Two-stage dual-level dispatch optimization model of multi-virtual power plants based on Stackelberg game 

preprint OA: closed
Full text JSON View at publisher
AI-generated deep summary by claude@2026-07, 2026-07-05 · read from full text

This paper studies a two-stage, dual-level dispatch optimization framework for multiple Virtual Power Plants (VPPs) that integrate large numbers of electric vehicles (EVs) and demand response. In the day-ahead stage, a two-layer scheduling model is formulated in which an EV layer maximizes comprehensive user satisfaction while the VPP layer minimizes operating costs and interaction power; in the intraday stage, a Stackelberg game is built with distribution network operators as the leader (aiming to maximize profits) and the VPP as the follower (aiming to minimize its operational costs) using electricity prices and energy consumption strategies. Simulation results are reported to verify the model’s effectiveness in reducing user costs and achieving full consumption of new energy. The study is presented as a preprint (not peer reviewed), without any additional limitations stated in the provided text, which is a major caveat regarding evidentiary strength. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Abstract

Abstract With the continuous increase in the number of electric vehicles (EVs) and the rapid development of demand response (DR) technology, the power grid faces unprecedented challenges. Two-stage dual-level dispatch optimization model of multi-virtual power plants based on Stackelberg game is proposed in this paper. In the day-ahead stage, a two-layer optimization scheduling model is established, where the EV layer optimizes for maximum comprehensive user satisfaction, and the VPP layer optimizes for minimal operating costs and interaction power, determining the scheduling arrangements for each distributed energy resource. In the intraday stage, a Stackelberg game model is constructed with the distribution network operators(DNO) as the leader, aiming to maximize proffts, and the VPP as the follower, aiming to minimize its own operational costs, with both parties engaging in a game based on electricity prices and energy consumption strategies. In the simulation case study, the effectiveness of the constructed model is veriffed, and the results show that the model can effectively reduce user costs and achieve full consumption of new energy.
Full text 9,665 characters · extracted from preprint-html · click to expand
Two-stage dual-level dispatch optimization model of multi-virtual power plants based on Stackelberg game | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Two-stage dual-level dispatch optimization model of multi-virtual power plants based on Stackelberg game jincheng Tang, Xiaolan Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5401210/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract With the continuous increase in the number of electric vehicles (EVs) and the rapid development of demand response (DR) technology, the power grid faces unprecedented challenges. Two-stage dual-level dispatch optimization model of multi-virtual power plants based on Stackelberg game is proposed in this paper. In the day-ahead stage, a two-layer optimization scheduling model is established, where the EV layer optimizes for maximum comprehensive user satisfaction, and the VPP layer optimizes for minimal operating costs and interaction power, determining the scheduling arrangements for each distributed energy resource. In the intraday stage, a Stackelberg game model is constructed with the distribution network operators(DNO) as the leader, aiming to maximize proffts, and the VPP as the follower, aiming to minimize its own operational costs, with both parties engaging in a game based on electricity prices and energy consumption strategies. In the simulation case study, the effectiveness of the constructed model is veriffed, and the results show that the model can effectively reduce user costs and achieve full consumption of new energy. Virtual Power Plant Electric Vehicles Double layer Stackelberg Game Two- stage scheduling Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5401210","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":375218346,"identity":"94a06cf5-236a-4182-9ab5-ddc07960430b","order_by":0,"name":"jincheng Tang","email":"","orcid":"","institution":"Yunnan Minzu University","correspondingAuthor":false,"prefix":"","firstName":"jincheng","middleName":"","lastName":"Tang","suffix":""},{"id":375218347,"identity":"9b094ab9-693c-49ec-828c-6e4e2c8ab1f9","order_by":1,"name":"Xiaolan Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYBACPmYGhgMMDBYMDOwNYAHGBkJa2CBaJBgYeA4QqwVCAbVIJBCrhZ3H8MCPCgl5c8k3ppt5GGxkNxxgfvYAv8PYEg72nJEw3Dk7x+w2D0Oa8YYDbOYG+LUwHzjA2ybBuOE2WMvhxA0HeNgk8GthbDj4t03CfsPNMyAt/4nRwnzgMNCWxA03eEBaDhCjhS3hsMwZieQNZ9LKbs4xSDaeeZjNDK8Wfv4zxh/fVNjYbjh+eNuNNxV2sn3Hm5/h1YIEOIDhBAoqZiLVAwH7A+LVjoJRMApGwYgCAH90RgL/s6q3AAAAAElFTkSuQmCC","orcid":"","institution":"Yunnan Minzu University","correspondingAuthor":true,"prefix":"","firstName":"Xiaolan","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-11-06 09:08:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5401210/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5401210/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70279396,"identity":"8f6f0f66-58cb-43e4-8e3d-027de71ed7d7","added_by":"auto","created_at":"2024-12-01 13:46:47","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1231600,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscriptfile.jcT.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5401210/v1_covered_7a2241ed-e11a-40bb-b55b-7d2c6b0b8947.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Two-stage dual-level dispatch optimization model of multi-virtual power plants based on Stackelberg game ","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Virtual Power Plant, Electric Vehicles, Double layer, Stackelberg Game, Two- stage scheduling","lastPublishedDoi":"10.21203/rs.3.rs-5401210/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5401210/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"With the continuous increase in the number of electric vehicles (EVs) and the rapid development of demand response (DR) technology, the power grid faces unprecedented challenges. Two-stage dual-level dispatch optimization model of multi-virtual power plants based on Stackelberg game is proposed in this paper. In the day-ahead stage, a two-layer optimization scheduling model is established, where the EV layer optimizes for maximum comprehensive user satisfaction, and the VPP layer optimizes for minimal operating costs and interaction power, determining the scheduling arrangements for each distributed energy resource. In the intraday stage, a Stackelberg game model is constructed with the distribution network operators(DNO) as the leader, aiming to maximize proffts, and the VPP as the follower, aiming to minimize its own operational costs, with both parties engaging in a game based on electricity prices and energy consumption strategies. In the simulation case study, the effectiveness of the constructed model is veriffed, and the results show that the model can effectively reduce user costs and achieve full consumption of new energy. ","manuscriptTitle":"Two-stage dual-level dispatch optimization model of multi-virtual power plants based on Stackelberg game ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-25 06:03:29","doi":"10.21203/rs.3.rs-5401210/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"16362edd-fa73-40dd-918d-d3ebb4a5a455","owner":[],"postedDate":"November 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-01T13:38:30+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-25 06:03:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5401210","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5401210","identity":"rs-5401210","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: preprint-html

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2024) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00