Water Science and Engineering     2020 13 (2):  136-144    ISSN: 1674-2370:  CN: 32-1785/TV

Multi-objective reservoir operation using particle swarm optimization with adaptive random inertia weights
Hai-tao Chen a, Wen-chuan Wang a, *, Xiao-nan Chen b, Lin Qiu a
a School of Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
b Construction and Administration Bureau of South-to-North Water Diversion Middle Route Project, Beijing 100038, China
Received 2019-08-25  Revised 2020-02-01  Online 2020-06-30
Reference  

Bai, T., Wu, L.Z., Chang, J.X., Huang, Q., 2015. Multi-objective optimal operation model of cascade reservoirs and its application on water and sediment regulation. Water Resources Management  29(3), 2751-2770. https://doi.org/10.1007/s11269-015-0968-0.

Chang, L.C., 2008. Guiding rational reservoir flood operation using penalty-type genetic algorithm. Journal of Hydrology 354(1-4), 65-74. https://doi.org/10.1016/j.jhydrol.2008.02.021.

Chang, L.C., Chang, F.J., 2009. Multi-objective evolutionary algorithm for operating parallel reservoir system. Journal of Hydrology. 377(1-2), 12-20. https:// doi.org/10.1061/j.jhydrol.2009.07.061.

Chang, L.C., Chang, F.J., Wang, K.W., Dai, S.Y., 2010. Constrained genetic algorithms for optimizing multi-use reservoir operation. Journal of Hydrology 390(1-2), 66-74. https://doi.org/10.1016/j.jhydrol.2010.06.031.

Chang, J.X., Bai, T., Huang, Q., Yang, D.W., 2013. Optimization of water resources utilization by PSO-GA. Water Resources Management 27(4), 3525-3540. https://doi.org/10.1007/s11269-013-0362-8.

Chaves, P., Chang, L.C., 2008. Intelligent reservoir operation system based on evolving neural networks. Advances in Water Resources 31(6), 926-936. https://doi.org/10.1016/j.advwatres.2008.03.002.

Chen, X.N., Duan, C.Q., Qiu, L., Huang, Q., 2008. Application of large scale system model base on particle swarm optimization to optimal allocation of water resources in irrigation areas. Transactions of the CSAE. 24 (3), 103-106 (in Chinese). 

Cheng, C.T., Wang, W.C., Wu, X.Y., Xu, D.M., Chau, K.W., 2008. Optimizing hydropower reservoir operation using hybrid genetic algorithm and chaos. Water Resources Managment 22 (7), 895-909. https://doi.org/10.1007/s11269-007-9200-1.

Dorigo, M., Maniezzo, V., Colorni, A., 1996. Ant system: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics). 26(1), 29-41. https://doi.org/10.1109/3477.484436.

Eberhart, D.E., Kennedy, J., 1995. A new optimizer using particle swarm theory. In: Proceedings of the 6th Symposium on Micro Machine and Human Science. IEEE Service Center, Piscataway.

Goldberg, D.E., 1989. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wiley, Reading.

Hadka, D., Reed, P., 2013. Borg: An auto-adaptive many-objective evolutionary computing framework. Evolutionary Computation 21(2), 231-259. https://doi.org/10.1162/EVCO_a_00075.

Huang, W.C., Yuan, L.C., 2004. A drought early warning system on real-time multi-reservoir operation. Water Resources Research 40(6), W06401. https://doi.org/10.1029/2003WR002910.

Jothiprakash, V., Arunkumar, R., 2013. Optimization of hydropower reservoir using evolutionary algorithms coupled with chaos. Water Resources Management 27(7), 1963-1979. https://doi.org/10.1007/s11269-013-0265-8.

Kang, L., Zhou, L.W., Li, Z.H., Hui, L.Y., 2019. Nonlinear safety degree flood control strategy of multi-reservoirs in upper Yangtze River. Advances in Science and Technology of Water Resources 39(3), 1-5 (in Chinese). https://doi.org/10.3880/j.issn.1006-7647.2019.03.001.

Kong, A.L., Liang, S., Li, C.L., Liang, Z.F., Chen, Y., 2017. Optimizing micro-grid operation based on improved PSO. Journal of Hohai University (Natural Sciences) 45(6), 550-555 (in Chinese). https://doi.org/10.3876/j.issn.1000-1980.2017.06.012.

Kumar, D.N., Reddy, M.J., 2007. Multipurpose reservoir operation using particle swarm optimization. Journal of Water Resources Planning and Management. 133(3), 192-201. https://doi.org/10.1061/(ASCE)0733-9496(2007)133:3(192).

Labadie, J.W., 2004. Optimal operation of multi-reservoir systems: State-of-the art-review. Journal of Water Resources Planning and Management 130(2), 93-111.

Li, F.F., Christine, A.S., Qiu, J., Wei, J.H., 2015. Hierarchical multi-reservoir optimization modeling for real-world complexity with application to the Three Gorges system. Environmental  Modeling & Software. 69, 319-329. https://doi.org/10.1016/j.envsoft.2014.11.030.

