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## Probabilistic Multi-Objective Optimal Power Flow in an AC/DC Hybrid Microgrid Considering Emission Cost | ||

Journal of Operation and Automation in Power Engineering | ||

دوره 10، شماره 1، تیر 2022، صفحه 13-27 اصل مقاله (724.58 K) | ||

نوع مقاله: Research paper | ||

شناسه دیجیتال (DOI): 10.22098/joape.2022.8156.1565 | ||

نویسندگان | ||

A. Jasemi؛ H. Abdi^{*}
| ||

^{}Department of Electrical Engineering, Razi University, Kermanshah, Iran. | ||

چکیده | ||

As a basic tool in power system control and operation, the optimal power flow (OPF) problem searches the optimal operation point via minimizing different objectives and maintaining the control variables within their applicable regions. In recent years, this problem has encountered many challenges due to the presence of renewable energy sources, which has led introducing of a combinatorial type of power networks known as AC/DC hybrid power systems. In this paper, the OPF problem is proposed in an AC/DC hybrid microgrid, including wind power plants. For the first time, the mentioned problem is considered as a multi-objective optimization problem via minimizing fuel cost and emission. The problem is modeled while considering the power flow equations, the voltage limits in AC and DC buses, the AC voltage angle limits, and the firing angle of the converters. Also, due to the uncertain power generated by wind power plants, the probabilistic OPF problem is modeled by the five-point estimation method. To solve the problem, the "fmincon" function in MATLAB software is used by applying the IP algorithm. The simulation case study on a 13-bus sample MG verifies the effectiveness of the proposed method. The numerical results confirm that increasing the wind farm capacity from 14.54 MW to 113 MW, will be led to increasing the fuel cost from 10% to 61%, in case of including the power losses compared to the condition in which they are neglected. It is also observed that in terms of different weights, the total air pollution including the power losses is 2.30 to 2.40 times higher than the total pollution without electrical losses | ||

کلیدواژهها | ||

Emission؛ Fuel cost؛ Multi-objective optimization؛ Optimal power flow (OPF)؛ Power losses؛ Wind power plants. | ||

