Dynamic economic dispatch (DED) problem considering prohibited operating zones (POZ), ramp rate constraints, transmission losses and spinning reserve constraints is a complicated non-linear problem which is difficult to solve efficiently. In this paper, a mixed integer linear programming (MILP) method is proposed to solve such a DED problem. Firstly, a novel MILP formulation for DED problem without considering the transmission losses, denoted by MILP-1, is presented by using perspective cut reformulation technique. When the transmission losses are considered, the quadratic terms in the transmission losses are replaced by their first order Taylor expansions, and then an MILP formulation for DED considering the transmission losses, denoted by MILP-2, is obtained. Based on MILP-1 and MILP-2, an MILP-iteration algorithm is proposed to solve the complicated DED problem. The effectiveness of the MILP formulation and MILP iteration algorithm are assessed by several cases and the simulation results show that both of them can solve to competitive solutions in a short time.
Citation: Shanshan Pan, Jinbao Jian, Linfeng Yang. Solution to dynamic economic dispatch with prohibited operating zones via MILP[J]. Mathematical Biosciences and Engineering, 2022, 19(7): 6455-6468. doi: 10.3934/mbe.2022303
Dynamic economic dispatch (DED) problem considering prohibited operating zones (POZ), ramp rate constraints, transmission losses and spinning reserve constraints is a complicated non-linear problem which is difficult to solve efficiently. In this paper, a mixed integer linear programming (MILP) method is proposed to solve such a DED problem. Firstly, a novel MILP formulation for DED problem without considering the transmission losses, denoted by MILP-1, is presented by using perspective cut reformulation technique. When the transmission losses are considered, the quadratic terms in the transmission losses are replaced by their first order Taylor expansions, and then an MILP formulation for DED considering the transmission losses, denoted by MILP-2, is obtained. Based on MILP-1 and MILP-2, an MILP-iteration algorithm is proposed to solve the complicated DED problem. The effectiveness of the MILP formulation and MILP iteration algorithm are assessed by several cases and the simulation results show that both of them can solve to competitive solutions in a short time.
[1] | X. Xia, A. M. Elaiw, Optimal dynamic economic dispatch of generation: A review, Electr. Power Syst. Res., 80 (2010), 975–986. https://doi.org/10.1016/j.epsr.2009.12.012 doi: 10.1016/j.epsr.2009.12.012 |
[2] | F. N. Lee, A. M. Breipohl, Reserve constrained economic dispatch with prohibited operating zones, IEEE Trans. Power Syst., 8 (1993), 246–254. https://doi.org/10.1109/59.221233 doi: 10.1109/59.221233 |
[3] | S. O. Orero, M. R. Irving, Economic dispatch of generators with prohibited operating zones: A genetic algorithm approach, IEE Proc. Gener. Transm. Distrib., 143 (1996), 529–534. https://doi.org/10.1049/ip-gtd:19960626 doi: 10.1049/ip-gtd:19960626 |
[4] | W. T. El-Sayed, E. F. El-Saadany, H. H. Zeineldin, A. S. Al-Sumaiti, Fast initialization methods for the nonconvex economic dispatch problem, Energy, 201 (2020), 117635. https://doi.org/10.1016/j.energy.2020.117635 doi: 10.1016/j.energy.2020.117635 |
[5] | F. X. Rugema, G. G. Yan, S. Mugemanyi, Q. Jia, S. F. Zhang, C. Bananeza, A cauchy-Gaussian quantum-behaved bat algorithm applied to solve the economic load dispatch problem, IEEE Access, 9 (2021), 3207-3228. https://doi.org/10.1109/ACCESS.2020.3034730 doi: 10.1109/ACCESS.2020.3034730 |
[6] | C. L. Chiang, Genetic-based algorithm for power economic load dispatch, IET Gener. Transm. Distrib., 1 (2007), 261–269. https://doi.org/10.1049/iet-gtd:20060130 doi: 10.1049/iet-gtd:20060130 |
