A MIQP model for optimal location and sizing of dispatchable DGs in DC networks
The allocation and dimensioning of distributed generators (DGs) in direct current (DC) power grids were addressed in this study by using a mixed-integer quadratic programming (MIQP) formulation. The MIQP model corresponded to an approximation of the mixed-integer nonlinear programming (MINLP) model...
- Autores:
-
Montoya, Oscar Danilo
Gil-González, Walter
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/9541
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/9541
https://link.springer.com/article/10.1007/s12667-020-00403-x
- Palabra clave:
- Direct current power grids
Distributed generators
Mixed-integer programming model
Mixed-integer nonlinear programming model
Optimal power flow
- Rights
- closedAccess
- License
- http://purl.org/coar/access_right/c_14cb
| id |
UTB2_12aed1b236aea7a30d8d9fabfa4551ef |
|---|---|
| oai_identifier_str |
oai:repositorio.utb.edu.co:20.500.12585/9541 |
| network_acronym_str |
UTB2 |
| network_name_str |
Repositorio Institucional UTB |
| repository_id_str |
|
| dc.title.spa.fl_str_mv |
A MIQP model for optimal location and sizing of dispatchable DGs in DC networks |
| title |
A MIQP model for optimal location and sizing of dispatchable DGs in DC networks |
| spellingShingle |
A MIQP model for optimal location and sizing of dispatchable DGs in DC networks Direct current power grids Distributed generators Mixed-integer programming model Mixed-integer nonlinear programming model Optimal power flow |
| title_short |
A MIQP model for optimal location and sizing of dispatchable DGs in DC networks |
| title_full |
A MIQP model for optimal location and sizing of dispatchable DGs in DC networks |
| title_fullStr |
A MIQP model for optimal location and sizing of dispatchable DGs in DC networks |
| title_full_unstemmed |
A MIQP model for optimal location and sizing of dispatchable DGs in DC networks |
| title_sort |
A MIQP model for optimal location and sizing of dispatchable DGs in DC networks |
| dc.creator.fl_str_mv |
Montoya, Oscar Danilo Gil-González, Walter |
| dc.contributor.author.none.fl_str_mv |
Montoya, Oscar Danilo Gil-González, Walter |
| dc.subject.keywords.spa.fl_str_mv |
Direct current power grids Distributed generators Mixed-integer programming model Mixed-integer nonlinear programming model Optimal power flow |
| topic |
Direct current power grids Distributed generators Mixed-integer programming model Mixed-integer nonlinear programming model Optimal power flow |
| description |
The allocation and dimensioning of distributed generators (DGs) in direct current (DC) power grids were addressed in this study by using a mixed-integer quadratic programming (MIQP) formulation. The MIQP model corresponded to an approximation of the mixed-integer nonlinear programming (MINLP) model that represents this problem correctly. The proposed MIQP had, for its objective function, the minimization of the power losses; as constraints, it had power balance, voltage regulation, distributed generation capacity, and the number of DGs available, among others. The general algebraic modeling system (GAMS) was employed for solving the proposed MIQP as well as the MINLP formulation. Simulation results for one DC network with 21 nodes and another with 69 revealed that the proposed MIQP model obtains high-quality results regarding the locations of the generators, the objective function, and the power dispatch in comparison to the exact MINLP model and metaheuristic techniques recently reported in specialized literature. |
| publishDate |
2020 |
| dc.date.accessioned.none.fl_str_mv |
2020-11-04T21:31:02Z |
| dc.date.available.none.fl_str_mv |
2020-11-04T21:31:02Z |
| dc.date.issued.none.fl_str_mv |
2020-08-27 |
| dc.date.submitted.none.fl_str_mv |
2020-11-03 |
| dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
| dc.type.hasVersion.spa.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.spa.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
| status_str |
publishedVersion |
| dc.identifier.citation.spa.fl_str_mv |
Montoya, O.D., Gil-González, W. A MIQP model for optimal location and sizing of dispatchable DGs in DC networks. Energy Syst (2020). https://doi.org/10.1007/s12667-020-00403-x |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/9541 |
| dc.identifier.url.none.fl_str_mv |
