Model Parameter Calibration in Power Systems

In power systems, accurate device modeling is crucial for grid reliability, availability, and resiliency. Many critical tasks such as planning or even realtime operation decisions rely on accurate modeling. This research presents an approach for model parameter calibration in power system models using deep learning. Existing calibration methods are based on mathematical approaches that suffer from being ill-posed and thus may have multiple solutions. We are trying to solve this problem by applying a deep learning architecture that is trained to estimate model parameters from simulated Phasor Measurement Unit (PMU) data. The data recorded after system disturbances proved to have valuable information to verify power system devices. A quantitative evaluation of the system results is provided. Results showed high accuracy in estimating model parameters of 0.017 MSE on the testing dataset. We also provide that the proposed system has scalability under the same topology. We consider these promising results to be the basis for further exploration and development of additional tools for parameter calibration

On-Line Estimation Assessment of Power Systems Inertia With High Penetration of Renewable Generation

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Data-Driven Situation Awareness for Power System Frequency Dynamics

As the penetration of renewable energy increases, system inertia decreases, causing changes in system frequency dynamics. The power industry desires situation awareness of power system frequency dynamics to ensure secure and economic operation and control. Moreover, FNET/Grideye has abundant measured data from power systems, making it possible to conduct data-driven situation awareness studies on power system frequency dynamics. This doctoral dissertation proposes several contributions: (a) Two accurate generator trip event MW estimation methods are proposed, in which one is based on long window RoCoF and another is based on multi-Beta values; (b) Two real-time system inertia estimation approaches are developed using ambient frequency fluctuation and pump turn-off events, along with techniques for improving RoCoF calculation in event-based inertia estimation; (c) An adaptive PV reserve estimation algorithm is established to provide PV reserve while saving energy for PV resources; (d) A practical load composition estimation tool is built for the industry to easily obtain essential load model parameters. Although conducting research using actual data from power systems for practical application is challenging and compilated, the proposed data-driven situation awareness methods in this doctoral dissertation solve practical problems and offer clear theoretical explanations for the industry. These methods address one of the key challenges for operating a high-renewable power grid and pave the way for the U.S. carbon-free power sector by 2035

Measurement-Based Monitoring and Control in Power Systems with High Renewable Penetrations

Power systems are experiencing rapid changes in their generation mixes because of the increasing integration of inverter-based resources (IBRs) and the retirement of traditional generations. This opens opportunities for a cleaner energy outlook but also poses challenges to the safe operation of the power networks. Enhanced monitoring and control based on the increasingly available measurements are essential in assisting stable operation and effective planning for these evolving systems. First, awareness of the evolving dynamic characteristics is quintessential for secure operation and corrective planning. A quantified monitoring study that keeps track of the inertial response and primary frequency response is conducted on the Eastern Interconnection (EI) for the past decade with field data. Whereas the inertia declined by at least 10%, the primary frequency response experienced an unexpected increase. The findings unveiled in the trending analysis also led to an improved event MW size estimation method, as well as discussions about regional dynamics. Experiencing a faster and deeper renewable integration, the Continental Europe Synchronous Area (CESA) system has been threatened by more frequent occurrences of inter-area oscillations during light-load high-renewable periods. A measurement-based oscillation damping control scheme is proposed for CESA with reduced reliance on system models. The design, implementation, and hardware-in-the-loop (HIL) testing of the controller are discussed in detail. Despite the challenges, the increasing presence of IBRs also brings opportunities for fast and efficient controls. Together with synchronized measurement, IBRs have the potential to flexibly complement traditional frequency and voltage control schemes for improved frequency and voltage recovery. The design, implementation, and HIL testing of the measurement-based frequency and voltage control for the New York State Grid are presented. In addition to the transmission level development, IBRs deployed in distribution networks can also be valuable assets in emergency islanding situations if controlled properly. A power management module is proposed to take advantage of measurements and automatically control the electric boundaries of islanded microgrids for maximized power utilization and improved frequency regulation. The module is designed to be adaptive to arbitrary non-meshed topologies with multiple source locations for increased flexibility, expedited deployment, and reduced cost

Efeitos da expansão da microgeração solar no desempenho do controle da frequência elétrica durante perturbações

