{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:33:21Z","timestamp":1787027601856,"version":"3.56.0"},"reference-count":90,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T00:00:00Z","timestamp":1752192000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The increasing integration of renewable energy sources (RES) in power systems presents challenges related to variability, stability, and efficiency, particularly in smart microgrids. This systematic review, following the PRISMA 2020 methodology, analyzed 66 studies focused on advanced energy storage systems, intelligent control strategies, and optimization techniques. Hybrid storage solutions combining battery systems, hydrogen technologies, and pumped hydro storage were identified as effective approaches to mitigate RES intermittency and balance short- and long-term energy demands. The transition from centralized to distributed control architectures, supported by predictive analytics, digital twins, and AI-based forecasting, has improved operational planning and system monitoring. However, challenges remain regarding interoperability, data privacy, cybersecurity, and the limited availability of high-quality data for AI model training. Economic analyses show that while initial investments are high, long-term operational savings and improved resilience justify the adoption of advanced microgrid solutions when supported by appropriate policies and financial mechanisms. Future research should address the standardization of communication protocols, development of explainable AI models, and creation of sustainable business models to enhance resilience, efficiency, and scalability. These efforts are necessary to accelerate the deployment of decentralized, low-carbon energy systems capable of meeting future energy demands under increasingly complex operational conditions.<\/jats:p>","DOI":"10.3390\/a18070429","type":"journal-article","created":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T13:44:19Z","timestamp":1752241459000},"page":"429","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Smart Microgrid Management and Optimization: A Systematic Review Towards the Proposal of Smart Management Models"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6721-1326","authenticated-orcid":false,"given":"Paul","family":"Ar\u00e9valo","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Electronics, and Telecommunications (DEET), Universidad de Cuenca, Cuenca 010101, Ecuador"},{"name":"Department of Electrical Engineering, University of Ja\u00e9n, 23700 Linares, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1624-8759","authenticated-orcid":false,"given":"Dario","family":"Benavides","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, University of Ja\u00e9n, 23700 Linares, Spain"},{"name":"Faculty of Systems, Electronics and Industrial Engineering, Universidad T\u00e9cnica de Ambato, Ambato 180207, Ecuador"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5633-1480","authenticated-orcid":false,"given":"Danny","family":"Ochoa-Correa","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Electronics, and Telecommunications (DEET), Universidad de Cuenca, Cuenca 010101, Ecuador"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7334-5681","authenticated-orcid":false,"given":"Alberto","family":"R\u00edos","sequence":"additional","affiliation":[{"name":"Faculty of Systems, Electronics and Industrial Engineering, Universidad T\u00e9cnica de Ambato, Ambato 180207, Ecuador"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1996-3240","authenticated-orcid":false,"given":"David","family":"Torres","sequence":"additional","affiliation":[{"name":"Faculty of Systems, Electronics and Industrial Engineering, Universidad T\u00e9cnica de Ambato, Ambato 180207, Ecuador"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0925-2541","authenticated-orcid":false,"given":"Carlos W.","family":"Villanueva-Machado","sequence":"additional","affiliation":[{"name":"Faculty of Mechanical Engineering, Universidad Nacional de Ingenier\u00eda, Lima 21036, Peru"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,11]]},"reference":[{"key":"ref_1","unstructured":"Aksoy, N. (2023). Design of Graphical User Interface for Artificial Intelligence-Based Energy Management System for Microgrids, Electrica."