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

Castro, Patrício Fernandes de; Rodríguez, Yuri Percy Molina; Carvalho, Fabrício Braga Soares de

doi:10.3390/en15155336

Cited by 3 publications

(3 citation statements)

References 25 publications

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“…Among these parameters of interest are the loss of load probability (LOLP) and the estimation of demand not supplied (EDNS). To carry out this type of analysis, it is vital that all generators present in our system have a stochastic model assigned that models the probability of these generators having to generate power at different operating points [30].…”

Section: Stochastic Analysismentioning

confidence: 99%

Combined Use of Python and DIgSILENT PowerFactory to Analyse Power Systems with Large Amounts of Variable Renewable Generation

Jiménez-Ruiz,

Honrubia-Escribano,

Gómez-Lázaro

2024

Electronics

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Over the last decade considerable efforts have been made to reduce greenhouse gas emissions, leading to the significant development and implementation of renewable energy plants across all power systems in the world. Wind energy has consolidated its position as one of the two key energy sources (in conjunction with solar photovoltaics) to achieve completely green power systems. Integrating wind energy into power systems is a more complicated task compared to traditional generation systems, as wind energy relies on a variable energy source characterised by high variability. Several tools currently exist to simulate the effect of wind energy generation in power systems, but they often lack the versatility demanded by researchers. This paper analyses how both Python 3.11 and DIgSILENT PowerFactory 2024 can be used synergistically to assess the implementation of wind power plants, highlighting how the use of these two tools combined can be of great interest for both researchers and grid operators.

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Section: Stochastic Analysismentioning

confidence: 99%

Combined Use of Python and DIgSILENT PowerFactory to Analyse Power Systems with Large Amounts of Variable Renewable Generation

Jiménez-Ruiz,

Honrubia-Escribano,

Gómez-Lázaro

2024

Electronics

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“…The capability of the RE system to transition into 100% and to sustainably deliver the energy system demand under various conditions and scenarios can be determined with the use of generation adequacy analysis [156][157][158][159][160][161], employing different deterministic and probabilistic techniques such as probability density function; convolution functions; correlation/regression; Markov process; frequency and duration; radial, parallel, and meshed network; point estimate; Monte Carlo; and artificial neural network techniques [162][163][164], which support the reliability evaluation of RE generation technology integrated into the national grid.…”

Section: General Adequacy Analysismentioning

confidence: 99%

Towards a Common Methodology and Modelling Tool for 100% Renewable Energy Analysis: A Review

Akpan,

Olanrewaju

2023

Energies

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Some advanced countries’ rapid population, economic growth, and energy consumption expansion contribute significantly to global CO2 emissions. And while developed countries have achieved 100% universal access to electricity, mainly from non-renewable sources, many developing countries still lack it. This presents challenges and opportunities for achieving the United Nations’ Sustainable Development Goals (SDGs) 7 and 13 of generating all energy from cleaner or low-carbon sources to reduce CO2 emissions in all countries and combating climate change consequences. Renewable energies have been widely acknowledged to greatly advance this endeavour, resulting in many studies and about 30 countries already with over 70% of their national electricity mix from RE. It has birthed a new paradigm and an emerging field of 100% RE for all purposes, recently receiving much attention from academia and in public discourse. The major challenge with this idea is that achieving such a feat requires a more diverse approach. This study emphasises the need to meet technical and non-technical requirements for working towards a 100% RE for all purposes. Therefore, our work introduces six methodological or evaluation mechanisms (herein, identified as 100% RE evaluation metrics) suitable for existing and future 100% renewable energy analysis. It then reviews energy modelling tools to identify their applicability to 100% RE analysis. The review and perspectives presented in this study will be valuable in developing a common integrated methodology and modelling tool for analysing full renewable energy adoption in countries or regions with best trade-offs, using performance indices that have not been previously used. It will also help with proper national and regional energy resources and system planning for new energy projects and installations, contributing to sustainable development.

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“…These equipment compose the main generation system of a FPSO platform which operates on island, with no connection to another power system. The platform's power system is composed of four main turbogenerators driven by a heavy-duty gas turbine, and each generator has a nominal power of 25 MW at 13.8 kV [26].…”

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

Cited by 3 publications

References 25 publications

Combined Use of Python and DIgSILENT PowerFactory to Analyse Power Systems with Large Amounts of Variable Renewable Generation

Combined Use of Python and DIgSILENT PowerFactory to Analyse Power Systems with Large Amounts of Variable Renewable Generation

Towards a Common Methodology and Modelling Tool for 100% Renewable Energy Analysis: A Review

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

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