Systems With Applications 41 (16): 7077–7094. doi:10.1016/j.eswa.2014.06.032.
  • Dolatabadi, Soheil, Ragab A. El-Sehiemy, and Saeid GhassemZadeh. 2019. “Scheduling of Combined Heat and Generation Outputs in Power Systems Using a new Hybrid Multi-Objective Optimization Algorithm.” Neural Computing & Applications 32 (14): 10741–10757. doi:10.1007/s00521-019-04610-1.
  • Duan, Longzhen, Shuqing Yang, and Dongbo Zhang. 2021. “Multilevel Thresholding Using an Improved Cuckoo Search Algorithm for Image Segmentation.” The Journal of Supercomputing 77 (7): 6734–6753. doi:10.1007/s11227-020-03566-7.
  • Faramarzi, Afshin, Mohammad Heidarinejad, Seyedali Mirjalili, and Amir H. Gandomi. 2020. “Marine Predators Algorithm: A Nature-Inspired Metaheuristic.” Expert Systems With Applications 152: Article 113377. doi:10.1016/j.eswa.2020.113377.
  • Geem, Zong Woo, and Yoon-Ho Cho. 2012. “Handling Non-Convex Heat-Power Feasible Region in Combined Heat and Power Economic Dispatch.” International Journal of Electrical Power & Energy Systems 34 (1): 171–173. doi:10.1016/j.ijepes.2011.08.024.
  • Ghorbani, Naser. 2016. “Combined Heat and Power Economic Dispatch Using Exchange Market Algorithm.” International Journal of Electrical Power & Energy Systems 82: 58–66. doi:10.1016/j.ijepes.2016.03.004.
  • Guo, Tao, Mark I. Henwood, and M. Ooijen van. 1996. “An Algorithm for Combined Heat and Power Economic Dispatch.” IEEE Transactions on Power Systems 11 (4): 1778–1784. doi:10.1109/59.544642.
  • Haghrah, A., M. Nazari-Heris, and B. Mohammadi-ivatloo. 2016. “Solving Combined Heat and Power Economic Dispatch Problem Using Real Coded Genetic Algorithm with Improved Mühlenbein Mutation.” Applied Thermal Engineering 99: 465–475. doi:10.1016/j.applthermaleng.2015.12.136.
  • Haghrah, A., M. A. Nekoui, M. Nazari-Heris, and B. Mohammadi-ivatloo. 2020. “An Improved Real-Coded Genetic Algorithm with Random Walk Based Mutation for Solving Combined Heat and Power Economic Dispatch.” Journal of Ambient Intelligence and Humanized Computing 12 (8): 8561–8584. doi:10.1007/s12652-020-02589-5.
  • Hh, A., B. Sdb, B. Ha, and A. Ar. 2022. “Society-based Grey Wolf Optimizer for Large Scale Combined Heat and Power Economic Dispatch Problem Considering Power Losses.” Applied Soft Computing 117: Article 108351. doi:10.1016/j.asoc.2021.108351.
  • Huang, Li, Shuai Ding, Shouhao Yu, Juan Wang, and Ke Lu. 2016. “Chaos-enhanced Cuckoo Search Optimization Algorithms for Global Optimization.” Applied Mathematical Modelling 40 (5-6): 3860–3875. doi:10.1016/j.apm.2015.10.052.
  • Huang, Zhenyu, Zhengzhong Gao, Liang Qi, and Hua Duan. 2019. “A Heterogeneous Evolving Cuckoo Search Algorithm for Solving Large-Scale Combined Heat and Power Economic Dispatch Problems.” IEEE Access 7: 111287–111301. doi:10.1109/access.2019.2933980.
  • Jena, C., M. Basu, and C. K. Panigrahi. 2014. “Differential Evolution with Gaussian Mutation for Combined Heat and Power Economic Dispatch.” Soft Computing 20 (2): 681–688. doi:10.1007/s00500-014-1531-2.
