With a growing share of inverter-interfaced generation in modern power systems, synchronous inertia is declining. This leads to faster frequency drop after large generation trip events. During low inertia conditions, frequency containment reserves might not be sufficient to arrest frequency before it reaches the threshold for underfrequency load shedding. It is therefore be-coming increasingly important for system operators to be able to assess frequency response in near real time. In contrast to detailed models, simplified models offer short simulation times and their parameters can be accurately identified and adapted to changing system conditions in near real time. In this paper, the parameters of governor response models are identified by minimizing the er-ror residuals between the simulation models' and the actual sys-tem's measured active power response. This is accomplished by using historic event data from two system operators: the Electric Reliability Council Of Texas (ERCOT) and the Swedish Svenska kraftnät (Svk). Then, the respective frequency response models are simulated to assess frequency response. The results show that, despite their simplicity, the models provide a very good fit com-pared to the actual response. The models of ERCOT and Svk are examined; however, a similar approach can be employed to repre-sent the frequency response of other power systems.

Synchronous power system inertia is declining, due to the increasing penetration of inverter-interfaced generation. This entails faster and greater frequency decrease after generation outages. When the system encounters low values of system inertia, frequency containment reserves may not be capable of retaining frequency over the threshold for underfrequency load shedding. These system changes necessitate the real time assessment of frequency response and specifically, the assessment of frequency nadir. The method that is currently used for frequency response assessment by the Swedish system operator examines the relation between the frequency nadir, the system kinetic energy, and the size of the disturbance through linear regression. This paper evaluates the aforementioned method and proposes a modified realization of the regression to achieve higher accuracy. Furthermore, the uncertainty that the system nonlinearities introduce in the method is quantified.

Power plant emissions constitute a major source of environmental pollution. This renders the gradual replacement of such power plants by renewable energy sources imperative. Changes in the quota between conventional generation and renewable energy sources introduce challenges that the modern power systems have to encounter. For example, conventional power plants are replaced by wind turbines and photovoltaics, which do not contribute to system's inertia. As a result, power system inertia decreases and frequency stability becomes a concern. Frequency stability is affected by the amount of power system inertia, along with the response of controllable frequency reserves and the amount of power imbalance. Therefore, the estimation of power system inertia, as well as the frequency response assessment is necessitated, so that appropriate actions can be taken to ensure frequency stability.

The first part of this thesis focuses on power system inertia estimation. Four disturbance based inertia estimation methods are proposed. The methods accommodate the frequency and/or voltage variations that arise after a disturbance and estimate both the total inertia constant and the total power imbalance of the system. This is achieved by considering suitable functions that can approximate the voltage and frequency dependency of the loads, as well as the response from the governors. The proposed methods are applied on frequency responses from simulations of a test system under several different scenarios. The performance of the methods under lack of certain data is investigated, in order to examine if they can be employed under realistic conditions. An extensive analysis is performed, which enables the selection of the most appropriate method, depending on the information that is available.

The second part of the thesis deals with frequency response assessment. First, the use of simplified dynamic equivalent models is examined. The parameters of either governor or frequency response models of the system are identified and validated by employing historic events. Data are obtained from events from the power systems of Sweden and Texas. After the identification, the frequency response model of the system can be simulated to assess frequency stability. Secondly, the thesis examines methods that deal solely with the prediction of frequency nadir. The examined methods either use neural networks or linear regression. The accuracy of the methods, as well as the uncertainty that is introduced by system non-linearities, are assessed through simulations.

By proposing methods for estimating power system inertia and frequency response, this thesis attempts to provide additional solutions to the challenges that modern power systems have to face. It offers supplementary tools to increase the system awareness, in order to take appropriate actions in case of frequency events.

Power system inertia is gradually being reduced due to the ongoing replacement of conventional synchronous power plants by intermittent generation. This affects the frequency response of the system and necessitates the estimation of power system inertia, so that sufficient power reserves are retained. This paper contributes with a novel disturbance-based inertia estimation method, that simultaneously estimates the power change after a disturbance. The proposed method accommodates the frequency and voltage dynamics, which significantly affect the system's power change, and hence the inertia estimation. Two separate approaches – that are also capable of standing alone – are combined, in order to accommodate the dynamics. An extended version of the Nordic32 test system is used for the application of the method, where several case studies and a comparison are investigated, so as to examine the method's accuracy and robustness.

The increased integration rate of inverter-interfaced devices is affecting the frequency response of the modern power systems. This leads to an increase of the variability of the power generation and to a reduction of the total system's inertia. This evolution of the system necessitates the prediction of frequency metrics, so that the frequency stability of the system can be guaranteed and that necessary mitigation measures can be taken. This paper proposes a method to predict the frequency nadir by using a Neural Network (NN) approach. As the approach uses measurements during a first short time period after the event, it more accurately predicts the frequency nadir compared to using static values. Several inputs for the NN are examined and when the appropriate ones are selected, a highly accurate prediction is accomplished.

Power system inertia is being globally reduced, due to the substitution of conventional synchronous power plants by intermittent generation. This threatens the frequency stability of the system and makes the estimation of power system inertia necessary, so that proactive measures can be imposed. A disturbance-based method is proposed in this paper, which estimates the total inertia constant of the power system. The method applies particle swarm optimization (PSO) to minimize a cost function, which is defined based on the swing equation. To do that, data available at the generator buses are employed. The proposed method is applied on the Nordic57 test system under twenty different scenarios, which include generator and load disconnections. Furthermore, a comparison with two methods presented in the literature is performed and demonstrates the higher performance of the proposed method, in the sense of the mean and the variance of the errors.

The substitution of conventional synchronous power plants by intermittent generation leads to reduced power system inertia. This transition deteriorates system's frequency response and necessitates the estimation of power system inertia, so that adequate power resources are preserved. An offline estimation method is proposed in this paper, which aims to estimate the power change of the loads due to voltage dependency after a disturbance. To do that, data available at the generator buses are employed. The proposed method is applied on a modified version of Nordic32 test system under twenty different scenarios, which include generator and load disconnections. Finally, a comparison with two offline methods presented in the past literature takes place and demonstrates the advantages and disadvantages of the proposed method.

Information about power system inertia is of utmost importance for the Transmission System Operators (TSOs), so that it can be guaranteed that the stability of the system is not under risk. A new offline inertia estimation method is proposed in this paper. The method includes the calculation of the total power change after a disturbance in the system, based on selection of appropriate time ranges of the Rate Of Change Of Frequency(ROCOF) curve. Nordic32 test system is used for the simulations, where different disturbances, load dynamics and data processing tools are considered. Finally, a comparison of the proposed method to two methods proposed in the past takes place.