Optimal Design Of Underground Gas Storage
Author(s)
S. Kravanja & B. Žlender
Abstract
This paper presents the cost optimization of an underground gas storage (UGS),
designed from lined rock caverns (LRCs). The optimization is performed by the
non-linear programming (NLP) approach. For this purpose, the NLP
optimization model OPTUGS was developed. The model comprises the cost
objective function, which is subjected to geomechanical and design constraints.
It is proposed that the geotechnical problem will be solved simultaneously. In
such a way, the optimization enables not only that the solution is optimal, but
also that the rock mass achieves enough strength, stability and safety. It is
proposed that the optimization will be performed for the phase of the conceptual
design. The numerical example at the end of the paper demonstrates the
efficiency of the introduced optimization approach.
Keywords: underground gas storage, UGS, lined rock cavern, LRC,
optimization, non-linear programming, NLP.
1 Introduction
The paper deals with the optimization of the investment and operational costs of
an underground gas storage (UGS), designed from lined rock caverns (LRCs)
[1-3]. The optimization is performed by the non-linear programming (NLP)
approach. For this purpose, the NLP optimization model is developed. Since the
optimization is proposed to be performed for the phase of the conceptual design,
only some basic conditions are defined in the optimization model in order to
assure enough strength safety of the rock mass and impermeability of the cavern
wall and steel lining. The latter is achieved by the limitation of steel lining and
concrete wall stains.
The considered UGS is performed by the construction of one or more LRCs.
The structure of the LRC is simple: its reservoir wall is designed from a concrete
wall and a steel lining. Although the concrete wall is reinforced, it just transports
Keywords
underground gas storage, UGS, lined rock cavern, LRC,
optimization, non-linear programming, NLP
Related Book
Other papers in this volume
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