PSIG Annual Meeting

ABSTRACT

Assessing the discharged volume during third party digging damages with efficiency and acceptable accuracy is a challenge for multiple reasons. It involves complex physics phenomena, requires taking the right assumptions and has to be perform relatively quickly as the number of cases to compute each year is important. This paper summarizes the application of a comprehensive methodology used to perform this task.

The first part deals with the required field measurements needed to be obtained, the selection of an adequate physics equation as a function of the flow regime and the linkage between an analytical equation and a commercial CFD software to obtain a valid network pressure at the damage point.

In the second section, a validation attempt between computed results and field measurements is made using two different sets of data. First, for some very specific incidents where the pipeline damage is close to a gate station with SCADA recording, it is possible to obtain an hourly flow profile at the break. Second, simple configurations of pipe rupture have been replicated in laboratory and tested with air. For most of the cases, the described methodology shows a good match with experimental data with typical discharge coefficient values in the range of 0.61 to 0.92.

INTRODUCTION AND BACKGROUND

Gaz Metro « GM » is the main natural gas distributor in the province of Quebec on the east part of Canada. The territory is connected to the TCPL Mainline (figure 1) at the very end of the transmission system.

GM distributes 97% of all natural gas in Quebec (figure 2) to over 200 000 customers located in more than 300 municipalities [1]. This can be achieved by an asset of 10 000 km of underground network pipeline with more than 90% being distribution mains and services, mostly small diameter plastic pipes. Along this distribution network, digging damages by third party represent by far the primary reason for unplanned emergency response and an important part of the total non-fugitive annual gas loss. Each year, 300 to 400 rupture cases are reported and analyzed.

ABSTRACT

This paper will focus on the utilization of advanced pipeline simulation software to proactively identify and rank distribution regulator stations based on their criticality to meet customer demand in an interconnected distribution system. A particularly complex distribution network modeled as a single system containing multiple subsystems operating at various pressure levels is analyzed over a large number of scenarios using PG&E’s Batch Analysis Tool (BAT).

BAT has the capability to run numerous simulations in a time efficient manner to discover critical regulator stations within an interconnected distribution system in one hydraulic model. A fundamental issue with performing regulator station failure analysis is shutting in regulator stations can cause the system to “crash,” that is, the model will not balance. If the model does not balance, it is not necessarily clear which portion of the system is affected based off of the software’s error log. For example, if a model doesn’t balance when an upstream regulator station is shut in, it may be difficult to conclude whether the upstream or the downstream subsystem is creating the hydraulic problem from the closure. With the help of BAT, system performance can be observed as temperatures decrease (demand increases) and the point at which the system crashes can be recorded. Furthermore, BAT can track the pressure at multiple locations to check at what point a certain area crashes.

BACKGROUND

Proactive gas system planning is to understand operating risks before they occur on the system. It is a goal of PG&E’s Gas System Planning department to utilize hydraulic simulation to gain broad system intelligence over a range of conditions and to identify facilities that are the most critical to system operations.

Hydraulic simulation requires the usage/input of Heating Degree Day (HDD), Peak Hour Hactor (PHF) and a demands file containing customer usage loads. PG&E designs its gas hydraulic system to Abnormal Peak Day (APD) conditions, which is an extremely cold day that has been recorded once in a 90 year time frame. From a previous PG&E paper presented on the BAT, it was shown that BAT can automate the entire loading process of an individual simulation. This paper will look at the impact of BAT on critical distribution regulator stations.

ABSTRACT

With the pipeline industry’s increased focus on pipeline safety and integrity, more frequent and complex pipeline outages are required to perform this safety work. How can dead-end, single feed natural gas systems be taken out of service to perform safety work while maintaining service to customers? It has become increasingly necessary to support customers using portable natural gas (PNG) in compressed (CNG) or liquefied (LNG) form. Pacific Gas & Electric Company (PG&E) has relied on PNG support during pipeline outages more frequently in recent years and recently undertook two separate projects that were unprecedented in scope and volume – in Santa Cruz and Redding, California.

