Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Applied Energyarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Applied Energy
Article . 2020 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
versions View all 2 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Optimization of renewable energy subsidy and carbon tax for multi energy systems using bilevel programming

Authors: Martelli E.; Freschini M.; Zatti M.;

Optimization of renewable energy subsidy and carbon tax for multi energy systems using bilevel programming

Abstract

Abstract The use of optimized Multi-Energy Systems, including renewables, combined heat and power units and energy storages, is proven to be effective in the reduction of fossil CO2 emissions. These systems can be efficiently operated to provide electricity, heating and cooling to energy districts and buildings. To increase the share of renewable sources and further decrease CO2 emissions, incentives and/or carbon taxes are set by governments. This work proposes a novel bi-level optimization approach which mimics the actual bilevel decision process to determine the optimal renewable subsidy and carbon tax for small-medium multi-energy systems. At the upper level the government decides the incentives/tax to meet the desired emission reduction target while minimizing its costs and, at the lower level, the owner/operator of the Multi-Energy System decides the optimal design and operation to minimize its Total Annual Cost (sum of investment and operating costs). We devise an efficient heuristic approach to solve the bilevel program and apply the approach to four different real-world applications, namely a university campus, a hospital, an urban district, and an office building.

Country
Italy
Related Organizations
Keywords

District energy systems, Carbon tax, Black-box optimization, Incentives, Energy policy, MILP

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    66
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
66
Top 1%
Top 10%
Top 1%