مراجع | ||

[1] D. Olivares et al. “Trends in microgrid control”, [2] W. Shi et al., “Real-time energy management in microgrids”, [3] W. Hu, P. Wang and H. Gooi, “Toward optimal energy management of microgrids via robust two-stage optimization”, [4] B. Panigrahi et al., “Multi-objective fuzzy dominance based bacterial foraging algorithm to solve economic emission dispatch problem”, [5] R. Hamidi et al., “Distributed cooperative control system for smart microgrids”, [6] L. Vasquez et al., “Optimal energy management within a microgrid: a comparative study”, [7] J. Guerrero et al., “Advanced control architectures for intelligent microgrids—Part II: Power quality, energy storage, and AC/DC microgrids”, [8] A. Kaur, J. Kaushal and P. Basak, “A review on microgrid central controller”, [9] A. Bidram and A. Davoudi, “Hierarchical structure of microgrids control system”, [10] L. Minchala-Avila et al., “A review of optimal control techniques applied to the energy management and control of microgrids”, [11] F. Katiraei et al., “Microgrids management”, [12] Z. Shuai et al., “Microgrid stability: Classification and a review”, [13] H. Moradi, A. Abtahi and M. Esfahanian, “Optimal operation of a multi-source microgrid to achieve cost and emission targets”, [14] L. Dulău and D. Bică, “Optimization of generation cost in a microgrid considering load demand”, [15] M. Zia, E. Elbouchikhi and M. Benbouzid, “Microgrids energy management systems: A critical review on methods, solutions, and prospects”, [16] R. Asad and A. Kazemi, “A quantitative analysis of effects of transition from ac to dc system, on loads and generation”, [17] S. Bahrami, V. Wong and J. Jatskevich, “Optimal power flow for AC-DC networks”, [18] M. Zolfaghari, M. Abedi and G. Gharehpetian, “Power flow control of interconnected AC-DC microgrids in grid-connected hybrid microgrids using modified UIPC”, [19] M. Rezvani and S. Mehraeen, “A new approach for steady-state analysis of a hybrid AC-DC microgrid”, [20] T. Adefarati and R. Bansal, “Reliability and economic assessment of a microgrid power system with the integration of renewable energy resources”, [21] A. Einaddin, A. Yazdankhah and R. Kazemzadeh, “Power management in a utility connected micro-grid with multiple renewable energy sources”, [22] K. Oureilidis and C. Demoulias, “A fault clearing method in converter-dominated microgrids with conventional protection means”, [23] J. Lopes, A. Madureira and C. Moreira, “A view of microgrids”, [24] Y. Xuan, N. Li and Z. Xu, “A new control strategy with fault ride through capability for VSC based offshore high power oil pump motor power supply system”, [25] Z. Li et al., “An optimal power flow algorithm for AC/DC hybrid power systems with VSC based MTDC considering converter power losses and voltage droop control strategy”, [26] E. Elattar, “Modified harmony search algorithm for combined economic emission dispatch of microgrid incorporating renewable sources”. [27] S. Brodsky and R. Hahn, “Assessing the influence of power pools on emission constrained economic dispatch”, [28] M. Banaei, “Multi-stage DC-AC converter based on new DC-DC converter for energy conversion”, [29] A. Martinez et al., “Modeling of VSC-based HVDC systems for a Newton-Raphson OPF algorithm”, [30] A. Martínez, C. Esquivel and C. Camacho, “Voltage source converter based high-voltage DC system modeling for optimal power flow studies”, [31] M. Baradar, M. Hesamzadeh and M. Ghandhari, “Modelling of multi-terminal HVDC systems in optimal power flow formulation”, [32] R. Wiget and G. Andersson, “Optimal power flow for combined AC and multi-terminal HVDC grids based on VSC converters”, [33] M. Baradar, M. Hesamzadeh and M. Ghandhari, “Second-order cone programming for optimal power flow in VSC-type AC-DC grids”, [34] S. Rodrigues et al., “Optimal power flow control of VSC-based multiterminal DC network for offshore wind integration in the north sea”, [35] M. Aragüés-Peñalba et al., “Optimal power flow tool for mixed high-voltage alternating current and high-voltage direct current systems for grid integration of large wind power plants”, [36] J. Cao et al., “Minimization of transmission loss in meshed AC/DC grids with VSC-MTDC networks”, [37] M. Aragues-Penalba et al., “Optimal power flow tool for hybrid AC/DC systems”, [38] D. Dhua, S. Huang and Q. Wu, “Optimal power flow modelling and analysis of hybrid AC-DC grids with offshore wind power plant”, [39] D. Kotur and P. Stefanov, “Optimal power flow control in the system with offshore wind power plants connected to the MTDC network”, [40] B. Zakeri and S. Syri, “Electrical energy storage systems: A comparative life cycle cost analysis”, [41] S. Brodsky and