{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T06:55:09Z","timestamp":1781592909411,"version":"3.54.5"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,11,25]],"date-time":"2024-11-25T00:00:00Z","timestamp":1732492800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2024,11,25]],"date-time":"2024-11-25T00:00:00Z","timestamp":1732492800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Energy Inform"],"DOI":"10.1186\/s42162-024-00416-1","type":"journal-article","created":{"date-parts":[[2024,11,25]],"date-time":"2024-11-25T09:44:40Z","timestamp":1732527880000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Micro-grid source-load storage energy minimization method based on improved competitive depth Q - network algorithm and digital twinning"],"prefix":"10.1186","volume":"7","author":[{"given":"Yibo","family":"Lai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiyan","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiqing","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuling","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,11,25]]},"reference":[{"key":"416_CR1","doi-asserted-by":"crossref","unstructured":"Tayab UB, Yang F, Metwally ASM, et al. Solar photovoltaic power forecasting for microgrid energy management system using an ensemble forecasting strategy[J]. Energy sources, Part A. Recovery, utilization, and environmental effects, 2022, 44(4):10045\u201310070","DOI":"10.1080\/15567036.2022.2143945"},{"key":"416_CR2","doi-asserted-by":"crossref","unstructured":"Alabdullah M H, Abido M A. Microgrid energy management using deep Q-network reinforcement learning[J].Alexandria Engineering Journal, 2022, 61(11):9069\u20139078","DOI":"10.1016\/j.aej.2022.02.042"},{"key":"416_CR3","doi-asserted-by":"crossref","unstructured":"Gassi K B, Baysal M. Analysis of a linear programming-based decision\u2010making model for microgrid energy management systems with renewable sources[J].International journal of energy research, 2022, 46(6):7495\u20137518.","DOI":"10.1002\/er.7656"},{"key":"416_CR4","doi-asserted-by":"crossref","unstructured":"Rashidi R, Hatami A, Abedini M. Multi-microgrid energy management through tertiary-level control: Structure and case study[J].Sustainable Energy Technologies and Assessments,2021, 47(3):1\u201321.","DOI":"10.1016\/j.seta.2021.101395"},{"key":"416_CR5","doi-asserted-by":"crossref","unstructured":"Abbas F A, Obed A A, Qasim M A, et al. An efficient energy-management strategy for a DC microgrid powered by a photovoltaic\/fuel cell\/battery\/supercapacitor[J].Clean Energy, 2022, 6(6):827\u2013839.","DOI":"10.1093\/ce\/zkac063"},{"key":"416_CR6","doi-asserted-by":"crossref","unstructured":"Nardelli P H J, Hussein M, Narayanan A, et al.Virtual Microgrid Management via Software-defined Energy Network for Electricity Sharing[J]. IEEE systems, man, and cybernetics magazine, 2021, 7(3):10\u201319.","DOI":"10.1109\/MSMC.2021.3062018"},{"key":"416_CR7","doi-asserted-by":"crossref","unstructured":"Khosravi N, Echalih S, Baghbanzadeh R, et al. Enhancement of power quality issues for a hybrid AC\/DC microgrid based on optimization methods[J]. IET renewable power generation, 2022, 16(8):1773\u20131791.","DOI":"10.1049\/rpg2.12476"},{"key":"416_CR8","doi-asserted-by":"crossref","unstructured":"Kavitha V, Malathi V, Guerrero J M, et al. Energy management system using Mimosa Pudica optimization technique for microgrid applications[J]. Energy, 2022, 244(1):1\u201315.","DOI":"10.1016\/j.energy.2021.122605"},{"key":"416_CR9","unstructured":"Li Y, Chen J, Wang X J, et al. Double Layer Fuzzy Control Optimization Strategy for Hybrid Energy Storage in Microgrid[J]. Computer Simulation, 2022, 39(6):103\u2013107,398."},{"key":"416_CR10","doi-asserted-by":"crossref","unstructured":"Xu X, Shang J, Chen Z, et al. Robust Planning Method for Photovoltaic Microgrid Energy Storage Considering Source-Load Flexibility Resources[J]. Journal of Physics:Conference Series, 2023, 2434(1): 012002.","DOI":"10.1088\/1742-6596\/2434\/1\/012002"},{"key":"416_CR11","unstructured":"Pang K, Wang C, Hatziargyriou N D, et al. Microgrid Formation and Real-Time Scheduling of Active Distribution Networks Considering Source-Load Stochasticity[J]. IEEE Transactions on Power Systems, 2023,37(1): 1\u201313."