Accident Triggered by Electrical Failures in Seveso Sites

Electrical maintenance is important for appropriate of Major Accident Prevention Policy MAPP at Seveso sites. At Seveso sites, many accidents include in the causes an electrical failure, due usually to a poor maintenance. Power outages, in particular, originate cascade effects, leading to a possible loss of hazardous materials. The repository of the minor incidents and near misses recorded at Seveso sites is a valuable source for investigating electrical failures, causes, effects and possible prevention and mitigation measures. The present paper discusses a number of incident records, gathered at Seveso establishments, during the mandatory inspections, required by the Seveso Directive. Gathered documents cover different types of plant, including refineries, oil terminal, LPG depots and chemical plants. They have been analysed, using advanced method, including machine learning. The results of this analysis have been exploited to provide the establishments’ operator with a few recommendations, essential to improve electrical safety and prevent major accidents

False Data Injection Impact on High RES Power Systems with Centralized Voltage Regulation Architecture

The increasing penetration of distributed generation (DG) across power distribution networks (DNs) is forcing distribution system operators (DSOs) to improve the voltage regulation capabilities of the system. The increase in power flows due to the installation of renewable plants in unexpected zones of the distribution grid can affect the voltage profile, even causing interruptions at the secondary substations (SSs) with the voltage limit violation. At the same time, widespread cyberattacks across critical infrastructure raise new challenges in security and reliability for DSOs. This paper analyzes the impact of false data injection related to residential and non-residential customers on a centralized voltage regulation system, in which the DG is required to adapt the reactive power exchange with the grid according to the voltage profile. The centralized system estimates the distribution grid state according to the field data and provides the DG plants with a reactive power request to avoid voltage violations. A preliminary false data analysis in the context of the energy sector is carried out to build up a false data generator algorithm. Afterward, a configurable false data generator is developed and exploited. The false data injection is tested in the IEEE 118-bus system with an increasing DG penetration. The false data injection impact analysis highlights the need to increase the security framework of DSOs to avoid facing a relevant number of electricity interruptions

Smart grids for power quality improvement

In the context of an increasing penetration of Distributed Generators, Distribution System Operators of any size are facing the transition to the Smart Grid, investigating how its role will change in the future. This work will present a comprehensive analysis of how a DSO would face the Power Quality issue in the future thanks to the technologies of the smart grids. The activities have been carried out in collaboration with the DSO of the city of Terni, namely ASM Terni S.p.A. (ASM) and its productivity unit Terni Distribuzione Elettrica (TDE) which owns and manages the distribution network in the municipality. During the work lifespan, there has been the opportunity to evaluate smart technologies and carry out grid analysis in a real environment, notably, the Medium Voltage distribution network of TDE and the living laboratory at ASM headquarters. Some activities have been totally developed within this work whilst others have been carried out in the context of some European projects that have been founded or cofounded by the Innovation and Research & Innovation actions for Energy sector established by the European Commission and involve ASM as consortiums’ partner. The consortiums of these projects have designed, produced and installed in the ASM facilities cutting-edge devices and software solutions for the distribution network and the electrical customers; this work has evaluated their contribution on the power quality. Considering Smart Grid definition, it is important to understand what is currently Power Quality for a DSO; in this respect, the main objective of a DSO is to reduce the interruptions, secondly abnormal voltages are also an issue as well as the reduction of technical losses (i.e., increasing the energy efficiency). However, DSOs are focused on outages since it means the lack of its main services to the users, namely, electrical energy, which also dramatically affects other crucial services such as Telecommunication, heating, cooling, water, industrial processes. Moreover, the Italian DSOs, which have been studied in this work, receive monetary incentives or have to pay penalties if the outages, recorded in a year, are less than defined objectives or more than these. Investigating on reduction of outages implies an increase of resilience of the distribution network, as the ability of a DSO to promptly react when a foreseen event and rapidly restore the network to the normal status. The reduction of outages are investigated in this work considering contributions on the network development plans and on real time operations. Therefore, in a first stage, the analysis of a component widely installed in the Italian distribution networks has been carried out; notably thermal analysis of MV cable and joint is performed in order to investigate on the anomalous number of faults on this component that have been recorded in summer during last years. Moreover, the distribution network of TDE has been analyzed with a Resilience assessment software and its related procedures for improving and validating the development plan of the distribution network. The homemade software, developed during this work lifespan, can be used for any networks and the resilience can be assessed for any type of treats. The last stage consists of theoretical evaluations and demonstration activities of innovative solutions that could help the DSO to reduce congestions in the network during real time operation (i.e., to prevent and foreseen outages). The enabling tools that have been used are Real time Smart Meters installed in the networks and proper management software. In this respect, main concern of this work has been the interaction between DSO and Aggregator who manages a pool of users in the Demand Response campaigns. The evaluated mechanisms allow DSO to increase hosting capacity of the network in respect of Photovoltaic plants (PV) and Electrical Vehicles (EV). Moreover, this work presents assessment on cooperation mechanism between DSO and a rural microgrid by means of a proper ICT infrastructure. In the context of power quality improvement thanks to the Smart Grids, further technologies have been evaluated in this work. With respect to the energy efficiency and voltage control, the support from storage systems have been studied by means of tests on the field, as well as it has been assessed the support from EV charging stations coordinate with the implementation of smart contracts leveraging on blockchain technology

