GASDECSYS: A Decision Support System for Gas Distribution Networks
GASDECSYS simulates flows and pressures in a gas distribution networks; it computes least cost reinforcements to meet increasing demands; and it proposes supply policies to minimize purchase costs.
The modeling of the design and operations of gas distribution networks raise many technical difficulties due to the non-linearity of the physical transmission laws. Thanks to a new and innovative approach, GASDECSYS can handle large scale real-life problems online, which makes it a versatile tool to explore on-line a variety of situations. The prototype version proposed here is based on the open-source solvers of the cvxopt library. For increased stability and the handling of very large scale instances, the fully fledged version will use an in-house solver.
» To learn more about GASDECSYS, explore the prototype version »
GASDECSYS can be tailored to your needs. Please contact us.
To experiment with GASDECSYS, the present web interface proposes a demonstration on illustrative examples, with the flexibility of changing components of the networks. The tool, based on the prototype version, is made of three interactive modules
- The Simulator module provides target values for the pressures at the inlets and outlets of the network, as well as compressors and regulators operating ratios, to meet supply and demand requirements.
- The Reinforcement module proposes investments in pipe reinforcement when the existing network cannot meet the supply and demand projections.
- The Supply Management module suggests efficient purchase and selling strategies that are compatible with the existing network.
GASDECSYS computes flows and pressures according to the nonlinear law of stationary flows of compressible fluids.
If you wish to know more about
- Specifics of the demo version
- The Simulator module
- The Reinforcement module
- The Supply Management module
- The fully fledged version
- GASDECSYS is based on the scientific contribution .
- GASDECSYS computes the stationary flows and the related pressures in a pipe of length L and inner diameter D according to Weymouth law , or more accurately to its approximation
The compressors are characterized by their compression ratio, which is the ratio between the discharge pressure and the suction pressure.
- The purchase and selling costs are inspired from .
- The investment cost function is of the form
- The network examples are inspired from published data. The characteristics of the network (pipe lengths, compressors and regulators locations, bounds on the flows at the inlets and outlets, bounds on the pressures) come from the cited references. The coefficient β and the cost function C(D,L) are those described above. The “simple network” appears in  and studied in . The “Belgium network” appears in [5, 6]. The “larger network” appears in  and is inspired by a real network at Gaz de France.
- Limitations of the demo version:
- Maximum number of nodes: 30
- Maximum number of arcs (including compressors and regulators): 50
- Maximum pipe diameters: 1200 mm
- The demo version uses an open-source solver with a maximum number of iterations of 200.
Compressors and regulators in the network create options in the operating mode. Each one of them call for power supply to activate the compressors within the network and/or at the terminals. A commonly used expression [1, 2] for the power supply cost of a compressor is of the form
Compressors impose a flow orientation. However, depending on the actual supply and demand, it may be necessary to change this orientation. The demo version searches for the best orientation to meet the current supply and demand needs.
The reinforcement module proposes a network reinforcement to meet increased demands. It balances the investment cost (installation of new pipes) and the power supply cost required to enforce the necessary flows. While investment costs are unambiguously known, the power supply operations costs are much uncertain, due to the seasonal and stochastic variations of demands. We believe that expert judgment is required to compare several alternatives proposed by the module. To this end, the user can vary a parameter, named weight on the reinforcement cost, to control the intensity of the investment. For each investment proposal, the simulation module computes the full flow solution and compressor requirements.
The supply management module suggests efficient purchase and selling strategies that are compatible with the existing network. It balances the supply cost and the power supply cost required to enforce the necessary flows. To this end, the user can vary a parameter, named weight on supply cost, to control the intensity put on the supply cost.
Purchase and selling strategies cannot be elaborated without concern to the seasonal and trend variations of the demand; storage facilities allow smoothing but call for a dynamic representation of the problem. The demo version does not take into account the time structure of the problem, but it is an essential building block in the tool for the design of a purchase policy.YS and developments in progress:
- General design module (e.g. design from scratch).
- Installed diameters restricted to commercial sizes.
- Incorporate power supply costs such as those in [1, 2].
- Incorporate seasonal effects to plan a dynamic supply/delivery strategy.
- Replacement of the open source solver by a dedicated in-house one.
 J. André and J. Bonnans. Optimal features of gas transmission networks. In J. Herskovits, editor, Proc. Eng. Opt. 2008. International Conference on Engineering Optimization, Rio de Janeiro, June 1-5, 2008, 2008.