Multiperiod model for the optimal production planning in the industrial gases sector

Cryogenic air separation to produce nitrogen, oxygen and argon with high quality requirements is an energy-intensive industrial process that requires large quantities of electricity. The complexity in operating these networks stems from the volatile conditions, namely electricity prices and products demands, which vary every hour, creating a clear need for computer-aided tools to attain economic and energy savings. In this article, we present a multiperiod mixed-integer linear programming (MILP) model to determine the optimal production schedule of an industrial cryogenic air separation process so as to maximize the net profit by minimizing energy consumption (which is the main contributor to the operating costs). The capabilities of the model are demonstrated by means of its application to an existing industrial process, where significant improvements are attained through the implementation of the MILP.

[1]  C. Floudas Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications , 1995 .

[2]  Gonzalo Guillén-Gosálbez,et al.  Multi-objective optimization of coal-fired electricity production with CO2 capture , 2012 .

[3]  Gonzalo Guillén-Gosálbez,et al.  Optimization of global and local pollution control in electricity production from coal burning , 2012 .

[4]  Carl D. Laird,et al.  Optimal operation of cryogenic air separation systems with demand uncertainty and contractual obligations , 2011 .

[5]  Colin Fitzpatrick,et al.  Demand side management of a domestic dishwasher: Wind energy gains, financial savings and peak-time load reduction , 2013 .

[6]  Halit Üster,et al.  Optimization for Design and Operation of Natural Gas Transmission Networks , 2014 .

[7]  Aldo R. Vecchietti,et al.  Modeling of discrete/continuous optimization problems: characterization and formulation of disjunctions and their relaxations , 2003, Comput. Chem. Eng..

[8]  Dongdong Ge,et al.  A Review of Piecewise Linearization Methods , 2013 .

[9]  Pieter Stroeve,et al.  The impact of scheduling appliances and rate structure on bill savings for net-zero energy communities: Application to West Village , 2014 .

[10]  J. G. Slootweg,et al.  Responsiveness of residential electricity demand to dynamic tariffs: Experiences from a large field test in the Netherlands , 2016 .

[11]  Tham Kwok Wai,et al.  A literature survey on measuring energy usage for miscellaneous electric loads in offices and commercial buildings , 2014 .

[12]  A. Smith,et al.  A review of air separation technologies and their integration with energy conversion processes , 2001 .

[13]  F.D. Mele,et al.  A novel rolling horizon strategy for the strategic planning of supply chains. Application to the sugar cane industry of Argentina , 2011, Comput. Chem. Eng..

[14]  Geert Deconinck,et al.  Potential of Active Demand Reduction With Residential Wet Appliances: A Case Study for Belgium , 2015, IEEE Transactions on Smart Grid.

[15]  Ignacio E. Grossmann,et al.  Disjunctive multiperiod optimization methods for design and planning of chemical process systems , 1999 .

[16]  Mark H. Karwan,et al.  Operations planning with real time pricing of a primary input , 2007, Comput. Oper. Res..

[17]  Gonzalo Guillén-Gosálbez,et al.  Optimal Planning of Supply Chains for Bioethanol and Sugar Production with Economic and Environmental Concerns , 2009 .

[18]  Ignacio E. Grossmann,et al.  Optimal production planning under time-sensitive electricity prices for continuous power-intensive processes , 2012, Comput. Chem. Eng..

[19]  Carlos M. Correa-Posada Gas Network Optimization: A comparison of Piecewise Linear Models , 2014 .

[20]  Joakim Widén,et al.  Improved photovoltaic self-consumption with appliance scheduling in 200 single-family buildings , 2014 .

[21]  Carl D. Laird,et al.  A multiperiod nonlinear programming approach for operation of air separation plants with variable power pricing , 2011 .

[22]  G. Gutierrez-Alcaraz,et al.  Effects of demand response programs on distribution system operation , 2016 .

[23]  Richard D. Tabors,et al.  Optimal demand-side response to electricity spot prices for storage-type customers , 1989 .

[24]  W. Luyben,et al.  Economic Incentive for Intermittent Operation of Air Separation Plants with Variable Power Costs , 2008 .

[25]  Colin J. Axon,et al.  Power-use profile analysis of non-domestic consumers for electricity tariff switching , 2016 .

[26]  Nikolaos V. Sahinidis,et al.  Global optimization of an industrial gas network operation , 2016 .

[27]  M. Ierapetritou,et al.  Cost Minimization in an Energy-Intensive Plant Using Mathematical Programming Approaches , 2002 .

[28]  Nina F. Thornhill,et al.  Optimization of a network of compressors in parallel: Operational and maintenance planning – The air separation plant case , 2015 .

[29]  R. Madlener,et al.  Power Plant Investments in the Turkish Electricity Sector: A Real Options Approach Taking into Account Market Liberalization , 2011 .

[30]  Nina F. Thornhill,et al.  Optimization of a network of compressors in parallel: Real Time Optimization (RTO) of compressors in chemical plants – An industrial case study , 2015 .

[31]  Risto Ritala,et al.  TMP production scheduling under uncertainty: Methodology and case studies , 2008 .