{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T21:51:29Z","timestamp":1768254689206,"version":"3.49.0"},"reference-count":32,"publisher":"Walter de Gruyter GmbH","issue":"11","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11,26]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>As greenhouse gases emissions continue to rise, society is actively seeking methods to reduce them. Microgrids (MGs), which predominantly consist of renewable energy sources, play a significant role in achieving this objective. This paper proposes an optimized methodology for power dispatch in MGs using mixed-integer linear programming (MILP). The MGs include photovoltaic systems, wind turbines, biogas (BG) generators, battery energy storage systems (BESS), electric vehicles (EV), and loads. The model features an objective function focused on cost minimization, power balance, and the necessary limits and constraints for the system\u2019s safe operation. Real-time pricing is employed for energy transactions between the MGs and the main grid. The results demonstrate a cost-efficient operation for the proposed system comprising two MGs and the main grid. During periods of negative power balance, the demand was met by discharging the BESS, EV\u2019s battery, or purchasing energy from the grid. The BESS was charged when energy prices were low and discharged during peak demand periods and high energy prices. The intermittent nature of renewable sources necessitates an efficient management system to ensure reliable operation. Additionally, storage systems help mitigate the variability in generation. The BG generator was another crucial component for power supply due to its flexibility. Integrating these components into the system improved reliability and ensured a secure and balanced operation.<\/jats:p>","DOI":"10.1515\/auto-2024-0094","type":"journal-article","created":{"date-parts":[[2024,11,5]],"date-time":"2024-11-05T13:19:13Z","timestamp":1730812753000},"page":"1030-1040","source":"Crossref","is-referenced-by-count":4,"title":["Optimal power dispatch in microgrids using mixed-integer linear programming"],"prefix":"10.1515","volume":"72","author":[{"given":"Renata","family":"Rodrigues Lautert","sequence":"first","affiliation":[{"name":"Institute of Electric Power Systems (IESY) , Otto von Guericke University (OVGU) , Magdeburg , Germany"},{"name":"Center for Excellence in Energy and Power Systems (CEESP) , Federal University of Santa Maria (UFSM) , Santa Maria , Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cl\u00e1udio Adriano C.","family":"Cambambi","sequence":"additional","affiliation":[{"name":"Center for Excellence in Energy and Power Systems (CEESP) , Federal University of Santa Maria (UFSM) , Santa Maria , Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mauro dos Santos","family":"Ortiz","sequence":"additional","affiliation":[{"name":"Institute of Electric Power Systems (IESY) , Otto von Guericke University (OVGU) , Magdeburg , Germany"},{"name":"Center for Excellence in Energy and Power Systems (CEESP) , Federal University of Santa Maria (UFSM) , Santa Maria , Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martin","family":"Wolter","sequence":"additional","affiliation":[{"name":"Institute of Electric Power Systems (IESY) , Otto von Guericke University (OVGU) , Magdeburg , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luciane Neves","family":"Canha","sequence":"additional","affiliation":[{"name":"Center for Excellence in Energy and Power Systems (CEESP) , Federal University of Santa Maria (UFSM) , Santa Maria , Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2024,11,5]]},"reference":[{"key":"2024110513190745206_j_auto-2024-0094_ref_001","unstructured":"H. Ritchie, P. Rosado, and M. Roser, \u201cCO2 and greenhouse gas emissions,\u201d OurWorldInData.org, 2024. Available at: https:\/\/ourworldindata.org\/co2-and-greenhouse-gas-emissions."