},{"key":"416_CR12","doi-asserted-by":"crossref","unstructured":"Chen S, Zhang L, Zhou Y, et al. Research on Flexible Resource Dynamic Interactive Regulation Technology for Microgrids with High Permeable New Energy[J]. International Transactions on Electrical Energy Systems, 2023, 23(1): 1\u201312.","DOI":"10.1155\/2023\/6304877"},{"key":"416_CR13","doi-asserted-by":"crossref","unstructured":"Tripathi J M, Mallik S K. Protection Coordination of DOCRs for Different Modes of Microgrid Operation[J]. Engineering Research Express, 2023, 5(2): 025045.","DOI":"10.1088\/2631-8695\/acd61a"},{"key":"416_CR14","doi-asserted-by":"crossref","unstructured":"Kannaian R B, Joseph B B, Ramachandran R P. An Adaptive Centralized Protection and Relay Coordination Algorithm for Microgrid[J]. Energies, 2023, 16(12): 4820.","DOI":"10.3390\/en16124820"},{"key":"416_CR15","doi-asserted-by":"crossref","unstructured":"Yang W, Kang X, Wang X, et al. MPC-based three-phase unbalanced power coordination control method for microgrid clusters[J]. Energy Reports, 2023, 9(1): 1830\u20131841.","DOI":"10.1016\/j.egyr.2022.12.079"},{"key":"416_CR16","doi-asserted-by":"crossref","unstructured":"Kudkelwar S B, Sinha B B, Gunturi S K. An Archimedes metaheuristic algorithm based optimum relay coordination in microgrid and combined overhead\/cable distribution network[J].The Journal of Supercomputing, 2023, 79(18): 21166\u201321184.","DOI":"10.1007\/s11227-023-05486-8"},{"key":"416_CR17","doi-asserted-by":"crossref","unstructured":"Wang Y, Liu Z, Liu J, et al. Analysis of Source-Load Coupling Characteristics and Stability in Battery Energy Storage System[J]. Sustainable Energy Technologies and Assessments, 2023, 57(1): 103110.","DOI":"10.1016\/j.seta.2023.103110"},{"key":"416_CR18","doi-asserted-by":"crossref","unstructured":"Nakamura T, Kobayashi M, Motoi N. Path Planning for Mobile Robot Considering Turnabouts on Narrow Road by Deep Q-Network[J]. IEEE Access, 2023, 11: 19111\u201319121.","DOI":"10.1109\/ACCESS.2023.3247730"},{"key":"416_CR19","doi-asserted-by":"crossref","unstructured":"Cai H, Shen Y, Hu S. Cascaded Deep Q-Network for Optimization of Substrate Integrated Waveguide Couplers[J]. IEEE Transactions on Circuits and Systems II: Express Briefs,2023, 70(11): 4196\u20134200.","DOI":"10.1109\/TCSII.2023.3268773"},{"key":"416_CR20","doi-asserted-by":"crossref","unstructured":"B M H A A, D M A A B C. Microgrid energy management using deep Q-network reinforcement learning - ScienceDirect[J]. Alexandria Engineering Journal, 2022, 61(11):9069\u20139078.","DOI":"10.1016\/j.aej.2022.02.042"},{"key":"416_CR21","doi-asserted-by":"crossref","unstructured":"Wang Z, Huang J, Yi M. A Stealth\u2013Distance Dynamic Weight Deep Q-Network Algorithm for Three-Dimensional Path Planning of Unmanned Aerial Helicopter[J]. Aerospace, 2023,10(8): 709.","DOI":"10.3390\/aerospace10080709"},{"key":"416_CR22","doi-asserted-by":"crossref","unstructured":"Zhou W, Yu B, Zhang J, et al. Ameliorated PGC demodulation technique based on the ODR algorithm with insensitivity to phase modulation depth[J]. Optics Express,2023, 31(5): 7175.","DOI":"10.1364\/OE.482473"},{"key":"416_CR23","doi-asserted-by":"crossref","unstructured":"Boonthiem S, Sutikasana C, Klongdee W, et al. Parameter Estimations of Normal Distribution via Genetic Algorithm and Its Application to Carbonation Depth[J]. WSEAS TRANSACTIONS ON MATHEMATICS, 2023, 22: 184\u2013189.","DOI":"10.37394\/23206.2023.22.23"},{"key":"416_CR24","doi-asserted-by":"crossref","unstructured":"Zhang L, Hao Q, Mao Y, et al. Beyond Trade-Off: An Optimized Binocular Stereo Vision Based Depth Estimation Algorithm for Designing Harvesting Robot in Orchards[J].Agriculture, 2023, 13(6): 1117.","DOI":"10.3390\/agriculture13061117"},{"key":"416_CR25","doi-asserted-by":"crossref","unstructured":"Liang S, Jin J, Ren J, et al. An Improved Dual-Channel Deep Q-Network Model for Tourism Recommendation[J]. Big Data, 2023, 206(1): 268\u2013281.","DOI":"10.1089\/big.2021.0353"},{"key":"416_CR26","doi-asserted-by":"crossref","unstructured":"Liang S, Jin J, Ren J, et al. An Improved Dual-Channel Deep Q-Network Model for Tourism Recommendation[J]. Big Data, 2023, 11(4): 268\u2013281.","DOI":"10.1089\/big.2021.0353"},{"key":"416_CR27","doi-asserted-by":"crossref","unstructured":"He Y, Wu X, Sun K, et al. Economic Optimization Scheduling Based on Load Demand in Microgrids Considering Source Network Load Storage[J]. Electronics, 2023, 12(12):2721.","DOI":"10.3390\/electronics12122721"},{"key":"416_CR28","doi-asserted-by":"crossref","unstructured":"Zheng F, Meng X, Xu T, et al. Optimization Method of Energy Storage Configuration for Distribution Network with High Proportion of Photovoltaic Based on Source\u2013Load Imbalance[J]. Sustainability, 2023, 15(13): 