A novel formulation of carbon emissions costs for optimal design configuration of system transmission planning

This paper describes a methodology developed for designing an optimal configuration for system transmission planning with carbon emissions costs. The power transmission network planning problem is modeled by the mixed integer programming model, a GA, and SA. At this moment environmental issues have the most serious problem to be concerned within every part of the world. Global warming, which is mainly caused by the emissions of Green House Gases (GHGs), is said to be a serious part of these environmental problems. Since green house gases issues become important and the new legislations are taken into account, carbon emissions costs are included in the total costs of the transmission network planning. This method of solution is demonstrated on the real problem. Finally, the genetic algorithm shows to be a very good option for network planning systems given that it obtains much accentuated reductions of iteration, which is very important for network planning.

[1]  John M. Reilly,et al.  The Kyoto Protocol and non-CO2 Greenhouse Gases and Carbon Sinks , 2002 .

[2]  R. Bradley Climate Alarmism Reconsidered , 2003 .

[3]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[4]  G. Metcalf Corporate Tax Reform , 2007 .

[5]  S. Sorrell,et al.  Carbon trading in the policy mix , 2003 .

[6]  Global scenarios for carbon dioxide emissions , 1993 .

[7]  S. DeCanio,et al.  International Cooperation to Avert Global Warming: Economic Growth, Carbon Pricing, and Energy Efficiency , 1992 .

[8]  Richard D. Tabors,et al.  Planning for future uncertainties in electric power generation: an analysis of transitional strategies for reduction of carbon and sulfur emissions , 1991 .

[9]  A. Sadegheih A NOVEL METHOD FOR DESIGNING AND OPTIMIZATION OF NETWORKS , 2007 .

[10]  Fushuan Wen,et al.  Transmission network optimal planning using the tabu search method , 1997 .

[11]  B. P. Herber,et al.  An International Carbon Tax to Combat Global Warming: An Economic and Political Analysis of the European Union Proposal , 1995 .

[12]  A. Sadegheih,et al.  Optimal design methodologies under the carbon emission trading program using MIP, GA, SA, and TS , 2011 .

[13]  A. Sadegheih,et al.  Sequence optimization and design of allocation using GA and SA , 2007, Appl. Math. Comput..

[14]  A. Sadegheih Scheduling problem using genetic algorithm, simulated annealing and the effects of parameter values on GA performance , 2006 .

[15]  John M. Reilly,et al.  Assessing the Impact of Carbon Tax Differentiation in the European Union , 2003 .

[16]  Ruben Romero,et al.  A zero-one implicit enumeration method for optimizing investments in transmission expansion planning , 1994 .

[17]  Paul R. Drake,et al.  A NOVEL EXPERIMENTAL ANALYSIS OF THE MINIMUM COST FLOW PROBLEM , 2009 .

[18]  J. Shogren,et al.  Tradable Permit Tariffs: How Local Air Pollution Affects Carbon Emissions Permit Trading , 2002, Land Economics.

[19]  A. Sharifnia,et al.  Transmission Network Planning: A Method for Synthesis of Minimum-Cost Secure Networks , 1985, IEEE Transactions on Power Apparatus and Systems.

[20]  Fushuan Wen,et al.  Tabu search approach to alarm processing in power systems , 1997 .

[21]  R. Yokoyama,et al.  Transmission expansion planning using neuro-computing hybridized with genetic algorithm , 1995, Proceedings of 1995 IEEE International Conference on Evolutionary Computation.

[22]  Denny K. S. Ng,et al.  Carbon and footprint-constrained energy planning using cascade analysis technique , 2008 .

[23]  Olivier Bahn,et al.  Modelling an international market of CO 2 emission permits , 1999 .

[24]  M. M. El-Metwally,et al.  New method for transmission planning using mixed-integer programming , 1988 .

[25]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[26]  Francisco D. Galiana,et al.  Expert systems in transmission planning , 1992, Proc. IEEE.

[27]  A. Sadegheih,et al.  Evolutionary algorithms and simulated annealing in the topological configuration of the spanning tree , 2008 .

[28]  Ruben Romero,et al.  Transmission system expansion planning by simulated annealing , 1995 .

[29]  Michael N. Vrahatis,et al.  Recent approaches to global optimization problems through Particle Swarm Optimization , 2002, Natural Computing.

[30]  A. Sadegheih New formulation and analysis of the system planning expansion model , 2009 .

[31]  Cameron Hepburn,et al.  Credible Carbon Policy , 2003 .

[32]  K. R. Padiyar,et al.  Comparison of methods for transmission system expansion using network flow and DC load flow models , 1988 .

[33]  A Strategy for Adequate Future World Energy Supply and Carbon Emission Control , 2006, 2006 IEEE EIC Climate Change Conference.

[34]  Hans-Paul Schwefel,et al.  Evolution and optimum seeking , 1995, Sixth-generation computer technology series.

[35]  Consolación Gil,et al.  Optimization methods applied to renewable and sustainable energy: A review , 2011 .

[36]  A. Sadegheih Optimization of network planning by the novel hybrid algorithms of intelligent optimization techniques , 2009 .

[37]  Sanna Syri,et al.  Extension of EU Emissions Trading Scheme to Other Sectors and Gases: Consequences for Uncertainty of Total Tradable Amount , 2007 .

[38]  Simon Harvey,et al.  The role of policy instruments for promoting combined heat and power production with low CO2 emissions in district heating systems , 2005 .

[39]  Anna Nagurney,et al.  Optimal endogenous carbon taxes for electric power supply chains with power plants , 2006, Math. Comput. Model..

[40]  Datu Buyung Agusdinata,et al.  System-of-Systems Perspective and Exploratory Modeling to Support the Design of Adaptive Policy for Reducing Carbon Emission , 2007, 2007 IEEE International Conference on System of Systems Engineering.

[41]  H. Whittington Electricity generation: options for reduction in carbon emissions , 2002, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[42]  R. Clémençon,et al.  The Bali Road Map , 2008 .

[43]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[44]  I. Parry Fiscal Interactions and the Case for Carbon Taxes over Grandfathered Carbon Permits , 2003 .

[45]  S.N. Singh,et al.  Implications of Carbon Tax on Generation Expansion Plan & GHG Emission: A Case Study on Indian Power Sector , 2005, 2004 International Conference on Power System Technology, 2004. PowerCon 2004..

[46]  J. Dumanski,et al.  Carbon Sequestration, Soil Conservation, and the Kyoto Protocol: Summary of Implications , 2004 .

[47]  Christoph Böhringer The Kyoto Protocol: A Review and Perspectives , 2003 .