PG&E’s Gas System Planning (GSP) department performed complex hydraulic analysis and operational support for the 2 major pipeline safety projects, each of which required more than 40,000+ customers to be supported solely with PNG for up to 4 weeks. In Redding, 130 tankers carried 110 mmscf of LNG to be injected into the pipeline, plus additional equipment provided 13 mmscf of CNG. Personnel traveled over 135,000 miles to support the project. In Santa Cruz, 119 loads of LNG injected a volume of 81 mmscf with personnel traveling 83,300 miles over the course of the outage.

This paper presents the analysis and tools used to perform extensive and complex gas system planning analysis. In the initial phases of the project, GSP provided input on the project schedule, how to phase the work to minimize customer impacts and maintain system reliability, and what additional PNG equipment would be needed to support the entire project. As we moved into the project design phase, GSP calculated total daily volumes and peak hourly flow rates, as well as found hydraulically feasible injection site locations and pressures for each tap off of the pipeline. Finally, during the outages, GSP provided real-time flow monitoring and operational support for field personnel.

ABSTRACT

Knowledge of natural gas quality in the short-term future (24 h) is expected by many of end users. Also, European Union Law requires to provide such information by Transmission System Operators. In case of multiloop network which is supplied with many sources and different gas compositions, the dynamic network simulation combined with forecasting of behavior all sources and offtakes, is necessary.

The article describes model of full chain of calculation. At entries, there are: productions, storages and interconnectors with more less stable gas compositions and LNG Terminals where gas composition smoothly change in function of time or significantly due to filing in from next vessel. At exits forecasting of demand relates to nomination processes (industrial end users) or forecasting systems (city gates to household areas). Between them the multiloop transmission network is dynamically simulated with full quality tracking model.

The paper contains also our practice experience based on Polish transmission system which has many entries from production, interconnectors, storages, more than 900 exits and new LNG Terminal. The multiloop network has also several compression stations and reduction points. There is a possibility of determining the degree of gas mixing i.e. providing clients with such information with simulation software. Such analyses are executed on a regular basis. Calculations are performed in three minute cycles (reconstruction network state) and future calculation are performed with the 15-minute step. For future calculations city gate exit points demand is obtained from the forecasting system (short-term forecasts - 10 days) or nominations used in supply points or industrial exits. Such values are compared up – to – date with the values obtained from chromatographs located in the transmission system network – reference chromatographs.

Finally, the article presents the case study of stream mixing degree depending on gas composition from different gas sources, exit point demand and settings of the non-linear network elements. The analyses were performed for both static and dynamic scenarios where one of the parameters is a dynamic change of the quantity and quality supply from LNG Terminal to the network.

ABSTRACT

Model calibration is the act (some might say “art”) of adjusting model parameters in such a way that the model’s behavior matches as closely as possible the behavior of the real-world system that it represents. In order to successfully calibrate a hydraulic model, certain hydraulic conditions must be known in order to have a defined calibration solution. Pipes that run parallel to each other (i.e. from the same upstream location to the same downstream location in roughly the same right-of-way) can pose serious difficulties to this requirement, especially when no inline flow measurement on any of the parallel lines exist, as the lack of knowing the exact flow distribution between the parallel lines means that the calibration problem either has no finite solution, or the finite solution is exceedingly difficult to determine.

A potential solution to this problem involves utilizing multiple data sets. Each data set will have a particular range of possible solutions, and by comparing the solution ranges of multiple data sets, a single solution can easily be found. This paper will describe this method and provide examples with the intent of enabling the reader to apply the methodology to his or her own hydraulic calibration challenges.

INTRODUCTION AND BACKGROUND

Most engineers involved with hydraulic simulation are probably quite familiar (too familiar?) with the Darcy- Weisbach flow equation that describes head loss in terms of flow, pipe length, and pipe diameter. A form of the equation is shown below, as understanding the equation will be crucial to understanding the fundamental difficulty of calibrating parallel pipes.

ABSTRACT

Testing of pipeline leak detection systems can be challenging. It is also a critical activity which provides key information on the systems capability for communications to regulators and key stakeholders. The authors describe an API RP 1130 compliant test method that relies on the development of a limited number of realistic "leak signatures" that are superimposed on archived SCADA data in a way that preserves not only a faithful representation of the leak, but the real-world impacts of noise, calculation uncertainties, and measurement errors as well. In addition to maintaining high hydraulic fidelity, coverage and flexibility, this procedure is performed at low cost while potentially providing a greater degree of insight into the detailed performance of the leak detection system than can be achieved with other methods.