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1109\/ICJECE.2022.3232213","article-title":"Energy Storage Management for Microgrids Using n -Step Bootstrapping Gestion du stockage de l\u2019energie pour les micro-reseaux a l\u2019aide d\u2019un Bootstrapping en n etapes","volume":"46","author":"Aksoy","year":"2023","journal-title":"IEEE Can. J. Electr. Comput. Eng."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Al-Saadi, M. (2023). Reinforcement Learning-Based Intelligent Control Strategies for Optimal Power Management in Advanced Power Distribution Systems: A Survey. Energies, 16.","DOI":"10.3390\/en16041608"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Alam, M. (2022). Deep learning based optimal energy management for photovoltaic and battery energy storage integrated home micro-grid system. Sci. Rep., 12.","DOI":"10.1038\/s41598-022-19147-y"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Almihat, M. (2025). The Role of Smart Grid Technologies in Urban and Sustainable Energy Planning. Energies, 18.","DOI":"10.3390\/en18071618"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Arbab-Zavar, B. (2022). Reducing Detrimental Communication Failure Impacts in Microgrids by Using Deep Learning Techniques. Sensors, 22.","DOI":"10.3390\/s22166006"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Ar\u00e9valo, P. (2024). Optimizing Microgrid Operation: Integration of Emerging Technologies and Artificial Intelligence for Energy Efficiency. Electronics, 13.","DOI":"10.3390\/electronics13183754"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1039","DOI":"10.1109\/TII.2022.3165890","article-title":"SIEMS: A Secure Intelligent Energy Management System for Industrial IoT Applications","volume":"19","author":"Asef","year":"2023","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"120247","DOI":"10.1016\/j.renene.2024.120247","article-title":"Optimal resilient operation and sustainable power management within an autonomous residential microgrid using African vultures optimization algorithm","volume":"224","author":"Elkholy","year":"2024","journal-title":"Renew. Energy"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"163819","DOI":"10.1109\/ACCESS.2024.3491100","article-title":"Advanced Control Technique for Optimal Power Management of a Prosumer-Centric Residential Microgrid","volume":"12","author":"Gbadega","year":"2024","journal-title":"IEEE Access"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"213","DOI":"10.52292\/j.laar.2024.1952","article-title":"Artificial intelligence applied for micro smart grids: A literature review","volume":"54","year":"2024","journal-title":"Lat. Am. Appl. Res. Int. J."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Maulik, A. (2022). Probabilistic Power Management of a Grid-Connected Microgrid Considering Electric Vehicles, Demand Response, Smart Transformers, and Soft Open Points, Elsevier Ltd.","DOI":"10.1016\/j.segan.2022.100636"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Kahrobaeian, A., and Mohamed, Y.R. (2015). Networked-Based Hybrid Distributed Power Sharing and Control for Islanded Microgrid Systems, Institute of Electrical and Electronics Engineers Inc.","DOI":"10.1109\/TPEL.2014.2312425"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Kermani, M., Adelmanesh, B., Shirdare, E., Sima, C., Carn\u00ec, D., and Martirano, L. (2021). Intelligent Energy Management Based on SCADA System in a Real Microgrid for Smart Building Applications, Elsevier Ltd.","DOI":"10.1016\/j.renene.2021.03.008"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Zhao, D., Zhang, C., Cao, X., Peng, C., Sun, B., Li, K., and Li, Y. (2023). Differential Privacy Energy Management for Islanded Microgrids with Distributed Consensus-Based ADMM Algorithm, Institute of Electrical and Electronics Engineers Inc.","DOI":"10.1109\/TCST.2022.3208456"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Wu, P., and Mei, X. (2024). Microgrids Energy Management Considering Net-Zero Energy Concept: The Role of Renewable Energy Landscaping Design and IoT Modeling in Digital Twin Realistic Simulator, Elsevier Ltd.","DOI":"10.1016\/j.seta.2024.103621"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Zhao, F. (2024). Optimizing Microgrid Management with Intelligent Planning: A Chaos Theory-Based Salp Swarm Algorithm for Renewable Energy Integration and Demand Response, Elsevier Ltd.","DOI":"10.1016\/j.compeleceng.2024.109847"},{"key":"ref_18","unstructured":"Kamankesh, H., Ghasemi, A., and Soltani, M. (2019). Smart Microgrid Solutions with a Storage System and Renewable Generation: A Review. Energies, 12."