Geometric deep learning for Alzheimer's disease analysis

Alzheimer’s Disease (AD) represents between 50-70% of the cases of dementia, which translates in around 25-35 million people affected by this disease. During its development, patients suffering from AD experience an irreversible cognitive decline, which limits their autonomy on their daily lives. While many of the causes of AD are still unknown, researchers have noticed a abnormal amyloid deposition and neurofibrillary tangles that will start affecting the short-term memory of the patient, together with other cognitive functions. In fact, these pathophysiological changes start taking place even before the patient experiences the first symptoms. One of the structures that is first affected by the disease is the hippocampus. During the development of AD, this part of the brain experiences an irregular deformation that affects its capabilities of forming new memories. Therefore, many clinical work has set a focus on studying this structure and its evolution along the disease. Identifying the changes it suffers can help us understand better the causes of the patient's cognitive decline. Given the complexity that characterizes AD, identifying patterns during its development is still a cumbersome task for physicians.Thus, aiding the diagnosis and prognosis of the disease using Deep Learning methods can be highly beneficial, as seen for other medical applications. In particular, if the focus is set on single structures (e.g. the hippocampus) Geometric Deep Learning offers a set of models that are best suited for 3D shape representations. We believe these methods can help doctors identify abnormalities in the structure that can lead to AD in the future. In this work, we first study the capabilities of current Geometric Deep Learning methods in diagnosing patients suffering from AD, by only looking at the hippocampus. We start by studying one of the simplest 3d representations, point clouds. We continue by comparing this representation to other non-Euclidean representations, such as meshes, and also Euclidean ones (e.g. 3d masks). We observe that meshes are one of the optimal ways of representing 3d structures for capturing fine-grained changes, but they carry additional pre-processing steps that Euclidean representations do not require. Finally, once we have confirmed that Geometric Deep Learning, particularly mesh neural networks, can properly capture the effects of AD on the hippocampus, we expand their application to longitudinal analysis of the structure. We propose a new temporal model based on Spiral Resnet and Transformers that sets a new state-of-the-art for the task of predicting longitudinal trajectories of the hippocampus. We also evaluated the effect that imputing missing longitudinal data has on detecting subjects that are developping to AD. Our experiments show an increase of a 3% in distinguishing between converting and stable trajectories

All4One: Symbiotic Neighbour Contrastive Learning via Self-Attention and Redundancy Reduction

Nearest neighbour based methods have proved to be one of the most successful self-supervised learning (SSL) approaches due to their high generalization capabilities. However, their computational efficiency decreases when more than one neighbour is used. In this paper, we propose a novel contrastive SSL approach, which we call All4One, that reduces the distance between neighbour representations using ''centroids'' created through a self-attention mechanism. We use a Centroid Contrasting objective along with single Neighbour Contrasting and Feature Contrasting objectives. Centroids help in learning contextual information from multiple neighbours whereas the neighbour contrast enables learning representations directly from the neighbours and the feature contrast allows learning representations unique to the features. This combination enables All4One to outperform popular instance discrimination approaches by more than 1% on linear classification evaluation for popular benchmark datasets and obtains state-of-the-art (SoTA) results. Finally, we show that All4One is robust towards embedding dimensionalities and augmentations, surpassing NNCLR and Barlow Twins by more than 5% on low dimensionality and weak augmentation settings. The source code would be made available soon.Comment: 14 pages, 9 figure

Simulation model of a variable-speed pumped-storage power plant in unstable operating conditions in pumping mode

This paper presents a dynamic simulation model of a laboratory-scale pumped-storage power plant (PSPP) operating in pumping mode with variable speed. The model considers the dynamic behavior of the conduits by means of an elastic water column approach, and synthetically generates both pressure and torque pulsations that reproduce the operation of the hydraulic machine in its instability region. The pressure and torque pulsations are generated each from a different set of sinusoidal functions. These functions were calibrated from the results of a CFD model, which was in turn validated from experimental data. Simulation model results match the numerical results of the CFD model with reasonable accuracy. The pump-turbine model (the functions used to generate pressure and torque pulsations inclusive) was up-scaled by hydraulic similarity according to the design parameters of a real PSPP and included in a dynamic simulation model of the said PSPP. Preliminary conclusions on the impact of unstable operation conditions on the penstock fatigue were obtained by means of a Monte Carlo simulation-based fatigue analysis

Pond head level control in a run-of-river hydro power plant using fuzzy controller

The run-of-river hydro power plant usually have low or nil water storage capacity, and therefore an adequate control strategy is required to keep the water level constant in pond. This paper presents a novel technique based on TSK fuzzy controller to maintain the pond head constant. The performance is investigated over a wide range of hill curve of hydro turbine. The results are compared with PI controller as discussed in [1]

A control system for low-head diversion run-of-river small hydro plants with pressure conduits considering the tailwater level variation

This paper presents a control system for low-head diversion run-of-river small hydro plants with pressure conduits. Since these hydropower plants usually have low or null water storage capacity, the water discharged through the turbines should be adapted to the possible extent to the natural river inflow. For this purpose, a control scheme aimed at maintaining a constant water level in the head pond is normally used in these cases. As an alternative, the option of maintaining a constant water level in the surge tank is studied in this paper. Furthermore, since in low-head hydro plants the tailwater level variation may represent a relatively important contribution to total head losses, it has been explicitly considered in the proposed control system. A small-perturbation stability analysis has been carried out in order to analyze the influence of the plant design and controller parameters in the plant dynamic response. Finally, in order to illustrate the applicability of the proposed control system, several simulations have been carried out using data gathered from a real hydro plan

