PDF
Abstract
In this paper, the recently developed optimization algorithm, namely equilibrium optimization (EO), will be utilized to solve the optimal power flow problem (OPF), combining stochastic wind power with conventional thermal power generators in the system. The objectives are to minimize generation costs, including those incurred in thermal and stochastic wind power generation, active power loss, voltage deviation, and emission. To evaluate the performance of the EO algorithm in the OPF problem, modified IEEE 30-bus and IEEE 57-bus test systems with stochastic wind power generators will be used. A comparative study will be performed to show the efficiency of the EO algorithm compared with other recently developed metaheuristic algorithms such as the marine predators algorithm (MPA), artificial ecosystem-based optimization (AEO), and slime mould algorithm (SMA), as well as with other well-known algorithms. Based on the obtained results, the EO algorithm offered the best results.
Keywords
Optimal power flow
/
Wind power
/
Equilibrium optimization
/
Marine predators algorithm
/
Artificial ecosystem-based optimization
/
Slime mould algorithm
Cite this article
Download citation ▾
Mohammed Amroune.
Wind integrated optimal power flow considering power losses, voltage deviation, and emission using equilibrium optimization algorithm.
Energy, Ecology and Environment, 2022, 7(4): 369-392 DOI:10.1007/s40974-022-00249-2
| [1] |
Abdel-Basset M, Chang V, Mohamed V. A novel equilibrium optimization algorithm for multi thresholding image segmentation problems. Neural Comput Appl, 2020
|
| [2] |
Abido A. Environmental/economic power dispatch using multiobjective evolutionary algorithms. IEEE Trans Power Syst, 2003, 18: 1529-1537
|
| [3] |
Adaryani R, Karami A. Artificial bee colony algorithm for solving multi-objective optimal power flow problem. Electr Power Energy Syst, 2013, 53: 219-230
|
| [4] |
Bansal C, Jadon S. Optimal power flow using artificial bee colony algorithm with global and local neighbourhoods. Int J Syst Assur Eng Manag, 2017, 8(4): 2158
|
| [5] |
Biswas P, Suganthan N, Gehan J, Amaratunga G. Optimal power flow solutions incorporating stochastic wind and solar power. Energy Convers Manage, 2017, 148: 1194-1207
|
| [6] |
Biswas P, Suganthan N, Mallipeddi R, Amaratunga G. Optimal power flow solutions using differential evolution algorithm integrated with effective constraint handling techniques. Eng Appl Artif Intell, 2018, 68: 81-100
|
| [7] |
Biswas P, Suganthan N, Mallipeddi R, Amaratunga G. Multi-objective optimal power flow solutions using a constraint handling technique of evolutionary algorithms. Soft Comput, 2020, 24: 2999-3023
|
| [8] |
Biswas P, Arora P, Mallipeddi R, Suganthan N, Panigrahi B. Optimal placement and sizing of FACTS devices for optimal power flow in a wind power integrated electrical network. Neural Comput Appl, 2021, 33: 6753-6774
|
| [9] |
Bonface O, Hideharu S, Tsuyoshi F. Optimal power flow considering line-conductor temperature limits under high penetration of intermittent renewable energy sources. Int J Electr Power Energy Syst, 2018, 101: 255-267
|
| [10] |
Bouchekara H, Chaib A, Abido A. Optimal power flow using GA with a new multi-parent crossover considering: prohibited zones, valve-point effect, multi-fuels and emission. Electr Eng, 2018, 100: 151-165
|
| [11] |
Chaib A, Bouchekara H, Mehasni R, Abido A. Optimal power flow with emission and non-smooth cost functions using backtracking search optimization algorithm. Int J Electr Power Energy Syst, 2016, 81: 64-77
|
| [12] |
Chang C, Lee Y, Chen L, Jan L. Optimal power flow of a wind-thermal generation system. Electr Power Energy Syst, 2014, 55: 312-320
|
| [13] |
Chen G, Yi X, Zhang Z, Wang H. Applications of multi-objective dimension-based firefly algorithm to optimize the power losses, emission, and cost in power systems. Appl Soft Comput, 2018, 68: 322-342
|
| [14] |
Chen G, Qian J, Zhang Z, Li S. Application of modified pigeon-inspired optimization algorithm and constraint-objective sorting rule on multi-objective optimal power flow problem. Appl Soft Comput J, 2020, 92
