Natural gas transmission and distribution model of the National Energy Modeling System

The present paper presents the development effort and pre-commercial deployment of Explorer II — a semi-autonomous, self-powered, tetherless robotic platform, carrying a Remote Field Eddy Current (RFEC) sensor, for the inspection of unpiggable natural gas transmission and distribution pipelines in the 6 to 8 inch (152 to 203 mm) range, including those that feature multiple diameters, short radius and mitered bends, and tees. The system is based on a modular design that allows the system to be deployed in various configurations to carry out visual inspection and/or non-destructive evaluation (NDE) of a pipeline. The heart of this system is a RFEC sensor able to measure the pipeline’s wall thickness. In addition, two fisheye cameras at each end of the robot provide high quality visual inspection capabilities for locating joints, tee-offs, and other pipeline features. The system can operate, including launching and retrieval, in live pipelines with pressures up to 750 psig (50 bars). The system is currently being offered for pre-commercial deployments and is expected to be commercially available in the Fall of 2010.

Problems and Prospects of Natural Gas Transmission and Distribution in Nigeria

10.2118/17732-ms ◽

1988 ◽

Author(s):

G.J.I. Igwe ◽

E.N. Wami ◽

J.M. Ewili

Keyword(s):

Natural Gas ◽

Natural Gas Transmission ◽

Transmission And Distribution

Economic Considerations Concerning the Use of Salt Caverns for Natural Gas Storage by an Integrated Natural Gas Transmission and Distribution System

Journal of Canadian Petroleum Technology ◽

10.2118/66-01-06 ◽

1966 ◽

Vol 5 (01) ◽

pp. 29-34

Author(s):

W.B. Clipsham ◽

D.G. Olafson ◽

B.G. Pratt ◽

B.A. Steuart

Keyword(s):

Natural Gas ◽

Distribution System ◽

Gas Storage ◽

Natural Gas Storage ◽

Natural Gas Transmission ◽

Salt Caverns ◽

Transmission And Distribution ◽

Economic Considerations

Investigation of Southern California Natural Gas Infrastructure to Transport and Store Hydrogen to Meet Electric Demand Based on a 100% Renewable Energy Portfolio

ASME 2020 Power Conference ◽

10.1115/power2020-16044 ◽

2020 ◽

Author(s):

Zahra Heydarzadeh ◽

Jack Brouwer

Keyword(s):

Renewable Energy ◽

Natural Gas ◽

Southern California ◽

Electricity Demand ◽

Hydrogen Gas ◽

Underground Storage ◽

Gas System ◽

Natural Gas Transmission ◽

Transmission And Distribution ◽

Transmission Pipelines

Abstract In this research, we utilize Southern California (SoCal) natural gas transmission pipelines and underground storage resources for transporting and storing hydrogen gas for a 100% renewable energy penetration. The goal is to determine to what extent natural gas infrastructure can be used to deliver and store hydrogen to meet SoCal electric demand for a 100% renewable energy portfolio. Hydrogen is produced from solar power generation using electrolysis next to the gas transmission pipelines whenever it is available in quantities greater than the electricity demand. It was found that using four main transmission pipelines owned by Southern California Gas company (SoCalGas) to transport hydrogen from the point of production to the four underground storage fields to store and later generate electricity through fuel cells can transport and store hydrogen sufficient to meet 40% of the SoCal electricity demand. That is, without any investment in additional transmission and distribution infrastructure, and without any investment in energy storage, the idea of building solar farms in the desert and using only the gas system for storage and transmission and distribution leads to a 40% increase in renewable electricity for the state.

Fault Diagnosis System Based on Dynamic Bayesian Network

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.55-57.1824 ◽

2011 ◽

Vol 55-57 ◽

pp. 1824-1829

Author(s):

Hong Bo Wang ◽

Zhong Gui Ma ◽

Xu Yan Tu

Keyword(s):

Fault Diagnosis ◽

Natural Gas ◽

Bayesian Network ◽

Distribution Network ◽

Dynamic Bayesian Network ◽

Start Time ◽

Inference System ◽

Basic Model ◽

Natural Gas Transmission ◽

Transmission And Distribution

The paper focus on dynamic bayesian network (DBN) inference system and its application on the natural gas transmission and distribution network for the system fault diagnosis which is including time restriction (that is the earliest start time and the latest end time) for task. DBN is a graphic model which can describe the relationships between variable data, and used for reasoning. After we research the basic model of DBN, and the maximum depend algorithm is improved which which can increase the feasibility of natural gas transmission and distribution network system. we can see the new model is more accuracy than the traditional technical fault diagnosis clearly. Also, simulation result can verify the design of DBN is effectively and valuable.