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Pricing and Inventory Control Strategy for a Periodic-Review Energy Buy-Back System
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. Beijing Foreign Studies University, China.
Number of Authors: 42016 (English)In: Journal of Systems Science and Complexity, ISSN 1009-6124, E-ISSN 1559-7067, Vol. 29, no 4, p. 1018-1033Article, review/survey (Refereed) 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.

Place, publisher, year, edition, pages
2016. Vol. 29, no 4, p. 1018-1033
Keywords [en]
Additive demand function, energy buy-back program, joint pricing and inventory control, Veinott's conditions
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:su:diva-175542DOI: 10.1007/s11424-016-4101-0ISI: 000384985600009OAI: oai:DiVA.org:su-175542DiVA, id: diva2:1368413
Available from: 2019-11-07 Created: 2019-11-07 Last updated: 2019-11-07Bibliographically approved

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