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Mbungu, N., Bansal, R., Naidoo, R., Bettayeb, M., Siti, M., and Bipath, M. (2020). A Dynamic Energy Management System Using Smart Metering, Elsevier Ltd.","DOI":"10.1016\/j.apenergy.2020.115990"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Giaouris, D., Papadopoulos, A., Patsios, C., Walker, S., Ziogou, C., Taylor, P., Voutetakis, S., Papadopoulou, S., and Seferlis, P. (2018). A Systems Approach for Management of Microgrids Considering Multiple Energy Carriers, Stochastic Loads, Forecasting and Demand Side Response, Elsevier Ltd.","DOI":"10.1016\/j.apenergy.2018.05.113"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Lu, X., Zhou, K., and Yang, S. (2017). Multi-Objective Optimal Dispatch of Microgrid Containing Electric Vehicles, Elsevier Ltd.","DOI":"10.1016\/j.jclepro.2017.07.221"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Comodi, G., Giantomassi, A., Severini, M., Squartini, S., Ferracuti, F., Fonti, A., D, N.C., Morodo, M., and Polonara, F. (2015). Multi-Apartment Residential Microgrid with Electrical and Thermal Storage Devices: Experimental Analysis and Simulation of Energy Management Strategies, Elsevier Ltd.","DOI":"10.1016\/j.apenergy.2014.07.068"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ahmed, H., Sindi, H., Azzouz, M., and Awad, A. (2023). An Energy Trading Framework for Interconnected AC-DC Hybrid Smart Microgrids, Institute of Electrical and Electronics Engineers Inc.","DOI":"10.1109\/TSG.2022.3197728"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Cao, W., and Zhou, L. (2024). Resilient Microgrid Modeling in Digital Twin Considering Demand Response and Landscape Design of Renewable Energy, Elsevier Ltd.","DOI":"10.1016\/j.seta.2024.103628"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Igualada, L., Corchero, C., Cruz-Zambrano, M., and Heredia, F.J. (2014). Optimal Energy Management for a Residential Microgrid Including a Vehicle-to-Grid System, Institute of Electrical and Electronics Engineers Inc.","DOI":"10.1109\/TSG.2014.2318836"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Shufian, A., and Mohammad, N. (2022). Modeling and Analysis of Cost-Effective Energy Management for Integrated Microgrids, Elsevier Ltd.","DOI":"10.1016\/j.clet.2022.100508"},{"key":"ref_27","unstructured":"Calogine, D., Chau, O., and Lauret, P. (2019). A Fractional Derivative Approach to Modelling a Smart Grid-Off Cluster of Houses in an Isolated Area, Biemdas Academic Publishers."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Esapour, K., Moazzen, F., Karimi, M., Dabbaghjamanesh, M., and Kavousi-Fard, A. (2023). A Novel Energy Management Framework Incorporating Multi-Carrier Energy Hub for Smart City, John Wiley and Sons Inc.","DOI":"10.1049\/gtd2.12500"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Cintuglu, M., Youssef, T., and Mohammed, O. (2018). Development and Application of a Real-Time Testbed for Multiagent System Interoperability: A Case Study on Hierarchical Microgrid Control, IEEE-Institute Electrical Electronics Engineers Inc.","DOI":"10.1109\/TSG.2016.2599265"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Polimeni, S., Moretti, L., Martelli, E., Leva, S., and Manzolini, G. (2023). A Novel Stochastic Model for Flexible Unit Commitment of Off-Grid Microgrids, Elsevier Ltd.","DOI":"10.1016\/j.apenergy.2022.120228"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Dehghanpour, K., and Nehrir, H. (2018). Real-Time Multiobjective Microgrid Power Management Using Distributed Optimization in an Agent-Based Bargaining Framework, IEEE-Institute Electrical Electronics Engineers Inc.","DOI":"10.1109\/TSG.2017.2708686"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Rathor, S., and Saxena, D. (2020, January 2\u20134). Decentralized Energy Management System for LV Microgrid Using Stochastic Dynamic Programming with Game Theory Approach Under Stochastic Environment. Proceedings of the IEEE International Conference on Power Electronics, Smart Grid and Renewable Energy (IEEE PESGRE), Cochin, India.","DOI":"10.1109\/PESGRE45664.2020.9070354"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"105162","DOI":"10.1016\/j.scs.2023.105162","article-title":"Navigating urban day-ahead energy management considering climate change toward using IoT enabled machine learning technique: Toward future sustainable urban","volume":"101","author":"Huang","year":"2024","journal-title":"Sustain. Cities Soc."