[7] | J. X. V. Neto, D. L. A. Bernert, L. D. S. Coelho, Improved quantum-inspired evolutionary algorithm with diversity information applied to economic dispatch problem with prohibited operating zones, Energy Convers. Manage., 52 (2011), 8–14. https://doi.org/10.1016/j.enconman.2010.05.023 doi: 10.1016/j.enconman.2010.05.023 |
[8] | M. Modiri-Delshad, S. H. A. Kaboli, E. Taslimi-Renani, N. A. Rahim, Backtracking search algorithm for solving economic dispatch problems with valve-point effects and multiple fuel options, Energy, 116 (2016), 637–649. https://doi.org/10.1016/j.energy.2016.09.140 doi: 10.1016/j.energy.2016.09.140 |
[9] | Z. L. Gaing, Particle swarm optimization to solving the economic dispatch considering the generator constraints, IEEE Trans. Power Syst., 18 (2003), 1187–1195. https://doi.org/10.1109/TPWRS.2003.814889 doi: 10.1109/TPWRS.2003.814889 |
[10] | M. Basu, Modified particle swarm optimization for nonconvex economic dispatch problems, Int. J. Electr. Power Energy Syst., 69 (2015), 304–312. https://doi.org/10.1016/j.ijepes.2015.01.015 doi: 10.1016/j.ijepes.2015.01.015 |
[11] | J. P. Zhan, Q. H. Wu, C. X. Guo, X. X. Zhou, Fast $\lambda$-iteration method for economic dispatch with prohibited operating zones, IEEE Trans. Power Syst., 29 (2014), 990–991. https://doi.org/10.1109/TPWRS.2013.2287995 doi: 10.1109/TPWRS.2013.2287995 |
[12] | C. Takeang, A. Aurasopon, Multiple of hybrid lambda iteration and simulated annealing algorithm to solve economic dispatch problem with ramp rate limit and prohibited operating zones, J. Electr. Eng. Technol., 14 (2019), 111–120. https://doi.org/10.1007/s42835-018-00001-z doi: 10.1007/s42835-018-00001-z |
[13] | X. Liu, On compact formulation of constraints induced by disjoint prohibited-zones, IEEE Trans. Power Syst., 25 (2010), 2004–2005. https://doi.org/10.1109/TPWRS.2010.2045928 doi: 10.1109/TPWRS.2010.2045928 |
[14] | R. A. Jabr, Solution to economic dispatching with disjoint feasible regions via semidefinite programming, IEEE Trans. Power Syst., 27 (2012), 572–573. https://doi.org/10.1109/TPWRS.2011.2166009 doi: 10.1109/TPWRS.2011.2166009 |
[15] | L. G. Papageorgiou, E. S. Fraga, A mixed integer quadratic programming formulation for the economic dispatch of generators with prohibited operating zones, Electr. Power Syst. Res., 77 (2007), 1292–1296. https://doi.org/10.1016/j.epsr.2006.09.020 doi: 10.1016/j.epsr.2006.09.020 |
[16] | T. Ding, R. Bo, W. Gu, H. B. Sun, Big-M based MIQP method for economic dispatch with disjoint prohibited zones, IEEE Trans. Power Syst., 29 (2014), 976–977. https://doi.org/10.1109/TPWRS.2013.2287993 doi: 10.1109/TPWRS.2013.2287993 |
[17] | M. Pourakbari-Kasmaei, M. J. Rider, J. R. S. Mantovani, An unambiguous distance-based MIQP model to solve economic dispatch problems with disjoint operating zones, IEEE Trans. Power Syst., 31 (2016), 825–826. https://doi.org/10.1109/TPWRS.2015.2394317 doi: 10.1109/TPWRS.2015.2394317 |
[18] | T. Ding, R. Bo, F. X. Li, H. B. Sun, A bi-level branch and bound method for economic dispatch with disjoint prohibited zones considering network losses, IEEE Trans. Power Syst., 30 (2015), 2841–2855. https://doi.org/10.1109/TPWRS.2014.2375322 doi: 10.1109/TPWRS.2014.2375322 |
[19] | Z. L. Gaing, Constrained dynamic economic dispatch solution using particle swarm optimization, in IEEE Power Engineering Society General Meeting, (2004), 153–158. https://doi.org/10.1109/PES.2004.1372777 |
[20] | X. H. Yuan, A. J. Su, Y. B. Yuan, H. Nie, L. Wang, Non-convex dynamic dispatch of generators with prohibited operating zones, Optim. Control Appl. Methods, 30 (2009), 103–120. https://doi.org/10.1002/oca.873 doi: 10.1002/oca.873 |
[21] | B. Mohammadi-Ivatloo, A. Rabiee, A. Soroudi, M. Ehsan, Imperialist competitive algorithm for solving non-convex dynamic economic power dispatch, Energy, 44 (2012), 228–240. https://doi.org/10.1016/j.energy.2012.06.034 doi: 10.1016/j.energy.2012.06.034 |
[22] | Q. Niu, H. Y. Zhang, K. Li, G. W. Irwin, An efficient harmony search with new pitch adjustment for dynamic economic dispatch, Energy, 65 (2014), 25–43. https://doi.org/10.1016/j.energy.2013.10.085 doi: 10.1016/j.energy.2013.10.085 |