An adaptive control scheme for variable speed wind turbines providing frequency regulation in isolated power systems with thermal generation

The lack of synchronous inertia, associated with the relevant penetration of variable speed wind turbines (VSWTs) into isolated power systems, has increased their vulnerability to strong frequency deviations. In fact, the activation of load shedding schemes is a common practice when an incident occurs, i.e., the outage of a conventional unit. Under this framework, wind power plants should actively contribute to frequency stability and grid reliability. However, the contribution of VSWTs to frequency regulation involves several drawbacks related to their efficiency and equipment wear due to electrical power requirements, rotational speed changes, and subsequently, shaft torque oscillations. As a result, wind energy producers are not usually willing to offer such frequency regulation. In this paper, a new control technique is proposed to optimize the frequency response of wind power plants after a power imbalanced situation. The proposed frequency controller depends on different power system parameters through a linear regression to determine the contribution of wind power plants for each imbalance condition. As a consequence, VSWTs frequency contribution is estimated to minimize their mechanical and electrical efforts, thus reducing their equipment wear. A group of sixty supply-side and imbalance scenarios are simulated and analyzed. Results of the case study are compared to previous proposals. The proposed adaptive control reduces the máximum torque and rotational speed variations while at the same time maintaining similar values of the load shedding program. Extensive results and discussion are included in the paper.This work was partially supported by ‘Ministerio de Educación, Cultura y Deporte’ of Spain (ref. FPU16/04282) and by ‘Ministerio de Economía y Competitividad’, under the project “Value of pumped-hydro energy storage in isolated power systems with high wind power penetration” of the National Plan for Scientific and Technical Research and Innovation 2013–2016, grant number ENE2016-77951-R

Contribution to Load-Frequency Regulation of a Hydropower Plant with Long Tail-Race Tunnel

In this paper, a hydroelectric power plant with long tail-race tunnel has been modelled for assessing its contribution to secondary regulation reserve. Cavitation problems, caused by the discharge conduit length, are expected downstream the turbine where low pressure appears during regulation manoeuvres. Therefore, governor's gains should be selected taking into account these phenomena. On the other hand, regulation services bidden by the plant operator should fulfil TSO (Transmission System Operator) quality requirements. A methodology for tuning governor PI gains is proposed and applied to a Hydro power plant in pre-design phase in northwest area of Spain. The PI gains adjustment proposed provides a proper plant response, according to some established indexes, while avoiding cavitation phenomena

Power-frequency control of hydropower plants with long penstocks in isolated systems with wind generation

In this paper the power-frequency control of hydropower plants with long penstocks is addressed. In such configuration the effects of pressure waves cannot be neglected and therefore commonly used criteria for adjustment of PID governors would not be appropriate. A second-order Π model of the turbine-penstock based on a lumped parameter approach is considered. A correction factor is introduced in order to approximate the model frequency response to the continuous case in the frequency interval of interest. Using this model, several criteria are analysed for adjusting the PI governor of a hydropower plant operating in an isolated system. Practical criteria for adjusting the PI governor are given. The results are applied to a real case of a small island where the objective is to achieve a generation 100% renewable (wind and hydro). Frequency control is supposed to be provided exclusively by the hydropower plant. It is verified that the usual criterion for tuning the PI controller of isolated hydro plants gives poor results. However, with the new proposed adjustment, the time response is considerably improve

Frequency control support of a wind-solar isolated system by a hydropower plant with long tail-race tunnel

Pumped storage hydro plants (PSHP) can provide adequate energy storage and frequency regulation capacities in isolated power systems having significant renewable energy resources. Due to its high wind and solar potential, several plans have been developed for La Palma Island in the Canary archipelago, aimed at increasing the penetration of these energy sources. In this paper, the performance of the frequency control of La Palma power system is assessed, when the demand is supplied by the available wind and solar generation with the support of a PSHP which has been predesigned for this purpose. The frequency regulation is provided exclusively by the PSHP. Due to topographic and environmental constraints, this plant has a long tail-race tunnel without a surge tank. In this configuration, the effects of pressure waves cannot be neglected and, therefore, usual recommendations for PID governor tuning provide poor performance. A PI governor tuning criterion is proposed for the hydro plant and compared with other criteria according to several performance indices. Several scenarios considering solar and wind energy penetration have been simulated to check the plant response using the proposed criterion. This tuning of the PI governor maintains La Palma system frequency within grid code requirements

Dynamic response of hydro power plants for providing secondary regulation reserves considering elastic water column effects

In this paper, the dynamic response of a hydro power plant for providing secondary regulation reserve is studied in detail. Special emphasis is given to the elastic water column effects both in the penstock and the tailrace tunnel. For this purpose, a nonlinear model based on the analogy between mass and momentum conservation equations of a water conduit and those of wave propagation in transmission lines is used. The influence of the plant configuration and design parameters on the fulfilment of the Spanish Electrical System Operator requirements is analyse