Extended mixed integer quadratic programming for simultaneous distributed generation location and network reconfiguration
DOI:
https://doi.org/10.20998/2074-272X.2023.2.14Keywords:
active distribution networks, distribution system reconfiguration, distributed generation, mixed-integer quadratic programming, power lossAbstract
Introduction. To minimise power loss, maintain the voltage within the acceptable range, and improve power quality in power distribution networks, reconfiguration and optimal distributed generation placement are presented. Power flow analysis and advanced optimization techniques that can handle significant combinatorial problems must be used in distribution network reconfiguration investigations. The optimization approach to be used depends on the size of the distribution network. Our methodology simultaneously addresses two nonlinear discrete optimization problems to construct an intelligent algorithm to identify the best solution. The proposed work is novel in that it the Extended Mixed-Integer Quadratic Programming (EMIQP) technique, a deterministic approach for determining the topology that will effectively minimize power losses in the distribution system by strategically sizing and positioning Distributed Generation (DG) while taking network reconfiguration into account. Using an efficient Quadratic Mixed Integer Programming (QMIP) solver (IBM ®), the resulting optimization problem has a quadratic form. To ascertain the range and impact of various variables, our methodology outperforms cutting-edge algorithms described in the literature in terms of the obtained power loss reduction, according to extensive numerical validation carried out on typical IEEE 33- and 69-bus systems at three different load factors. Practical value. Examining the effectiveness of concurrent reconfiguration and DG allocation versus sole reconfiguration is done using test cases. According to the findings, network reconfiguration along with the installation of a distributed generator in the proper location, at the proper size, with the proper loss level, and with a higher profile, is effective.
References
Wu Y.-K., Lee C.-Y., Liu L.-C., Tsai S.-H. Study of reconfiguration for the distribution system with distributed generators. IEEE Transactions on Power Delivery, 2010, vol. 25, no. 3, pp. 1678-1685. doi: https://doi.org/10.1109/TPWRD.2010.2046339.
Kansal S., Kumar V., Tyagi B. Optimal placement of different type of DG sources in distribution networks. International Journal of Electrical Power & Energy Systems, 2013, vol. 53, pp. 752-760. doi: https://doi.org/10.1016/j.ijepes.2013.05.040.
Esmaeilian H.R., Fadaeinedjad R. Energy Loss Minimization in Distribution Systems Utilizing an Enhanced Reconfiguration Method Integrating Distributed Generation. IEEE Systems Journal, 2015, vol. 9, no. 4, pp. 1430-1439. doi: https://doi.org/10.1109/JSYST.2014.2341579.
Sambaiah K.S., Jayabarathi T. Loss minimization techniques for optimal operation and planning of distribution systems: A review of different methodologies. International Transactions on Electrical Energy Systems, 2020, vol. 30, no. 2, pp. 1-48. doi: https://doi.org/10.1002/2050-7038.12230.
Bayat A., Bagheri A., Noroozian R. Optimal siting and sizing of distributed generation accompanied by reconfiguration of distribution networks for maximum loss reduction by using a new UVDA-based heuristic method. International Journal of Electrical Power & Energy Systems, 2016, vol. 77, pp. 360-371. doi: https://doi.org/10.1016/j.ijepes.2015.11.039.
Lotfipour A., Afrakhte H. A discrete Teaching–Learning-Based Optimization algorithm to solve distribution system reconfiguration in presence of distributed generation. International Journal of Electrical Power & Energy Systems, 2016, vol. 82, pp. 264-273. doi: https://doi.org/10.1016/j.ijepes.2016.03.009.
Tebbakh N., Labed D., Labed M.A. Optimal size and location of distributed generations in distribution networks using bald eagle search algorithm. Electrical Engineering & Electromechanics, 2022, no. 6, pp. 75-80. doi: https://doi.org/10.20998/2074-272X.2022.6.11.
Taher S.A., Karimi M.H. Optimal reconfiguration and DG allocation in balanced and unbalanced distribution systems. Ain Shams Engineering Journal, 2014, vol. 5, no. 3, pp. 735-749. doi: https://doi.org/10.1016/j.asej.2014.03.009.
Dogan A., Alci M. Simultaneous Optimization of Network Reconfiguration and DG Installation Using Heuristic Algorithms. Elektronika Ir Elektrotechnika, 2019, vol. 25, no. 1, pp. 8-13. doi: https://doi.org/10.5755/j01.eie.25.1.22729.
