Determining approximate Stackelberg strategies in carbon constrained energy planning using a hybrid fuzzy optimisation and adaptive multi-particle simulated annealing technique
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The Institution of Engineers, Malaysia
2011
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my.unimap-137152011-09-10T16:09:24Z Determining approximate Stackelberg strategies in carbon constrained energy planning using a hybrid fuzzy optimisation and adaptive multi-particle simulated annealing technique Raymond, R. Tan, Prof. raymond.tan@dlsu.edu.ph Bi-level programming Carbon constraints Energy planning Source-sink model Stackelberg game Link to publisher's homepage at http://www.myiem.org.my/ In recent years, there has been growing international concern about climate change as a result of greenhouse gas emissions from human activity. Various process integration techniques have thus been developed to assist in determining the optimal allocation of energy sources to sectoral or regional demands under carbon footprint constraints; for example, the source-sink representation of this problem has been solved using graphical and algebraic pinch analysis techniques as well as linear programming. This work presents an extension of the original problem by incorporating a game-theoretic, two-level decision framework, which is a more accurate representation of real-life energy planning applications. The upper level decision-maker (i.e., the government) seeks to minimise total costs to society by selecting appropriate emission limits for each sector as well as subsidy levels for clean energy sources; on the other hand, the lower level decision-maker (i.e., industry) seeks to minimize total energy-related costs subject to the emission limits set by the government. This problem is a static Stackelberg game which may be formulated as a fuzzy bi-level optimisation model. A numerical example from literature is used to illustrate the modeling approach. The case study is then solved using an adaptive multi-particle simulated annealing algorithm to yield an approximate Stackelberg solution. 2011-09-10T16:09:24Z 2011-09-10T16:09:24Z 2010-09 Article The Journal of the Institution of Engineers, Malaysia, vol. 71(3), 2010, pages 19-25 0126-513X http://www.myiem.org.my/content/iem_journal_2010-181.aspx http://hdl.handle.net/123456789/13715 en The Institution of Engineers, Malaysia |
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English |
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Bi-level programming Carbon constraints Energy planning Source-sink model Stackelberg game |
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Bi-level programming Carbon constraints Energy planning Source-sink model Stackelberg game Raymond, R. Tan, Prof. Determining approximate Stackelberg strategies in carbon constrained energy planning using a hybrid fuzzy optimisation and adaptive multi-particle simulated annealing technique |
| description |
Link to publisher's homepage at http://www.myiem.org.my/ |
| author2 |
raymond.tan@dlsu.edu.ph |
| author_facet |
raymond.tan@dlsu.edu.ph Raymond, R. Tan, Prof. |
| format |
Article |
| author |
Raymond, R. Tan, Prof. |
| author_sort |
Raymond, R. Tan, Prof. |
| title |
Determining approximate Stackelberg strategies in carbon constrained energy planning using a hybrid fuzzy optimisation and adaptive multi-particle simulated annealing technique |
| title_short |
Determining approximate Stackelberg strategies in carbon constrained energy planning using a hybrid fuzzy optimisation and adaptive multi-particle simulated annealing technique |
| title_full |
Determining approximate Stackelberg strategies in carbon constrained energy planning using a hybrid fuzzy optimisation and adaptive multi-particle simulated annealing technique |
| title_fullStr |
Determining approximate Stackelberg strategies in carbon constrained energy planning using a hybrid fuzzy optimisation and adaptive multi-particle simulated annealing technique |
| title_full_unstemmed |
Determining approximate Stackelberg strategies in carbon constrained energy planning using a hybrid fuzzy optimisation and adaptive multi-particle simulated annealing technique |
| title_sort |
determining approximate stackelberg strategies in carbon constrained energy planning using a hybrid fuzzy optimisation and adaptive multi-particle simulated annealing technique |
| publisher |
The Institution of Engineers, Malaysia |
| publishDate |
2011 |
| url |
http://dspace.unimap.edu.my/xmlui/handle/123456789/13715 |
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1643791005388898304 |