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Ability of black-box optimisation to efficiently perform simulation studies in power engineering

Petersson Lukas, Kutzner Rüdiger, Schäfer Marc, Hofmann Lutz

Acta Mechanica et Automatica

2023

Vol. 17, no. 2

292--302

In this study, the potential of the so-called black-box optimisation (BBO) to increase the efficiency of simulation studies in power engineering is evaluated. Three algorithms (“Multilevel Coordinate Search” (MCS) and “Stable Noisy Optimization by Branch and Fit” (SNOBFIT) by Huyer and Neumaier and “blackbox: A Procedure for Parallel Optimization of Expensive Black-box Functions” (blackbox) by Knysh and Korkolis) are implemented in MATLAB and compared for solving two use cases: the analysis of the maximum rotational speed of a gas turbine after a load rejection and the identification of transfer function parameters by measurements. The first use case has a high computational cost, whereas the second use case is computationally cheap. For each run of the algorithms, the accuracy of the found solution and the number of simulations or function evaluations needed to determine the optimum and the overall runtime are used to identify the potential of the algorithms in comparison to currently used methods. All methods provide solutions for potential optima that are at least 99.8% accurate compared to the reference methods. The number of evaluations of the objective functions differs significantly but cannot be directly compared as only the SNOBFIT algorithm does stop when the found solution does not improve further, whereas the other algorithms use a predefined number of function evaluations. Therefore, SNOBFIT has the shortest runtime for both examples. For computationally expensive simulations, it is shown that parallelisation of the function evaluations (SNOBFIT and blackbox) and quantisation of the input variables (SNOBFIT) are essential for the algorithmic performance. For the gas turbine overspeed analysis, only SNOBFIT can compete with the reference procedure concerning the runtime. Further studies will have to investigate whether the quantisation of input variables can be applied to other algorithms and whether the BBO algorithms can outperform the reference methods for problems with a higher dimensionality.

Pilot Study on the Application of Employee Scheduling for the Problem of Safety Instrumented System Design and Maintenance Planning for Remotely Located Oil and Gas Facilities

Redutskiy Y.

Engineering Management in Production and Services

2018

Vol. 10, no. 4

55--64

The technology of production, transportation, and processing of oil and gas involves various hazardous processes. To mitigate the risk that these processes pose, the technological solutions work closely with the automated control and safety systems. The design and organisation of maintenance for the automated safety instrumented systems (SIS) have a significant bearing on the overall safety of operations in this industry. Over the past few decades, many hydrocarbon resources have been discovered in unconventional environments, such as remote, offshore, and arctic locations. Transportation of engineering personnel to these remote locations and back, and thereby, the organisation of the shift work poses additional challenges for the petroleum sector. Under such circumstances, the workforce-related costs play a considerable role in the overall cost of the technological solution and thereby the decisions regarding the workforce organisation should be addressed in the framework of evaluating and choosing the appropriate safety measures. That is why the research presented in this paper aims to address the lifecycle of the technological solution integrating the problems of SIS design, maintenance planning, and employee scheduling into a single decision-making framework to optimise the set of technical and organisational safety measures inherent in the SIS. The performance and maintenance of the SIS are described with a Markov model of device failures, repairs and technological incidents occurrence. The employee scheduling part of the mathematical model utilises the set-covering formulation of maintenance crews taking particular trips. A black-box optimisation algorithm is used to find reasonable solutions to the integrated problem of engineering design and workforce planning. The decisions include the choices of the components and structures for the safety system, the facility overhaul frequencies, the maintenance personnel size, as well as the schedules of trips and shifts for the crews.