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Erschienen in: Arabian Journal for Science and Engineering 2/2021

08.11.2020 | Research Article-Electrical Engineering

Optimal Operation of Unbalanced Microgrid Utilizing Copula-Based Stochastic Simultaneous Unit Commitment and Distribution Feeder Reconfiguration Approach

verfasst von: Ahmad Fakharian, Mostafa Sedighizadeh, Masoud Khajehvand

Erschienen in: Arabian Journal for Science and Engineering | Ausgabe 2/2021

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Abstract

Currently, the microgrid operators try to operate this special type of the electrical grid in an optimal way due to the energy and cost saving and enhancing the other technical, environmental and economic aspects. Two of the most important tasks of operators to improve the efficiency of the microgrid are the optimal unit commitment and the distribution feeder reconfiguration. If these tasks are individually carried out, it may not lead to the optimal operation. Simultaneously, performing these two tasks in an unbalanced microgrid is a challenging multi-objective problem that this paper is faced with it. The assumed unbalanced microgrid has been equipped by two hybrid energy systems which include the dispatchable distributed generations that are fuel cell units and the non-dispatchable ones that are wind turbines and photovoltaic cells. The stochastic behavior of the non-dispatchable generation units and electrical demand is modeled by a stochastic copula scenario-based framework. The objective functions are minimization of the operational cost of the microgrid, minimization of active power loss, maximization of voltage stability index, minimization of emissions, and minimization of the voltage and current unbalance indices subject to diverse technical constraints. The proposed multi-objective problem is optimized by multi-objective covariance matrix adaption-evolution strategy (MOCMA-ES) algorithm, and a set of Pareto solutions is achieved. The best compromised solution is then chosen by using the fuzzy technique. The capability of the proposed model is investigated on an unbalanced 25-bus microgrid. The simulation results show the efficacy of the proposed model to optimize objective functions, while the constraints are satisfied.

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Literatur
2.
Zurück zum Zitat Sedghi, L., Emam, M., Fakharian, A., Savaghebi, M.: Decentralized control of an islanded microgrid based on offline model reference adaptive control. J. Renew. Sustain Energy 10(6), 065301 (2018) Sedghi, L., Emam, M., Fakharian, A., Savaghebi, M.: Decentralized control of an islanded microgrid based on offline model reference adaptive control. J. Renew. Sustain Energy 10(6), 065301 (2018)
3.
Zurück zum Zitat Rahmani, R.; Fakharian, A.: Guerrero, J.: An optimal power management system for automatic connection of DC and AC resources of hybrid-microgrid systems. In: 2017 IEEE Second International Conference on DC Microgrids (ICDCM), 2017: IEEE, pp. 181–187 Rahmani, R.; Fakharian, A.: Guerrero, J.: An optimal power management system for automatic connection of DC and AC resources of hybrid-microgrid systems. In: 2017 IEEE Second International Conference on DC Microgrids (ICDCM), 2017: IEEE, pp. 181–187
5.
Zurück zum Zitat Wang, H., Huang, J.: Joint investment and operation of microgrid. IEEE Trans. Smart Grid 8(2), 833–845 (2015) Wang, H., Huang, J.: Joint investment and operation of microgrid. IEEE Trans. Smart Grid 8(2), 833–845 (2015)
7.
Zurück zum Zitat Leite, J.C., Abril, I.P., Azevedo, M.S.S.: Capacitor and passive filter placement in distribution systems by nondominated sorting genetic algorithm-II. Electric Power Syst. Res. 143, 482–489 (2017) Leite, J.C., Abril, I.P., Azevedo, M.S.S.: Capacitor and passive filter placement in distribution systems by nondominated sorting genetic algorithm-II. Electric Power Syst. Res. 143, 482–489 (2017)
8.
9.