  • Jena, C., M. Basu, and C. K. Panigrahi. 2016. “Improved Differential Evolution for Combined Heat and Power Economic Dispatch.” International Journal of Emerging Electric Power Systems 17 (2): 151–163. doi:10.1515/ijeeps-2015-0065.
  • Kamoona, Ammar Mansoor, and Jagdish Chandra Patra. 2019. “A Novel Enhanced Cuckoo Search Algorithm for Contrast Enhancement of Gray Scale Images.” Applied Soft Computing 85: Article 105749. doi:10.1016/j.asoc.2019.105749.
  • Khare, Ankit, and Sunil Agrawal. 2020. “Effective Heuristics and Metaheuristics to Minimise Total Tardiness for the Distributed Permutation Flowshop Scheduling Problem.” International Journal of Production Research 59 (23): 7266–7282. doi:10.1080/00207543.2020.1837982.
  • Kumar, Abhishek, Swagatam Das, and Ivan Zelinka. 2020. “A Self-Adaptive Spherical Search Algorithm for Real-World Constrained Optimization Problems.” Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, 13–14. doi:10.1145/3377929.3398186.
  • Kumar, Abhishek, Guohua Wu, Mostafa Z. Ali, Rammohan Mallipeddi, Ponnuthurai Nagaratnam Suganthan, and Swagatam Das. 2020. “A Test-Suite of Non-Convex Constrained Optimization Problems from the Real-World and Some Baseline Results.” Swarm and Evolutionary Computation 56: 100693 . doi:10.1016/j.swevo.2020.100693.
  • Lashkar Ara, Afshin, Nastaran Mohammad Shahi, and Mohammad Nasir. 2019. “CHP Economic Dispatch Considering Prohibited Zones to Sustainable Energy Using Self-Regulating Particle Swarm Optimization Algorithm.” Iranian Journal of Science and Technology, Transactions of Electrical Engineering 44 (3): 1147–1164. doi:10.1007/s40998-019-00293-5.
  • Li, Xiangtao, and Minghao Yin. 2015a. “Modified Cuckoo Search Algorithm with Self Adaptive Parameter Method.” Information Sciences 298: 80–97. doi:10.1016/j.ins.2014.11.042.
  • Li, Xiangtao, and Minghao Yin. 2015b. “A Particle Swarm Inspired Cuckoo Search Algorithm for Real Parameter Optimization.” Soft Computing 20 (4): 1389–1413. doi:10.1007/s00500-015-1594-8.
  • Li, Zongyan, Dexuan Zou, and Zhi Kong. 2019. “A Harmony Search Variant and a Useful Constraint Handling Method for the Dynamic Economic Emission Dispatch Problems Considering Transmission Loss.” Engineering Applications of Artificial Intelligence 84: 18–40. doi:10.1016/j.engappai.2019.05.005.
  • Liang, Zhongyuan, Mei Liu, Peisi Zhong, and Chao Zhang. 2023. “Application Research of a new Neighbourhood Structure with Adaptive Genetic Algorithm for job Shop Scheduling Problem.” International Journal of Production Research 61: 362–381. doi:10.1080/00207543.2021.2007310.
  • Liang, Wei, Zeqiang Zhang, Yu Zhang, Peiyu Xu, and Tao Yin. 2022. “Improved Social Spider Algorithm for Partial Disassembly Line Balancing Problem Considering the Energy Consumption Involved in Tool Switching.” International Journal of Production Research, doi: 10.1080/00207543.2022.2069059.
  • Liu, Di, Zhongbo Hu, Qinghua Su, and Mianfang Liu. 2021. “A Niching Differential Evolution Algorithm for the Large-Scale Combined Heat and Power Economic Dispatch Problem.” Applied Soft Computing 113: Article 108017. doi:10.1016/j.asoc.2021.108017.
  • Mantegna, Rosario Nunzio. 1994. “Fast, Accurate Algorithm for Numerical Simulation of Lévy Stable Stochastic Processes.” Phys Rev E 49 (5): 4677–4683. doi:10.1103/physreve.49.4677.
