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

Document Type : Research paper

Authors

Department of Electrical Engineering, Razi University, Kermanshah, Iran.‎

Abstract

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

Keywords

#### References

[1]    D. Olivares et al. “Trends in microgrid control”, IEEE Trans. Smart Grid, vol. 54, pp. 1905-19, 2014.
[2]    W. Shi et al., “Real-time energy management in microgrids”, IEEE Trans. Smart Grid, vol. 81, pp. 228-38, 2015.
[3]    W. Hu, P. Wang and H. Gooi, “Toward optimal energy management of microgrids via robust two-stage optimization”, IEEE Trans. Smart Grid, vol. 92, pp. 1161-74, 2016.
[4]    B. Panigrahi et al., “Multi-objective fuzzy dominance based bacterial foraging algorithm to solve economic emission dispatch problem”, Energy, vol. 35, pp. 4761-70, 2010.
[5]    R. Hamidi et al., “Distributed cooperative control system for smart microgrids”, Electr. Power Syst. Res., vol. 130, pp. 241-250, 2016.
[6]    L. Vasquez et al., “Optimal energy management within a microgrid: a comparative study”, Energies, vol. 118, pp. 1-22, 2018.
[7]    J. Guerrero et al., “Advanced control architectures for intelligent microgrids—Part II: Power quality, energy storage, and AC/DC microgrids”, IEEE Trans. Ind. Electron., vol. 60, pp. 1263-70, 2012.
[8]    A. Kaur, J. Kaushal and P. Basak, “A review on microgrid central controller”, Renew. Sustain. Energy Rev., vol. 55, pp. 338-45, 2016.
[9]    A. Bidram and A. Davoudi, “Hierarchical structure of microgrids control system”, IEEE Trans. Smart Grid, vol. 3, pp. 1963-76, 2012.
[10]    L. Minchala-Avila et al., “A review of optimal control techniques applied to the energy management and control of microgrids”, Procedia Comput. Sci., vol. 52, pp. 780-87, 2015.
[11]    F. Katiraei et al., “Microgrids management”, IEEE Power Energy Mag., vol. 6, pp. 54-65, 2008.
[12]    Z. Shuai et al., “Microgrid stability: Classification and a review”, Renew. Sustain. Energy Rev., vol. 58, pp. 167-179, 2016.
[13]    H. Moradi, A. Abtahi and M. Esfahanian, “Optimal operation of a multi-source microgrid to achieve cost and emission targets”, IEEE Power Energy Conf., 2016.
[14]    L. Dulău and D. Bică, “Optimization of generation cost in a microgrid considering load demand”, Proc. Manuf., vol. 32, pp. 390-396, 2019.
[15]    M. Zia, E. Elbouchikhi and M. Benbouzid, “Microgrids energy management systems: A critical review on methods, solutions, and prospects”, Appl. Energy, vol. 222, pp. 1033-55, 2018.
[16]    R. Asad and A. Kazemi, “A quantitative analysis of effects of transition from ac to dc system, on loads and generation”, IEEE Smart Grid Conf., 2012.
[17]    S. Bahrami, V. Wong and J. Jatskevich, “Optimal power flow for AC-DC networks”, IEEE Int. Conf. Smart Grid Commun., 2014.
[18]    M. Zolfaghari, M. Abedi and G. Gharehpetian, “Power flow control of interconnected AC-DC microgrids in grid-connected hybrid microgrids using modified UIPC”, IEEE Trans. Smart Grid, vol. 10.6, pp. 6298-07, 2016.
[19]    M. Rezvani and S. Mehraeen, “A new approach for steady-state analysis of a hybrid AC-DC microgrid”, IEEE Texas Power Energy Conf., 2019.
[20]    T. Adefarati and R. Bansal, “Reliability and economic assessment of a microgrid power system with the integration of renewable energy resources”, Appl. Energy, vol. 206, pp. 911-33, 2017.
[21]    A. Einaddin, A. Yazdankhah and R. Kazemzadeh, “Power management in a utility connected micro-grid with multiple renewable energy sources”, J. Oper. Autom. Power Eng., vol. 5, pp. 1-10, 2017.
[22]    K. Oureilidis and C. Demoulias, “A fault clearing method in converter-dominated microgrids with conventional protection means”, IEEE Trans. Power Electron., vol. 31 pp. 4628-40, 2015.
[23]    J. Lopes, A. Madureira and C. Moreira, “A view of microgrids”, Wiley Interdiscip. Rev.: Energy Environ., vol. 2, pp. 86-103, 2013.
[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”, IEEJ Trans. Electr. Electron. Eng., vol. 11, pp. 655-64, 2016.
[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”, IEEJ Trans. Electr. Electron. Eng., vol. 13, pp. 1690-98, 2018.
