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This paper presents a novel protection strategy for assuring power-system frequency stability. After many years of use, the existing (static) under-frequency load-shedding concept has proven to be reliable and fast. However, it does not adapt well to volatile operating conditions, which might often lead to a system collapse. This developed into a major obstacle, since operational conditions of modern power systems are persistently subjected to fast and unpredictable changes. Therefore, there is a need to introduce a new capability in under-frequency load-shedding that would be able to fine-tune the mismatch in active power in any conditions. From the practical aspect, a systematic implementation of improvements should not threaten system stability. In terms of cost, a minimum intervention in the existing concept is desirable. This is why we developed an effective upgrade of the existing concept by introducing a specialized group of intelligent electronic devices supported by a principal component analysis technique. This group should be operated alongside the existing solution to monitor the actual frequency conditions and to take over power-balancing when fine-tuning is required. This supports the existing load-shedding and improves the process of frequency stabilization. [ABSTRACT FROM AUTHOR]

Underfrequency load shedding (UFLS) is one of the measures performed when an emergency situation occurs in the power system in order to prevent system collapse. Owing to its importance, a lot of effort is dedicated to research and development of the optimal UFLS. Therefore, several different approaches are available to improve the so‐called traditional UFLS schemes into more sophisticated adaptive schemes. On the other hand, the literature lacks a systematic analysis of traditional UFLS schemes, which still present the majority within all UFLS schemes actually used in real power systems. For that reason, the probabilistic power flow is used to quantify the level of performance of many different configurations of traditional UFLS schemes (varied both in the number of shedding steps as well as their size) in the whole variety of operating conditions. With the use of probability power flow the probability density function of active‐power imbalance is calculated. The obtained results enable to extract those configurations that yield the best results in most probable events and at the same time avoid giving too much attention on poor performance during less probable system conditions. The results were obtained by performing dynamic simulations on the north‐western part of a Slovenian power system. [ABSTRACT FROM AUTHOR]

Abstract: The research and development of underfrequency load-shedding protection tends to rely on an adaptive approach. Unfortunately, adaptive schemes are very dependent on an active power imbalance determination, based on a measurement of the frequency first derivative. Therefore, their effectiveness might be seriously reduced by a lack of data or the wrong estimation of certain parameters that are needed to accurately define the relation between the frequency first derivative and the active power imbalance. Consequently, it is reasonable to attempt to avoid having to calculate the imbalance. A novel approach to underfrequency load shedding is presented in this paper, using the frequency second derivative as a source of information for a forecast of the frequency trajectory. A Newton-method-based approximation and the interpolation of the frequency second derivative are continuously performed in order to forecast the minimum frequency value using a numerical integration. [ABSTRACT FROM AUTHOR]

This research represents a conceptual shift in the process of introducing flexibility into power system frequency stability-related protection. The existing underfrequency load shedding (UFLS) solution, although robust and fast, has often proved to be incapable of adjusting to different operating conditions. It triggers upon detection of frequency threshold violations, and functions by interrupting the electricity supply to a certain number of consumers, both of which values are decided upon beforehand. Consequently, it often does not comply with its main purpose, i.e., bringing frequency decay to a halt. Instead, the power imbalance is often reversed, resulting in equally undesirable frequency overshoots. Researchers have sought a solution to this shortcoming either by increasing the amount of available information (by means of wide-area communication) or through complex changes to all involved protection relays. In this research, we retain the existing concept of UFLS that performs so well for fast-occurring frequency events. The flexible rebalancing of power is achieved by a small and specialized group of intelligent electronic devices (IEDs) with machine learning functionalities. These IEDs interrupt consumers only when the need to do so is detected with a high degree of certainty. Their small number assures the fine-tuning of power rebalancing and, at the same time, poses no serious threat to system stability in cases of malfunction. [ABSTRACT FROM AUTHOR]