Zurück zum Zitat Jabbari-Sabet, R., Moghaddas-Tafreshi, S.-M., Mirhoseini, S.-S.: Microgrid operation and management using probabilistic reconfiguration and unit commitment. Int. J. Electr. Power Energy Syst. 75, 328–336 (2016) Jabbari-Sabet, R., Moghaddas-Tafreshi, S.-M., Mirhoseini, S.-S.: Microgrid operation and management using probabilistic reconfiguration and unit commitment. Int. J. Electr. Power Energy Syst. 75, 328–336 (2016)
10.
Zurück zum Zitat Gutiérrez-Alcaraz, G., Galván, E., González-Cabrera, N., Javadi, M.: Renewable energy resources short-term scheduling and dynamic network reconfiguration for sustainable energy consumption. Renew. Sustain. Energy Rev. 52, 256–264 (2015) Gutiérrez-Alcaraz, G., Galván, E., González-Cabrera, N., Javadi, M.: Renewable energy resources short-term scheduling and dynamic network reconfiguration for sustainable energy consumption. Renew. Sustain. Energy Rev. 52, 256–264 (2015)
11.
Zurück zum Zitat Gazijahani, F.S., Salehi, J.: Integrated DR and reconfiguration scheduling for optimal operation of microgrids using Hong’s point estimate method. Int. J. Electr. Power Energy Syst. 99, 481–492 (2018) Gazijahani, F.S., Salehi, J.: Integrated DR and reconfiguration scheduling for optimal operation of microgrids using Hong’s point estimate method. Int. J. Electr. Power Energy Syst. 99, 481–492 (2018)
12.
Zurück zum Zitat Kaveh, M.R., Hooshmand, R.-A., Madani, S.M.: Simultaneous optimization of re-phasing, reconfiguration and DG placement in distribution networks using BF-SD algorithm. Appl. Soft Comput. 62, 1044–1055 (2018) Kaveh, M.R., Hooshmand, R.-A., Madani, S.M.: Simultaneous optimization of re-phasing, reconfiguration and DG placement in distribution networks using BF-SD algorithm. Appl. Soft Comput. 62, 1044–1055 (2018)
13.
Zurück zum Zitat Shukla, J., Das, B., Pant, V.: Stability constrained optimal distribution system reconfiguration considering uncertainties in correlated loads and distributed generations. Int. J. Electr. Power Energy Syst. 99, 121–133 (2018) Shukla, J., Das, B., Pant, V.: Stability constrained optimal distribution system reconfiguration considering uncertainties in correlated loads and distributed generations. Int. J. Electr. Power Energy Syst. 99, 121–133 (2018)
18.
Zurück zum Zitat Zidan, A., Shaaban, M.F., El-Saadany, E.F.: Long-term multi-objective distribution network planning by DG allocation and feeders’ reconfiguration. Electric Power Syst. Res. 105, 95–104 (2013) Zidan, A., Shaaban, M.F., El-Saadany, E.F.: Long-term multi-objective distribution network planning by DG allocation and feeders’ reconfiguration. Electric Power Syst. Res. 105, 95–104 (2013)
19.
Zurück zum Zitat Rao, R.S., Ravindra, K., Satish, K., Narasimham, S.: Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation. IEEE Trans. Power Syst. 28(1), 317–325 (2013) Rao, R.S., Ravindra, K., Satish, K., Narasimham, S.: Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation. IEEE Trans. Power Syst. 28(1), 317–325 (2013)
21.
Zurück zum Zitat Mohammadi, M., Rozbahani, A.M., Bahmanyar, S.: Power loss reduction of distribution systems using BFO based optimal reconfiguration along with DG and shunt capacitor placement simultaneously in fuzzy framework. J. Central South Univ. 24(1), 90–103 (2017) Mohammadi, M., Rozbahani, A.M., Bahmanyar, S.: Power loss reduction of distribution systems using BFO based optimal reconfiguration along with DG and shunt capacitor placement simultaneously in fuzzy framework. J. Central South Univ. 24(1), 90–103 (2017)
22.