},{"key":"2024110513190745206_j_auto-2024-0094_ref_002","unstructured":"IRENA, International Renewable Energy Agency, World Energy Transitions Outlook 2022: 1.5 \u00b0C Pathway \u2013 Executive Summary, Abu Dhabi, International Renewable Energy Agency, 2022."},{"key":"2024110513190745206_j_auto-2024-0094_ref_003","doi-asserted-by":"crossref","unstructured":"A. Hirsch, Y. Parag, and J. Guerrero, \u201cMicrogrids: a review of technologies, key drivers, and outstanding issues,\u201d Renew. Sustain. Energy Rev., vol. 90, no. 1, pp. 402\u2013411, 2018. https:\/\/doi.org\/10.1016\/j.rser.2018.03.040.","DOI":"10.1016\/j.rser.2018.03.040"},{"key":"2024110513190745206_j_auto-2024-0094_ref_004","doi-asserted-by":"crossref","unstructured":"D. T. Ton and M. A. Smith, \u201cThe U.S. department of energy\u2019s microgrid initiative,\u201d Electr. J., vol. 25, no. 8, pp. 84\u201394, 2012. https:\/\/doi.org\/10.1016\/j.tej.2012.09.013.","DOI":"10.1016\/j.tej.2012.09.013"},{"key":"2024110513190745206_j_auto-2024-0094_ref_005","doi-asserted-by":"crossref","unstructured":"A. P. Medeiros, L. N. Canha, V. J. Garcia, and C. A. S. Rangel, \u201cA matheuristic for active flexibility management of battery energy storage systems in the context of local flexibility markets,\u201d J. Energy Storage, vol. 95, no. 1, 2024, Art. no. 112625, https:\/\/doi.org\/10.1016\/j.est.2024.112625.","DOI":"10.1016\/j.est.2024.112625"},{"key":"2024110513190745206_j_auto-2024-0094_ref_006","doi-asserted-by":"crossref","unstructured":"S. F. Contreras, C. A. Cortes, and J. M. A. Myrzik, \u201cOpti-mal microgrid planning for enhancing ancillary service provision,\u201d J. Mod. Power Syst. Clean Energy, vol. 7, no. 4, pp. 862\u2013875, 2019. https:\/\/doi.org\/10.1007\/s40565-019-0528-3.","DOI":"10.1007\/s40565-019-0528-3"},{"key":"2024110513190745206_j_auto-2024-0094_ref_007","doi-asserted-by":"crossref","unstructured":"J. L. Martinez-Ramos, et al.., \u201cProvision of ancillary ser-vices by a smart microgrid: an OPF approach,\u201d in 2018 International Conference on Smart Energy Systems and Technologies (SEST) Sevilla, 2018.","DOI":"10.1109\/SEST.2018.8495883"},{"key":"2024110513190745206_j_auto-2024-0094_ref_008","doi-asserted-by":"crossref","unstructured":"Z. Huang, Z. Guo, P. Ma, M. Wang, Y. Long, and M. Zhang, \u201cEconomic-environmental scheduling of microgrid considering V2G-enabled electric vehicles integration,\u201d Sustain. Energy, Grids Netw., vol. 32, no. 1, 2022, Art. no. 100872, https:\/\/doi.org\/10.1016\/j.segan.2022.100872.","DOI":"10.1016\/j.segan.2022.100872"},{"key":"2024110513190745206_j_auto-2024-0094_ref_009","doi-asserted-by":"crossref","unstructured":"X. Zhang, Z. Wang, and Z. Lu, \u201cMulti-objective load dispatch for microgrid with electric vehicles using modified gravitational search and particle swarm optimization algorithm,\u201d Appl. Energy, vol. 306, no. 1, 2022, Art. no. 118018, https:\/\/doi.org\/10.1016\/j.apenergy.2021.118018.","DOI":"10.1016\/j.apenergy.2021.118018"},{"key":"2024110513190745206_j_auto-2024-0094_ref_010","doi-asserted-by":"crossref","unstructured":"A. Jagan, P. K. Ray, B. P. Behera, and G. Panda, \u201cA fuzzy-logic-based smart power management strategy for reliability enhancement of energy storage system in a hybrid AC-DC microgrid with EV charging station,\u201d Int. J. Emerg. Electr. Power Syst., vol. 25, no. 3, pp. 405\u2013419, 2023. https:\/\/doi.org\/10.1515\/ijeeps-2023-0128.","DOI":"10.1515\/ijeeps-2023-0128"},{"key":"2024110513190745206_j_auto-2024-0094_ref_011","doi-asserted-by":"crossref","unstructured":"V. Z. Gjorgievski, S. Cundeva, and G. E. Georghiou, \u201cSocial arrangements, technical designs and impacts of energy communities: a review,\u201d Renew. Energy, vol. 169, no. 1, pp. 1138\u20131156, 2021. https:\/\/doi.org\/10.1016\/j.renene.2021.01.078.","DOI":"10.1016\/j.renene.2021.01.078"},{"key":"2024110513190745206_j_auto-2024-0094_ref_012","doi-asserted-by":"crossref","unstructured":"T. M. M. Guibentif and F. Vuille, \u201cProspects