ABSTRACT

If you want to know if your network can handle a predicted load, you can perform a steady state simulation. It is not necessary to be an operator to perform such a simulation. Current steady state simulation programs require that prior to a simulation, the user has to define all kinds of pressure and flow settings that may prove to be inconsistent after the simulation. Recognition of the steady state problem in the right way saves you a lot of trouble. The network simulation problem is actually a constrained optimization problem. There are nodal balance equations and pressure drop equations. constraints on flows, pressures and pressure differences a desire to use the least amount of fuel. In this paper an approach will be discussed that takes this three points into account. A demonstration will be given that shows the power of this approach.

1. Introduction

2. Natural framework

3. Pipe and Valve

4. Demand and Supply

5. Compressor and Reducer

6. Nodal issues

7. Gas Quality

8. Mathematical framework

9. Demo

10. Math in Gas. in Alexandria

1 INTRODUCTION

In the ninetieth of the last century Gasunie changed their way of planning. One used to make plans based on scenarios. However the choice of scenarios is always more or less arbitrarily. Therefore one started to plan based on reliability of the network. So given the reliability figures of the components, the reliability of the whole network had to be calculated. In order to do so thousands of simulations had to be performed where compressors and supplies acted in a degraded fashion. Because of the large amount of simulations, they had to be performed without human intervention. This is how this new approach is born. Gasunie has a very dense network of 6000 km (4000 mile) with an average diameter of 1 m (40 inch) on an area of 200 x 300 km2 (125 x 200 mile2) Moreover Gasunie accepts different qualities of gas which are brought to different markets via a more or less integrated network. In most networks in the world a station is a compressor station with one or more compressors in series or parallel. They form one functional compression group. In the Gasunie network a station consist of more functional groups. One of our biggest stations, named Ommen, consist of three functional compression groups and three mixing groups. It is a hell of a job to come up with consistent control modes with setpoints for all these functional groups prior to a simulation. This is why finding a solution within bounds is such a powerful concept in the Gasunie situation.

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