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Energy and Resource Efficiency: multi-criteria optimization

Multi-criteria optimization for large, distributed industrial production systems
based on previous work for Shanxi Province, PRC, Decision Support Systems (DSS) for Economic Development (5 year) Planning:
Expert Systems for Integrated Development (Fedra et al., 1987).

An industrial park or zone is represented by a set of hierarchically organized (into Production Companies, PCO) and partly linked production processes units, a Production-Distribution Area (PDA).

Basic economic assumption: production volumes do not affect market prices (even though, such a feedback could easily be built in).

A production process unit (PPU) is defined by:

  • one or more products to be generated that require
  • a set of inputs (water energy, materials [array] labor)
  • a set of technologies that convert these inputs into the product(s) and
  • one or more waste streams/emissions.
The coupled PDU's (in some cases, output from one PU can form input into another with some transportation costs involved) form a basic model of the PDA.

Given (all variables could be functions of time)

  • a set of external demands for products
  • constraints in the availability of inputs and waste output (waste treatment is yet another set of PU that result in final waste to be exported)
  • costs of inputs, technologies (investment, operations) benefits for product
an optimal (pareto-optimal or simplified into maximum net benefit) configuration can be found by adaptive heuristics and genetic algorithms for steady-state configurations. For dynamic scenarios, replacement or re-scaling of technologies also has a technology and size specific delay.

OBJECTIVES:
The PDA model keeps track of costs and benefits (steady state or over time, e.g., by quarter) for each PCU, PPU and the entire PDA;
Multiple objectives and criteria can be formulated for

  • specific resource use (absolute and as efficiency, in particular energy and water)
  • waste generation (including CO2e and GHG)

Considering global (PDA) as well as individual (PCO) economic and resource performance, the system can be used to design COLLABORATIVE (non-zero sum game) strategies for the use of shared resources (water, energy (gas, electricity), waste treatment capacity)

(Cooperative) gaming scenarios:
other than in (global) optimization mode, the system can also be run in a (cooperative) gaming mode, where individual PCO operators as players set the prices for product, competing (or forming coalitions) with all other players for

  • inputs (they may have to be bid for if limiting)
  • sales (depending on market demand and competitors prices and production volume)
while meeting the resource and environmental constraints. For the environmental constraints, the emissions generated by the PDA modeling can be further processed by fate and transport models to generate ambient concentration (versus environmental standards to determine compliance) and population exposure as additional, non-linear criteria in the multi-criteria optimization.

References

Fedra, K., Li, Z., Wang, Z. and Zhao, C. (1987)
Expert Systems for Integrated Development: A Case Study of Shanxi Province, The People's Republic of China. SR-87-001.
International Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria.
Fedra, K., Karhu, M., Rys, T., Skocz, M., Zebrowski, M. and Ziembla, W. (1987)
Model-based Decision Support for Industry-Environment Interactions. A Pesticide Industry Example. WP-87-97.
International Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria.
Grauer, M. and Fedra, K. (1987)
Intelligent Decision Support for Technology Assessment: The Chemical Process Industry. In: Lecture Notes in Economics and Mathematical Systems.
Vol. 286: Toward Interactive and Intelligent Decision Support Systems, Volume 2. [Eds.] Y. Sawaragi, K. Inoue and H. Nakayama.
Proceedings of the Seventh International Conference on Multiple Criteria Decision Making. 18-22 August, 1986, Kyoto, Japan. Springer Verlag. pp.40-55.
Fedra, K. (1985)
Advanced Computer Applications for Large-scale Systems Analysis. In: Fandel, G., M. Grauer., A. Kurzhanski, and A.P. Wierzbicki [eds.]
Large-Scale Modelling and Interactive Decision Analysis. Proceedings of a Workshop held at Eisenach, GDR, 18-21 November 1985. Springer-Verlag. 363p.

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