  • Marín-Quintero, J., C. Orozco-Henao, Juan C. Velez, and A. S. Bretas. 2021. “Micro Grids Decentralized Hybrid Data-Driven Cuckoo Search Based Adaptive Protection Model.” International Journal of Electrical Power & Energy Systems 130: Article 106960. doi:10.1016/j.ijepes.2021.106960.
  • Mellal, Mohamed Arezki, and Edward J. Williams. 2015. “Cuckoo Optimization Algorithm with Penalty Function for Combined Heat and Power Economic Dispatch Problem.” Energy 93: 1711–1718. doi:10.1016/j.energy.2015.10.006.
  • Meng, Anbo, Peng Mei, Hao Yin, Xiangang Peng, and Zhuangzhi Guo. 2015. “Crisscross Optimization Algorithm for Solving Combined Heat and Power Economic Dispatch Problem.” Energy Conversion and Management 105: 1303–1317. doi:10.1016/j.enconman.2015.09.003.
  • Mishra, Gargi, Virendra P. Vishwakarma, and Apoorva Aggarwal. 2020. “Constrained L1-Optimal Sparse Representation Technique for Face Recognition.” Optics & Laser Technology 129: Article 106232. doi:10.1016/j.optlastec.2020.106232.
  • Mohammadi-Ivatloo, Behnam, Mohammad Moradi-Dalvand, and Abbas Rabiee. 2013. “Combined Heat and Power Economic Dispatch Problem Solution Using Particle Swarm Optimization with Time Varying Acceleration Coefficients.” Electric Power Systems Research 95: 9–18. doi:10.1016/j.epsr.2012.08.005.
  • Murugan, R., M. R. Mohan, C. Christober Asir Rajan, P. Deiva Sundari, and S. Arunachalam. 2018. “Hybridizing bat Algorithm with Artificial bee Colony for Combined Heat and Power Economic Dispatch.” Applied Soft Computing 72: 189–217. doi:10.1016/j.asoc.2018.06.034.
  • Nazari-Heris, M., M. Mehdinejad, B. Mohammadi-Ivatloo, and Gevork Babamalek-Gharehpetian. 2017. “Combined Heat and Power Economic Dispatch Problem Solution by Implementation of Whale Optimization Method.” Neural Computing and Applications 31 (2): 421–436. doi:10.1007/s00521-017-3074-9.
  • Nazari-Heris, Morteza, Behnam Mohammadi-Ivatloo, Somayeh Asadi, and Zong Woo Geem. 2019. “Large-scale Combined Heat and Power Economic Dispatch Using a Novel Multi-Player Harmony Search Method.” Applied Thermal Engineering 154: 493–504. doi:10.1016/j.applthermaleng.2019.03.095.
  • Nguyen, Thang Trung, Dieu Ngoc Vo, and Bach Hoang Dinh. 2016. “Cuckoo Search Algorithm for Combined Heat and Power Economic Dispatch.” International Journal of Electrical Power & Energy Systems 81: 204–214. doi:10.1016/j.ijepes.2016.02.026.
  • Nguyen, Thang Trung, Thuan Thanh Nguyen, and Dieu Ngoc Vo. 2017. “An Effective Cuckoo Search Algorithm for Large-Scale Combined Heat and Power Economic Dispatch Problem.” Neural Computing & Applications 30 (11): 3545–3564. doi:10.1007/s00521-017-2941-8.
  • Paul, Chandan, Provas Kumar Roy, and V. Mukherjee. 2020. “Chaotic Whale Optimization Algorithm for Optimal Solution of Combined Heat and Power Economic Dispatch Problem Incorporating Wind.” Renewable Energy Focus 35: 56–71. doi:10.1016/j.ref.2020.06.008.
  • Ramesh, V., T. Jayabarathi, Nishant Shrivastava, and Anup Baska. 2009. “A Novel Selective Particle Swarm Optimization Approach for Combined Heat and Power Economic Dispatch.” Electric Power Components and Systems 37 (11): 1231–1240. doi:10.1080/15325000902994348.
