Optimised TSO-DSO Coordination to Integrate Renewables in Flexibility Markets

The necessary energy transition to decarbonize power systems is leading to increasingly important challenges for the operation of power systems. On the one hand, the intermittent nature of renewable generation requires system operators to procure ancillary services in larger volumes than in the past. On the other, the growing penetration of medium- and small-scale, flexible demand and storage systems in distribution networks could potentially offer network services, if they are aggregated effectively and there is an appropriate coordination between transmission system operators (TSOs), distribution system operators (DSOs) and aggregators. Therefore, an important topic to be analysed is whether distributed energy resources (DER) can replace traditional generation in the provision of ancillary services (AS), how this replacement will affect the system operators’ roles and how to improve the coordination between TSOs and DSOs. This paper shows the results of the cost-benefit analysis (CBA) performed within the project SmartNet to assess the advantages or disadvantages of different TSO-DSO coordination schemes, as well as the follow-up activities to be carried out in the project CoordiNet.These projects have received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements No 691405 & No 824414

The Indiana Cybersecurity Services Center (INCSC): A Cost-Benefit Analysis For K-12 Schools

The aim of this thesis is to determine if there are greater benefits than costs associated in the participation of public K-12 school corporations in the Indiana Cybersecurity Services Center (INCSC). This thesis is an ex-antecost-benefit analysis policy assessment of the INCSC. The study consisted of a sample of 6 school corporations from which 5 were classified as small and 1 was large. Three methods were considered for data collection; however conducting interviews was the most effective method due to the interaction with IT personnel from each organization in order to analyze current costs related to 4 areas of interest: (a) networking hardware; (b) Antivirus software; (c) computer hardware; (d) IT personnel. These costs were compared to those potential costs if products and/or services would be procured through the INCSC. School corporations, with the goal to enhance their level of information security, would only receive benefit from participating in the INCSC when procuring networking equipment and Antivirus software. The author also recommends exploring the costs and legal implications of data breaches as well as considering insurance products

Applications, Operational Architectures and Development of Virtual Power Plants as a Strategy to Facilitate the Integration of Distributed Energy Resources

In this article, we focus on the development and scope of virtual power plants (VPPs) as a strategy to facilitate the integration of distributed energy resources (DERs) in the power system. Firstly, the concepts about VPPs and their scope and limitations are introduced. Secondly, smart management systems for the integration of DERs are considered and a scheme of DER management through a bottom-up strategy is proposed. Then, we analyze the coordination of VPPs with the system operators and their commercial integration in the electricity markets. Finally, the challenges that must be overcome to achieve the large-scale implementation of VPPs in the power system are identified and discussed.The authors acknowledge the support from GISEL research group IT1191-19, as well as from the University of the Basque Country UPV/EHU (research group funding 181/18)

Local flexibility market design for aggregators providing multiple flexibility services at distribution network level

This paper presents a general description of local flexibility markets as a market-based management mechanism for aggregators. The high penetration of distributed energy resources introduces new flexibility services like prosumer or community self-balancing, congestion management and time-of-use optimization. This work is focused on the flexibility framework to enable multiple participants to compete for selling or buying flexibility. In this framework, the aggregator acts as a local market operator and supervises flexibility transactions of the local energy community. Local market participation is voluntary. Potential flexibility stakeholders are the distribution system operator, the balance responsible party and end-users themselves. Flexibility is sold by means of loads, generators, storage units and electric vehicles. Finally, this paper presents needed interactions between all local market stakeholders, the corresponding inputs and outputs of local market operation algorithms from participants and a case study to highlight the application of the local flexibility market in three scenarios. The local market framework could postpone grid upgrades, reduce energy costs and increase distribution grids’ hosting capacity.Postprint (published version

A Fully Attention-Based Information Retriever

Recurrent neural networks are now the state-of-the-art in natural language processing because they can build rich contextual representations and process texts of arbitrary length. However, recent developments on attention mechanisms have equipped feedforward networks with similar capabilities, hence enabling faster computations due to the increase in the number of operations that can be parallelized. We explore this new type of architecture in the domain of question-answering and propose a novel approach that we call Fully Attention Based Information Retriever (FABIR). We show that FABIR achieves competitive results in the Stanford Question Answering Dataset (SQuAD) while having fewer parameters and being faster at both learning and inference than rival methods.Comment: Accepted for presentation at the International Joint Conference on Neural Networks (IJCNN) 201