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Wang, Y., Wang, B., and Farjam, H. (2024). Multi-Objective Scheduling and Optimization for Smart Energy Systems with Energy Hubs and Microgrids, Elsevier B.V.","DOI":"10.1016\/j.jestch.2024.101649"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Jonban, M. (2023). Flexible Smart Energy-Management Systems Using an Online Tendering Process Framework for Microgrids. Energies, 16.","DOI":"10.3390\/en16134914"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Haghi, H., Lotfifard, S., and Qu, Z. (2016). Multivariate Predictive Analytics of Wind Power Data for Robust Control of Energy Storage, IEEE Computer Society.","DOI":"10.1109\/TII.2016.2569531"},{"key":"ref_37","unstructured":"Chowdhury, V., Son, Y., Guruwacharya, N., Blonsky, M., and Mather, B. (2024, January 20\u201324). Implementation of Advanced Grid Support Functionalities by Smart Operation of Residential Loads with low Cost Converter Interface. Proceedings of the 2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024\u2014Proceedings, Phoenix, AZ, USA."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Khan, M. (2024). A Comprehensive Review of Microgrid Energy Management Strategies Considering Electric Vehicles, Energy Storage Systems, and AI Techniques. Processes, 12.","DOI":"10.3390\/pr12020270"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"C\u00f3rdova, S., Ca\u00f1izares, C., Lorca, A., and Olivares, D. (2022). Frequency-Constrained Energy Management System for Isolated Microgrids, IEEE-Institute Electrical Electronics Engineers Inc.","DOI":"10.1109\/TSG.2022.3170871"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"5436","DOI":"10.1016\/j.egyr.2024.05.018","article-title":"A novel modified artificial rabbit optimization for stochastic energy management of a grid-connected microgrid: A case study in China","volume":"11","author":"Khan","year":"2024","journal-title":"Energy Rep."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Kumar, A., Alaraj, M., Rizwan, M., and Nangia, U. (2021). Novel AI Based Energy Management System for Smart Grid with RES Integration, Institute of Electrical and Electronics Engineers Inc.","DOI":"10.1109\/ACCESS.2021.3131502"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Shahinzadeh, H., Moradi, J., Gharehpetian, G., Fathi, S., and Abedi, M. (2018, January 28\u201329). Optimal Energy Scheduling for a Microgrid Encompassing DRRs and Energy Hub Paradigm Subject to Alleviate Emission and Operational Costs. Proceedings of the Proceedings\u20142018 Smart Grid Conference, SGC 2018, Sanandaj, Iran.","DOI":"10.1109\/SGC.2018.8777808"},{"key":"ref_43","unstructured":"M, J.K., Sampradeepraj, T., Sivajothi, E., and Singh, G. (2024). An Efficient Hybrid Technique for Energy Management System with Renewable Energy System and Energy Storage System in Smart Grid, Elsevier Ltd."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"556","DOI":"10.1016\/j.energy.2017.05.123","article-title":"Smart energy and smart energy systems","volume":"137","author":"Lund","year":"2017","journal-title":"Energy"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"105906","DOI":"10.1016\/j.ijsu.2021.105906","article-title":"The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews","volume":"88","author":"Page","year":"2021","journal-title":"Int. J. Surg."},{"key":"ref_46","first-page":"203","article-title":"Adaptive control of distributed energy resources in microgrids: A review","volume":"155","author":"Liu","year":"2020","journal-title":"Renew. Energy"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Sandgani, M., and Sirouspour, S. (2018). Priority-Based Microgrid Energy Management in a Network Environment, Institute of Electrical and Electronics Engineers Inc.","DOI":"10.1109\/TSTE.2017.2769558"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"El-Faouri, F., Alzahlan, M., Batarseh, M., Mohammad, A., and Za\u2019ter, M. (2019). Modeling of a Microgrid\u2019s Power Generation Cost Function in Real-Time Operation for a Highly Fluctuating Load, Elsevier B.V.","DOI":"10.1016\/j.simpat.2019.01.002"},{"key":"ref_49","unstructured":"RA, I.I., Janer, A., and Tria, L. (December, January 29). A Machine-learning Based Energy Management System for Microgrids with Distributed Energy Resources and Storage. Proceedings of the 2022 International Conference on Electrical Machines and Systems, ICEMS 2022, Chiang Mai, Thailand."