Zurück zum Zitat Ravadanegh, S.N., Oskuee, M.R.J., Karimi, M.: Multi-objective planning model for simultaneous reconfiguration of power distribution network and allocation of renewable energy resources and capacitors with considering uncertainties. J. Central South Univ. 24(8), 1837–1849 (2017) Ravadanegh, S.N., Oskuee, M.R.J., Karimi, M.: Multi-objective planning model for simultaneous reconfiguration of power distribution network and allocation of renewable energy resources and capacitors with considering uncertainties. J. Central South Univ. 24(8), 1837–1849 (2017)
23.
Zurück zum Zitat Li, K; Zhang, J.; Che, J.; Wang, F.; Ren, H.; Mi, Z.: Capacity configuration optimization for stand-alone microgrid considering the uncertainties of wind and solar resource. In: 2018 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2018. IEEE, pp. 1–5 Li, K; Zhang, J.; Che, J.; Wang, F.; Ren, H.; Mi, Z.: Capacity configuration optimization for stand-alone microgrid considering the uncertainties of wind and solar resource. In: 2018 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2018. IEEE, pp. 1–5
25.
Zurück zum Zitat Ding, F., Loparo, K.A.: Feeder reconfiguration for unbalanced distribution systems with distributed generation: a hierarchical decentralized approach. IEEE Trans. Power Syst. 31(2), 1633–1642 (2015) Ding, F., Loparo, K.A.: Feeder reconfiguration for unbalanced distribution systems with distributed generation: a hierarchical decentralized approach. IEEE Trans. Power Syst. 31(2), 1633–1642 (2015)
26.
Zurück zum Zitat Esmaeilian, H.R., Fadaeinedjad, R.: Energy loss minimization in distribution systems utilizing an enhanced reconfiguration method integrating distributed generation. IEEE Syst. J. 9(4), 1430–1439 (2014) Esmaeilian, H.R., Fadaeinedjad, R.: Energy loss minimization in distribution systems utilizing an enhanced reconfiguration method integrating distributed generation. IEEE Syst. J. 9(4), 1430–1439 (2014)
27.
Zurück zum Zitat Zidan, A., El-Saadany, E.F.: Distribution system reconfiguration for energy loss reduction considering the variability of load and local renewable generation. Energy 59, 698–707 (2013) Zidan, A., El-Saadany, E.F.: Distribution system reconfiguration for energy loss reduction considering the variability of load and local renewable generation. Energy 59, 698–707 (2013)
28.
Zurück zum Zitat Sedighizadeh, M., Dakhem, M., Sarvi, M., Kordkheili, H.H.: Optimal reconfiguration and capacitor placement for power loss reduction of distribution system using improved binary particle swarm optimization. Int. J. Energy Environ. Eng. 5(1), 3 (2014) Sedighizadeh, M., Dakhem, M., Sarvi, M., Kordkheili, H.H.: Optimal reconfiguration and capacitor placement for power loss reduction of distribution system using improved binary particle swarm optimization. Int. J. Energy Environ. Eng. 5(1), 3 (2014)
29.
Zurück zum Zitat Nasiraghdam, H., Jadid, S.: Optimal hybrid PV/WT/FC sizing and distribution system reconfiguration using multi-objective artificial bee colony (MOABC) algorithm. Sol. Energy 86(10), 3057–3071 (2012) Nasiraghdam, H., Jadid, S.: Optimal hybrid PV/WT/FC sizing and distribution system reconfiguration using multi-objective artificial bee colony (MOABC) algorithm. Sol. Energy 86(10), 3057–3071 (2012)
30.
Zurück zum Zitat Niknam, T., Fard, A.K., Seifi, A.: Distribution feeder reconfiguration considering fuel cell/wind/photovoltaic power plants. Renew. Energy 37(1), 213–225 (2012) Niknam, T., Fard, A.K., Seifi, A.: Distribution feeder reconfiguration considering fuel cell/wind/photovoltaic power plants. Renew. Energy 37(1), 213–225 (2012)
31.
Zurück zum Zitat Olamaei, J., Niknam, T., Gharehpetian, G.: Application of particle swarm optimization for distribution feeder reconfiguration considering distributed generators. Appl. Math. Comput. 201(1–2), 575–586 (2008)MathSciNetMATH Olamaei, J., Niknam, T., Gharehpetian, G.: Application of particle swarm optimization for distribution feeder reconfiguration considering distributed generators. Appl. Math. Comput. 201(1–2), 575–586 (2008)MathSciNetMATH
32.