https://link.springer.com/article/10.1007/s12667-020-00403-x |
| dc.identifier.doi.none.fl_str_mv |
10.1007/s12667-020-00403-x |
| dc.identifier.instname.spa.fl_str_mv |
Universidad Tecnológica de Bolívar |
| dc.identifier.reponame.spa.fl_str_mv |
Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
Montoya, O.D., Gil-González, W. A MIQP model for optimal location and sizing of dispatchable DGs in DC networks. Energy Syst (2020). https://doi.org/10.1007/s12667-020-00403-x 10.1007/s12667-020-00403-x Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
| url |
https://hdl.handle.net/20.500.12585/9541 https://link.springer.com/article/10.1007/s12667-020-00403-x |
| dc.language.iso.spa.fl_str_mv |
eng |
| language |
eng |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_14cb |
| dc.rights.accessRights.spa.fl_str_mv |
info:eu-repo/semantics/closedAccess |
| eu_rights_str_mv |
closedAccess |
| rights_invalid_str_mv |
http://purl.org/coar/access_right/c_14cb |
| dc.format.mimetype.spa.fl_str_mv |
application/pdf |
| dc.publisher.place.spa.fl_str_mv |
Cartagena de Indias |
| dc.source.spa.fl_str_mv |
Energy Systems (2020) Article in Press |
| institution |
Universidad Tecnológica de Bolívar |
| bitstream.url.fl_str_mv |
https://repositorio.utb.edu.co/bitstream/20.500.12585/9541/1/80.pdf https://repositorio.utb.edu.co/bitstream/20.500.12585/9541/2/license.txt https://repositorio.utb.edu.co/bitstream/20.500.12585/9541/3/80.pdf.txt https://repositorio.utb.edu.co/bitstream/20.500.12585/9541/4/80.pdf.jpg |
| bitstream.checksum.fl_str_mv |
5cea01bcb47a44a2b619e279f3c0a0aa e20ad307a1c5f3f25af9304a7a7c86b6 c590acfe6954216d0a70de249f18b333 0f82e6676cc6a03e91809166c09596b8 |
| bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 |
| repository.name.fl_str_mv |
Repositorio Institucional UTB |
| repository.mail.fl_str_mv |
repositorioutb@utb.edu.co |
| _version_ |
1814021570958458880 |
| spelling |
Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Gil-González, Walterce1f5078-74c6-4b5c-b56a-784f85e52a082020-11-04T21:31:02Z2020-11-04T21:31:02Z2020-08-272020-11-03Montoya, O.D., Gil-González, W. A MIQP model for optimal location and sizing of dispatchable DGs in DC networks. Energy Syst (2020). https://doi.org/10.1007/s12667-020-00403-xhttps://hdl.handle.net/20.500.12585/9541https://link.springer.com/article/10.1007/s12667-020-00403-x10.1007/s12667-020-00403-xUniversidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThe allocation and dimensioning of distributed generators (DGs) in direct current (DC) power grids were addressed in this study by using a mixed-integer quadratic programming (MIQP) formulation. The MIQP model corresponded to an approximation of the mixed-integer nonlinear programming (MINLP) model that represents this problem correctly. The proposed MIQP had, for its objective function, the minimization of the power losses; as constraints, it had power balance, voltage regulation, distributed generation capacity, and the number of DGs available, among others. The general algebraic modeling system (GAMS) was employed for solving the proposed MIQP as well as the MINLP formulation. Simulation results for one DC network with 21 nodes and another with 69 revealed that the proposed MIQP model obtains high-quality results regarding the locations of the generators, the objective function, and the power dispatch in comparison to the exact MINLP model and metaheuristic techniques recently reported in specialized literature.application/pdfengEnergy Systems (2020) Article in PressA MIQP model for optimal location and sizing of dispatchable DGs in DC networksinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Direct current power gridsDistributed generatorsMixed-integer programming modelMixed-integer nonlinear programming modelOptimal power flowinfo:eu-repo/semantics/closedAccesshttp://purl.org/coar/access_right/c_14cbCartagena de IndiasPúblico generalGarces, A.: Uniqueness of the power flow solutions in low voltage direct current grids. Electr. Power Syst. Res. 151(Supplement C), 149–153 (2017)Montoya, O.D., Gil-González, W., Garces, A.: Numerical methods for power flow analysis in DC networks: state of the art, methods and challenges. Int. J. Electr. Power Energy Syst. 123, 106299 (2020)Simpson-Porco, J.W., Dorfler, F., Bullo, F.: On resistive networks of constant-power devices. IEEE Trans. Circ. Syst. II