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Optimal expansion of generating capacity in national electric power energy system

  • Environmental And Energy Systems
  • Conference paper
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Optimization Techniques Part 1

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 6))

Abstract

The present paper deals with a long-range expansion policy of generating capacity in national electric power energy system. In order to take into account the originally regional feature of environmental problems, the national system is divided into several regional subsystems throughout the paper, and the overall national decision on capacity expansion is investigated as a cooperation between national decision unit and regional decision units.

By the material balance approach, a capacity balance model is firstly developed to represent generating capacity balance in each time period. A power plant evaluation model is secondly developed, where an environmental impreference measure is introduced to provide an order in regional environmental preference to each power plant type. By interfacing the models under electric demand restrictions, a least cost capacity expansion model is clearly developed and grasped as a hierarchical multiobjective system in such a way that regional subsystems hold rights in capacity expansion planning to select power plant type from the point of view of environmental preference, while nationalsystem dominates regional selection through allocation of available energy resource to the subsystems. The parametric linear programming plays a fundamental role in this modelling.

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References

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J. Stoer

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© 1978 Springer-Verlag

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Ogino, K. (1978). Optimal expansion of generating capacity in national electric power energy system. In: Stoer, J. (eds) Optimization Techniques Part 1. Lecture Notes in Control and Information Sciences, vol 6. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0007266

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  • DOI: https://doi.org/10.1007/BFb0007266

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-08707-6

  • Online ISBN: 978-3-540-35891-6

  • eBook Packages: Springer Book Archive

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