Tiny ML in Microcontroller to Classify EEG Signal into Three States

This thesis investigates how to implement an own-built neural network for electroencephalography signals classification on an STM32L475VG microcontroller unit. The original dataset is analyzed and processed to better understand the brain signals. There is a comparison between three machine learning algorithms (linear support vector machine, extreme gradient boosting, and deep neural network) in three testing paradigms: specific-subject, all-subject, and adaptable to select the most appropriate approach for deploying on the microcontroller. The implementation procedure with detailed notation is presented, and the inference is also performed to feasible observation. Finally, possible improvement solutions are proposed within a clear demonstration.This thesis investigates how to implement an own-built neural network for electroencephalography signals classification on an STM32L475VG microcontroller unit. The original dataset is analyzed and processed to better understand the brain signals. There is a comparison between three machine learning algorithms (linear support vector machine, extreme gradient boosting, and deep neural network) in three testing paradigms: specific-subject, all-subject, and adaptable to select the most appropriate approach for deploying on the microcontroller. The implementation procedure with detailed notation is presented, and the inference is also performed to feasible observation. Finally, possible improvement solutions are proposed within a clear demonstration

Intelligent agent based-Real time monitoring and Evaluation of GSM quality of service

Most Telecommunication companies could not guarantee complete free and quality communication network service. In recent times there had been Undesirable service delivery, this problem is traced to not having free and quality network which had arisen as a result of not monitoring when there is high bit error rate. The problem had been addressed and a solution proffered in this paper by Real time Evaluation and Monitoring of GSM quality of service utilizing intelligent agent device. This was achieved by first determining the channel capacity for GSM quality network, obtaining the bit error rate for the determined capacity, designing an intelligent GSM rule that will monitor and minimize the high bit error rate for quality service and finally designing a Simulink model for real time monitoring and evaluation of GSM quality of service using intelligent agent. The result obtained was10% better than using the conventional methods or techniques like Hieratical, Proportional Integral Derivative (PID). Real time monitoring and Evaluation of GSM quality of service using intelligent agent is preferred to other conventional methods as it can guarantee a perfect and free network in our communication network. Key words: Real time monitoring and evaluation of GSM quality of service, intelligent agent DOI: 10.7176/IKM/11-4-05 Publication date:June 30th 202

Enhancing Cybersecurity in the Private Sector by Means of Civil Liability Lawsuits - The Connie Francis Effect

The purpose of this article is to explore the threats posed by cybersecurity breaches, outline the steps taken by the government to address those threats in the private sector economy, and call attention to the ultimate solution, which will most certainly spur private businesses to create a more secure cyber environment for the American people-a Connie Francis-styled cyber civil action lawsuit

A hyper-heuristic for adaptive scheduling in computational grids

In this paper we present the design and implementation of an hyper-heuristic for efficiently scheduling independent jobs in computational grids. An efficient scheduling of jobs to grid resources depends on many parameters, among others, the characteristics of the resources and jobs (such as computing capacity, consistency of computing, workload, etc.). Moreover, these characteristics change over time due to the dynamic nature of grid environment, therefore the planning of jobs to resources should be adaptively done. Existing ad hoc scheduling methods (batch and immediate mode) have shown their efficacy for certain types of resource and job characteristics. However, as stand alone methods, they are not able to produce the best planning of jobs to resources for different types of Grid resources and job characteristics. In this work we have designed and implemented a hyper-heuristic that uses a set of ad hoc (immediate and batch mode) scheduling methods to provide the scheduling of jobs to Grid resources according to the Grid and job characteristics. The hyper-heuristic is a high level algorithm, which examines the state and characteristics of the Grid system (jobs and resources), and selects and applies the ad hoc method that yields the best planning of jobs. The resulting hyper-heuristic based scheduler can be thus used to develop network-aware applications that need efficient planning of jobs to resources. The hyper-heuristic has been tested and evaluated in a dynamic setting through a prototype of a Grid simulator. The experimental evaluation showed the usefulness of the hyper-heuristic for planning of jobs to resources as compared to planning without knowledge of the resource and job characteristics.Peer ReviewedPostprint (author's final draft

Ancillary Services 4.0: A Top-To-Bottom Control-Based Approach for Solving Ancillary Services Problems in Smart Grids

Power systems are experiencing a large amount of renewable generation with highly stochastic and partly unpredictable characteristics. This change in energy production implies significant consequences related to the provision of ancillary services (AS). Current markets dedicated to the provision of AS are not able to benefit from the flexible energy resources. They also cannot cope with the new level of stochasticity, non-linearity and dynamics of generation and flexibility. To overcome such issues and exploit the potential of flexibility resources, a new strategy is required. In this paper, by capitalising on flexibility resources’ potential, AS 4.0 approach is proposed, which offers a comprehensive solution for the AS provision in the smart grid era