Comparison of Baseline Load Forecasting Methodologies for Active and Reactive Power Demand

Forecasting the electricity consumption is an essential activity to keep the grid stable and avoid problems in the devices connected to the grid. Equaling consumption to electricity production is crucial in the electricity market. The grids worldwide use different methodologies to predict the demand, in order to keep the grid stable, but is there any difference between making a short time prediction of active power and reactive power into the grid? The current paper analyzes the most usual forecasting algorithms used in the electrical grids: ‘X of Y’, weighted average, comparable day, and regression. The subjects of the study were 36 different buildings in Terni, Italy. The data supplied for Terni buildings was split into active and reactive power demand to the grid. The presented approach gives the possibility to apply the forecasting algorithm in order to predict the active and reactive power and then compare the discrepancy (error) associated with forecasting methodologies. In this paper, we compare the forecasting methodologies using MAPE and CVRMSE. All the algorithms show clear differences between the reactive and active power baseline accuracy. ‘Addition X of Y middle’ and ‘Addition Weighted average’ better follow the pattern of the reactive power demand (the prediction CVRMSE error is between 12.56% and 13.19%) while ‘Multiplication X of Y high’ and ‘Multiplication X of Y middle’ better predict the active power demand (the prediction CVRMSE error is between 12.90% and 15.08%)

Transition to electric vehicles in a company's fleet. Design and policy on a case study

Many private and public companies are moving towards fleet electrification; this new trend is significantly fostered by public strategies about decarbonization, market conditions and companies' policies for reducing their carbon footprint. Nevertheless, the impact of the electrical fleet on logistics and electrical consumptions has not been extensively evaluated in the literature. This paper aims to assess these impacts considering the data of an existing traditional fleet. The presented model takes into account several parameters and conditions and it validates different policies and design solutions. The results show that the proposed solutions would enable company managers painlessly adopting electric vehicles in their fleets

Moving towards self-consumption and self-sufficiency: COVID-19 impact in the city of Terni

This paper presents a statistical analysis on producers’ data collected between 2015 and 2020 by the DSO in the city of Terni (Italy). The integration of prosumers with the electrical system is investigated through appropriate indicators, such as self-consumption and self-sufficiency, the case study is placed within the Italian and International scenario and enriched with comments and observations. In particular, effects of Covid-19 pandemic to prosumers’ behaviour are reported, highlighting an increasing of self-consumption by domestic prosumers, in line with the European and national policy

Exploiting RES for Hydrogen mobility: a new scenario for the company's fleet management

Hydrogen aroused a great interest in the last decades as a promising energy vector for the energy transition as well as renewable energy storage. This article investigates the technical feasibility of a hydrogen-powered fleet, in the context of a microgrid with renewable generation. The hydrogen demand is satisfied through the electrolyser powered by local RES and periodical external refueling of a local hydrogen storage system. The model of the microgrid is implemented in the open-source GNU Octave environment and is exploited to size the local storage capacity. Different types of vehicles were considered and hydrogen pressure levels were distinguished among the system components. The model was applied to the waste collection fleet and the headquarters of ASM S.p.A., a utility located in the center of Italy, chosen as a case study. The dataset of 143 vehicles was used to model the hydrogen-powered fleet. Three scenarios were evaluated: hydrogen production using i) Reverse Power Flow, ii) PV production and iii) electricity drown from the grid. The storage capacity depends on the scenarios and in the case study it ranges from about 35 to 47 m^3 , in comparison with 13.6 m^3 of current diesel refueling system, assuming the same frequency of external refueling

Optimizing EV company fleet management in an energy district

In the context of the widespread of electrical vehicles and electrical company fleets, this paper investigates optimal strategies for scheduling the charging sessions in an energy district. Indeed, the adoption of charging stations and electric vehicles could dramatically impact the load profiles of private companies, nevertheless, there is an opportunity to consider the vehicle recharge flexible by design. For this reason, the paper shows an optimization model for managing the charging sessions and its application in a real energy district. The presented results were collected after simulating several configuration scenarios, main findings highlight benefits for the operators that could justify the adoption of these strategies on their fleets

Electrical Energy Production from Natural Gas. Technical and Economic Performances during the Last Twenty Years

During the last twenty years (2000 - 2020) natural gas was the second fuel for electrical energy production. Even if its availability could be affected by force majeure events because of its geographical distribution, it has still a great share in many countries. The paper presents an analysis of the last twenty years of natural gas production, it analyses the technical indicators (i.e., capacity factor, energy efficiency and emissions) as well as the levelized cost of energy. The work is based on data publicly available, evaluating the actual working conditions of the power plants supplied by natural gas. Main outcomes show that actual indicators are significantly lower than rated values; this is mainly due to market conditions that are often unfavorable for production from coal. Finally, the results can be used for adjusting the most recent energy policies, that are going to face new market conditions because of force majeure events (i.e., Ukraine invasion) as well as decarbonization processes, already developed in many European countries