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Bonfiglio, A., Delfino, F., Labella, A., Mestriner, D., Pampararo, F., Procopio, R., and Guerrero, J. (2018). Modeling and Experimental Validation of an Islanded No-Inertia Microgrid Site, Institute of Electrical and Electronics Engineers Inc.","DOI":"10.1109\/TSTE.2018.2816401"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Clarke, W., Brear, M., and Manzie, C. (2020). Control of an Isolated Microgrid Using Hierarchical Economic Model Predictive Control, Elsevier Ltd.","DOI":"10.1016\/j.apenergy.2020.115960"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"AL-Dhaifallah, M., Ali, Z., Alanazi, M., Dadfar, S., and Fazaeli, M. (2021). An Efficient Short-Term Energy Management System for a Microgrid with Renewable Power Generation and Electric Vehicles, Springer Science and Business Media Deutschland GmbH.","DOI":"10.1007\/s00521-021-06247-5"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Rezaei, N., and Kalantar, M. (2015). Smart Microgrid Hierarchical Frequency Control Ancillary Service Provision Based on Virtual Inertia Concept: An Integrated Demand Response and Droop Controlled Distributed Generation Framework, Elsevier Ltd.","DOI":"10.1016\/j.enconman.2014.12.049"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Wang, Q., Yin, Y., Chen, Y., and Liu, Y. (2024). Carbon Peak Management Strategies for Achieving Net-Zero Emissions in Smart Buildings: Advances and Modeling in Digital Twin, Elsevier Ltd.","DOI":"10.1016\/j.seta.2024.103661"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Mbungu, N., Siti, M., Bansal, R., Naidoo, R., Elnady, A., Ismail, A., Abokhali, A., and Hamid, A.K. (2025). A Dynamic Coordination of Microgrids, Elsevier Ltd.","DOI":"10.1016\/j.apenergy.2024.124486"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Chekired, D., Khoukhi, L., and Mouftah, H. (2018). Decentralized Cloud-SDN Architecture in Smart Grid: A Dynamic Pricing Model, IEEE Computer Society.","DOI":"10.1109\/TII.2017.2742147"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Gottwalt, S., G\u00e4rttner, J., Schmeck, H., and Weinhardt, C. (2017). Modeling and Valuation of Residential Demand Flexibility for Renewable Energy Integration, IEEE-Institute Electrical Electronics Engineers Inc.","DOI":"10.1109\/TSG.2016.2529424"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"e Silva, D.P., F\u00e9lix Salles, J.L., Fardin, J., and Rocha Pereira, M.M. (2020). Management of an Island and Grid-Connected Microgrid Using Hybrid Economic Model Predictive Control with Weather Data, Elsevier Ltd.","DOI":"10.1016\/j.apenergy.2020.115581"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Solanki, A., Nasiri, A., Bhavaraju, V., Familiant, Y., and Fu, Q. (2016). A New Framework for Microgrid Management: Virtual Droop Control, IEEE-Institute Electrical Electronics Engineers Inc.","DOI":"10.1109\/TSG.2015.2474264"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Wynn, S., Boonraksa, T., Boonraksa, P., Pinthurat, W., and Marungsri, B. (2023). Decentralized Energy Management System in Microgrid Considering Uncertainty and Demand Response. Electronics, 12.","DOI":"10.3390\/electronics12010237"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Nakabi, T., and Toivanen, P. (2021). Deep Reinforcement Learning for Energy Management in a Microgrid with Flexible Demand, Elsevier Ltd.","DOI":"10.20944\/preprints202010.0156.v1"},{"key":"ref_62","unstructured":"Alhasnawi, B., Jasim, B., Sedhom, B., and Guerrero, J. (2025). A New Communication Platform for Smart EMS Using a Mixed-Integer-Linear-Programming, Springer."