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Measurements from the on-board systems of marine vessels are increasingly available for data analysis and are growing in importance as the ship industry enters a phase of digitalization. The purposes of the data analysis from vessels in operation include the verification of the power system design in general and improvement of the electrical power load analysis in particular. In this paper, we show how to extract valuable information from the data-driven operational profile analysis, which reveals the real power demand, and how the vessel was operated. Using the real power range analysis, we emphasize the significance of rarely occurring high power demands, which are critical for power system design and optimization. We propose a methodology for the quantification of variability in the generated power, which explains the tails of probability distributions of a power signal based on signal decomposition. The proposed methodology makes use of the data and it can facilitate the selection of the optimal size, number, and configuration of generators or batteries when designing new power systems. Measurements from a data collection system are used to demonstrate the methodology for dynamic positioning mode of the operation of a platform supply vessel. [ABSTRACT FROM AUTHOR]

This paper describes the use of large electric grids in university electric power system courses. Since much actual power system information is not publicly available, the application of public domain synthetic grids developed by the authors is presented including a 2000-bus grid. Discussion of the educational applications utilized in a senior level class are given for power flow analysis and sensitivity, economic dispatch, contingency analysis, optimal power flow (OPF), security-constrained OPF, transient stability, and real-time dynamic operations. In each of these, the application of the large synthetic grids give students insights and experience with cases closer to actual power systems in complexity and size. [ABSTRACT FROM AUTHOR]

The paper proposes a new adaptive approach to power system model reduction for fast and accurate time-domain simulation. This new approach is a compromise between linear model reduction for faster simulation and nonlinear model reduction for better accuracy. During the simulation period, the approach adaptively switches among detailed and linearly or nonlinearly reduced models based on variations of the system state: it employs unreduced models for the fault-on period, uses weighted column norms of the admittance matrix to decide which functions to be linearized in power system differential-algebraic equations for large changes of the state, and adopts a linearly reduced model for small changes of the state. Two versions of the adaptive model reduction approach are introduced. The first version uses traditional power system partitioning where the model reduction is applied to a defined large external area in a power system and the other area defined as the study area keeps full detailed models. The second version applies the adaptive model reduction to the whole system. The paper also conducts comprehensive case studies comparing simulation results using the proposed adaptively reduced models with the linearly reduced model and coherency-based reduced model on the Northeast Power Coordinating Council 140-bus 48-machine system. [ABSTRACT FROM AUTHOR]

The system frequency response (SFR) model describes the average network frequency response after a disturbance and has been applied to a wide variety of dynamic studies. However, the traditional literature does not provide a generic, analytical method for obtaining the SFR model parameters when the system contains multiple generators; instead, a numerical simulation-based approach or the operators’ experience is the common practice to obtain an aggregated model. In this paper, an analytical method is proposed for aggregating the multi-machine SFR model into a single-machine model. The verification study indicates that the proposed aggregated SFR model can accurately represent the multi-machine SFR model. Furthermore, the detailed system simulation illustrates that the SFR model can also accurately represent the average frequency response of large systems for power system dynamic studies. Finally, three applications of the proposed method are explored, with system frequency control, frequency stability, and dynamic model reduction. The results show the method is promising with broad potential applications. [ABSTRACT FROM AUTHOR]

Rooftop photovoltaic (PV) hosting capacity has become a concern for utilities in scenarios of high penetration due to impacts on voltage quality, such as over/undervoltage and voltage unbalance, and on equipment loading (conductors and transformers). This paper uses a simplified Monte Carlo-based method to analyze this issue, which is applied to 50 000 real low-voltage (LV) systems. Results show that it is possible to perform a risk-based analysis of hosting capacity by means of a lognormal distribution. Furthermore, overvoltage is found to be the most restrictive impact of PV integration; such information can help to guide utility actions to avoid technical violations. Extensive sensitivity studies are also presented to quantify the effects of several factors on the PV hosting capacity. The effects of number of customers with PV generators, PV power factor, voltage magnitude on the medium-voltage system, load level, and conductor impedances are investigated. It is also shown that the hosting capacity for the entire utility can be estimated by performing simulations only on 1% of the circuits randomly selected. In addition to providing a comprehensive overview of PV hosting capacity in real systems, the method can be used by utilities to improve the management of LV systems with high PV penetration. [ABSTRACT FROM PUBLISHER]

POWER plants are subject to introduce disturbances in the power grid, resulting from interactions with the dynamical behavior of the energy source subsystem. In the case of hydropower plants when used to compensate for variations of power generation and consumption, instabilities or undesirable disturbances may arise. They may be caused by phenomena such as part load vortex rope pulsations in the draft tube of Francis turbines. This may affect the dynamical behavior of the power plant and lead to troublesome interactions with the grid. This paper presents a case study of an existing hydropower plant that illustrates the effects of pressure pulsations due to vortex rope precession on the draft tube of Francis turbines. It also showcases possible solutions to the mitigation of the effects of this disturbing hydraulic phenomenon over the operation of the generators and electrical system. The investigated system is a 1-GW hydropower plant (4 × 250 MW units). The assessment of the power swings is performed through modal analysis combined with frequency-domain and time-domain simulations, which are then compared with onsite measurements. [ABSTRACT FROM AUTHOR]

This paper presents a new approach in adaptive out-of-step (OOS) protection settings in power systems in real time. The proposed method uses extended equal area criterion (EEAC) to determine the critical clearing time and critical clearing angle of the system, which are vital information for the OOS protection setting calculation. The dynamic model parameters and the coherency groups of the system for EEAC analysis are determined in real time to ensure that the newly calculated settings suit with the prevalent system operating condition. The effectiveness of the method is demonstrated in simulated data from a 16-machine 68-bus system model. [ABSTRACT FROM PUBLISHER]