Combination of statistical process control (SPC) methods and classification strategies for situation assessment of batch processes

Postprint (published version

Probabilistic models to assist maintenance of multiple instruments

The paper discusses maintenance challenges of organisations with a huge number of devices and proposes the use of probabilistic models to assist monitoring and maintenance planning. The proposal assumes connectivity of instruments to report relevant features for monitoring. Also, the existence of enough historical registers with diagnosed breakdowns is required to make probabilistic models reliable and useful for predictive maintenance strategies based on them. Regular Markov models based on estimated failure and repair rates are proposed to calculate the availability of the instruments and Dynamic Bayesian Networks are proposed to model cause-effect relationships to trigger predictive maintenance services based on the influence between observed features and previously documented diagnostic

Leveraging bi-directional EV charging for flexibility services in the distribution grid - the case of fever project

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistributionDistribution System Operators face a challenging environment largely affected by the ever-growing integration of Distributed Energy Resources. Especially, Electric Vehicles have a rapidly growing presence in the distribution grids, being both a challenge, but also an enabler for active network management. This work analyses the operation of charging infrastructures in coordination with the DSO in the context of the FEVER project. The objective of the project is to exploit control of power flow through DC/AC converters towards demand management and voltage compensation. The paper describes the different modules required to coordinate this operation in a flexibility market context. DSO support tools have been developed to forecast possible critical events and prepare a mitigation plan leveraging flexibility. Response to this flexibility demand is covered by Vehicle-to-Grid charging stations, equipped with DC converters, capable of implementing flexibility strategies.Peer ReviewedObjectius de Desenvolupament Sostenible::13 - Acció per al ClimaObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantPostprint (published version

Developing novel technologies and services for intelligent low voltage electricity grids: cost–benefit analysis and policy implications

The paper presents a set of prototype smart grid technologies and services and validates the economic viability of the proposed solution using cost–benefit analysis (CBA). The study considered the EU-funded project called RESOLVD and implemented the technologies and services in a real-life pilot. the technologies and services on the EU-funded H2020. The paper focuses on the analysis of technological solutions which enhance the operational efficiency and the hosting capacity of low-voltage electricity distribution grids. The solutions provided better integration of a hybrid battery storage system, with the grid interfacing power electronics, smart gateways for the interconnection of assets at the grid edge, and sensors enhancing infrastructure observability and control. The result from the CBA indicates the economic viability of the project, high scalability, and replicability. The economic benefits were realized with the breakeven value of eight secondary substations (SS) and 16 feeders. The scenario test on the DSO’s willingness to pay for the software as a service (SaaS) revealed that the payback period can further be reduced by almost half with a higher internal rate of return (IRR) and net present value (NPV). Both the CBA and scenario tests showed RESOLVD solution can become more economically viable when deployed in largescale. Moreover, the CBA results provide evidence to the energy policy by allowing DSOs to consider both CAPEX and OPEX for better investment decisions. Further, the paper proposes an alternative business approach that shifts from grid reinforcement to service provision. The paper also discusses the research implications on energy policy and business.Peer ReviewedObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraObjectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats SosteniblesPostprint (published version

Integration of knowledge-based, qualitative and numeric tools for real time dynamic systems supervision

The proposal presented in this thesis is to provide designers of knowledge based supervisory systems of dynamic systems with a framework to facilitate their tasks avoiding interface problems among tools, data flow and management.The approach is thought to be useful to both control and process engineers in assisting their tasks. The use of AI technologies to diagnose and perform control loops and, of course, assist process supervisory tasks such as fault detection and diagnose, are in the scope of this work. Special effort has been put in integrationof tools for assisting expert supervisory systems design. With this aim the experience of Computer Aided Control Systems Design (CACSD) frameworkshave been analysed and used to design a Computer Aided Supervisory Systems (CASSD) framework. In this sense, some basic facilities are required to be available in this proposed framework:·ion Tools, for signal processing,representation and analysis to obtain significative information.· To deal with process variables, measures or numerical estimations, and expert observations, with uncertainty and imprecision.· Expert knowledge representation at different levels by using a rule-based system or simple qualitative relations.· Modularity and encapsulation of data and knowledge would be useful for structuring information.· Graphical user interface to manage all those facilities in the same environment as actual CACSD packages.Several tools from the AI domain have been added as Simulink ToolBoxes to deal with abstracted information, qualitative relationship and rule-based ES. Simple and intuitive qualitative relationship can be implemented by means of ablock-based qualitative representation language called ALCMEN. An ES shell, called CEES, has also been embedded into MATLAB/Simulink as a block toallow modularisation and partition of large expert KBs. Finally, the numeric to qualitative interfaces is performed by a set of algorithms, called abstraction tools, encapsulated also in Simulink blocks. The functionality of the wholeframework is able due to the use of object oriented approach in the development and implementation of those tools.In this thesis an attempt is undertaken to make steps towards integration of tools for expert supervision, including once for qualitative and symbolic data representation and management and symbolic knowledge processing. The main research objectives of this work include the following points :1. Incorporation of object-variables into classical numerical data processing system. The aim is to allow structural qualitative and symbolic knowledge representation. Complex information is encapsulated in a single source/sink structure, called object-variable, providing methods for knowledge access and processing.2. Implementation of selected particular tools for qualitative and symbolic knowledge representation and interfacing. Higher abstract level information processing based on the introduced object-variables.3. Embedding an object oriented rule-based expert system into a classical CACSD framework in order to provide high level knowledge processing facilities based on the domain of expert knowledge, heuristics, and logic.The object approach forces engineers to structure knowledge becoming highly locatable, modular and encapsulated. This features are very important to getexpert supervisory system design closer to process. The objective is to approach design tools to process engineers avoiding extra-time in learning application functionality and interfacing process variables and design tools. Thus, objects are used in the process variables descriptions as sources of information, encapsulating tools to provide significant (qualitative or numerical) information. Object oriented features will permit to divide large KBs into smaller ones to deal with complex systems adopting distributed solutions. Consequently, ES becomes more specialised, maintainable, and easier to validate

Inteligencia artificial para la detección y el diagnóstico de fallos

L' ús de tècniques de la intel·ligència artificial per a la detecció, la diagnòsi i control d' error

Visual management of sags and incidents gathered in distribution substations for power quality management

Monitor a distribution network implies working with a huge amount of data coining from the different elements that interact in the network. This paper presents a visualization tool that simplifies the task of searching the database for useful information applicable to fault management or preventive maintenance of the networ

Probabilistic models to assist maintenance of multiple instruments

The paper discusses maintenance challenges of organisations with a huge number of devices and proposes the use of probabilistic models to assist monitoring and maintenance planning. The proposal assumes connectivity of instruments to report relevant features for monitoring. Also, the existence of enough historical registers with diagnosed breakdowns is required to make probabilistic models reliable and useful for predictive maintenance strategies based on them. Regular Markov models based on estimated failure and repair rates are proposed to calculate the availability of the instruments and Dynamic Bayesian Networks are proposed to model cause-effect relationships to trigger predictive maintenance services based on the influence between observed features and previously documented diagnostic

Visual management of sags and incidents gathered in distribution substations for power quality management

Monitor a distribution network implies working with a huge amount of data coining from the different elements that interact in the network. This paper presents a visualization tool that simplifies the task of searching the database for useful information applicable to fault management or preventive maintenance of the networ