[23] | M. K. Sharma, P. Phonrattanasak, N. Leeprechanon, Improved bees algorithm for dynamic economic dispatch considering prohibited operating zones, in 2015 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA), (2015), 1–6. https://doi.org/10.1109/ISGT-Asia.2015.7386972 |
[24] | L. L. Li, Z. F. Liu, M. L. Tseng, S. J. Zheng, M. K. Lim, Improved tunicate swarm algorithm: Solving the dynamic economic emission dispatch problems, Appl. Soft Comput., 108 (2021), 107504. https://doi.org/10.1016/j.asoc.2021.107504 doi: 10.1016/j.asoc.2021.107504 |
[25] | Z. F. Liu, L. L. Li, Y. W. Liu, J. Q. Liu, H. Y. Li, Q. Shen, Dynamic economic emission dispatch considering renewable energy generation: A novel multi-objective optimization approach, Energy, 235 (2021), 121407. https://doi.org/10.1016/j.energy.2021.121407 doi: 10.1016/j.energy.2021.121407 |
[26] | A. Kalakova, H. S. V. S. Kumar Nunna, P. K. Jamwal, S. Doolla, A novel genetic algorithm based dynamic economic dispatch with short-term load forecasting, IEEE Trans. Ind. Appl., 57 (2021), 2972–2982. https://doi.org/10.1109/TIA.2021.3065895 doi: 10.1109/TIA.2021.3065895 |
[27] | T. G. Hlalele, J. F. Zhang, R. M. Naidoo, R. C. Bansal, Multi-objective economic dispatch with residential demand response programme under renewable obligation, Energy, 218 (2021), 119473. https://doi.org/10.1016/j.energy.2020.119473 doi: 10.1016/j.energy.2020.119473 |
[28] | K. Vaisakh, P. Praveena, S. R. M. Rao, K. Meah, Solving dynamic economic dispatch problem with security constraints using bacterial foraging PSO-DE algorithm, Int. J. Electr. Power Energy Syst., 39 (2012), 56–67. https://doi.org/10.1016/j.ijepes.2012.01.005 doi: 10.1016/j.ijepes.2012.01.005 |
[29] | S. Titus, A. E. Jeyakumar, A hybrid EP-PSO-SQP algorithm for dynamic dispatch considering prohibited operating zones, Electr. Power Compon. Syst., 36 (2008), 449–467. https://doi.org/10.1080/15325000701735256 doi: 10.1080/15325000701735256 |
[30] | A. Rabiee, B. Mohammadi-Ivatloo, M. Moradi-Dalvand, Fast dynamic economic power dispatch problems solution via optimality condition decomposition, IEEE Trans. Power Syst., 29 (2014), 982–983. https://doi.org/10.1109/TPWRS.2013.2288028 doi: 10.1109/TPWRS.2013.2288028 |
[31] | M. Q. Wang, X. S. Han, M. Yang, M. X. Wang, Dynamic economic dispatch with valve point effect, prohibited operation zones, and multiple fuel option, in 2014 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), (2014), 1–5. https://doi.org/10.1109/APPEEC.2014.7066147 |
[32] | R. A. Jabr, Tight polyhedral approximation for mixed-integer linear programming unit commitment formulations, IET Gener. Transm. Distrib., 6 (2012), 1104–1111. https://doi.org/10.1049/iet-gtd.2012.0218 doi: 10.1049/iet-gtd.2012.0218 |
[33] | H. Saadat, Power System Analysis, McGraw-Hill, New York, 1999. Available from: https://catalogue.library.cern/literature/hdgzv-pqv44. |
[34] | A. Frangioni, C. Gentile, Perspective cuts for a class of convex 0-1 mixed integer programs, Math. Program., 106 (2006), 225–236. https://doi.org/10.1007/s10107-005-0594-3 doi: 10.1007/s10107-005-0594-3 |
[35] | A. Frangioni, C. Gentile, F. Lacalandra, Tighter approximated MILP formulations for unit commitment problems, IEEE Trans. Power Syst., 24 (2009), 105–113. https://doi.org/10.1109/TPWRS.2008.2004744 doi: 10.1109/TPWRS.2008.2004744 |
[36] | IBM ILOG CPLEX Optimization Studio CPLEX User's Manual, 2014. Available from: http://www.ibm.com/support/knowledgecenter/en/SSSA5P_12.6.1/ilog.odms.studio.help/pdf/usrcplex.pdf. |
[37] | F. Benhamida, A. Bendaoued, K. Medles, A. Ayad, A. Tilmatine, A solution to dynamic economic dispatch with prohibited zones using a Hopfield neural network, in 2011 7th International Conference on Electrical and Electronics Engineering (ELECO), (2011), II-444–II-448. Available from: https://ieeexplore.ieee.org/document/6140224. |