and barriers for microgrids in Switzerland,\u201d Energy Strat. Rev., vol. 39, no. 1, 2022, Art. no. 100776. https:\/\/doi.org\/10.1016\/j.esr.2021.100776.","DOI":"10.1016\/j.esr.2021.100776"},{"key":"2024110513190745206_j_auto-2024-0094_ref_013","doi-asserted-by":"crossref","unstructured":"J. Hu, Y. Shan, K. W. Cheng, and S. Islam, \u201cOverview of power converter control in microgrids \u2013 challenges, advances, and future trends,\u201d IEEE Trans. Power Electron., vol. 37, no. 8, pp. 9907\u20139922, 2022. https:\/\/doi.org\/10.1109\/TPEL.2022.3159828.","DOI":"10.1109\/TPEL.2022.3159828"},{"key":"2024110513190745206_j_auto-2024-0094_ref_014","doi-asserted-by":"crossref","unstructured":"K. I. Ibekwe, et al.., \u201cMicrogrid systems in U.S. energy infrastructure: a comprehensive review: exploring decentralized energy solutions, their benefits, and challenges in regional implementation,\u201d World J. Adv. Res. Rev., vol. 21, no. 1, pp. 973\u2013987, 2024. https:\/\/doi.org\/10.30574\/wjarr.2024.21.1.0112.","DOI":"10.30574\/wjarr.2024.21.1.0112"},{"key":"2024110513190745206_j_auto-2024-0094_ref_015","doi-asserted-by":"crossref","unstructured":"M. F. Zia, M. Benbouzid, E. Elbouchikhi, S. M. Muyeen, K. Techato, and J. M. Guerrero, \u201cMicrogrid transactive energy: review, architectures, distributed ledger technologies, and market analysis,\u201d IEEE Access, vol. 8, no. 1, pp. 19410\u201319432, 2020. https:\/\/doi.org\/10.1109\/ACCESS.2020.2968402.","DOI":"10.1109\/ACCESS.2020.2968402"},{"key":"2024110513190745206_j_auto-2024-0094_ref_016","doi-asserted-by":"crossref","unstructured":"G. S. Thirunavukkarasu, M. Seyedmahmoudian, E. Jamei, B. Horan, S. Mekhilef, and A. Stojcevski, \u201cRole of optimization techniques in microgrid energy management systems \u2013 a review,\u201d Energy Strat. Rev., vol. 43, no. 1, 2022, Art. no. 100899. https:\/\/doi.org\/10.1016\/j.esr.2022.100899.","DOI":"10.1016\/j.esr.2022.100899"},{"key":"2024110513190745206_j_auto-2024-0094_ref_017","doi-asserted-by":"crossref","unstructured":"A. R. Battula, S. Vuddanti, and S. R. Salkuti, \u201cReview of energy management system approaches in microgrids,\u201d Energies, vol. 14, no. 17, p. 5459, 2021. https:\/\/doi.org\/10.3390\/en14175459.","DOI":"10.3390\/en14175459"},{"key":"2024110513190745206_j_auto-2024-0094_ref_018","doi-asserted-by":"crossref","unstructured":"G. Papazoglou and P. Biskas, \u201cReview and comparison of genetic algorithm and particle swarm optimization in the optimal power flow problem,\u201d Energies, vol. 16, no. 3, p. 1152, 2023. https:\/\/doi.org\/10.3390\/en16031152.","DOI":"10.3390\/en16031152"},{"key":"2024110513190745206_j_auto-2024-0094_ref_019","doi-asserted-by":"crossref","unstructured":"X. S. Yang, Engineering Optimization: An Introduction with Metaheuristic Applications, United Kingdom, John Wiley & Sons, 2010.","DOI":"10.1002\/9780470640425"},{"key":"2024110513190745206_j_auto-2024-0094_ref_020","unstructured":"R. R. Lautert, C. A. C. Cambambi, C. A. S. Rangel, L. N. Canha, M. Wolter, and M. S. Ortiz, \u201cModeling and optimization of transactive energy management for microgrids,\u201d in Dresdener Kreis, 2024, to appear."},{"key":"2024110513190745206_j_auto-2024-0094_ref_021","doi-asserted-by":"crossref","unstructured":"F. A. Kassab, B. Celik, F. Locment, M. Sechilariu, S. Liaquat, and T. M. Hansen, \u201cOptimal sizing and energy management of a microgrid: a joint MILP approach for minimization of energy cost and carbon emission,\u201d Renew. Energy, vol. 224, no. 1, 2024, Art. no. 120186. https:\/\/doi.org\/10.1016\/j.renene.2024.120186.","DOI":"10.1016\/j.renene.2024.120186"},{"key":"2024110513190745206_j_auto-2024-0094_ref_022","doi-asserted-by":"crossref","unstructured":"A. Nurkanovi\u0107, et al.., \u201cOptimization-based primary and secondary control of microgrids,\u201d Automatisierungstechnik, vol.\u00a068, no.\u00a012, pp.