×

A systems approach for the optimal retrofitting of utility networks under demand and market uncertainties. (English) Zbl 1359.90021

Rebennack, Steffen (ed.) et al., Handbook of power systems. I. Berlin: Springer (ISBN 978-3-642-02492-4/hbk; 978-3-642-02493-1/ebook). Energy Systems, 293-306 (2010).
Summary: This paper presents a systematic optimization approach to the retrofitting of utility systems whose operation faces uncertainties in the steam demand and the fuel and power prices. The optimization determines retrofit configurations to minimize an (expected) annualised total cost, using a stochastic programming approach deployed at two levels. The upper level optimizes structural modifications, while the second level optimizes the operation of the network. Uncertainties, modelled by distribution functions, link the two stages as the lower layer produces statistical information used, in aggregate form, by the upper level. The approach uses a case study to demonstrate its potential and value, producing evidence that uncertainties are important to consider early and that the two-level optimization effectively screens networks capable to afford unexpected changes in the parameters.
For the entire collection see [Zbl 1201.00002].

MSC:

90B15 Stochastic network models in operations research
90C15 Stochastic programming
62P30 Applications of statistics in engineering and industry; control charts

Software:

CONDOR
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] Iman RL, Helton JC, Campbell JE (1981) An approach to sensitivity analysis of computer models: Part I-introduction, input variable selection and preliminary variable assessment. J Qual Technol 13(3):174-183
[2] Papoulias SA, Grossmann IE (1983) A structural optimization approach in process synthesis-I utility systems. Comput Chem Eng 7:695-706
[3] Hui CW, Natori Y (1996) An industrial application using mixed integer-programming technique: a multi-period utility system model. Comput Chem Eng 20:s1577-s1582
[4] Maia LOA, Qassim RY (1997) Synthesis of utility systems with variable demands using simulated annealing. Comput Chem Eng 21:947-950
[5] Iyer RR, Grossmann IE (1998) Synthesis and operational planning of utility systems for multiperiod operation. Comput Chem Eng 22:979-993
[6] Papalexandri KP, Pistikopoulos EN, Kalitventzeff B (1998) Modelling and optimization aspects in energy management and plant operation with variable energy demands-application to industrial problems. Comput Chem Eng 22:1319-1333
[7] Bruno JC, Fernandez F, Castells F, Grossmann IE (1998) A rigorous MINLP model for the optimal synthesis and operation of utility plants. Chem Eng Res Des 76:246-258
[8] Mavromatis SP, Kokossis AC (1998a) Conceptual optimisation of utility networks for operational variations-1: targets and level optimisation. Chem Eng Sci 53:1585-1608
[9] Mavromatis SP, Kokossis AC (1998b) Conceptual optimisation of utility networks for operational variations-2: network development and optimisation. Chem Eng Sci 53:1609-1630
[10] Berghen F, Bersini H (2004) CONDOR, an new parallel, constrained extension of Powell’s UOBYQA algorithm. Experimental results and comparison with the DFO algorithm. Technical report, IRIDIA, Universite Libre de Bruxelles, Belgium. · Zbl 1072.65088
[11] Varbanov PS, Doyle S, Smith R (2004) Modelling and optimization of utility systems. Chem Eng Res Des 82(A5):561-578
[12] Sahinidis NV (2004) Optimization under uncertainty: state-of-the-art and opportunities. Comput Chem Eng 28:971-983
[13] Shang Z, Kokossis AC (2004) A transhipment model for the optimization of steam levels of total site utilitysy stem for multiperiod operation. Comput Chem Eng 28:1673-1688
[14] Shang Z, Kokossis A (2005) A systematic approach to the synthesis and design of flexible site utility systems. Chem Eng Sci 60:4431-4451
[15] Aguilar O, Perry SJ, Kim J-K, Smith R (2007a) Design and optimization of flexible utility systems subject to variable conditions. Part 1: Modelling framework. Chem Eng Res Des 85(A8):1136-1148
[16] Aguilar O, Perry SJ, Kim J-K, Smith R (2007b) Design and optimization of flexible utility systems subject to variable conditions. Part 2: Methodology and applications. Chem Eng Res Des 85(A8):1149-1168
[17] Energy Information Administration (2008) Selected National Average Natural Gas Prices, 2004-2009. Available online at
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.