  • Rong, Aiying, and Risto Lahdelma. 2007. “An Efficient Envelope-Based Branch and Bound Algorithm for Non-Convex Combined Heat and Power Production Planning.” European Journal of Operational Research 183 (1): 412–431. doi:10.1016/j.ejor.2006.09.072.
  • Rooijers, Frans J., and Robert A.M. van Amerongen. 1994. “Static Economic Dispatch for co-Generation Systems.” IEEE Transactions on Power Systems 9 (3): 1392–1398. doi:10.1109/59.336125.
  • Roy, Provas Kumar, Chandan Paul, and Sneha Sultana. 2014. “Oppositional Teaching Learning Based Optimization Approach for Combined Heat and Power Dispatch.” International Journal of Electrical Power & Energy Systems 57: 392–403. doi:10.1016/j.ijepes.2013.12.006.
  • Salgotra, Rohit, Urvinder Singh, and Sriparna Saha. 2018. “New Cuckoo Search Algorithms with Enhanced Exploration and Exploitation Properties.” Expert Systems With Applications 95: 384–420. doi:10.1016/j.eswa.2017.11.044.
  • Shaheen, Abdullah M., Abdallah M. Elsayed, Ahmed R. Ginidi, Ragab A. El-Sehiemy, Mosleh M. Alharthi, and Sherif S. M. Ghoneim. 2022. “A Novel Improved Marine Predators Algorithm for Combined Heat and Power Economic Dispatch Problem.” Alexandria Engineering Journal 61 (3): 1834–1851. doi:10.1016/j.aej.2021.07.001.
  • Song, Y. H., and Q. Y. Xuan. 1998. “Combined Heat and Power Economic Dispatch Using Genetic Algorithm Based Penalty Function Method.” Electric Machines & Power Systems 26 (4): 363–372. doi:10.1080/07313569808955828.
  • Srivastava, Abhishek, and Dushmanta Kumar Das. 2020. “A new Kho-Kho Optimization Algorithm: An Application to Solve Combined Emission Economic Dispatch and Combined Heat and Power Economic Dispatch Problem.” Engineering Applications of Artificial Intelligence 94: Article 103763. doi:10.1016/j.engappai.2020.103763.
  • Su, Ching-Tzong, and Chao-Lung Chiang. 2004. “An Incorporated Algorithm for Combined Heat and Power Economic Dispatch.” Electric Power Systems Research 69 (2-3): 187–195. doi:10.1016/j.epsr.2003.08.006.
  • Takahama, T., and S. Sakai. 2006. “Constrained Optimization by the ϵ Constrained Differential Evolution with Gradient-Based Mutation and Feasible Elites.” Paper presented at the 2006 IEEE International Conference on Evolutionary Computation, July 16-21, 2006.
  • Tang, Jun, Gang Liu, and Qing Tao Pan. 2021. “A Review on Representative Swarm Intelligence Algorithms for Solving Optimization Problems: Applications and Trends.” IEEE/CAA Journal of Automatica Sinica 8 (10): 1627–1643. doi:10.1109/jas.2021.1004129.
  • Thirugnanasambandam, Kalaipriyan, Sourabh Prakash, Venkatesan Subramanian, Sujatha Pothula, and Vengattaraman Thirumal. 2019. “Reinforced Cuckoo Search Algorithm-Based Multimodal Optimization.” Applied Intelligence 49 (6): 2059–2083. doi:10.1007/s10489-018-1355-3.
  • Toloueiashtian, Mahnaz, Mehdi Golsorkhtabaramiri, and Seyed Yaser Bozorgi Rad. 2022. “An Improved Whale Optimization Algorithm Solving the Point Coverage Problem in Wireless Sensor Networks.” Telecommunication Systems 79 (3): 417–436. doi:10.1007/s11235-021-00866-y.
  • Vasebi, A., M. Fesanghary, and S. M. T. Bathaee. 2007. “Combined Heat and Power Economic Dispatch by Harmony Search Algorithm.” International Journal of Electrical Power & Energy Systems 29 (10): 713–719. doi:10.1016/j.ijepes.2007.06.006.