10628.","DOI":"10.3390\/su151310628"},{"key":"416_CR29","doi-asserted-by":"crossref","unstructured":"Luo S Q, Ding X H, Han T. Day-ahead Multi-objective Coordinated Optimization Strategy for Regional Scale Source Network Load Storage System[J].IOP Conference Series:Earth and Environmental Science, 2021, 702(1):012042.","DOI":"10.1088\/1755-1315\/702\/1\/012042"},{"key":"416_CR30","doi-asserted-by":"crossref","unstructured":"Li S W, Xiao S C, Bie F M, et al. The Analysis of Business Scenarios and Implementation Path of \u201c5G\u2009+\u2009Source-network-load-storage \u201cmulti-station integration[J]. E3S Web of Conferences, 2021, 248(5):02031.","DOI":"10.1051\/e3sconf\/202124802031"},{"key":"416_CR31","doi-asserted-by":"crossref","unstructured":"Jiang P, Dong J, Zhu Y. Mixed Linear Model of a Safety Dispatch Model in an Active Distribution Network for Source\u2013Grid\u2013Load Interactions[J]. World Electric Vehicle Journal, 2023, 14(6): 159.","DOI":"10.3390\/wevj14060159"},{"key":"416_CR32","doi-asserted-by":"crossref","unstructured":"Hu J, Xie W, Chen Z. Coordinated planning of source load storage flexible resources for photovoltaic access to power system[J]. Journal of Physics: Conference Series,2023, 2495(1): 012015.","DOI":"10.1088\/1742-6596\/2495\/1\/012015"},{"key":"416_CR33","doi-asserted-by":"crossref","unstructured":"Wang Y, Chu Z, Chen G, et al. A Robust Control Strategy for the Automatic Load Commutation Device Considering Uncertainties of Source and Load[J]. Applied Sciences,2023, 13(13): 7390.","DOI":"10.3390\/app13137390"},{"key":"416_CR34","doi-asserted-by":"crossref","unstructured":"Lv G, Xing L, Wang H, et al. Load Redistribution-based Reliability Enhancement for Storage Area Networks[J]. International Journal of Mathematical, Engineering and Management Sciences, 2023, 8(1): 1\u201314.","DOI":"10.33889\/IJMEMS.2023.8.1.001"},{"key":"416_CR35","doi-asserted-by":"crossref","unstructured":"Dong M, Liu K, He J, et al. Power grid load frequency control based on Fractional Order PID combined with pumped storage and battery energy storage[J]. Energy Reports,2023,14(1): 1402\u20131411.","DOI":"10.1016\/j.egyr.2023.05.117"},{"key":"416_CR36","doi-asserted-by":"crossref","unstructured":"Tian F, Huang L, Zhou C G. Photovoltaic power generation and charging load prediction research of integrated photovoltaic storage and charging station[J]. Energy Reports,2023, 9(1):61\u2013871.","DOI":"10.1016\/j.egyr.2023.04.250"},{"key":"416_CR37","unstructured":"Lin Z T, Lin Z Y, Huang Z C. Low Latency and High-Reliability Data Query Algorithm In Deep Double Q Network[J]. Computer Simulation, 2021,38(8):417\u2013439."},{"key":"416_CR38","unstructured":"Rajesh K, Pyne S. Droplet Routing Based on Double Deep Q-Network Algorithm for Digital Microfluidic Biochips[J].Journal of circuits, systems and computers, 202231(17):1\u201323."},{"key":"416_CR39","doi-asserted-by":"crossref","unstructured":"Kender R, Rler F, Wunderlich B, et al. Improving the load flexibility of industrial air separation units using a pressure-driven digital twin[J].AIChE Journal, 2022,68(7):1\u201323.","DOI":"10.1002\/aic.17692"},{"key":"416_CR40","doi-asserted-by":"crossref","unstructured":"Molinaro C L D. Embedding data analytics and CFD into the digital twin concept[J].Computers & Fluids, 2021, 214(1):1\u201313.","DOI":"10.1016\/j.compfluid.2020.104759"}],"container-title":["Energy Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s42162-024-00416-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s42162-024-00416-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s42162-024-00416-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,25]],"date-time":"2024-11-25T10:05:33Z","timestamp":1732529133000},"score":1,"resource":{"primary":{"URL":"https:\/\/energyinformatics.springeropen.com\/articles\/10.1186\/s42162-024-00416-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,25]]},"references-count":40,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["416"],"URL":"https:\/\/doi.org\/10.1186\/s42162-024-00416-1","relation":{},"ISSN":["2520-8942"],"issn-type":[{"value":"2520-8942","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,25]]},"assertion":[{"value":"24 July 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 October 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 November 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"Not Applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Not applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}}],"article-number":"126"}}