Communications for smart grid substation monitoring using WIMAX protocol

The SMARTGRID is a general term for a series of infrastructural changes applied to the electric transmission and distribution systems. By using the latest communication and computing technology, additional options such as Condition Monitoring can now be implemented to further improve and optimise complex electricity supply grid operation. Lifecycle optimisation of high voltage assets and other system components in the utility provide a case in point. Today Utility experts agree that application of scheduled maintenance is not the effective use of resources. To reduce maintenance expenses and unnecessary outages and repairs of equipment due to scheduled maintenance, utilities are adopting condition based approaches. Real time online monitoring of substation parameters can be achieved by retrofitting the existing substation with SMARTGRID technology. The IEC 61850 is a common protocol meant for Substation Automation Systems, designed for the purpose of establishing interoperability, one that all manufacturers of all different assets must comply with. This thesis advocates the estimation of bandwidth required for monitoring a substation after retrofitting the existing substation with smart communication technologies. This includes establishing a latest wireless communication infrastructure from the substation to the control centre and evaluating the performance modelling and simulating the physical layer of communication technologies such as WIMAX (IEEE802.16) and MICROWAVE point to point using MATLAB SIMULINK and RADIO mobile online simulation software. Also, link budget of the satellite communication for the same application is calculated. Satellite communication in this case is considered as a redundant or back up technology to ensure that the communication between entities is continuous. On performing the simulation on different environments the results prove that the selected protocols are best suited for condition monitoring. The measured Latency could be the best approximated value which complies with the current objective. However the white noise that exists in the substation has significant hazard with respect to the security of the wireless network. To compensate this constraint whole substation is hard wired by means of plastic fibre optics and the data sent to the base station located near the substation

Cost drivers of integrated maintenance in high-value systems

High value systems are determined by a wide structure, where operations are considered to be one structural component. Nowadays “down-time” as a major impact in the operation costs of any system. To avoid or minimize “down-time” it is essential to match the appropriate maintenance to each failure. Therefore, it is relevant to determine the cost drivers of integrated maintenance in any system, in order to minimize the overall cost. It is common to use Value Driven Maintenance (VDM) to capture the cost drivers in maintenance. VDM is a methodology which relies in four distinct areas: Asset Utilization; Resource Allocation; Control Cost and Health and Safety and Environment. Within each category it is possible to allocate different cost drivers, building a framework for each system studied. The aim of this paper is to categorize the cost drivers of rail infrastructure networks, associating them with the maintenance preformed for each case. Furthermore, analysis of which part of the track falls under each VDM category as well as the general failure causes and effects will be included in the framework presented. Finally relating the maintenance type for each effect will provide the necessary inputs towards a cost model structure. The benefit of achieving a successful model will be the optimization of the cost in integrated maintenance of the rail infrastructure

The impact of bad sensors on the water industry and possible alternatives

Advanced monitoring of water quality in order to perform a real-time hazard analysis prior to Water Treatment Works (WTW) is more important nowadays, both to give warning of contamination and also to avoid downtime of the WTW. Downtimes could be a major contributor to risk. Any serious accident will cause a significant loss in customer and investor confidence. In this paper, two treatment plants (case studies) were examined. One was a groundwater WTW and the other a river WTW. The results showed that good correlations existed between the controlling parameters measured at the river WTW, but not at the Groundwater Treatment Works (GWTW), where there was a lack of good correlation between warning parameters. Results emphasised the value of backup monitoring and self-adjusting automation processes that are needed to counteract the rise in power costs. The study showed that a relationship between the different types of sensors and/or measured parameters can be deduced in order to cross-check the sensors performance and be used as a guide to when maintenance is really needed. Operating hierarchal procedures within the WTWs could also be used to cut costs, by improving condition monitoring. Both of the case studies highlighted the need for new non-invasive/remote sensors and some new investment in information technology infrastructure

Implementing intelligent asset management systems (IAMS) within an industry 4.0 manufacturing environment

9th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2019; Berlin; Germany; 28 August 2019 through 30 August 2019. Publicado en IFAC-PapersOnLine 52(13), p. 2488-2493This paper aims to define the different considerations and results obtained in the implementation in an Intelligent Maintenance System of a laboratory designed based on basic concepts of Industry 4.0. The Intelligent Maintenance System uses asset monitoring techniques that allow, on-line digital modelling and automatic decision making. The three fundamental premises used for the development of the management system are the structuring of information, value identification and risk management

Importance and applications of robotic and autonomous systems (RAS) in railway maintenance sector: a review

Maintenance, which is critical for safe, reliable, quality, and cost-effective service, plays a dominant role in the railway industry. Therefore, this paper examines the importance and applications of Robotic and Autonomous Systems (RAS) in railway maintenance. More than 70 research publications, which are either in practice or under investigation describing RAS developments in the railway maintenance, are analysed. It has been found that the majority of RAS developed are for rolling-stock maintenance, followed by railway track maintenance. Further, it has been found that there is growing interest and demand for robotics and autonomous systems in the railway maintenance sector, which is largely due to the increased competition, rapid expansion and ever-increasing expense