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Morsali, R., Thirunavukkarasu, G., Seyedmahmoudian, M., Stojcevski, A., and Kowalczyk, R. (2020). A Relaxed Constrained Decentralised Demand Side Management System of a Community-Based Residential Microgrid with Realistic Appliance Models, Elsevier Ltd.","DOI":"10.1016\/j.apenergy.2020.115626"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Rosini, A., Bonfiglio, A., Invernizzi, M., Procopio, R., and Serra, P. (October, January 29). Power Management in Islanded Hybrid Diesel-Storage Microgrids. Proceedings of the 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019, Bucharest, Romania.","DOI":"10.1109\/ISGTEurope.2019.8905522"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Rezaei, N., and Kalantar, M. (2015). Hierarchical Energy and Frequency Security Pricing in a Smart Microgrid: An Equilibrium-Inspired Epsilon Constraint Based Multi-Objective Decision Making Approach, Elsevier Ltd.","DOI":"10.1016\/j.enconman.2015.04.004"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Wang, Y., Huang, Y., Wang, Y., Yu, H., Li, R., and Song, S. (2018). Energy management for smart multi-energy complementary micro-grid in the presence of demand response. Energies, 11.","DOI":"10.3390\/en11040974"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Rezaei, N., Ahmadi, A., Khazali, A., and Guerrero, J. (2018). Energy and Frequency Hierarchical Management System Using Information Gap Decision Theory for Islanded Microgrids, Institute of Electrical and Electronics Engineers Inc.","DOI":"10.1109\/TIE.2018.2798616"},{"key":"ref_68","unstructured":"Ali, I., and Hussain, S. (2018). Communication Design for Energy Management Automation in Microgrid, IEEE-Institute Electrical Electronics Engineers Inc."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Muzumdar, A., Modi, C., Madhu, G., and Vyjayanthi, C. (2022). Designing a Robust and Accurate Model for Consumer Centric Short Term Load Forecasting in Microgrid Environment, IEEE-Institute Electrical Electronics Engineers Inc.","DOI":"10.1109\/JSYST.2021.3073493"},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Thornburg, J. (2022, January 20\u201322). A Probabilistic Tool for Modeling Smart Microgrids with Renewable Energy and Demand Side Management. Proceedings of the International Conference on Computational Intelligence and Sustainable Engineering Solution, CISES 2022, Noida, India.","DOI":"10.1109\/CISES54857.2022.9844342"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Sujil, A., and Kumar, R. (2018). Multi Agent Based Energy Management System for Smart Microgrid, Institute of Electrical and Electronics Engineers Inc.","DOI":"10.1109\/RDCAPE.2017.8358253"},{"key":"ref_72","unstructured":"Sujil, A., Kumar, R., Bansal, R., and Naidoo, R. (2021, January 26\u201330). Stateflow based Modeling of Multi Agent System for Smart Microgrid Energy Management. Proceedings of the 2021 31st Australasian Universities Power Engineering Conference, AUPEC 2021, Virtual."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"109031","DOI":"10.1016\/j.jobe.2024.109031","article-title":"Multi-agent-based Decentralized Residential Energy Management Using Deep Reinforcement Learning","volume":"87","author":"Kumari","year":"2024","journal-title":"J. Build. Eng."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Zareein, M., J, S.F., Nikoofard, A., and Amraee, T. (2023). Optimizing Energy Management in Microgrids Based on Different Load Types in Smart Buildings. Energies, 16.","DOI":"10.3390\/en16010073"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Ray, S., Ali, A., Eshchanov, T., and Khudoynazarov, E. (2025, January 14). Optimal Energy Management of the Smart Microgrid Considering Uncertainty of Renewable Energy Sources and Demand Response Programs. Proceedings of the Operations Research Forum, Catonsville, MD, USA.","DOI":"10.1007\/s43069-025-00450-z"},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Yadollahi, Z., Gharibi, R., Dashti, R., and Jahromi, A. (2024). Optimal Energy Management of Energy Hub: A Reinforcement Learning Approach, Elsevier.","DOI":"10.1016\/j.scs.2024.105179"},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Billah, M., Yousif, M., Numan, M., Salam, I., Kazmi, S., and Alghamdi, T. (2023). Decentralized Smart Energy Management in Hybrid Microgrids: Evaluating Operational Modes, Resources Optimization, and Environmental Impacts, Institute of Electrical and Electronics Engineers Inc.","DOI":"10.1109\/ACCESS.2023.3343466"},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Trigkas, D., Ziogou, C., Voutetakis, S., and Papadopoulou, S. (2021). Virtual energy storage in res-powered smart grids with nonlinear model predictive control. Energies, 14.","DOI":"10.3390\/en14041082"},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Manbachi, M., and