Express Briefs 62(8), 811–815 (2015)Sanchez, S., Ortega, R., Griño, R., Bergna, G., Molinas, M.: Conditions for existence of equilibria of systems with constant power loads. IEEE Trans. Circuits Syst. I Regul. Pap. 61(7), 2204–2211 (2014)Karimipour, D., Salmasi, F.R.: Stability analysis of AC microgrids with constant power loads based on Popov’s absolute stability criterion. IEEE Trans. Circ. Syst. II Express Briefs 62(7), 696–700 (2015)Barabanov, N., Ortega, R., Griñó, R., Polyak, B.: On existence and stability of equilibria of linear time-invariant systems with constant power loads. IEEE Trans. Circuits Syst. I Regul. Pap. 63(1), 114–121 (2016)Montoya, O.D., Gil-González, W., Garces, A.: Sequential quadraticprogramming models for solving the OPF problem in DC grids. Electr. Power Syst. Res. 169, 18–23 (2019)Garces, A.: On convergence of Newton’s method in power flow study for DC microgrids. IEEE Trans. Power Syst. 33(5), 5770–5777 (2018)Montoya, O.D., Grisales-Noreña, L.F., González-Montoya, D., Ramos-Paja, C., Garces, A.: Linear power flow formulation for low-voltage DC power grids. Electr. Power Syst. Res. 163, 375–381 (2018)Garces, A., Montoya, D., Torres, R.: Optimal power flow in multiterminal HVDC systems considering DC/DC converters. In: 2016 IEEE 25th International Symposium on Industrial Electronics (ISIE), pp. 1212–1217 (2016)Molzahn, D.K.: Identifying and characterizing non-convexities in feasible spaces of optimal power flow problems. IEEE Trans. Circ. Syst. II 65(5), 672–676 (2018)Li, J., Liu, F., Wang, Z., Low, S., Mei, S.: Optimal power flow in stand-alone DC microgrids. IEEE Trans. Power Syst. 33(5), 5496–5506 (2018)Gil-González, W., Montoya, O.D., Grisales-Noreña, L.F., Cruz-Peragón, F., Alcalá, G.: Economic dispatch of renewable generators and BESS in DC microgrids using second-order cone optimization. Energies 13(7), 1703 (2020)Kaur, S., Kumbhar, G., Sharma, J.: A MINLP technique for optimal placement of multiple DG units in distribution systems. Int. J. Electr. Power Energy Syst. 63, 609–617 (2014)Grisales-Noreña, L.F., Gonziez-Montoya, D., Ramos-Paja, C.A.: Optimal sizing and location of distributed generators based on PBIL and PSO techniques. Energies 11(4), 1–27 (2018)Kansal, S., Kumar, V., Tyagi, B.: Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks. Int. J. Electr. Power Energy Syst. 75, 226–235 (2016)Gampa, S.R., Das, D.: Optimum placement and sizing of DGs considering average hourly variations of load. Int. J. Electr. Power Energy Syst. 66, 25–40 (2015)Ali, E., Elazim, S.A., Abdelaziz, A.: Ant lion optimization algorithm for optimal location and sizing of renewable distributed generations. Renewable Energy 101, 1311–1324 (2017)Georgilakis, P.S., Hatziargyriou, N.D.: Optimal distributed generation placement in power distribution networks: models, methods, and future research. IEEE Trans. Power Syst. 28(3), 3420–3428 (2013)Nekooei, K., Farsangi, M.M., Nezamabadi-Pour, H., Lee, K.Y.: An improved multi-objective harmony search for optimal placement of DGs in distribution systems. IEEE Trans. Smart Grid 4(1), 557–567 (2013)Acharya, N., Mahat, P., Mithulananthan, N.: An analytical approach for DG allocation in primary distribution network. Int. J. Electr. Power Energy Syst. 28(10), 669–678 (2006)Shaaban, M.F., Atwa, Y.M., El-Saadany, E.F.: DG allocation for benefit maximization in distribution networks. IEEE Trans. Power Syst. 28(2), 639–649 (2013)Khalesi, N., Rezaei, N., Haghifam, M.-R.: DG allocation with application of dynamic programming for loss reduction and reliability improvement. Int. J. Electr. Power Energy Syst. 33(2), 288–295 (2011)Montoya, O.D.: A convex OPF approximation for selecting the best candidate nodes for optimal location of power sources on DC resistive networks. Eng. Sci. Technol. Int. J. (2019)Montoya, O.D., Gil-González, W., Grisales-Noreña, L.: Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approaches. Int. J. Electr. Power Energy Syst. 115, 105442 (2020)Nasir, M., Iqbal, S., Khan, H.A.: Optimal planning and design of low-voltage low-power solar DC microgrids. IEEE Trans. Power Syst. 33(3), 2919–2928 (2018)Montoya, O.D., Garrido, V.M., Grisales-Noreña, L.F., Gil-González, W., Garces, A., Ramos-Paja, C.A.: Optimal location of DGs in DC Power Grids Using a MINLP Model Implemented in GAMS. In: 2018 IEEE 9th Power, Instrumentation