TCC (graduação) - Universidade Federal de Santa Catarina. Centro Tecnológico. Engenharia Elétrica.A expansão da geração fotovoltaica contribui para a redução da emissão de gases de efeito estufa, provenientes da queima de combustíveis fósseis, revelando-se um processo irreversível. Entretanto, a expansão deste tipo de fonte de geração assíncrona, que é conectada à rede por meio de conversores eletrônicos, pode dar origem a problemas técnicos ligados à operação do sistema elétrico. Por não agregar inércia ao sistema, a inserção da geração fotovoltaica tende a aumentar as taxas de variação de frequência elétrica e a reduzir os níveis da frequência mínima quando da ocorrência de contingências. Como consequência, o sistema elétrico fica sujeito ao agravamento de perturbações em função de possíveis desligamentos intempestivos de geração, incluindo o da microgeração fotovoltaica distribuída. Ressalta-se que a microgeração fotovoltaica tende a ter requisitos de conexão ao sistema elétrico menos exigentes, em função de sua conexão ser realizada na baixa tensão. Adicionalmente, a verificação de tais requisitos de conexão impõe dificuldades práticas, em função da pulverização desse tipo de fonte de geração. Para caracterizar tais efeitos, este trabalho apresenta aspectos do controle de frequência em sistemas elétricos, destacando sua relação com a proporção de geração síncrona e assíncrona em operação. Utilizando simulações computacionais, o trabalho ilustra a tendência da degradação do desempenho do controle frequência do Sistema Interligado Nacional (SIN) como consequência da substituição gradual de parte da geração síncrona pela geração assíncrona, de fonte eólica ou solar fotovoltaica. As análises têm como foco os efeitos da redução da inércia equivalente do sistema elétrico e de desligamentos intempestivos de geração durante perturbações, em particular da microgeração fotovoltaica.The expansion of photovoltaic generation contributes to the reduction of greenhouse effect gases emission, that are originated by the combustion of fossil fuels, revealing itself to be an irreversible process. However, the expansion of this type of asynchronous generation source, connected to the grid by electronic converters, can lead to technical problems related to the power system operation. The photovoltaic generation penetration tends to increase the Rate of Change of Frequency (RoCoF) and to reduces the minimum frequency levels when contingencies occurs, since it does not aggregate inertia to the power system. Therefore, the power system is more subjected to worsening disturbances due to potential sudden generation shutdown, including the distributed photovoltaic microgeneration. It is worth to point out that photovoltaic microgeneration tends to have less demanding grid connection requirements, given it that its connection occurs on low voltage grids. In addition, verifying such connection requirements impose practical difficulties due to the pulverization of this type of generation. As to characterize said effects, this work presents frequency control aspects in power systems, highlighting its relation with the proportion of synchronous and asynchronous generation. Through computational simulations, this work illustrates the tendency of degradation of Brazilian NIS’ (National Interconnected System) frequency control performance, as a consequence of the gradual replacement of a portion of synchronous generation by an wind or solar asynchronous generation. The analyses focus on the effects of the reduction of the power system’s equivalent inertia and sudden generation shutdowns during disturbances, such as photovoltaic microgeneration in particularly

Power systems inertial constant estimation using synchrophasors

Orientador: Daniel DottaDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: A estabilidade de frequência se tornou uma preocupação para operadores de sistemas com o aumento na presença de geradores de baixa-inércia conectados à rede. Ao contrário de máquinas síncronas, essas máquinas não dispõem de capacidade considerável de armazenamento de energia cinética em suas massas girantes. O conhecimento da constante inercial é desafiador dadas as incertezas a respeito do modelo e intermitência desses novos geradores. Este trabalho apresenta uma nova metodologia para determinação automática da constante inercial do sistema de potência utilizando modelo autorregressivo de média móvel e entrada exógena (ARMAX). Esse método não intrusivo faz uso de eventos regulares da rede medidos por Sistemas de Medição Fasorial Sincronizada (WAMS, na sigla inglesa). O uso de um conjunto de dados pequeno e constante assim como o modelo ARMAX de identificação permite uma estimação célere e de baixo custo computacional. O método é validado na estimação da inércia regional do sistema teste 68 barras. Finalmente, a robustez do método a ruído e medidas espúrias é avaliada através de simulações Monte Carlo e estimações de inércia para o mesmo sistema, com participação de geração eólicaAbstract: The frequency stability has become a concern for the system operators with the increase of low-inertia generator connected to power systems. Different from synchronous machines, these sources lack the capacity for storing kinetic energy in rotating masses. Assessing the power system inertial constant is challenging due to uncertainties regarding modeling and generation intermittency of these new generators. This work presents a novel methodology to automatically assess the power system inertial constant using autoregressive moving average exogenous input (ARMAX) model. This non-intrusive approach uses regular power system disturbances measured by Wide-Area Measurement Systems (WAMS). The use of a fixed and small measurement data set as well as ARMAX model identification allows a fast and low computational burden estimation. The method is validated on the estimation of regional inertias for 68 bus power test system. Finally, the method robustness to noise and outliers is evaluated via Monte Carlo simulations and initial inertia estimation results for the same system with wind generationMestradoEnergia EletricaMestre em Engenharia Elétric