[26]    E. Elattar, “Modified harmony search algorithm for combined economic emission dispatch of microgrid incorporating renewable sources”. Energy, vol. 159, pp. 496-507, 2018.
[27]    S. Brodsky and R. Hahn, “Assessing the influence of power pools on emission constrained economic dispatch”, IEEE Trans. Power Syst., vol. 1, pp. 57-62, 1986.
[28]    M. Banaei, “Multi-stage DC-AC converter based on new DC-DC converter for energy conversion”, J. Oper. Autom. Power Eng., vol. 4, pp. 42-53, 2016.
[29]    A. Martinez et al., “Modeling of VSC-based HVDC systems for a Newton-Raphson OPF algorithm”, IEEE Trans. Power Syst., vol. 22, pp. 1794-1803, 2007.
[30]    A. Martínez, C. Esquivel and C. Camacho, “Voltage source converter based high-voltage DC system modeling for optimal power flow studies”, Electr. Power Compon. Syst., vol. 40, pp. 312-20, 2012.
[31]    M. Baradar, M. Hesamzadeh and M. Ghandhari, “Modelling of multi-terminal HVDC systems in optimal power flow formulation”, IEEE Electr. Power Energy Conf., pp. 170-175, 2012.
[32]    R. Wiget and G. Andersson, “Optimal power flow for combined AC and multi-terminal HVDC grids based on VSC converters”, IEEE Power Energy Soc. Meet., 2012.
[33]    M. Baradar, M. Hesamzadeh and M. Ghandhari, “Second-order cone programming for optimal power flow in VSC-type AC-DC grids”, IEEE Trans. Power Syst., vol. 28.4, pp. 4282-91, 2012.
[34]    S. Rodrigues et al., “Optimal power flow control of VSC-based multiterminal DC network for offshore wind integration in the north sea”, IEEE J. Emerg. Selected Topics Power Electron., vol. 1, pp. 260-8, 2013.
[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”, IET Renew. Power Gener., vol. 9, pp. 876-81, 2015.
[36]    J. Cao et al., “Minimization of transmission loss in meshed AC/DC grids with VSC-MTDC networks”, IEEE Trans. Power Syst., vol. 28, pp. 3047-55, 2013.
[37]    M. Aragues-Penalba et al., “Optimal power flow tool for hybrid AC/DC systems”, IET Int. Conf. AC and DC Power Transm., 2015.
[38]    D. Dhua, S. Huang and Q. Wu, “Optimal power flow modelling and analysis of hybrid AC-DC grids with offshore wind power plant”, Energy Proc., vol. 141, pp. 572-9, 2017.
[39]    D. Kotur and P. Stefanov, “Optimal power flow control in the system with offshore wind power plants connected to the MTDC network”, Int. J. Electr. Power Energy Syst., vol. 105, pp. 142-150, 2019.
[40]    B. Zakeri and S. Syri, “Electrical energy storage systems: A comparative life cycle cost analysis”, Renew. Sustain. Energy rev., vol. 42, pp. 569-96, 2015.
[41]    S. Brodsky and R. Hahn, “Assessing the influence of power pools on emission constrained economic dispatch”, IEEE Power Eng. Rev. vol. PER-6.2, pp. 30-31, 1986.
[42]    P. Venkatesh, R. Gnanadass and N. Padhy, “Comparison and application of evolutionary programming techniques to combined economic emission dispatch with line flow constraints”, IEEE Trans. Power syst., vol. 18, pp. 688-97, 2003.
[43]    M. Bhoye et al., “An emission constraint economic load dispatch problem solution with microgrid using JAYA algorithm”, Int. Conf. Energy Efficient Technol. Sustain., pp. 497-502, 2016.
[44]    S. Alfredo, “Evolutionary multi objective environmental economic dispatch: stochastic & deterministic approaches”, MSc. thesis, Italy: university of del salento, 2019.
[45]    T. Gildenhuys et al., “Optimization of the operational cost and environmental impact of a multi-microgrid system”, Energy Proc., vol. 158, pp. 3827-32, 2019.
[46]    V. Sarfi, I. Niazazari and H. Livani, “Multiobjective fireworks optimization framework for economic emission dispatch in microgrids”, North American Power Symp., pp. 1-6, 2016.
[47]    F. Gazijahani, A. Abadi and J. Salehi, “Optimal multi-objective operation of multi microgrids with considering uncertainty”, Power Syst. Conf., pp. 228-35, 2016.
[48]    Y. Li et al., “Multi-objective optimal dispatch of microgrid under uncertainties via interval optimization”, IEEE Trans. Smart Grid, vol. 10, pp. 2046-58, 2017.
[49]    T. Adefarati, C. Ramesh and J. Jackson, “Reliability and economic evaluation of a microgrid power system”, Energy Proc., vol. 142, pp.43-48, 2017.
[50]    V. Jani and H. Abdi, “Optimal allocation of energy storage systems considering wind power uncertainty”, J. Energy Storage, vol. 20, pp. 244-53, 2018.