and Measurement Meeting (EPIM), pp. 1–5 (Nov 2018)Grisales-Noreña, L.F., Garzon-Rivera, O.D., Montoya, O.D., Ramos-Paja, C.A.: Hybrid metaheuristic optimization methods for optimal location and sizing DGs in DC networks. Springer, ch. Applied Computer Sciences in Engineering, pp. 214–225 (2019)Gil-González, W., Montoya, O.D., Holguín, E., Garces, A., Grisales-Noreña, L.F.: Economic dispatch of energy storage systems in DC microgrids employing a semidefinite programming model. J. Energy Storage 21, 1–8 (2019)Garces, A., Montoya, O.D.: A potential function for the power flow in DC microgrids: an analysis of the uniqueness and existence of the solution and convergence of the algorithms. J. Control Autom. Electr. Syst. 5(30), 794–801 (2019)Skworcow, P., Paluszczyszyn, D., Ulanicki, B., Rudek, R., Belrain, T.: Optimisation of pump and valve schedules in complex large-scale water distribution systems using gams modelling language. Procedia Eng. 12th International Conference on Computing and Control for the Water Industry, vol. 70, pp. 1566–1574 (2014)Montoya, O.D., Gil-González, W., Grisales-Noreña, L.: An exact MINLP model for optimal location and sizing of DGs in distribution networks: A general algebraic modeling system approach. Ain Shams Eng. J. (2019)Gil-González, W., Montoya, O.D., Grisales-Noreña, L.F., Perea-Moreno, A.-J., Hernandez-Escobedo, Q.: Optimal placement and sizing of wind generators in AC grids considering reactive power capability and wind speed curves. Sustainability 12(7), 2983 (2020)Montoya, O.D., Grisales-Noreña, L.F., Gil-González, W., Alcalá, G., Hernandez-Escobedo, Q.: Optimal location and sizing of PV sources in DC networks for minimizing greenhouse emissions in diesel generators. Symmetry 12(2), 322 (2020)Naghiloo, A., Abbaspour, M., Mohammadi-Ivatloo, B., Bakhtari, K.: GAMS based approach for optimal design and sizing of a pressure retarded osmosis power plant in Bahmanshir river of Iran. Renew Sustain. Energy Rev. 52, 1559–1565 (2015)Montoya, O.D., Gil-González, W., Grisales-Noreña, L., Orozco-Henao, C., Serra, F.: Economic dispatch of BESS and renewable generators in DC microgrids using voltage-dependent load models. Energies 12(23), 4494 (2019)Soroudi, A.: Power System Optimization Modeling in GAMS. Springer, New York (2017)Amin, W.T., Montoya, O.D., Grisales-Noreña, L.F.: Determination of the Voltage Stability Index in DC Networks with CPLs: A GAMS Implementation. In: Communications in Computer and Information Science. Springer, New York, pp. 552–564 (2019)Tartibu, L., Sun, B., Kaunda, M.: Multi-objective optimization of the stack of a thermoacoustic engine using GAMS. Appl. Soft Comput. 28, 30–43 (2015)Floudas, C.A., Pardalos, P.M. (eds.): Encyclopedia of Optimization. Springer, New York (2009)Bertsimas, D., Shioda, R.: Algorithm for cardinality-constrained quadratic optimization. Comput. Optim. Appl. 43(1), 1–22 (2007)Bliek, C., Bonami, P., Lodi, A.: Solving Mixed-Integer Quadratic Programming problems with IBM-CPLEX : a progress report. In: Proceedings of the Twenty-Sixth RAMP Symposium, pp. 171–180 (2014). http://www.orsj.or.jp/ramp/2014/paper/4-3.pdfMontoya, O.D., Gil-González, W., Garces, A.: Optimal power flow on DC microgrids: a quadratic convex approximation. IEEE Trans. Circ. Syst. II, 1–1 (2018)Montoya, O.D., Garces, A., Castro, C.A.: Optimal conductor size selection in radial distribution networks using a mixed-integer non-linear programming formulation. IEEE Latin Am. Trans. 16(8), 2213–2220 (2018)http://purl.org/coar/resource_type/c_2df8fbb1ORIGINAL80.pdf80.pdfapplication/pdf61468https://repositorio.utb.edu.co/bitstream/20.500.12585/9541/1/80.pdf5cea01bcb47a44a2b619e279f3c0a0aaMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-83182https://repositorio.utb.edu.co/bitstream/20.500.12585/9541/2/license.txte20ad307a1c5f3f25af9304a7a7c86b6MD52TEXT80.pdf.txt80.pdf.txtExtracted texttext/plain1139https://repositorio.utb.edu.co/bitstream/20.500.12585/9541/3/80.pdf.txtc590acfe6954216d0a70de249f18b333MD53THUMBNAIL80.pdf.jpg80.pdf.jpgGenerated Thumbnailimage/jpeg48689https://repositorio.utb.edu.co/bitstream/20.500.12585/9541/4/80.pdf.jpg0f82e6676cc6a03e91809166c09596b8MD5420.500.12585/9541oai:repositorio.utb.edu.co:20.500.12585/95412020-11-25 13:02:14.53Repositorio Institucional UTBrepositorioutb@utb.edu.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 |