FPSO electrical network optimization for significant savings: where lies the cost?

Vollet, C.; Angays, Philippe; Oliveira, Avelino De; Grandperrin, Philippe

doi:10.23919/pciceurope.2017.8015068

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…In Brazil, especially for pre-salt fields, FPSO are currently the most deployed production facilities [4]. In general, these platforms' power systems are insulated and use gas turbine driven generators [5]. Hence, given its size and the significant amount of electrical load, the power generation system is one of the core for maintaining the operation and production of FPSO.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Inference System Development for Turbogenerator Failure Diagnosis on Floating Production Offloading and Storage Platform

Castro,

Lira,

Vilar

et al. 2024

Energies

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This paper introduces a novel approach for diagnosing failures within a turbogenerator mineral lube oil system, employing a fuzzy inference system (FIS) model. The study leverages real operational data collected from supervisory monitoring sensors across four turbogenerators over a three-year operational span, resulting in a dataset comprising 40,456,663 input parameters. The failure modes were established through expert knowledge, using the Failure Mode, Effect, and Criticality Analysis (FMECA) documentation as the basis. Initially, the model’s universe variables were constructed using the sensor calibration range, and then the fuzzy membership functions were formulated based on the operational thresholds inherent to each measured parameter. The fault identification mechanism is underpinned by an inference system employing predefined rules, extrapolated from expert judgments encapsulating failure typologies specific to the turbogenerators’ mineral lube oil system, as delineated in the FMECA. The FIS model demonstrates notable efficacy in failure diagnosis with an overall performance evaluation of the system yielding satisfactory outcomes, having a 98.35% true positive rate for failure classification, coupled with a 99.99% true negative rate for accurate classification during normal system operation. These results highlight the visibility of the FIS model in diagnosing failures within the turbogenerator mineral lube oil system, thereby showcasing its potential for enhancing operational reliability and maintenance efficiency.

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Section: Introductionmentioning

confidence: 99%

Fuzzy Inference System Development for Turbogenerator Failure Diagnosis on Floating Production Offloading and Storage Platform

Castro,

Lira,

Vilar

et al. 2024

Energies

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show abstract

“…In Brazil, especially for pre-salt fields, production platforms FPSO are currently the most deployed production facilities. In general, these platforms' power systems are insulated from other power systems and use gas turbine-driven generators [5]. In this context, the generation system is a core for those types of platforms given its size and the amount of load that is electrically driven.…”

Section: Introductionmentioning

confidence: 99%

“…However, studies on offshore platform power system reliability are relatively scarce [8]. Cost reductions of an FPSO electrical installation at the project phase, where some changes in a typical configuration of the electrical network architecture for an FPSO was proposed, are detailed in [5]. Those changes had an impact on the power system reliability and different operational conditions were evaluated in terms of unavailability.…”

Section: Introductionmentioning

confidence: 99%

Application of Generation Adequacy Analysis for Reliability Evaluation of a Floating Production Storage and Offloading Platform Power System

2022

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This paper proposes the application of generation adequacy analysis for reliability evaluation of an insulated power generation system that supplies a FPSO (Floating Production Storage and Offloading) oil and gas production platform. The frequency and duration method was adopted for generating system reliability evaluation. The historical reliability data of the floating production storage and offloading platform power system and the continuous Markov process are used to determine the generator’s reliability model. The load model was also based on the platform daily peak load variation curve. The system risk indexes were obtained using Monte Carlo simulation. Two system scenarios were simulated using different failure data for one of the generators and the software PowerFactory© has been used as a tool for this simulation. For a complete generation system modeling, frequency and duration methods were developed to calculate the probabilities, frequencies and duration of the system states. Numerical results are presented and discussed to demonstrate the applicability of the proposed method.

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Mv Motors Starting With Auto-Transformer

Penkov

Gaudeaux

2018

2018 Petroleum and Chemical Industry Conference Europe (PCIC Europe)

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FPSO electrical network optimization for significant savings: where lies the cost?

Cited by 3 publications

References 2 publications

Fuzzy Inference System Development for Turbogenerator Failure Diagnosis on Floating Production Offloading and Storage Platform

Fuzzy Inference System Development for Turbogenerator Failure Diagnosis on Floating Production Offloading and Storage Platform

Application of Generation Adequacy Analysis for Reliability Evaluation of a Floating Production Storage and Offloading Platform Power System

Mv Motors Starting With Auto-Transformer

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