Publication:
Stochastic generation scheduling with variable renewable generation: Methods, applications, and future trends

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dc.citedby11
dc.contributor.authorTan W.-S.en_US
dc.contributor.authorShaaban M.en_US
dc.contributor.authorAb Kadir M.Z.A.en_US
dc.contributor.authorid55336912400en_US
dc.contributor.authorid57189064979en_US
dc.contributor.authorid25947297000en_US
dc.date.accessioned2023-05-29T07:30:19Z
dc.date.available2023-05-29T07:30:19Z
dc.date.issued2019
dc.descriptionElectric power transmission networks; Optimization; Renewable energy resources; Scheduling; Uncertainty analysis; Computational performance; Electrical power generation; Integration of renewable energies; Operating constraints; Renewable energy generation; Stochastic generation; Stochastic optimisation; Uncertainty modelling; Stochastic systemsen_US
dc.description.abstractOne of the most intricate optimisation problems in power systems is generation scheduling. It determines the schedule and dispatch of electrical power generation to meet the load demand under various technical and operating constraints. Generation scheduling is a vivid problem, particularly in recent years, due to the aggressive integration of renewable energy, with stochastic nature, into power grids. As the literature size has swollen substantially in the past several years, this study critically looks into uncertainty modelling and the formulation of various techniques that were implemented in stochastic optimisation-based generation scheduling. The strengths and weaknesses of existing methods are fully exposed. Market operation policies that significantly affect the scheduling of renewable energy generation in different timescales are elaborated. Potential applications and future trends in terms of modelling, computational performance, and incorporation of flexibility and resilience notions are thoroughly discussed. � The Institution of Engineering and Technology 2019.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1049/iet-gtd.2018.6331
dc.identifier.epage1480
dc.identifier.issue9
dc.identifier.scopus2-s2.0-85066735689
dc.identifier.spage1467
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85066735689&doi=10.1049%2fiet-gtd.2018.6331&partnerID=40&md5=dcb8ec1c79043ff3bef52ab0be5d6b45
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25010
dc.identifier.volume13
dc.publisherInstitution of Engineering and Technologyen_US
dc.relation.ispartofAll Open Access, Green
dc.sourceScopus
dc.sourcetitleIET Generation, Transmission and Distribution
dc.titleStochastic generation scheduling with variable renewable generation: Methods, applications, and future trendsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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