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Ability of Black-Box Optimisation to Efficiently Perform Simulation Studies in Power Engineering
(2023)
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.
The shift towards RES introduces challenges related to power system stability due to the characteristics of inverter-based resources (IBRs) and the intermittent nature of renewable resources. This paper addresses these challenges by conducting comprehensive time and frequency simulations on the IEEE two-area benchmark power system with detailed type 4 wind turbine generators (WTGs), including turbines, generators, converters, filters, and controllers. The simulations analyse small-signal and transient stability, considering variations in active and reactive power, short-circuit events, and wind variations. Metrics such as rate of change of frequency (RoCoF), frequency nadir, percentage of frequency variation, and probability density function (PDF) are used to evaluate the system performance. The findings emphasise the importance of including detailed models of RES in stability analyses and demonstrate the impact of RES penetration on power system dynamics. This study contributes to a deeper understanding of RES integration challenges and provides insights for ensuring the reliable and secure operation of power systems in the presence of high levels of RES penetration.
This paper presents the implementation of a GMVC-based WAPSS to damp the interarea modes of power systems. The choise for the GMVC to tackle this problem lies on the fact that it can be used to compensate the time delay due to the latency of the transmission system in a more natural way than other controllers. The paper shows that it is possible to improve system’s closed-loop stability since its behavior is the same as if the time delay is not regarded. Simulation results with Kundur’s System prove that a latency of 1 second at a conventional WAPSS might lead system’s power to oscillate for 50 seconds for a short-circuit at the transmission line, whereas the oscillation decreases to only 5 seconds if the GMVC-based WAPSS is implemented.