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Titel: Activation of electrical loads under electricity price uncertainty
VerfasserIn: Minhas, Daud Mustafa
Khalid, Raja Rehan
Frey, Georg
Sprache: Englisch
Titel: 2017 the 5th IEEE International Conference on Smart Energy Grid Engineering (SEGE) : August 14-17, 2017, UOIT, Oshawa, Canada
Startseite: 373
Endseite: 378
Verlag/Plattform: IEEE
Erscheinungsjahr: 2017
Erscheinungsort: Piscataway
Konferenzort: Oshawa, Canada
Freie Schlagwörter: Load modeling
Forecasting
Predictive models
Training
Real-time systems
Logistics
Optimal scheduling
DDC-Sachgruppe: 600 Technik
Dokumenttyp: Konferenzbeitrag (in einem Konferenzband / InProceedings erschienener Beitrag)
Abstract: The electricity price is an uncertain and changeable entity, mostly depends on power generating source and consumer's power demands behavior. The problem arises when all the consumers try to avail specific low price time slot to activate their power demands. It ends up with energy congestion or system destabilization. A better strategy is, to forecast a day ahead price and update it instantly, whenever a new consumer purchases an amount of energy for its next day demands. Therefore, every time a new price is applicable for the upcoming purchasers on day-ahead basis. This strategy may be adopted by an aggregator. An aggregator, which is equipped with renewable energy resources (RES), also imports electricity from the grid. It forecasts and updates a day-ahead fluctuating electricity price for its consumers. So that, all the consumers can avail relatively low price electricity slots based on their energy purchasing decisions. In this paper, a regression base statistical model is adopted to investigate two major problems: 1) accurate forecasting of day-ahead electricity price by an aggregator; 2) activate load demands by the consumers at lower electricity prices. In our proposed solution, linear regression is used to forecast the electricity price, exploiting intermittent nature of the renewables. Whereas, load activation strategy is proposed by introducing electrical loads with different levels of delay tolerance. Applying boundary condition values using logistic regression, a consumer can activate its loads on different electricity prices. The simulation results have established an effectively forecasted value of electricity price and an accurate activation of consumer's load demands.
DOI der Erstveröffentlichung: 10.1109/SEGE.2017.8052828
URL der Erstveröffentlichung: https://ieeexplore.ieee.org/document/8052828
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-366147
hdl:20.500.11880/33257
http://dx.doi.org/10.22028/D291-36614
ISBN: 978-1-5386-1776-2
978-1-5386-1775-5
Datum des Eintrags: 4-Jul-2022
Fakultät: NT - Naturwissenschaftlich- Technische Fakultät
Fachrichtung: NT - Systems Engineering
Professur: NT - Prof. Dr. Georg Frey
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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