Data-Driven Power System Stability Analysis and Control

In recent years, with the expansion of power system size, the increase of interconnection and the use of large-scale renewable energy, power system stability and safe operations have become more prominent, causing challenges to the normal operation of power grid. Traditional analysis rely on detailed models of the system. But for real power systems, the operating state of the system is variable, and the model-based analysis methods may not accurately reflect the real operating state of the system. Therefore, this dissertation is focused on data-driven stability analysis and control. First, a method for locating the oscillation source of multi-machine systems is proposed. The electromagnetic torque expressions of various generators in a multi-machine system are deduced, and it is found that in each oscillation mode, the electromagnetic torque can be decomposed into a damping torque and a synchronous torque. Based on this development, an oscillation source positioning scheme based on decoupling mode is proposed. Then, a transfer and CNN-LSTM-based method is developed to accelerate and improve the accuracy of the dynamic frequency prediction process. The proposed method exploits system spatial-temporal information and mines the local features of inputs, which highly improves the performance compared with other machine learning methods. Next, a Distributional Soft Actor-Critic (DSAC) method is developed to solve the emergency frequency control problem. The frequency control is formulated as a MDP problem and solved through a novel distributional deep reinforcement learning method. Further, high penetration renewable energy source increase the system uncertainties and impact the cyber security. We propose a detection method based on Bayesian GAN. It can successfully distinguish between securely operating measurements and those that have been attacked with imbalanced training data. Simulation results of this dissertation show the effectiveness of the proposed methods

Advanced analysis of load management and environment friendly energy technologies integration in electric power system

The Commonwealth Scholarship Commission (CSC) in the United Kingdom places its primary emphasis on six distinct development-related themes namely, science and technology for development, strengthening health systems, promoting global prosperity, strengthening resilience and response to crises, access, inclusion, and opportunity, and strengthening global peace, security, and governance. My motivation as a Commonwealth scholar, comes from the discussion surrounding the application of science and technology for the development, which is related to the seventh among 17 sustainable development goals (SDGs). The endorsed goal aims at ensuring that all people have access to energy that is both clean and affordable. In this context, my research focuses on the advanced analysis of load management and energy conservation strategies in developing countries, with Rwanda as its primary focus. Firstly, this research work supports the development of Rwanda's energy system and addresses gaps in the existing energy data by proposing a set of Future Energy Scenarios (FES). The developed FES are used to estimate the energy consumption and generation capacity until 2050. Secondly, this research analyses the impact of technologies that are adopted in the developed FES on the Rwanda’s power system. As Electric Vehicles (EVs) are highlighted as an important component in decarbonisation of transport, the study analyses the EVs deployment into the country’s transport and electricity networks. Another challenge that this research is addressing, is the impact the proposed FESs imposes on the power system inertia constant as a result of the integration of renewable energy sources. This is because conventional power plants are replaced by renewable generation (e.g., photovoltaics considered in this study) that contribute to the reduction of power system inertia. In addition to the feasibility study for the deployment of EVs in the country’s transport and electricity networks, this research also developed a methodology to estimates the inertia constant for three different periods in future, namely, 2025, 2035 and 2050 based on the produced FESs for Rwandan’s power system. Furthermore, the research evaluates the frequency response dynamics for each scenario. Results show that the highest progression in renewable energy sources penetration results in a larger reduction in the system inertia constant. The largest frequency drop was observed during the high progression scenario in the year 2050 where the PV generation and imported power from neighbouring countries through interconnectors is expected to reach more than 30% of the total installed capacity. Finally, to mitigate this large drop in frequency, the work proposed a method for stabilising grid frequency by considering demand flexibility. With the help of the load aggregator, prosumers receive price incentive signals based on their energy consumption and prepare them for their participation in grid frequency stabilisation. By considering the operation of a wide range of renewable energy sources and load management system, the study investigates the reduction of the total reliance on electricity from the grid, in day-ahead and real-time energy markets, while also balancing an anticipated load. The proposed control framework considers the estimated power availability and it is used in conjunction with the participation of a load aggregator for contributing to the stabilisation of grid frequency