Index for asset value measure obtained from condition monitoring digitalized data interpretation. A railway asset management application

Hosted by the Johannes Kepler University, Linz, Austria. May 23-24, 2019The objective of any asset is to provide value to the organization, being the corner stone to get a highest possible economic benefit in a sustainable way. An effective asset value management demands method that allow measuring and comparing the expected value with the real value realized at any time during its life cycle for value informed decision-making. Digitalization is providing new data about events and states related to asset condition and risk, information that can be reinterpreted to generate value measure strategies. This paper presents a proposal of TVO (Total Value of Ownership) model where it is possible to quantify and measure the value, including its monitoring throughout the life cycle of the asset and/or system. Proposed TVO model is focused on Safety, one of the most relevant value factors for Industry and Infrastructure sectors. Asset events and states are intrinsically linked to the defined failure modes. Consequently, it is necessary to structure the system information around the failure modes that have been defined, in order to obtain a value measurement index. A railway use case is presented

Uncertainty of net present value calculations and the impact on applying integrated maintenance approaches to the UK rail industry

The Public performance indicator (PPI) is an important Key Performance Indicator for Network Rail and monitored carefully by the organisation and their external stakeholders. Condition monitoring is of increasing interest within network rail as a suitable method for increasing asset reliability and improving the PPI metric. As condition monitoring methods are identified each will need assessment to establish the cost and benefit. Benefit can be measured in cost savings as poor PPI performance results in fines. Within many industries Net Present Value (NPV) calculations are used to determine how quickly investments will break-even. Cost-risk is a term that is used to describe the financial impact of an unexpected event (a risk). This paper outlines a more detailed approach to calculating NPV which considers the cost-risk effect of changes of the denial of service charging rate. NPV prediction is of importance when assessing when to deploy different fault detection strategies to maintenance issues, and therefore the cost-risk of the NPV calculation should be used to support asset management decisions

Mapping and assessment of ecosystems and their services. Urban ecosystems

Action 5 of the EU Biodiversity Strategy to 2020 requires member states to Map and Assess the state of Ecosystems and their Services (MAES). This report provides guidance for mapping and assessment of urban ecosystems. The MAES urban pilot is a collaboration between the European Commission, the European Environment Agency, volunteering Member States and cities, and stakeholders. Its ultimate goal is to deliver a knowledge base for policy and management of urban ecosystems by analysing urban green infrastructure, condition of urban ecosystems and ecosystem services. This report presents guidance for mapping urban ecosystems and includes an indicator framework to assess the condition of urban ecosystems and urban ecosystem services. The scientific framework of mapping and assessment is designed to support in particular urban planning policy and policy on green infrastructure at urban, metropolitan and regional scales. The results are based on the following different sources of information: a literature survey of 54 scientific articles, an online-survey (on urban ecosystems, related policies and planning instruments and with participation of 42 cities), ten case studies (Portugal: Cascais, Oeiras, Lisbon; Italy: Padua, Trento, Rome; The Netherlands: Utrecht; Poland: Poznań; Spain: Barcelona; Norway: Oslo), and a two-day expert workshop. The case studies constituted the core of the MAES urban pilot. They provided real examples and applications of how mapping and assessment can be organized to support policy; on top, they provided the necessary expertise to select a set of final indicators for condition and ecosystem services. Urban ecosystems or cities are defined here as socio-ecological systems which are composed of green infrastructure and built infrastructure. Urban green infrastructure (GI) is understood in this report as the multi-functional network of urban green spaces situated within the boundary of the urban ecosystem. Urban green spaces are the structural components of urban GI. This study has shown that there is a large scope for urban ecosystem assessments. Firstly, urban policies increasingly use urban green infrastructure and nature-based solutions in their planning process. Secondly, an increasing amount of data at multiple spatial scales is becoming available to support these policies, to provide a baseline, and to compare or benchmark cities with respect to the extent and management of the urban ecosystem. Concrete examples are given on how to delineate urban ecosystems, how to choose an appropriate spatial scale, and how to map urban ecosystems based on a combination of national or European datasets (including Urban Atlas) and locally collected information (e.g., location of trees). Also examples of typologies for urban green spaces are presented. This report presents an indicator framework which is composed of indicators to assess for urban ecosystem condition and for urban ecosystem services. These are the result of a rigorous selection process and ensure consistent mapping and assessment across Europe. The MAES urban pilot will continue with work on the interface between research and policy. The framework presented in this report needs to be tested and validated across Europe, e.g. on its applicability at city scale, on how far the methodology for measuring ecosystem condition and ecosystem service delivery in urban areas can be used to assess urban green infrastructure and nature-based solutions