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Pricing and Inventory Control Strategy for a Periodic-Review Energy Buy-Back System
Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutionen för data- och systemvetenskap. Beijing Foreign Studies University, China.
Antal upphovsmän: 42016 (Engelska)Ingår i: Journal of Systems Science and Complexity, ISSN 1009-6124, E-ISSN 1559-7067, Vol. 29, nr 4, s. 1018-1033Artikel, forskningsöversikt (Refereegranskat) Published
Abstract [en]

Along with the rapid development of economics and enhancement of industrialization, the power demand keeps rising and frequently creates mismatch between demand and supply in electricity. This provides miscellaneous energy buy-back programs with great opportunities. Such programs, when activated, offer certain amount of financial compensations to participants for reducing their energy consumption during peak time. They aim at encouraging participants to shift their electricity usage from peak to non-peak time, and thereby release the demand pressure during peak time. This paper considers a periodic-review joint pricing and inventory decision model under an energy buy-back program over finite planning horizons, in which the compensation levels, setup cost and additive random demand function are incorporated. The objective is to maximize a manufacturer's expected total profit. By using Veinott's conditions, it is shown that the manufacturer's optimal decision is a state dependent (s, S, P) policy under a peak market condition, or partly an (s, S, A, P) policy under the normal market condition.

Ort, förlag, år, upplaga, sidor
2016. Vol. 29, nr 4, s. 1018-1033
Nyckelord [en]
Additive demand function, energy buy-back program, joint pricing and inventory control, Veinott's conditions
Nationell ämneskategori
Elektroteknik och elektronik
Identifikatorer
URN: urn:nbn:se:su:diva-175542DOI: 10.1007/s11424-016-4101-0ISI: 000384985600009OAI: oai:DiVA.org:su-175542DiVA, id: diva2:1368413
Tillgänglig från: 2019-11-07 Skapad: 2019-11-07 Senast uppdaterad: 2019-11-07Bibliografiskt granskad

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