[51]    J. Radosavljević, “A solution to the combined economic and emission dispatch using hybrid PSOGSA algorithm”, Appl. Artif. Intell., vol. 30, pp. 445-74, 2016.
[52]    Z. Liu et al., “Wind-solar micro grid reliability evaluation based on sequential monte carlo”, IEEE Int. Conf. Probab. Methods Appl. Power Syst., 2016.
[53]    N. Nikmehr and S. Ravadanegh, “Optimal power dispatch of multi-microgrids at future smart distribution grids”, IEEE Trans. Smart Grid, vol.6, pp.1648-57, 2015.
[54]    J. Zhan et al., “Impacts of wind power penetration on risk constrained economic dispatch”, IEEE PES Asia-Pacific Power Energy Eng. Conf., 2013.
[55]    A. Maulik and D. Das, “Optimal operation of a droop-controlled DCMG with generation and load uncertainties”, IET Gener. Transm. Distrib., vol. 12, pp. 2905-17, 2018.
[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”, Energy, vol. 43, pp. 427-37, 2012.
[57]    S. Bahrami and M. Amini, “A decentralized trading algorithm for an electricity market with generation uncertainty”, Appl. Energy, vol. 218, pp. 520-32, 2018.
[58]    P. Baboli et al., “Energy management and operation modelling of hybrid AC–DC microgrid”, IET Gener. Transm. Distrib., vol. 8, pp. 1700-11, 2014.
[59]    M. Hosseinzadeh and F. Salmasi, “Power management of an isolated hybrid AC/DC micro-grid with fuzzy control of battery banks”, IET Renew. Power Gener., vol. 9, pp. 484-93, 2015.
[60]    M. Hosseinzadeh and F. Salmasi, “Robust optimal power management system for a hybrid AC/DC micro-grid”, IEEE Trans. Sustain. Energy, vol. 6, pp. 675-87, 2015.
[61]    P. Li et al., “Optimal operation of AC/DC hybrid microgrid under spot price mechanism”, IEEE Power Energy Soc. Meet., 2016.
[62]    C. Qi et al., “A decentralized optimal operation of AC/DC hybrid distribution grids”, IEEE Trans. Smart Grid, vol. 9, pp. 6095-105, 2017.
[63]    L. Peng et al., “Double-uncertainty optimal operation of hybrid AC/DC microgrids with high proportion of intermittent energy sources”, J. Modern Power Syst. Clean Energy, vol. 5, pp. 838-49, 2017.
[64]    A. Hussain, V. Bui and H. Kim, “Robust optimal operation of AC/DC hybrid microgrids under market price uncertainties”, IEEE Access, vol. 6, pp. 2654-67, 2017.
[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”, John Wiley & Sons, 2017.
[67]    S. Wen et al., “Economic allocation for energy storage system considering wind power distribution”, IEEE Trans. Power Syst., vol. 30, pp. 644-52, 2014.
[68]    T. Thakur et al., “A particle swarm optimization solution to NO2 and SO2 emissions for environmentally constrained economic dispatch problem”, IEEE/PES Transm. Distrib. Conf. Expos., 2006.
[69]    A. Panosyan and B. Oswald, “Modified Newton-Raphson load flow analysis for integrated AC/DC power systems”, Int. Univ. Power Eng. Conf., vol. 3, pp. 1223-27, 2004.
[70]    S. Cole, J. Beerten and R. Belmans, “Generalized dynamic VSC MTDC model for power system stability studies”, IEEE Trans. Power Syst., vol. 25, pp. 1655-62, 2010.
[71]    M. Khan et al., “A load flow analysis for AC/DC hybrid distribution network incorporated with distributed energy resources for different grid scenarios”, Energies, vol. 11, pp. 367, 2018.
[72]    A. Azad et al., “Analysis of wind energy conversion system using Weibull distribution”, Proc. Eng., vol. 90, pp. 725-32, 2014.
[73]    Q. Fu, D. Yu and J. Ghorai, “Probabilistic load flow analysis for power systems with multi-correlated wind sources”, IEEE Power Energy Soc. Meet., 2011.
[74]    R. Waltz et al., “An interior algorithm for nonlinear optimization that combines line search and trust region steps”, Math. Program., vol. 107, pp. 391-408, 2006.
[75]    S. Rao, “Engineering optimization: theory and practice”, John Wiley & Sons, 2019.
[76]    K. Deb, “Multi-objective optimization”, Search methodologies, pp. 403-449, 2014.
[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’ SIAM J. Optim., vol. 9, 877-900, 1999.
[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.

### History

• Receive Date: 15 December 2020
• Revise Date: 21 February 2021
• Accept Date: 27 March 2021
• First Publish Date: 28 April 2021