Zurück zum Zitat Sedighizadeh, M., Ahmadi, S., Sarvi, M.: An efficient hybrid big bang–big crunch algorithm for multi-objective reconfiguration of balanced and unbalanced distribution systems in fuzzy framework. Electric Power Compon. Syst. 41(1), 75–99 (2013) Sedighizadeh, M., Ahmadi, S., Sarvi, M.: An efficient hybrid big bang–big crunch algorithm for multi-objective reconfiguration of balanced and unbalanced distribution systems in fuzzy framework. Electric Power Compon. Syst. 41(1), 75–99 (2013)
33.
Zurück zum Zitat Sedighizadeh, M., Ghalambor, M., Rezazadeh, A.: Reconfiguration of radial distribution systems with fuzzy multi-objective approach using modified big bang-big crunch algorithm. Arabian J. Sci. Eng. 39(8), 6287–6296 (2014) Sedighizadeh, M., Ghalambor, M., Rezazadeh, A.: Reconfiguration of radial distribution systems with fuzzy multi-objective approach using modified big bang-big crunch algorithm. Arabian J. Sci. Eng. 39(8), 6287–6296 (2014)
34.
Zurück zum Zitat Sedighizadeh, M., Esmaili, M., Mohammadkhani, N.: Stochastic multi-objective energy management in residential microgrids with combined cooling, heating, and power units considering battery energy storage systems and plug-in hybrid electric vehicles. J. Clean. Prod. 195, 301–317 (2018) Sedighizadeh, M., Esmaili, M., Mohammadkhani, N.: Stochastic multi-objective energy management in residential microgrids with combined cooling, heating, and power units considering battery energy storage systems and plug-in hybrid electric vehicles. J. Clean. Prod. 195, 301–317 (2018)
35.
Zurück zum Zitat Teng, J.-H.: A direct approach for distribution system load flow solutions. IEEE Trans. Power Deliv. 18(3), 882–887 (2003) Teng, J.-H.: A direct approach for distribution system load flow solutions. IEEE Trans. Power Deliv. 18(3), 882–887 (2003)
36.
Zurück zum Zitat Shahryari, E.; Shayeghi, H.; Mohammadi-Ivatloo, B.; Morad Zadeh, M.: Optimal energy management of microgrid in day-ahead and intra-day markets using a copula-based uncertainty modeling method. J. Oper. Autom. Power Eng. (2019). Shahryari, E.; Shayeghi, H.; Mohammadi-Ivatloo, B.; Morad Zadeh, M.: Optimal energy management of microgrid in day-ahead and intra-day markets using a copula-based uncertainty modeling method. J. Oper. Autom. Power Eng. (2019).
37.
Zurück zum Zitat Hagspiel, S., Papaemannouil, A., Schmid, M., Andersson, G.: Copula-based modeling of stochastic wind power in Europe and implications for the Swiss power grid. Appl. Energy 96, 33–44 (2012) Hagspiel, S., Papaemannouil, A., Schmid, M., Andersson, G.: Copula-based modeling of stochastic wind power in Europe and implications for the Swiss power grid. Appl. Energy 96, 33–44 (2012)
38.
Zurück zum Zitat Sklar, M.: Fonctions de repartition an dimensions et leurs marges. Publ. inst. statist. univ. Paris 8, 229–231 (1959)MathSciNetMATH Sklar, M.: Fonctions de repartition an dimensions et leurs marges. Publ. inst. statist. univ. Paris 8, 229–231 (1959)MathSciNetMATH
39.
Zurück zum Zitat Zakariazadeh, A., Jadid, S., Siano, P.: Smart microgrid energy and reserve scheduling with demand response using stochastic optimization. Int. J. Electr. Power Energy Syst. 63, 523–533 (2014) Zakariazadeh, A., Jadid, S., Siano, P.: Smart microgrid energy and reserve scheduling with demand response using stochastic optimization. Int. J. Electr. Power Energy Syst. 63, 523–533 (2014)
40.