INTRODUCTION AND BACKGROUND

The Need for Testing of Pipeline Leak Detection Systems

A leak detection system (LDS) is a safety and integrity-critical component of an operating pipeline that is designed to help mitigate negative consequences following an unplanned commodity release. Its intended purpose is to reduce the potential negative impacts from a breach in pipeline hydraulic integrity (e.g., a leak with its resulting spill). Reducing these potential negative impacts is achieved by rapidly detecting the leak and determining its most probable location. Determination of these factors in as short as time frame as possible provides key information that is critical in terms of enabling the pipeline operator to respond faster, more effectively, and with greater precision. Note that the most commonly applied method for leak detection is via Computational Pipeline Monitoring (CPM) systems, which are the explicit focus of this document.

As part of the operator’s overall spill response plan the organization should be able to quantify the leak detection system’s predicted performance. This allows the operator to identify areas where further leak detection improvements are desirable and refine location specific response plans. It also provides a mechanism by which the LDS performance can be monitored and tracked over time.

Quantifying the leak detection performance requires testing. As stated in the American Petroleum Institute recommended practice 1130 (API 1130), “[t]he primary purpose of testing [quantifying] is to assure that the CPM system will alarm if a commodity release occurs.” Note that while API 1130 is specific to Computational Pipeline Monitoring leak detection systems, the quantification of system testing is applicable to all leak detection systems.

ABSTRACT

When designing a piping system, normally the inherent control valve characteristics, e.g. linear or equal percentage valve opening/closing curves, are considered. However, inherent valve curves only consider the control valve as a “bobble”. The characteristics of the valve will change once it is installed with piping connections, meters, equipment, or other valves and fittings. The additional friction loss introduced by piping connections or valve combinations is normally a function of the flow rate instead of staying as constant. This will change the overall opening and closing characteristics of the control valve. It is well known that surge pressure is directly related to valve characteristics. The combination of control valve with other components may create undesirable surge scenarios in operation which is commonly neglected in the design.

This paper examines how the connections of the control valve with other piping components can influence the installed valve characteristics and surge pressure level in valve closings. The focus is on two aspects: how other components such as an ESD valve immediately upstream or downstream can influence the surge behavior of the control valve closing; how the upstream or downstream control valve influences the surge behavior of the ESD or Mainline Block Valve closing. The paper will present how the installed valve characteristics are different from the inherent characteristics and how significant the increase in the pressure surge was developed.

The results and conclusions provided in this paper will serve as a general guideline for valve arrangement and piping design for reducing potential surge pressure in liquid systems.

INTRODUCTION AND BACKGROUND

In piping design the control valves present unique influence to system hydraulics resistance. It is well known that once installed in the piping system, the control valve characteristics (the relationship between valve flow coefficient and valve opening will change) (Sines, 2009, Headley 2003). A so called installed valve coefficient is introduced to describe this behavior. The valve coefficient is normally tested in the shop as a “bobble”.

ABSTRACT

The objective of this paper is to describe a method that simulates an energy recovery system (ERS), which exploits water hydraulic power to boost inlet flow pressure. The impact of pipeline pressure surge (water hammer) on water treatment units was investigated. Surge pressure and pressure rise rate were calculated.

A novel methodology has been developed in this paper to simulate an energy recovery system and estimate pressure rise rate. This method integrated an energy recovery system into an existing pipeline simulation model. The energy recovery system model was developed using basic hydraulic pump equations. Actual system efficiency was used. Both maximum surge pressure and pressure rise rate are calculated each model time step. This same method can be used for other energy recovery systems hydraulic analysis.

In this study, a high-pressure feed pump with a discharge pressure of 630 psig was analyzed. The model was used to calculate the maximum surge pressure downstream of the ERS.

In this analysis, downstream of the ERS there is an RO (reverse osmosis) filtration system. The maximum pressure and rate of change of pressure must be controlled so as not to damage the filter membranes.

Different surge scenarios were investigated. For the cases analyzed it was possible to keep the maximum surge pressure to 1117 psig that is below the maximum membrane design pressure. It was also possible to keep the maximum pressure rise rate for all cases simulated to below 5.2 psi/second. The membrane warranty for the cases analyzed limited the pressure rise rate to 10 psi/second and stipulated a maximum pressure or 1200 psig. The simulation results also provide design parameters for sizing surge relief devices and designing the required control system.

