[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-128676-en":3,"doc-seo-128676-105":31,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},128676,962084928432,"Emma Wilson","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Optimal management of Smart Grids using Machine Learning techniques - Research Assignment report","The research assignment addresses optimal electric supply management under the growing role of intermittent renewables and the need to maintain reliability, security, and cost efficiency. It introduces Smart Grids as cyber-physical energy systems that must handle uncertainties from weather, economic conditions, and environmental factors. The work builds a baseline solution using Model Predictive Control, specifically Economic MPC, and compares it with Deep Learning approaches while outlining controller construction, machine learning pipeline, results, and supporting MATLAB implementations.","Optimal management of Smart Grids using Machine Learning techniques  \nResearch Assignment report  \nStudent: Orianne Atance Loustaunau  \nTutor: Vicenç Puig-Full Professor of Automatic Control, Universitat Politècnica de Catalunya (UPC) -Institut de Robòtica i Informàtica Industrial (IRI)  \nSummary  \nSUMMARY ................................................................................ 2  \nI. INTRODUCTION ..............................................................3  \nII. CONSTRUCTING THE MPC CONTROLLER .........................4  \nEXAMPLE WITH ONE BATTERY .......................................................4  \nSMART GRID MODEL ................................................................... 6  \nIII. MACHINE LEARNING PROCESS ........................................8  \nIV . RESULTS ..........................................................................9  \nMPC FUNCTIONS: MPCMOVE AND OPTIMIZER ............................... 10  \nDNN FUNCTIONS: TRAINNETWORK AND PREDICT........................... 11  \nV . CONCLUSION ................................................................ 14  \nVI. ANNEXES ...................................................................... 15  \nANNEX 1 : MATLAB CODE FOR CREATING THE MPC MODEL FOR ONE SINGLE BATTERY (BATTERY_MPC. M ) ........................................... 15  \nANNEX 2: MATLAB CODE FOR SOLVING THE MPC PROBLEM WITH MACHINE LEARNING (BATTERY_MPCTODL) ................................ 17  \nANNEX 3: MATLAB CODE FOR CREATING THE MPC MODEL FOR OUR SMART GRID PROBLEM (SG_MPC_ORIANNE . M ) ..........................23  \nANNEX 4: MATLAB CODE FOR SOLVING THE MPC SMART GRID PROBLEM WITH MACHINE LEARNING (SG_MPCTODL) ..................29  \nANNEX 5: MATLAB CODE OF THE STATE-SPACE MPC DESIGNER FOR A SINGLE BATTERY (MPC_DESIGNER ) .............................................33  \nANNEX 6: MATLAB CODE OF THE STATE-SPACE MPC DESIGNER FOR THE SMART GRID SYSTEM (MPC_SG_DESIGNER ) ................................34  \nI. Introduction  \nFossil fuels-including coal, oil, and natural gas-have been powering economies for over 150 years, and currently supply about 80% of the world's energy. But this number is meant to decrease drastically before the end of the century to prevent global warming. Russia’s invasion of Ukraine has created shock waves in global energy markets, leading to price volatility, supply shortages, security issues and economic uncertainty, leading us to the biggest energy crisis of the history.  \nTo deal with these problems, our society has to take serious actions to optimize the electric supply in the world while taking into account intermittent energy sources such as solar, wind or hydraulic power. As a consequence, the target of climate neutrality by 2050 has encouraged the growth of renewable energy in Europe: in 2020, around one-fifth of the European electricity was generated from wind and solar electricity, surpassing fossil-based electricity generation. This same year, electricity generation from coal decreased by almost 50% since 2015, which is equivalent to avoiding around 320 Mt CO2 per year 1.  \nSmart grids have the potential to optimize the efficiency, reliability, economics, and sustainability of the production, distribution, and consumption of electrical energy. In 2021, the Smart Grid Index benchmarked a total of 86 Smart Grid utilities across 37 countries 2, with Enedis achieving the number one position.  \nIndeed, a classical electrical grid is defined as a reliable integrated power delivery system consisting of interconnected Distributed Energy Resources (DERs), which has the purpose of satisfying load demands without any interruption. However, introducing renewable energies in the grid requires some predictive measures in order to guarantee the reliability and stability of the energy supply as they are highly influenced by weather conditions, economic situations, and environmental issues. As a solution, Smart Grids can handle the presence of uncertainties as well","cbCailutLzmGVLLo","https://ap.wps.com/l/cbCailutLzmGVLLo","pdf",1307154,3,1,34,"English","en",105,"# Summary\n# I. Introduction\n# II. Constructing the MPC controller\n## Example with one battery\n## Smart grid model\n# III. Machine learning process\n# IV. Results\n## MPC functions: MPCmove and optimizer\n## DNN functions: trainNetwork and predict\n# V. Conclusion\n# VI. Annexes","[{\"question\":\"What baseline control method is used to manage the Smart Grid problem?\",\"answer\":\"The assignment uses Model Predictive Control as a baseline, starting from Economic MPC to minimize economic costs such as electricity, influenced by load demands and energy prices.\"},{\"question\":\"Why are Smart Grids needed when integrating renewables?\",\"answer\":\"Renewable generation is highly affected by weather, economic, and environmental conditions, creating uncertainties. Smart Grids help ensure reliability and stability while reducing production and distribution costs.\"},{\"question\":\"What roles do MPC and deep learning play in the study?\",\"answer\":\"The study uses MPC to construct an optimization-based controller and then applies machine learning methods, including DNN training and prediction, to compare against the MPC baseline and evaluate performance.\"}]","Optimal management of Smart Grids using Machine Learning techniques - Research Assignment report | PDF",1786002501,86,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"optimal-management-of-smart-grids-using-machine-learning-techniques-research-assignment-report","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":20},"https://docshare.wps.com/document/research-report/",{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/optimal-management-of-smart-grids-using-machine-learning-techniques-research-assignment-report/128676/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-25","2026-08-06",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What baseline control method is used to manage the Smart Grid problem?","Question",{"text":76,"@type":77},"The assignment uses Model Predictive Control as a baseline, starting from Economic MPC to minimize economic costs such as electricity, influenced by load demands and energy prices.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Why are Smart Grids needed when integrating renewables?",{"text":81,"@type":77},"Renewable generation is highly affected by weather, economic, and environmental conditions, creating uncertainties. Smart Grids help ensure reliability and stability while reducing production and distribution costs.",{"name":83,"@type":74,"acceptedAnswer":84},"What roles do MPC and deep learning play in the study?",{"text":85,"@type":77},"The study uses MPC to construct an optimization-based controller and then applies machine learning methods, including DNN training and prediction, to compare against the MPC baseline and evaluate performance.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":48,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]