Zurück zum Zitat Sedighizadeh, M., Esmaili, M., Jamshidi, A., Ghaderi, M.-H.: Stochastic multi-objective economic-environmental energy and reserve scheduling of microgrids considering battery energy storage system. Int. J. Electr. Power Energy Syst. 106, 1–16 (2019) Sedighizadeh, M., Esmaili, M., Jamshidi, A., Ghaderi, M.-H.: Stochastic multi-objective economic-environmental energy and reserve scheduling of microgrids considering battery energy storage system. Int. J. Electr. Power Energy Syst. 106, 1–16 (2019)
41.
Zurück zum Zitat Talari, S., Yazdaninejad, M., Haghifam, M.-R.: Stochastic-based scheduling of the microgrid operation including wind turbines, photovoltaic cells, energy storages and responsive loads. IET Gener. Transm. Distrib. 9(12), 1498–1509 (2015) Talari, S., Yazdaninejad, M., Haghifam, M.-R.: Stochastic-based scheduling of the microgrid operation including wind turbines, photovoltaic cells, energy storages and responsive loads. IET Gener. Transm. Distrib. 9(12), 1498–1509 (2015)
42.
Zurück zum Zitat Motevasel, M., Seifi, A.R.: Expert energy management of a micro-grid considering wind energy uncertainty. Energy Convers. Manag. 83, 58–72 (2014) Motevasel, M., Seifi, A.R.: Expert energy management of a micro-grid considering wind energy uncertainty. Energy Convers. Manag. 83, 58–72 (2014)
43.
Zurück zum Zitat Zakariazadeh, A., Jadid, S., Siano, P.: Economic-environmental energy and reserve scheduling of smart distribution systems: A multiobjective mathematical programming approach. Energy Convers. Manag. 78, 151–164 (2014) Zakariazadeh, A., Jadid, S., Siano, P.: Economic-environmental energy and reserve scheduling of smart distribution systems: A multiobjective mathematical programming approach. Energy Convers. Manag. 78, 151–164 (2014)
44.
Zurück zum Zitat Sedighizadeh, M., Mohammadpour, A.H., Alavi, S.M.M.: A two-stage optimal energy management by using ADP and HBB-BC algorithms for microgrids with renewable energy sources and storages. J. Energy Storage 21, 460–480 (2019) Sedighizadeh, M., Mohammadpour, A.H., Alavi, S.M.M.: A two-stage optimal energy management by using ADP and HBB-BC algorithms for microgrids with renewable energy sources and storages. J. Energy Storage 21, 460–480 (2019)
45.
Zurück zum Zitat Petrollese, M., Valverde, L., Cocco, D., Cau, G., Guerra, J.: Real-time integration of optimal generation scheduling with MPC for the energy management of a renewable hydrogen-based microgrid. Appl. Energy 166, 96–106 (2016) Petrollese, M., Valverde, L., Cocco, D., Cau, G., Guerra, J.: Real-time integration of optimal generation scheduling with MPC for the energy management of a renewable hydrogen-based microgrid. Appl. Energy 166, 96–106 (2016)
46.
Zurück zum Zitat Su, W., Wang, J., Roh, J.: Stochastic energy scheduling in microgrids with intermittent renewable energy resources. IEEE Trans. Smart Grid 5(4), 1876–1883 (2014) Su, W., Wang, J., Roh, J.: Stochastic energy scheduling in microgrids with intermittent renewable energy resources. IEEE Trans. Smart Grid 5(4), 1876–1883 (2014)
47.
Zurück zum Zitat Sachs, J., Sawodny, O.: Multi-objective three stage design optimization for island microgrids. Appl. Energy 165, 789–800 (2016) Sachs, J., Sawodny, O.: Multi-objective three stage design optimization for island microgrids. Appl. Energy 165, 789–800 (2016)
48.
