dc.contributor.author Zhang, S. dc.contributor.author Wang, X. dc.contributor.author Wang, Song dc.date.accessioned 2018-12-13T09:09:17Z dc.date.available 2018-12-13T09:09:17Z dc.date.created 2018-12-12T02:46:42Z dc.date.issued 2018 dc.identifier.citation Zhang, S. and Wang, X. and Wang, S. 2018. Modeling and computation of energy efficiency management with emission permits trading. Journal of Industrial and management optimization. 14 (4): pp. 1349-1365. dc.identifier.uri http://hdl.handle.net/20.500.11937/71225 dc.identifier.doi 10.3934/jimo.2018010 dc.description.abstract In this paper, we present an optimal feedback control model to deal with the problem of energy efficiency management. Especially, an emission permits trading scheme is considered in our model, in which the decision maker can trade the emission permits exibly. We make use of the optimal control theory to derive a Hamilton-Jacobi-Bellman (HJB) equation satisfied by the value function, and then propose an upwind finite difference method to solve it. The stability of this method is demonstrated and the accuracy, as well as the usefulness, is shown by the numerical examples. The optimal management strategies, which maximize the discounted stream of the net revenue, together with the value functions, are obtained. The effects of the emission permits price and other parameters in the established model on the results have been also examined. We find that the in uences of emission permits price on net revenue for the economic agents with different initial quotas are quite different. All the results demonstrate that the emission permits trading scheme plays an important role in the energy efficiency management. dc.publisher American Institute of Mathematical Sciences dc.title Modeling and computation of energy efficiency management with emission permits trading dc.type Journal Article dcterms.source.volume 14 dcterms.source.number 4 dcterms.source.startPage 1349 dcterms.source.endPage 1365 dcterms.source.issn 1547-5816 dcterms.source.title Journal of Industrial and management optimization curtin.department School of Electrical Engineering, Computing and Mathematical Science (EECMS) curtin.accessStatus Fulltext not available
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