|
| [15] |
Daryani N, Hagh T, Teimourzadeh S. Adaptive group search optimization algorithm for multi-objective optimal power flow problem. Appl Soft Comput, 2018, 38: 1012-1024
|
| [16] |
Devesh R, Muthuselvan M, Somasundaram P. Swarm-inspired artificial bee colony algorithm for solving optimal power flow with wind farm. Arab J Sci Eng, 2014, 39: 4775-4787
|
| [17] |
Duman S, Li J, Wu L, Guvenc U. Optimal power flow with stochastic wind power and FACTS devices: a modified hybrid PSOGSA with chaotic maps approach. Neural Comput Appl, 2020, 32: 8463-8492
|
| [18] |
El Attar E. Optimal power flow of a power system incorporating stochastic wind power based on modified moth swarm algorithm. IEEE Access, 2019, 7: 89581-89593
|
| [19] |
El-Ferganya A, Hasanien M. Single and multi-objective optimal power flow using grey wolf optimizer and differential evolution algorithms. Electric Power Compon Syst, 2015, 43(13): 1548-1559
|
| [20] |
Evangeline S, Rathika P. Real-time optimal power flow solution for wind farm integrated power system using evolutionary programming algorithm. Int J Environ Sci Technol, 2021, 18: 1893-1910
|
| [21] |
Evangeline S, Rathika P. A real-time multi-objective optimization framework for wind farm integrated power systems. J Power Sources, 2021
|
| [22] |
Faramarzi A, Heidarinejad M, Mirjalili S, Amir H. Gandomi marine predators algorithm: a nature-inspired metaheuristic. Expert Syst Appl, 2020, 15
|
| [23] |
Faramarzi A, Heidarinejad M, Stephens B, Mirjalili S. Equilibrium optimizer: a novel optimization algorithm. Knowl-Based Syst, 2020, 191 1
|
| [24] |
Genc A, Erisoglu M, Pekgor A, Oturanc G, Hepbasli A, Ulgen K. Estimation of wind power potential using weibull distribution. Energy Sources, 2005, 27: 809-822
|
| [25] |
Ghasemi M, Ghavidel S, Ghanbarian M, Gharibzadeh M, Vahed A. Multi-objective optimal power flow considering the cost, emission, voltage deviation and power losses using multi-objective modified imperialist competitive algorithm. Energy, 2014, 78: 276-289
|
| [26] |
Ghasemi M, Ghavidel S, Ghanbarian MM, Massrur HR, Gharibzadeh M. Application of imperialist competitive algorithm with its modified techniques for multi-objective optimal power flow problem: a comparative stud. Inform Sci, 2014, 281: 225-247
|
| [27] |
Kahraman HT, Akbel M, Duman S. Optimization of optimal power flow problem using multi-objective manta ray foraging optimizer. Appl Soft Comput, 2022, 16
|
| [28] |
Kaymaz E, Duman S, Guvenc U. Optimal power flow solution with stochastic wind power using the Le´vy coyote optimization algorithm. Neural Comput Appl, 2021, 33: 6775-6804
|
| [29] |
Kumar R, Premalatha L. Optimal power flow for a deregulated power system using adaptive real coded biogeography-based optimization. Int J Electr Power Energy Syst, 2015, 73: 393-354
|
| [30] |
Li S, Gong W, Wang L, Gu Q. Multi-objective optimal power flow with stochastic wind and solar power. Appl Soft Comput, 2022, 114
|
| [31] |
Liang H, Liu Y, Shen Y, Li F, Man Y. A hybrid bat algorithm for economic dispatch with random wind power. IEEE Trans Power Syst, 2018, 33(5): 5052-5061
|
| [32] |
Liao C. A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reduction in power system integrated wind power. Energy, 2010, 36: 1018-1029
|
| [33] |
Mahdad B, Sairi K. Solving multi-objective optimal power flow problem considering wind-STATCOM using differential evolution. Front Energy, 2013, 7(1): 75-89
|
| [34] |
Makhloufi S, Mekhaldi A, Teguar M. Three powerful nature-inspired algorithms to optimize power flow in Algeria's Adrar power system. Energy, 2016, 116: 1117-1130
|
| [35] |
Man-Im A, Ongsakul W, Singh G. Multi-objective optimal power flow considering wind power cost functions using enhanced PSO with chaotic mutation and stochastic weights. Electr Eng, 2019, 101: 699-718
|
| [36] |
Mohamed A, Yahia S, Mohamed S, El-Gaafary A, Hemeida A. Optimal power flow using moth swarm algorithm. Electric Power Syst Res, 2017, 142: 190-206
|
| [37] |