Ordonez, M. (2019). AMI-Based Energy Management for Islanded AC\/DC Microgrids Utilizing Energy Conservation and Optimization, Institute of Electrical and Electronics Engineers Inc.","DOI":"10.1109\/TSG.2017.2737946"},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Li, Q., Cui, Z., Cai, Y., Su, Y., and Wang, B. (2023). Renewable-Based Microgrids\u2019 Energy Management Using Smart Deep Learning Techniques: Realistic Digital Twin Case, Elsevier Ltd.","DOI":"10.1016\/j.solener.2022.12.030"},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Onile, A., Petlenkov, E., Levron, Y., and Belikov, J. (2024). Smartgrid-Based Hybrid Digital Twins Framework for Demand Side Recommendation Service Provision in Distributed Power Systems, Elsevier B.V.","DOI":"10.1016\/j.future.2024.03.018"},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Long, B., Liao, Y., Chong, K., Rodr\u00edguez, J., and Guerrero, J. (2021). Enhancement of Frequency Regulation in AC Microgrid: A Fuzzy-MPC Controlled Virtual Synchronous Generator, IEEE-Institute Electrical Electronics Engineers Inc.","DOI":"10.1109\/TSG.2021.3060780"},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"Keshtkar, H., Mohammadi, F., Ghorbani, J., Solanki, J., and Feliachi, A. (2014, January 4\u20137). Proposing an improved optimal LQR controller for frequency regulation of a smart microgrid in case of cyber intrusions. Proceedings of the Canadian Conference on Electrical and Computer Engineering, Toronto, ON, Canada.","DOI":"10.1109\/CCECE.2014.6901017"},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1007\/978-3-031-21216-1_38","article-title":"Sizing, Modeling and Energy Flow Management of PV-Diesel-Batteries Microgrid for Agricultural Application","volume":"Volume 591","author":"Hatti","year":"2023","journal-title":"Advanced Computational Techniques for Renewable Energy Systems"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"3528","DOI":"10.1109\/TPEL.2015.2464277","article-title":"DC microgrids\u2014Part II: A review of power architectures, applications, and standardization issues","volume":"Volume 31","author":"Dragicevic","year":"2016","journal-title":"Proceedings of the IEEE Transactions on Power Electronics"},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Rumniak, P., Michalczuk, M., Kaszewski, A., Galecki, A., and Grzesiak, L. (2017, January 11\u201314). Multifunctional energy storage system for smart grid applications. Proceedings of the 2017 19th European Conference on Power Electronics and Applications, EPE 2017 ECCE Europe, Warsaw, Poland.","DOI":"10.23919\/EPE17ECCEEurope.2017.8099343"},{"key":"ref_87","doi-asserted-by":"crossref","unstructured":"Rezaei, N., Khazali, A., Mazidi, M., and Ahmadi, A. (2020). Economic Energy and Reserve Management of Renewable-Based Microgrids in the Presence of Electric Vehicle Aggregators: A Robust Optimization Approach, Elsevier Ltd.","DOI":"10.1016\/j.energy.2020.117629"},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"El-Fawair, A.B., Al-Aubidy, K.M., and Al-Khawaldeh, M.A. (2023, January 20\u201323). Energy Management in Microgrids with Renewable Energy Sources and Energy Storage System. Proceedings of the 2023 20th International Multi-Conference on Systems, Signals & Devices (SSD), Mahdia, Tunisia.","DOI":"10.1109\/SSD58187.2023.10411198"},{"key":"ref_89","doi-asserted-by":"crossref","unstructured":"Pasetti, M., Rinaldi, S., and Manerba, D. (2018). A Virtual Power Plant Architecture for the Demand-Side Management of Smart Prosumers. Appl. Sci., 8.","DOI":"10.3390\/app8030432"},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1109\/TSG.2010.2055904","article-title":"Management and Control of Domestic Smart Grid Technology","volume":"1","author":"Molderink","year":"2010","journal-title":"IEEE Trans. Smart Grid"}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/18\/7\/429\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:08:43Z","timestamp":1760033323000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/18\/7\/429"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,11]]},"references-count":90,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2025,7]]}},"alternative-id":["a18070429"],"URL":"https:\/\/doi.org\/10.3390\/a18070429","relation":{},"ISSN":["1999-4893"],"issn-type":[{"value":"1999-4893","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,11]]}}}