  • Wei, Jiamin, and Yongguang Yu. 2018. “An Effective Hybrid Cuckoo Search Algorithm for Unknown Parameters and Time Delays Estimation of Chaotic Systems.” IEEE Access 6: 6560–6571. doi:10.1109/access.2017.2738006.
  • Yang, Xin-She. 2014. Nature-inspired Optimization Algorithms. first ed. London: Elsevier.
  • Yang, Xin-She, and Suash Deb. 2009. Cuckoo search via Lévy flights. Paper presented at the 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC 2009), India.
  • Yang, Xin-She, and Suash Deb. 2013. “Cuckoo Search: Recent Advances and Applications.” Neural Computing & Applications 24 (1): 169–174. doi:10.1007/s00521-013-1367-1.
  • Yang, Bo, Jingbo Wang, Mengting Zhang, Hongchun Shu, Tao Yu, Xiaoshun Zhang, Wei Yao, and Liming Sun. 2020. “A State-of-the-art Survey of Solid Oxide Fuel Cell Parameter Identification: Modelling, Methodology, and Perspectives.” Energy Conversion and Management 213: Article 112856. doi:10.1016/j.enconman.2020.112856.
  • Yousri, Dalia, and Seyedali Mirjalili. 2020. “Fractional-order Cuckoo Search Algorithm for Parameter Identification of the Fractional-Order Chaotic, Chaotic with Noise and Hyper-Chaotic Financial Systems.” Engineering Applications of Artificial Intelligence 92: Article 103662. doi:10.1016/j.engappai.2020.103662.
  • Yu, Jiangtao, Chang-Hwan Kim, and Sang-Bong Rhee. 2020. “Clustering Cuckoo Search Optimization for Economic Load Dispatch Problem.” Neural Computing & Applications 32 (22): 16951–16969. doi:10.1007/s00521-020-05036-w.
  • Zhang, Zichen, Shifei Ding, and Weikuan Jia. 2019. “A Hybrid Optimization Algorithm Based on Cuckoo Search and Differential Evolution for Solving Constrained Engineering Problems.” Engineering Applications of Artificial Intelligence 85: 254–268. doi:10.1016/j.engappai.2019.06.017.
  • Zhao, Jian, Shi Xin Liu, Meng Chu Zhou, Xi Wang Guo, and Liang Qi. 2018. “Modified Cuckoo Search Algorithm to Solve Economic Power Dispatch Optimization Problems.” IEEE/CAA Journal of Automatica Sinica 5 (4): 794–806. doi:10.1109/jas.2018.7511138.
  • Zhou, Suyang, Zijian Hu, Wei Gu, Meng Jiang, Meng Chen, Qiteng Hong, and Campbell Booth. 2020. “Combined Heat and Power System Intelligent Economic Dispatch: A Deep Reinforcement Learning Approach.” International Journal of Electrical Power & Energy Systems 120: Article 106016. doi:10.1016/j.ijepes.2020.106016.
  • Zhou, Jiajun, and Xifan Yao. 2017. “A Hybrid Approach Combining Modified Artificial bee Colony and Cuckoo Search Algorithms for Multi-Objective Cloud Manufacturing Service Composition.” International Journal of Production Research 55 (16): 4765–4784. doi:10.1080/00207543.2017.1292064.
  • Zou, Dexuan, and Dunwei Gong. 2021. “Differential Evolution Based on Migrating Variables for the Combined Heat and Power Dynamic Economic Dispatch.” Energy 238: Article 121664. doi:10.1016/j.energy.2021.121664.
  • Zou, Dexuan, Steven Li, Xiangyong Kong, Haibin Ouyang, and Zongyan Li. 2019. “Solving the Combined Heat and Power Economic Dispatch Problems by an Improved Genetic Algorithm and a new Constraint Handling Strategy.” Applied Energy 237: 646–670. doi:10.1016/j.apenergy.2019.01.056.

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