Nguyen T. A high performance social spider optimization algorithm for optimal power flow solution with single objective optimization. Energy, 2019, 171: 218-240
|
| [38] |
Panda A, Tripathy M. Security constrained optimal power flow solution of wind-thermal generation system using modified bacteria foraging algorithm. Energy, 2015, 93: 816-827
|
| [39] |
Pulluri H, Naresh R, Sharma V. Application of stud krill algorithm for solution of optimal power problems. Int Trans Electr Energy Syst, 2017, 27(6): 2316
|
| [40] |
Radosavljević J, Klimenta D, Jevtić M, Arsić N. Optimal power flow using a hybrid optimization algorithm of Particle swarm optimization and gravitational search algorithm. Electric Power Compon Syst, 2015, 43: 1958-1970
|
| [41] |
Reddy S, Momoh J. Minimum emissions optimal power flow in wind-thermal power system using opposition based bacterial dynamics algorithm. IEEE Power Energy Soc General Meet, 2016
|
| [42] |
Roberge V, Tarbouchi M, Okou F. Optimal power flow based on parallel metaheuristics for graphics processing units. Electric Power Syst Res, 2016, 140: 344-353
|
| [43] |
Roy R, Jadhav T. Optimal power flow solution of power system incorporating stochastic wind power using Gbest guided artificial bee colony algorithm. Electr Power Energy Syst, 2015, 64: 562-578
|
| [44] |
Roy K, Paul C. Optimal power flow using krill herd algorithm. Int Trans Electr Energ Syst, 2015, 25(8): 1397-1419
|
| [45] |
Salkuti R. Optimal power flow using multi-objective glowworm swarm optimization algorithm in a wind energy integrated power system. Int J Green Energy, 2019, 16(15): 1547-1561
|
| [46] |
Shaheen M, Farrag SM, El-Sehiemy RA. Mopf solution methodology. IET Gener Transm Distrib, 2017, 11(2): 570-581
|
| [47] |
Shimin L, Chen H, Wang M, Asghar Heidari A, Mirjalilim S. Slime mould algorithm: a new method for stochastic optimization. Futur Gener Comput Syst, 2020, 111: 300-323
|
| [48] |
Sulaiman MH, Mustaffa Z. Optimal power flow incorporating stochastic wind and solar generation by metaheuristic optimizers. Microsyst Technol, 2021, 27: 3263-3277
|
| [49] |
Sulaiman MH, Mustaffa Z. Solving optimal power flow problem with stochastic wind–solar–small hydro power using barnacles mating optimizer. Control Eng Pract, 2021
|
| [50] |
Teeparthi K, Vinod M. Security-constrained optimal power flow with wind and thermal power generators using fuzzy adaptive artificial physics optimization algorithm. Neural Comput Appl, 2018, 29: 855-871
|
| [51] |
Teeparthi K, Vinod Kumar M. Multi-objective hybrid PSO-APO algorithm based security constrained optimal power flow with wind and thermal generators. Eng Sci Technol Int J, 2017, 20: 411-426
|
| [52] |
Wang Z, Shi Y, Wang X, Zhang Q, Qu S. Economic dispatch of power system containing wind power and photovoltaic considering carbon trading and spare capacity variation. Int J Green Energy, 2016, 13(12): 1267-1280
|
| [53] |
Warid W. Optimal power flow using the AMTPG-Jaya algorithm. Appl Soft Comput J, 2020, 91
|
| [54] |
Warid W, Hizam H, Mariun N, Abdul-Wahab I. Optimal power flow using the Jaya algorithm. Energies, 2016, 9(9): 678
|
| [55] |
Xia S, Luo X, Wing Chan K, Zhou M, Li G. Probabilistic transient stability constrained optimal power flow for power systems with multiple correlated uncertain wind generations. IEEE Trans Sustain Energy, 2016, 7(3): 1133-1144
|
| [56] |
Yuan X, Zhang B, Wang P, Liang J, Yuan Y, Huang Y, Lei X. Multi-objective optimal power flow based on improved strength Pareto evolutionary algorithm. Energy, 2017, 122: 70-82
|
| [57] |
Zhao W, Wang L, Zhang Z. Artificial ecosystem-based optimizations: a novel nature-inspired metaheuristic algorithm. Neural Comput Applic, 2020, 32: 9383-9425
|
| [58] |
Zimmerman D, Murillo-Sanchez E, Thomas J. MATPOWER: steady-state operations, planning and analysis tools for power systems research and education. IEEE Trans Power Syst, 2011, 26(1): 12-19
|
| [59] |
Hınıslıoğlu Y (2018) Kaotik guve surusu algoritması kullanarak ruzgar gucu entegreli optimal guc¸ akıs¸ı. M.Sc. thesis, Department of Electrics & Electronics and Computer Engineering, Duzce University, Duzce
|