R. Hahn, “Assessing the influence of power pools on emission constrained economic dispatch”, [42] P. Venkatesh, R. Gnanadass and N. Padhy, “Comparison and application of evolutionary programming techniques to combined economic emission dispatch with line flow constraints”, [43] M. Bhoye et al., “An emission constraint economic load dispatch problem solution with microgrid using JAYA algorithm”, [44] S. Alfredo, “Evolutionary multi objective environmental economic dispatch: stochastic & deterministic approaches”, [45] T. Gildenhuys et al., “Optimization of the operational cost and environmental impact of a multi-microgrid system”, [46] V. Sarfi, I. Niazazari and H. Livani, “Multiobjective fireworks optimization framework for economic emission dispatch in microgrids”, [47] F. Gazijahani, A. Abadi and J. Salehi, “Optimal multi-objective operation of multi microgrids with considering uncertainty”, [48] Y. Li et al., “Multi-objective optimal dispatch of microgrid under uncertainties via interval optimization”, [49] T. Adefarati, C. Ramesh and J. Jackson, “Reliability and economic evaluation of a microgrid power system”, [50] V. Jani and H. Abdi, “Optimal allocation of energy storage systems considering wind power uncertainty”, [51] J. Radosavljević, “A solution to the combined economic and emission dispatch using hybrid PSOGSA algorithm”, [52] Z. Liu et al., “Wind-solar micro grid reliability evaluation based on sequential monte carlo”, [53] N. Nikmehr and S. Ravadanegh, “Optimal power dispatch of multi-microgrids at future smart distribution grids”, [54] J. Zhan et al., “Impacts of wind power penetration on risk constrained economic dispatch”, [55] A. Maulik and D. Das, “Optimal operation of a droop-controlled DCMG with generation and load uncertainties”, [56] T. Niknam, F. Golestaneh and A. Malekpour, “Probabilistic energy and operation management of a microgrid containing wind/photovoltaic/fuel cell generation and energy storage devices based on point estimate method and self-adaptive gravitational search algorithm”, [57] S. Bahrami and M. Amini, “A decentralized trading algorithm for an electricity market with generation uncertainty”, [58] P. Baboli et al., “Energy management and operation modelling of hybrid AC–DC microgrid”, [59] M. Hosseinzadeh and F. Salmasi, “Power management of an isolated hybrid AC/DC micro-grid with fuzzy control of battery banks”, [60] M. Hosseinzadeh and F. Salmasi, “Robust optimal power management system for a hybrid AC/DC micro-grid”, [61] P. Li et al., “Optimal operation of AC/DC hybrid microgrid under spot price mechanism”, [62] C. Qi et al., “A decentralized optimal operation of AC/DC hybrid distribution grids”, [63] L. Peng et al., “Double-uncertainty optimal operation of hybrid AC/DC microgrids with high proportion of intermittent energy sources”, [64] A. Hussain, V. Bui and H. Kim, “Robust optimal operation of AC/DC hybrid microgrids under market price uncertainties”, [65] "OFFSHORE WIND VISION" http://offshorewind. works/wp-content/uploads/2015/11/151106_offshore _ Wind _vision_FINAL. Pdf. [66] J. Zhu, “Optimization of power system operation”, [67] S. Wen et al., “Economic allocation for energy storage system considering wind power distribution”, [68] T. Thakur et al., “A particle swarm optimization solution to NO2 and SO2 emissions for environmentally constrained economic dispatch problem”, [69] A. Panosyan and B. Oswald, “Modified Newton-Raphson load flow analysis for integrated AC/DC power systems”, [70] S. Cole, J. Beerten and R. Belmans, “Generalized dynamic VSC MTDC model for power system stability studies”, [71] M. Khan et al., “A load flow analysis for AC/DC hybrid distribution network incorporated with distributed energy resources for different grid scenarios”, [72] A. Azad et al., “Analysis of wind energy conversion system using Weibull distribution”, [73] Q. Fu, D. Yu and J. Ghorai, “Probabilistic load flow analysis for power systems with multi-correlated wind sources”, [74] R. Waltz et al., “An interior algorithm for nonlinear optimization that combines line search and trust region steps”, [75] S. Rao, “Engineering optimization: theory and practice”, [76] K. Deb, “Multi-objective optimization”, [77] A. Kidwell, “Optimization under parameter uncertainties with application to product cost minimization”, 2018. [78] R. Byrd, E. Mary and J. Nocedal, “An interior point algorithm for large-scale nonlinear programming’ [79] Mathworks Global Optimization Toolbox User's Guid. MATLAB Global Optimization Toolbox User's Guid, R2017, 2017. [80] "Test Case P.M. Anderson Power System" http://fglongatt.org/OLD/Test_Case_Anderson.html. | ||

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