\u00a01044\u20131058, 2020. https:\/\/doi.org\/10.1515\/auto-2020-0088.","DOI":"10.1515\/auto-2020-0088"},{"key":"2024110513190745206_j_auto-2024-0094_ref_023","doi-asserted-by":"crossref","unstructured":"R. R. Lautert, W. D. S. Brignol, L. N. Canha, O. M. Adeyanju, and V. J. Garcia, \u201cA flexible-reliable operation model of storage and distributed generation in a biogas power plant,\u201d Energies, vol.\u00a015, no.\u00a09, p.\u00a03154, 2022. https:\/\/doi.org\/10.3390\/en15093154.","DOI":"10.3390\/en15093154"},{"key":"2024110513190745206_j_auto-2024-0094_ref_024","doi-asserted-by":"crossref","unstructured":"P. Faria and Z. Vale, \u201cDemand response in electrical energy supply: an optimal real time pricing approach,\u201d Energy, vol.\u00a036, no.\u00a08, pp.\u00a05374\u20135384, 2011. https:\/\/doi.org\/10.1016\/j.energy.2011.06.049.","DOI":"10.1016\/j.energy.2011.06.049"},{"key":"2024110513190745206_j_auto-2024-0094_ref_025","doi-asserted-by":"crossref","unstructured":"K. Milis, H. Peremans, and S. Van Passel, \u201cThe impact of policy on microgrid economics: a review,\u201d Renew. Sustain. Energy Rev., vol. 81, no. 1, pp. 3111\u20133119, 2018. https:\/\/doi.org\/10.1016\/j.rser.2017.08.091.","DOI":"10.1016\/j.rser.2017.08.091"},{"key":"2024110513190745206_j_auto-2024-0094_ref_026","doi-asserted-by":"crossref","unstructured":"T. Achterberg, R. E. Bixby, Z. Gu, E. Rothberg, and D. Weninger, \u201cPresolve reductions in mixed integer programming,\u201d INFORMS J. Comput., vol.\u00a032, no.\u00a02, pp.\u00a0473\u2013506, 2020. https:\/\/doi.org\/10.1287\/ijoc.2018.0857.","DOI":"10.1287\/ijoc.2018.0857"},{"key":"2024110513190745206_j_auto-2024-0094_ref_027","doi-asserted-by":"crossref","unstructured":"J. O. Lee and Y. S. Kim, \u201cNovel battery degradation cost formulation for optimal scheduling of battery energy storage systems,\u201d Int. J. Electr. Power Energy Syst., vol. 137, no. 1, 2022, Art. no. 107795. https:\/\/doi.org\/10.1016\/j.ijepes.2021.107795.","DOI":"10.1016\/j.ijepes.2021.107795"},{"key":"2024110513190745206_j_auto-2024-0094_ref_028","doi-asserted-by":"crossref","unstructured":"C. A. C. Cambambi, L. N. Canha, M. Sperandio, C. A. S. Rangel, and I. Milani, \u201cEnergy exchange optimization among multiple geolocated microgrids: a coalition formation approach for cost reduction,\u201d SSRN, 2024, https:\/\/doi.org\/10.2139\/ssrn.4870166.","DOI":"10.2139\/ssrn.4870166"},{"key":"2024110513190745206_j_auto-2024-0094_ref_029","doi-asserted-by":"crossref","unstructured":"G. Rancilio, M. Merlo, A. Lucas, E. Kotsakis, and M. Delfanti, \u201cBESS modeling: investigating the role of auxiliary system consumption in efficiency derating,\u201d in 2020 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), Sorrento, Italy, 2020, pp.\u00a0189\u2013194.","DOI":"10.1109\/SPEEDAM48782.2020.9161875"},{"key":"2024110513190745206_j_auto-2024-0094_ref_030","doi-asserted-by":"crossref","unstructured":"C. A. Sep\u00falveda Rangel, L. N. Canha, M. Sperandio, and V. Miranda, \u201cMixed-integer stochastic evaluation of battery energy storage system integration strategies in distribution systems,\u201d IET Gener. Transm. Distrib., vol.\u00a016, no.\u00a04, pp.\u00a0641\u2013655, 2022. https:\/\/doi.org\/10.1049\/gtd2.12316.","DOI":"10.1049\/gtd2.12316"},{"key":"2024110513190745206_j_auto-2024-0094_ref_031","doi-asserted-by":"crossref","unstructured":"Z. Xiaohui, G. Wenbo, and Z. Jiaqing, \u201cDecentralized economic dispatching of multi-micro grid considering wind power and photovoltaic output uncertainty,\u201d IEEE Access, vol. 9, no. 1, pp. 104093\u2013104103, 2021. https:\/\/doi.org\/10.1109\/ACCESS.2021.3099401.","DOI":"10.1109\/ACCESS.2021.3099401"},{"key":"2024110513190745206_j_auto-2024-0094_ref_032","doi-asserted-by":"crossref","unstructured":"M. Gholami, S. M. Muyeen, and S. Lin, \u201cOptimizing microgrid efficiency: coordinating commercial and residential demand patterns with shared battery energy storage,\u201d J. 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