Liu, P., Cai, X.M., Guo, S.L., 2011. Deriving multiple near-optimal solutions to deterministic reservoir operation problems. Water Resources Research 47, W08506. https://doi.org/10.1029/2011WR010998.

Ma, C.H., Li, Y., Huang, Q., Li, F., 2018. Parallel particle swarm optimization algorithm based on Spark multi-objective optimal scheduling of reservoir group. Journal of Xian University of Technology 34(3), 309-313 (in Chinese). https://doi.org/10.19322/j.cnki.issn.1006-4710.2018.03.010.

Mao, J.Q., Tian, M.M., Hu, T.F., Ji, K., Dai, L.Q., Dai, H.C., 2019. Shuffled complex evolution coupled with stochastic ranking for reservoir scheduling problems. Water Science and Engineering 12(4), 307-318. https://doi.org/10.1016/j.wse.2019.12.003.

Mirjalili, S., Mirjalili, S.M., Lewis, A., 2014. Grey wolf optimizer. Advances in Engineering Software 69, 46-61. https://doi.org/10.1016/j.advengsoft.2013.12.007.

Oliveira, R., Loucks, D.P., 1997. Operating rules for multi-reservoir systems. Water Resources Research 33(4), 839-852. https://doi.org/10.1029/96WR03745.

Peng, Y., Xue, Z.C., 2011. Generalized ant colony optimization method for optimal operation of cascade reservoirs. Water Resources and Power 29(4), 48-50 (in Chinese).

Salazar, J.Z., Reed, P.M., Quinn, J.D., Giuliani, M., Castelletti, A., 2017. Balancing exploration, uncertainty and computational demands in many objective reservoir optimization. Advances in Water Resources 109, 196-210. https://doi.org/10.1016/j.advwatres.2017.09.014.

Shi, Y., Eberhart, R.C., 1998. A modified particle swarm optimizer. In: Proceedings of the 1998 IEEE International Conference on Evolutionary Computatio. IEEE Press, pp. 69-73. https://doi.org/10.1109/ICEC.1998.699146.

Vrugt, J.A., Robinson, B.A., Hyman, J.M., 2009. Self-adaptive multimethod search for global optimization in real-parameter spaces. IEEE Transactions on Evolutionary Computation 13(2), 243-259. https://doi.org/10.1109/TEVC.2008.924428.

Wardlaw, R, Sharif, M., 1999. Evaluation of genetic algorithms for optimal reservoir system operation. Journal of Water Resources Planning and Management  125(1), 25-33. https://doi.org/10.1061/(ASCE)0733-9496(1999)125:1(25).

Xu, G., Ma, G.W., Liang, W.H., Chen, J.C., Wu S.Y., 2005. Application of ant colony algorithm to reservoir optimal operation. Advanced in Water Science 16(3), 397-400 (in Chinese).

Yang, G., Guo, S.L., Li, L.P., Hong, X.J., Wang, L., 2016a. Multi-objective operating rules for Danjiangkou Reservoir under climate change. Water Resources Management 30, 1183-1202. https://doi.org/10.1007/s11269-015-1220-7.

Yang, G., Guo, S.L., Liu, P., Li, L.P., Liu, Z.J., 2016b. PA-DDS algorithm for multi-objective reservoir operation. Journal of Hydraulic Engineering 47, 789-797 (in Chinese). https://doi.org/10.13243/j.cnki.slxb.20150773.

Yeh, W.W.G., 1985. Reservoir management and operations models: A state-of-the-art review. Water Resources Research 21(12), 1797-1818. https://doi.org/10.1029/WR021i012p01797.

Zhan, Z.H., Zhang, J., Li, Y., Chung, H.S.H., 2009. Adaptive particle swarm optimization. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 39(6),1362-1380. https://doi.org/10.1109/TSMCB.2009.2015956.

Zhang, Z.B., He, X.Y., Geng, S.M., Li, H., Zhang, D.W., Jiang, X.M., 2017. The application of improved particle swarm algorithm to reservoir operation optimization. Journal of China Institute of Water Resources and Hydropower Research 15(5), 338-345 (in Chinese).

Zhao, J.S., Cai, X.M., Wang, Z.J., 2011. Optimality conditions for a two-stage reservoir operation problem. Water Resources Research 47(8), W08503. https://doi.org/10.1029/2010WR009971.

Zhao, T.T.G., Zhao, J.S., 2014. Improved multiple-objective dynamic programming model for reservoir operation optimization. Journal of Hydroinformatics. 16(5), 1142-1157. https://doi.org/10.2166/hydro.2014.004.

Zheng J., Yang, K., Ni, F.Q., Liu, G.S., 2013. Research on overall improved genetic algorithm applied in optimal operation. Journal of Hydraulic Engineering 44(2), 205-211 (in Chinese). 

Zhu, D.G., Sun, H., Zhao, J., Yu, Q., 2014. Particle swarm optimization algorithm based on Gaussian disturbance. Journal of Computer Applications 34(3), 754-759 (in Chinese). https://doi.org/10.11772/j.issn.1001-9081.2014.03.0754.


Corresponding author: Wen-chuan Wang