Esmaeili M., Sedighizadeh M., Esmaili M. Multi-objective optimal reconfiguration and DG (Distributed Generation) power allocation in distribution networks using Big Bang-Big Crunch algorithm considering load uncertainty. Energy, 2016, vol. 103, pp. 86-99. doi: https://doi.org/10.1016/j.energy.2016.02.152.
Jasthi K., Das D. Simultaneous distribution system reconfiguration and DG sizing algorithm without load flow solution. IET Generation, Transmission & Distribution, 2018, vol. 12, no. 6, pp. 1303-1313. doi: https://doi.org/10.1049/iet-gtd.2017.0338.
Mohamed Imran A., Kowsalya M., Kothari D.P. A novel integration technique for optimal network reconfiguration and distributed generation placement in power distribution networks. International Journal of Electrical Power & Energy Systems, 2014, vol. 63, pp. 461-472. doi: https://doi.org/10.1016/j.ijepes.2014.06.011.
Nguyen T.T., Truong A.V., Phung T.A. A novel method based on adaptive cuckoo search for optimal network reconfiguration and distributed generation allocation in distribution network. International Journal of Electrical Power & Energy Systems, 2016, vol. 78, pp. 801-815. doi: https://doi.org/10.1016/j.ijepes.2015.12.030.
Sambaiah K.S., Jayabarathi T. Optimal reconfiguration and renewable distributed generation allocation in electric distribution systems. International Journal of Ambient Energy, 2021, vol. 42, no. 9, pp. 1018-1031. doi: https://doi.org/10.1080/01430750.2019.1583604.
Rao R.S., Ravindra K., Satish K., Narasimham S.V.L. Power Loss Minimization in Distribution System Using Network Reconfiguration in the Presence of Distributed Generation. IEEE Transactions on Power Systems, 2013, vol. 28, no. 1, pp. 317-325. doi: https://doi.org/10.1109/TPWRS.2012.2197227.
Nayak M.R. Optimal Feeder Reconfiguration of Distribution System with Distributed Generation Units using HC-ACO. International Journal on Electrical Engineering and Informatics, 2014, vol. 6, no. 1, pp. 107-128. doi: https://doi.org/10.15676/ijeei.2014.6.1.8.
Rajaram R., Sathish Kumar K., Rajasekar N. Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG). Energy Reports, 2015, vol. 1, pp. 116-122. doi: https://doi.org/10.1016/j.egyr.2015.03.002.
Hamida I.B., Salah S.B., Msahli F., Mimouni M.F. Simultaneous Distribution Network Reconfiguration and Optimal Distributed Generations Integration using a Pareto Evolutionary Algorithm. International Journal of Renewable Energy Research, 2018, vol. 8, no. 1, pp. 345-356. doi: https://doi.org/10.20508/ijrer.v8i1.6789.g7309.
Nawaz S., Singh S., Awasthi S. Power Loss Minimization in Radial Distribution System using Network Reconfiguration and Multiple DG Units. European Journal of Scientific Research, 2018, vol. 148, no. 4, pp. 474-483.
Tami Y., Sebaa K., Lahdeb M., Nouri H. Mixed-Integer Quadratic Constrained Programming versus Quadratic Programming Methods for Distribution Network Reconfiguration. 2019 International Conference on Advanced Electrical Engineering (ICAEE), 2019, pp. 1-5. doi: https://doi.org/10.1109/ICAEE47123.2019.9015181.
Rosseti G.J.S., de Oliveira E.J., de Oliveira L.W., Silva I.C., Peres W. Optimal allocation of distributed generation with reconfiguration in electric distribution systems. Electric Power Systems Research, 2013, vol. 103, pp. 178-183. doi: https://doi.org/10.1016/j.epsr.2013.05.017.
Taylor J.A., Hover F.S. Convex Models of Distribution System Reconfiguration. IEEE Transactions on Power Systems, 2012, vol. 27, no. 3, pp. 1407-1413. doi: https://doi.org/10.1109/TPWRS.2012.2184307.
Boyd S., Vandenberghe L. Convex Optimization. New York, Cambridge University Press, 2004. 716 p.
Abd El-salam M., Beshr E., Eteiba M. A New Hybrid Technique for Minimizing Power Losses in a Distribution System by Optimal Sizing and Siting of Distributed Generators with Network Reconfiguration. Energies, 2018, vol. 11, no. 12, art. no. 3351. doi: https://doi.org/10.3390/en11123351.
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