Participation of Nepal in Real Time Market in Indian Energy Exchange: Analysis of Optimal Bidding Strategies using Machine Learning

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dc.contributor.advisorKarki, Nawaraj
dc.contributor.authorParajuli, Elina
dc.date.accessioned2024-08-14T09:30:42Z
dc.date.available2024-08-14T09:30:42Z
dc.date.issued2024-06
dc.descriptionPrecise load prediction is vital for electric utilities, as it provides crucial information for scheduling power generation, managing energy distribution, and optimizing resources. Nepal Electricity Authority, is currently participating in Indian Energy Exchange’s (IEX) Day Ahead Market (DAM) for the import/export of electricity which is itself a huge milestone for Nepal but is also required to forecast their loads in 15-minute intervals a day in advance with high accuracy to bid in the energy market.
dc.description.abstractPrecise load prediction is vital for electric utilities, as it provides crucial information for scheduling power generation, managing energy distribution, and optimizing resources. Nepal Electricity Authority, is currently participating in Indian Energy Exchange’s (IEX) Day Ahead Market (DAM) for the import/export of electricity which is itself a huge milestone for Nepal but is also required to forecast their loads in 15-minute intervals a day in advance with high accuracy to bid in the energy market. To discourage excessive power drawl or insufficient power injection, a frequency-based component called the deviation settlement charge (DSM) is incorporated into the bulk electricity pricing in the IEX market. Due to in accurate load forecasting, weather changes, holidays, Nepal has also been subjected to deviation charges to account for any deviations from the agreed-upon energy transactions. RTM provide a mechanism for balancing the fluctuations in supply and demand by allowing market participants to adjust their electricity purchases or sales in response to changing conditions. It also provides more flexibility and responsiveness compared to day-ahead markets, which can help grid operators manage their systems more effectively. Therefore, RTM bidding in addition to Day Ahead Market bidding is of paramount importance to handle this deviation.
dc.description.provenanceSubmitted by Govind Bist (govind.bist@ncc.tu.edu.np) on 2024-08-14T09:30:42Z No. of bitstreams: 1 Elina Parajuli Master thesis electrical power system july 2024.pdf: 7576568 bytes, checksum: 66425626e7fcccf11ad31e2d008ff9fd (MD5)en
dc.description.provenanceMade available in DSpace on 2024-08-14T09:30:42Z (GMT). No. of bitstreams: 1 Elina Parajuli Master thesis electrical power system july 2024.pdf: 7576568 bytes, checksum: 66425626e7fcccf11ad31e2d008ff9fd (MD5) Previous issue date: 2024-06en
dc.identifier.urihttps://hdl.handle.net/20.500.14540/22697
dc.language.isoen
dc.publisherI.O.E
dc.subjectReal Time Market
dc.subjectEnergy Exchange
dc.subjectMachine Learning
dc.titleParticipation of Nepal in Real Time Market in Indian Energy Exchange: Analysis of Optimal Bidding Strategies using Machine Learning
dc.typeThesis
local.academic.levelMasters
local.institute.titleInstitute of Engineering
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