Traditional surge analysis tools can properly estimate surge pressure within the pipeline system. However, energy recovery system behavior in a surge scenario was not simulated previously. The provided method can simulate energy recovery systems, calculate maximum surge pressure and pressure rise rate. The method sheds light on simulating energy recovery system and can be adopted for different simulation tools.

ABSTRACT

The paper concerns the problem of optimal control of a natural gas transmission system consisting of a compressor station and adjacent pipeline sections. Natural gas is supplied with two types of compressors, namely gas turbine driven centrifugal compressors and motor-compressors. For a given simulation scenario, the suction pressure, suction temperature, discharge pressure, and total compressor station mass flow are predicted from the non-isothermal transient gas flow model. Next the nonlinear programming problem with continuous and, in case of motor-compressors, discrete variables is solved to evaluate the type and the number of simultaneously operating compressors, while determining such a distribution of the capacity that the total unit fuel consumption in each time interval is minimized subject to the constraints imposed. The paper presents an algorithm of automatic search for the optimal values of the operating parameters of the compressor station. The method presented has been verified experimentally on the telemetry data.

INTRODUCTION AND BACKGROUND

Natural gas is usually transported by pipeline networks which serve as the most cost effective transportation means. Transmission systems usually have a linear topology corresponding to a linear arrangement of compressor stations. The fuel consumption of compressors is responsible for a large fraction of the costs of gas network operation. Luongo et al. (1989) reported that AGA estimates the operating cost of running the compressor stations to vary between 25% and 50% of the total company's operating budget, therefore minimizing fuel usage is a major objective in the control of gas transmission costs.

This work is concerned with the optimization of a single compressor station operated under transient conditions. More specifically, we consider variable boundary conditions, i.e. unsteady inlet and outlet pressures together with a variable flowrate through the compressor, and search for the optimal values of the operating parameters that minimize the running costs of the compressor station.

ABSTRACT

New designs or modifications of existing pump or gathering facilities are required frequently in many industries due to new operating conditions, increase in product demand, pump-pipeline interaction issues, pulsations problems, Net Positive Suction Head (NPSH) requirements, and so forth. In many cases, harsh transient events are experienced due to the lack of proper design, change in operating conditions, or unexpected process conditions. Piping systems are frequently subject to transient events such as slugs, water hammer, and cavitation that can create high amplitude forces and pressure spikes. Liquid systems are more susceptible to damaging forces during transients than gas systems due to the high density and incompressibility of the operating fluid. These events often result in high impact forces and vibrations that sometimes cause failures. This paper presents a general approach for modeling critical transient events in liquid and multiphase piping systems. In addition, case studies will be presented to identify the critical areas of the modeling, show model-field data comparison, results interpretation, and present some possible mitigation actions.

INTRODUCTION AND BACKGROUND

Transient events can introduce large pressure forces and rapid fluid accelerations into large pipeline systems, small manifolds, or distribution systems. These disturbances may result in different types of failures in pump, pipes, and devices such as pipe rupture or components reduced life due to cycle fatigue. Many transient events can lead to column separation or water hammer, which can result in catastrophic pipeline failures. Thus, transient flow simulation has become an essential requirement for increasing reliability and ensuring the safe operation of different pipeline systems and processes. Liquid systems are sometimes difficult to analyze for transient events as these can be dependent on factors that are not always known or finalized in the design stage or change during the lifetime of the system. Dependent variables include the characteristics of the fluid, the piping geometry, pressure reducing valves, operating conditions and nature of the events, scenarios and flow rates. Various modeling tools exist to provide reliable predictions and cost-effective solutions for hydraulic transient events, vibration or pulsation problems, but often multiple types of analyses must be used in combination to evaluate the system as a whole or solve complex problems.

The traditional method of analyzing transient events in liquid systems is to only use commercially available software to predict the extreme pressure conditions; however, often these transient fluid models need to be combined with mechanical or thermal stress analyses; dynamic pressure versus time inputs, and sensitivity studies or field data evaluations to be effective in resolving problems and ensuring pipeline integrity.