Zurück zum Zitat Jose-Garcia, A., Gómez-Flores, W.: Automatic clustering using nature-inspired metaheuristics: a survey. Appl. Soft Comput. 41, 192–213 (2016) Jose-Garcia, A., Gómez-Flores, W.: Automatic clustering using nature-inspired metaheuristics: a survey. Appl. Soft Comput. 41, 192–213 (2016)
49.
Zurück zum Zitat Fu, M.C.: Handbook of Simulation Optimization. Springer, Berlin (2015)MATH Fu, M.C.: Handbook of Simulation Optimization. Springer, Berlin (2015)MATH
50.
Zurück zum Zitat Hansen, N.: The CMA evolution strategy: a tutorial. arXiv preprint arXiv:1604.00772. Hansen, N.: The CMA evolution strategy: a tutorial. arXiv preprint arXiv:1604.00772.
51.
Zurück zum Zitat Hansen, N.: The CMA evolution strategy: a comparing review. In: Towards a new evolutionary computation, pp. 75–102. Springer (2006). Hansen, N.: The CMA evolution strategy: a comparing review. In: Towards a new evolutionary computation, pp. 75–102. Springer (2006).
52.
Zurück zum Zitat Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evolut. Comput. 6(2), 182–197 (2002) Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evolut. Comput. 6(2), 182–197 (2002)
53.
Zurück zum Zitat Whitley, D.: A genetic algorithm tutorial. Stat. Comput. 4(2), 65–85 (1994) Whitley, D.: A genetic algorithm tutorial. Stat. Comput. 4(2), 65–85 (1994)
54.
Zurück zum Zitat Trelea, I.C.: The particle swarm optimization algorithm: convergence analysis and parameter selection. Inf. Process. Lett. 85(6), 317–325 (2003)MathSciNetMATH Trelea, I.C.: The particle swarm optimization algorithm: convergence analysis and parameter selection. Inf. Process. Lett. 85(6), 317–325 (2003)MathSciNetMATH
55.
Zurück zum Zitat Karaboga, D.; Basturk, B.: Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems. In International Fuzzy Systems Association World Congress. Springer, pp. 789–798 (2007) Karaboga, D.; Basturk, B.: Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems. In International Fuzzy Systems Association World Congress. Springer, pp. 789–798 (2007)
56.
Zurück zum Zitat Simon, D.: Biogeography-based optimization. IEEE Trans. Evolut. Comput. 12(6), 702–713 (2008) Simon, D.: Biogeography-based optimization. IEEE Trans. Evolut. Comput. 12(6), 702–713 (2008)
57.
Zurück zum Zitat Zhang, N., Kang, C., Xia, Q., Liang, J.: Modeling conditional forecast error for wind power in generation scheduling. IEEE Trans. Power Syst. 29(3), 1316–1324 (2013) Zhang, N., Kang, C., Xia, Q., Liang, J.: Modeling conditional forecast error for wind power in generation scheduling. IEEE Trans. Power Syst. 29(3), 1316–1324 (2013)
58.
Zurück zum Zitat Vulasala, G., Sirigiri, S., Thiruveedula, R.: Feeder reconfiguration for loss reduction in unbalanced distribution system using genetic algorithm. Int. J. Electr. Power Energy Syst. Eng. 3(12), 754–762 (2009) Vulasala, G., Sirigiri, S., Thiruveedula, R.: Feeder reconfiguration for loss reduction in unbalanced distribution system using genetic algorithm. Int. J. Electr. Power Energy Syst. Eng. 3(12), 754–762 (2009)
Metadaten
Titel
Optimal Operation of Unbalanced Microgrid Utilizing Copula-Based Stochastic Simultaneous Unit Commitment and Distribution Feeder Reconfiguration Approach
verfasst von
Ahmad Fakharian
Mostafa Sedighizadeh
Masoud Khajehvand
Publikationsdatum
08.11.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
Arabian Journal for Science and Engineering / Ausgabe 2/2021
Print ISSN: 2193-567X
Elektronische ISSN: 2191-4281
DOI
https://doi.org/10.1007/s13369-020-04965-x

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