An AI-Layered with Multi-Agent Systems Architecture for Prognostics Health Management of Smart Transformers:A Novel Approach for Smart Grid-Ready Energy Management Systems

After the massive integration of distributed energy resources, energy storage systems and the charging stations of electric vehicles, it has become very difficult to implement an efficient grid energy management system regarding the unmanageable behavior of the power flow within the grid, which can cause many critical problems in different grid stages, typically in the substations, such as failures, blackouts, and power transformer explosions. However, the current digital transition toward Energy 4.0 in Smart Grids allows the integration of smart solutions to substations by integrating smart sensors and implementing new control and monitoring techniques. This paper is proposing a hybrid artificial intelligence multilayer for power transformers, integrating different diagnostic algorithms, Health Index, and life-loss estimation approaches. After gathering different datasets, this paper presents an exhaustive algorithm comparative study to select the best fit models. This developed architecture for prognostic (PHM) health management is a hybrid interaction between evolutionary support vector machine, random forest, k-nearest neighbor, and linear regression-based models connected to an online monitoring system of the power transformer; these interactions are calculating the important key performance indicators which are related to alarms and a smart energy management system that gives decisions on the load management, the power factor control, and the maintenance schedule planning

A step to clean energy - Sustainability in energy system management in an emerging economy context

Due to high consumption of energy, its associated concerns such as energy security and demand, wastage of resources, and material-energy recovery are leading to the importance of sustainable energy system development. This is a high time to assess the sustainability in energy systems for meeting the requirements of energy with an enhanced economic, ecological, and social performance from a nation context. The energy system plays a significant role in deciding the economic progress of emerging economies such as India, China, Brazil, and Africa. In this paper, an original attempt has been made to list and evaluate important indicators for sustainability assessment of energy systems development and management in an emerging economy especially India. Firstly, based on the analysis of the extant literature and then followed by expert opinion, potential key sustainability assessment indicators for energy systems development and management were identified. Further, grey based Decision-Making Trial and Evaluation Laboratory technique to understand the causal interactions amongst indicators and segregate them into cause and effect groups, is used. This work can provide useful aids to decision making bodies, sustainability practitioners and business organisations in selective implementation, monitoring and control of sustainable strategies in energy systems development and management and meeting sustainable development goals of clean energy in a nation context.N

Multivariate KPI for energy management of cooling system in food industry

Within EU, the food industry is currently ranked among the energy-intensive sectors, mainly as a consequence of the cooling system shareover the total energy demand. As such, the definition of appropriate key performance indicators (KPI) for ammonia chillers can play a strategic role for the efficient monitoring of the energy performance of the cooling systems. The goal of this paper is to develop an appropriate management approach, to account for energy inefficiency of the single compressors, and to identify the specific variables driving the performance outliers. To this end, a new KPI is proposed which correlates the energy consumption and the different process variables. The construction of the new indicator was carried out by means of multivariate statistical analysis, in particular using Kernel Partial Least Square (KPLS).This method is able to evaluate the maximum correlation between dataset and energy consumption employing nonlinear regression techniques. The validity of the new KPI is discussed on a case study relevant to the cooling system of a frozen ready meals industry. The assessment of the proposed metric is one against Specific Energy Consumption (SEC) like indicator, typically used in the context of the Energy Management Systems

Proposal for a Performance Dashboard for the Monitoringof Water and Sewage Service Companies (WaSCs)

The water and sewage industry provides an essential service to the community, but it is characterized by natural monopoly tendencies of service suppliers. In this framework, it is very important to assist regulators with a small set of critical indicators (performance dashboard) for the evaluation and monitoring of the service provided by Water and Sewage Companies (WaSCs). The paper originates from the analysis of situation of Piemonte (Italy), where each regional and local body adopts a proprietary Performance Measurement System (PMS). In order to improve the coordination of information flow and to support the definition of common service standards, a methodology to merge existing PMSs and define a unique shared reference system is proposed. The Kaplan and Norton's Balanced Scorecard (BSC) is adopted as the reference model of this approach. BSC is widely recognized to be an exhaustive and balanced framework in describing the performances of an organization and ensures that all the operational aspects of WaSCs are adequately monitored. The output of the proposed procedure is a general performance dashboard for the monitoring of WaSCs. The dashboard is shown and some remarks about indicators properties are developed. In particular, this analysis highlights some common pitfalls originated by a ‘rushed' aggregation of several performance indicators. Description is supported by several example

Measuring social, economic and environmental sustainability at the enterprise level: a case study of an Australian Utility Corporation’s Sustainability Report

The debate on a sustainable future for Australia has focused enterprises on developing triple bottom line or sustainability reports. Enterprises now commonly provide reports to their stakeholders on sustainability. However it is argued in this paper that shortcomings in current reporting practices are limiting the measurement of sustainability. The Global Reporting Initiative (GRI), the most commonly applied consistent framework for enterprises, recommends the application of indicators that consider the inter-relations between the economy, society and the environment. However, these recommendations are not generally being translated into practice by firms. The environmental aspects of enterprise sustainability reports tend to be privileged over the social and economic components. Indicators of the social and economic impact of an enterprise generally draw upon productivity and human relation measurements rather than measures directly relevant to the impact of enterprise actions on the community. To illustrate these arguments we offer a case study of the Australian Gas Light Company, (AGL), 2004 Sustainability Report, and a critique of the GRI. AGL is a large Australian energy company. We argue that inter-related indicators tend not to be considered within enterprise sustainability reports. It is argued that social and economic externalities of enterprises have an impact on surrounding communities and hence should be measured and reported in conjunction with environmental factors. Moreover, these reports should to be developed in a manner that enables the context of sustainability to be adequately explored

Sustainability Assessment Methods for the Gulf Region

This paper describes the development of a sustainability assessment framework designed to be used in the Gulf Region, which is an area which has experienced large scale building development and also a region in which sustainability assessment is not yet widely used. The complexity and time resources needed to apply existing methods act as a deterrent to active use. Three well-known methods available at the time of the study were investigated in some detail. These were: BREEAM Gulf; Green Building Council LEED; and Estidama Pearl. Cross comparisons of the factors involved in each method were carried out on several levels including: theoretical comparison; practical development and usability; compliance with regulations and standards; and ability to achieve synchronization. A considerable degree of compatibility was found to exist between the methods, particularly if focused on key criteria. As a result a new and specific framework was developed which grouped 24 indicators under five principal headings: site/location, biodiversity and accessibility; energy; water; occupant well-being; and resources and wastes. This new framework was then evaluated by testing with practitioners resulting in confirmation of 20 out of the 24 indicators, and identification of suitable benchmarks