A system dynamics model for optimal allocation of natural gas to various demand sectors

Abstract Natural gas is the most promising fossil fuel in the transition to a low-carbon energy future, and many countries have long term plans to increase its share in their energy supply mix through pricing regulations. While these policies encourage substitution of natural gas with more polluting fossil fuels, its over consumption and inefficient use can lead to misallocation of resources and CO2 emission increase. This paper develops a supply-demand model to optimally allocate natural gas to various demand sectors through determining a price path for each sector. The dynamic effects of price on demand, and income on supply are modeled using system dynamics. The model is applied to a case study on the optimal consumption share of each demand sector according to economic and environmental criteria. The results show that the residential sector should have a much smaller and export much larger share of the recommended consumption mix in 2040.

[1]  G Hamed Shakouri,et al.  A study on the future of unconventional oil development under different oil price scenarios: A system dynamics approach , 2016 .

[2]  Ali Azadeh,et al.  An adaptive network-based fuzzy inference system for short-term natural gas demand estimation: Uncertain and complex environments , 2010 .

[3]  Qiang Ji,et al.  Forecasting Natural Gas Demand in China: Logistic Modelling Analysis , 2016 .

[4]  Adelino J. C. Pereira,et al.  Generation expansion planning (GEP) – A long-term approach using system dynamics and genetic algorithms (GAs) , 2011 .

[5]  S. Thomas.  Enhanced Oil Recovery - An Overview , 2008 .

[6]  Vahid Ghorbani Pashakolaie,et al.  Oil Production Cost Function and Oil Recovery Implementation- Evidence from an Iranian Oil Field , 2015 .

[7]  Philipp M. Richter,et al.  The Role of Natural Gas in a Low-Carbon Europe: Infrastructure and Regional Supply Security in the Global Gas Model , 2013 .

[8]  S. Bhattacharyya.  Energy Economics: Concepts, Issues, Markets and Governance , 2011 .

[9]  Numan Çelebi,et al.  Forecasting of daily natural gas consumption on regional basis in Turkey using various computational methods , 2013 .

[10]  Wei Zhang,et al.  Natural gas price effects in China based on the CGE model , 2017 .

[11]  Rogelio Oliva,et al.  A comprehensive analytical approach for policy analysis of system dynamics models , 2010, Eur. J. Oper. Res..

[12]  Angel Mena-Nieto,et al.  System dynamics modeling for renewable energy and CO2 emissions: A case study of Ecuador , 2014 .

[13]  Sergey Paltsev,et al.  Natural gas pricing reform in China: Getting closer to a market system? , 2015 .

[14]  Gi-Tae Yeo,et al.  Analysis of dynamic effects on seaports adopting port security policy , 2013 .

[15]  Hamidreza Zareipour,et al.  A real option assessment of flexibilities in the integrated planning of natural gas distribution network and distributed natural gas-fired power generations , 2018 .

[16]  M. Arouri,et al.  Short- and long-run relationships between natural gas consumption and economic growth: Evidence from Pakistan , 2014 .

[17]  Nurkholis,et al.  Impact analysis of natural gas policy in Indonesia , 2017 .

[18]  John G. Rowse.  Allocation of Canadian Natural Gas to Domestic and Export Markets , 1986 .

[19]  A. Orlov.  Distributional effects of higher natural gas prices in Russia , 2017 .

[20]  K. Schneider,et al.  Removing energy subsidies in developing and transition economies , 2000 .

[21]  Zhishuang Zhu,et al.  Effects of gas pricing reform on China’s price level and total output , 2016, Natural Hazards.

[22]  Leila Dagher,et al.  Natural gas demand at the utility level: An application of dynamic elasticities , 2012 .

[23]  Mehmet Melikoglu,et al.  Vision 2023: Forecasting Turkey's natural gas demand between 2013 and 2030 , 2013 .

[24]  Camilo Mancilla,et al.  Two methods of data reconciliation for pipeline networks , 2018, Comput. Chem. Eng..

[25]  Hassan Qudrat-Ullah,et al.  How to make better energy policy decisions? The stock and flow perspective , 2018 .

[26]  Adel Azar,et al.  A hybrid fuzzy satisfying optimization model for sustainable gas resources allocation , 2015 .

[27]  A. Hutagalung.  The economic value of Indonesia's natural gas : a quantitative assessment of three gas policies , 2014 .

[28]  A. Orlov.  An assessment of optimal gas pricing in Russia: A CGE approach , 2015 .

[29]  Fatih Emre Boran,et al.  Forecasting Natural Gas Consumption in Turkey Using Grey Prediction , 2015 .

[30]  Behdad Kiani,et al.  A system dynamic model for production and consumption policy in Iran oil and gas sector , 2010 .

[31]  Chaoyu Li,et al.  A system dynamics simulation model of chemical supply chain transportation risk management systems , 2016, Comput. Chem. Eng..

[32]  John D. W. Morecroft,et al.  System dynamics and microworlds for policymakers , 1988 .

[33]  Bassam Fattouh,et al.  Energy subsidies in the Middle East and North Africa , 2013 .

[34]  Hweeung Kwon,et al.  Optimization of naphtha purchase price using a price prediction model , 2016, Comput. Chem. Eng..

[35]  Boqiang Lin,et al.  China's natural gas consumption and subsidies—From a sector perspective , 2014 .

[36]  P. Helo,et al.  Role of renewable energy policies in energy dependency in Finland: System dynamics approach , 2014 .

[37]  Felipe da Silva Alves,et al.  Multi-objective design optimization of natural gas transmission networks , 2016, Comput. Chem. Eng..

[38]  Dagnija Blumberga,et al.  Implementation of Different Policy Strategies Promoting the Use of Wood Fuel in the Latvian District Heating System: Impact Evaluation through a System Dynamic Model , 2014 .

[39]  John D. Sterman,et al.  System Dynamics: Systems Thinking and Modeling for a Complex World , 2002 .

[40]  M. Fowler,et al.  A System Dynamics Model for Analyzing Future Natural Gas Supply and Demand , 2018, Industrial & Engineering Chemistry Research.

[41]  Victor M. Zavala,et al.  Stochastic optimal control model for natural gas networks , 2014, Comput. Chem. Eng..