Load forecasting has always been an important part in the planning and operation of electric utilities, i.e. both transmission and distribution companies. With technological advancement, change in economic condition and many other factors (to be discussed in this work), load forecasting is becoming more important. The forecast affects as well as gets affected because of the load impacting factors and actions taken in different time horizons. However, due to its stochastic and uncertainty characteristics, it has been one challenging problem for electrical utilities to accurately forecast future load demand. This study aims at reviewing the different load forecasting techniques developed for the mid‐ and long‐term horizons of electrical power systems. Since there has never been an explicit literature study of the various forecasting techniques for mid‐ and long‐term horizons, this study reviews techniques for each of the forecasting horizons, citing various methodologies developed so far supported by published literature. This study is concluded with discussion on future research directions.

Cascading effects in the power grid involve an uncontrolled, successive failure of elements. The root cause of such failures is the combined occurrence of multiple, statistically rare events that may result in a blackout. With increasing digitalisation, power systems are vulnerable to emergent cyber threats. Furthermore, such threats are not statistically limited and can simultaneously occur at multiple locations. In the absence of real-world attack information, however, it is imperative to investigate if and how cyber attacks can cause power system cascading failures. Hence, in this work we present a fundamental analysis of the connection between the cascading failure mechanism and cyber security. We hypothesise and demonstrate how cyber attacks on power grids may cause cascading failures and a blackout. To do so, we perform a systematic survey of major historic blackouts caused by physical disturbances, and examine the cascading failure mechanism. Subsequently, we identify critical cyber-physical factors that can activate and influence it. We then infer and discuss how cyber attack vectors can enable these factors to cause and accelerate cascading failures. A synthetic case-study and software-based simulation results prove our hypothesis. This analysis enables future research into cyber resilience of power grids.

This paper addresses the use of the continuous wavelet transform (CWT) in the study of power system low-frequency electromechanical oscillations (LFEOs). Based on a modified complex Morlet mother-wavelet function, an approach is proposed to exploit the relationship between system low-frequency oscillation features and the Morlet CWT of a system ringdown signal for detection of modal parameter changes as well as for modal frequency and damping computation. Also, several guidelines for selecting the center frequency and bandwidth parameters, the scaling factor and the translation factor, are proposed in order to provide reliable modal identification estimates. The efficiency of the proposed approach is confirmed by applying it to synthetic, simulated and measured signals.

This paper proposes a probabilistic small signal stability assessment (PSSSA) methodology based on the application of Monte Carlo approach for iterative evaluation, via modal analysis of small signal stability (SSS). Operation states represented by random values of generation and demand are analyzed. A probabilistic instability risk index based on cumulative probability distribution function of damping ratios of oscillatory modes is calculated, as well as a power system stabilizer (PSS) devices location index based on eigenvectors and participation factors, which are considered random variables. Moreover, the impact of long-distance power flows on oscillatory modes (OM) and how the damping of OM depends on the orientation and magnitude of power flows is investigated. Further, an additional index concerns qualitatively the determination of transfer capability as affected by small signal stability. PSSSA is tested on a reduced order model of New England-New York's interconnected system considering uncertainties around three different system conditions separately: highly loaded, fairly loaded, and lowly loaded. The results highlight the main advantages of PSSSA over deterministic SSS studies such as instability risk assessment, small signal stability enhancement through adequate PSS location, and the proposal of possible restrictions for transfer capability in order to avoid poorly damped oscillations in the face of the diversity in power system operation.

Hydrogen as an energy carrier holds promising potential for future power systems. An excess of electrical power from renewables can be stored as hydrogen, which can be used at a later moment by industries, households or the transportation system. The stability of the power system could also benefit from electrolysers as these have the potential to participate in frequency and voltage support. Although some electrical models of small electrolysers exist, practical models of large electrolysers have not been described in literature yet. In this publication, a generic electrolyser model is developed in RSCAD, to be used in real‐time simulations on the real‐time digital simulator. This model has been validated against field measurements of a 1 MW pilot electrolyser installed in the northern part of The Netherlands. To study the impact of electrolysers on power system stability, various simulations have been performed. These simulations show that electrolysers have a positive effect on frequency stability, as electrolysers are able to respond faster to frequency deviations than conventional generators.