Electricity infrastructure enhancement for the security of supply against coordinated malicious attacks

© 2016 IEEE. The impact of coordinated malicious attacks may be dramatically severe and may yield a wide area blackout. A preventive measure is enhancing the infrastructure through investment. Due to limited budget, a decision making is required to select the best possible options, considering cost/benefit ratio. We designed a time-step simulation framework representing the evolution of post-contingency failures and load/system restoration. System unserved energy is translated into economic losses. Different enhancement options can be compared in terms of benefit (reduction in the cost of unserved energy) and of cost (investments needed) to eventually rank them. The simulation framework also provides a way to derive an optimal lost load recovering strategy to accelerate system restoration. In this paper the simulation framework is applied to a real network (Austrian transmission grid) to evaluate the technical and economic impacts of a coordinated malicious attack

Techno-economic impacts of automatic undervoltage load shedding under emergency

© 2015 Elsevier B.V. All rights reserved. Different schemes for voltage control under emergency are adopted in different jurisdictions around the world. While some features, such as Automatic Voltage Regulation (AVR), are common in all countries, for what concerns undervoltage load shedding (UVLS), to contrast voltage instability or collapse, different schemes are adopted. Most US transmission system operators (TSOs) adopt automatic UVLS schemes, with different capabilities and settings while TSOs in EU usually do not implement automatic UVLS but leave the decisions to the control room operators. The two options may lead to different impacts in terms of trajectory and final status of the transmission grid under emergency, with different unserved energy. In this paper we analyze the impacts from a technical and economic perspective, modeling the grid behavior with different UVLS schemes (none, manual and automatic). The comparison between the different schemes is done resorting to the Incident Response System (IRS), a software tool developed by the authors in the EU-FP7 SESAME project. An illustrative example to a realistic test case is presented and discussed. This paper shows that automatic UVLS is superior to Manual UVLS, from both technical and economic point of view, due to the fast evolution of voltage collapse phenomena and insufficient time for system operators' manual reaction. The benefits of the scheme involving the automatic UVLS can be then compared with the investment costs of equipping the network with those devices

Optimal battery charge/discharge strategies for prosumers and suppliers

We discuss the application of classical variational methods to optimal charging/discharging strategies for a prosumer or storage supplier, where the price of electrical power is known in advance. We outline how a classical calculus of variations approach can be applied to two related problems: (i) how can a prosumer minimise the cost of charging/discharging a battery, when the price of electrical power is known throughout the charging/discharging period? and (ii) how can an electricity supplier incentivise desired prosumer/storage supplier behaviour by adjusting the price

Nonsy load flow: Smart grid load flow using non-synchronized measurements

© 2017 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 redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This paper presents a novel algorithm for load flow analysis in smart grids, using non-synchronized measurements collected at the main substation and at the terminals of Distributed Generators (DGs) and microgrids. This allows the use of already available measurements along with a proper communication system to calculate the magnitude and phase angle of nodal voltages, power flow in each branch, power injected by each electricity source, and system losses. The proposed non-synchronized measurements-based load flow (Nonsy load flow) algorithm is based on the conventional backward-forward sweep and it considers the synchronization angles as unknown variables to be calculated. Simulation studies on a smart grid model with several DG units and microgrids validate the performance of the proposed method. In all the studied cases, the load flow results are accurate and the unknown synchronization angles are precisely calculated as a byproduct of the algorithm without any significant extra computational effort. The calculated synchronization angles can satisfy the need of other smart grid applications requiring synchronized measurements

Power grids vulnerability: a complex network approach

Power grids exhibit patterns of reaction to outages similar to complex networks. Blackout sequences follow power laws, as complex systems operating near a critical point. Here, the tolerance of electric power grids to both accidental and malicious outages is analyzed in the framework of complex network theory. In particular, the quantity known as efficiency is modified by introducing a new concept of distance between nodes. As a result, a new parameter called net-ability is proposed to evaluate the performance of power grids. A comparison between efficiency and net-ability is provided by estimating the vulnerability of sample networks, in terms of both the metrics.Comment: 16 pages, 3 figures. Figure 2 and table II modified. Typos corrected. Version accepted for publication in Chao

An improved fault location method for distribution networks exploiting emerging LV smart meters

© 2016 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 redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. In the last years, the electrical distribution systems are undergoing one of their largest transitions in their long history towards smart grids. One of the key requirements and the first step in the path of smart grid is developing and deploying smart metering systems in distribution networks. In this regard, several projects co-funded by the European Commission (EC) have been carried out. FLEXMETER is one of the ongoing EU Horizon 2020 projects aiming at the development and demonstration of a flexible smart metering architecture. In this paper, first the different available measurements in the FLEXMETER project are introduced. Then different fault location methods are compared qualitatively and quantitatively to find the most appropriate one based on the FLEXMETER infrastructure. Finally a combined method as a hybrid solution is proposed to overcome the drawbacks of the previously proposed ones, while keeping their advantages

A comparison framework for distribution system outage and fault location methods

Finding the location of faults in distribution networks has been a long standing problem for utility operators, and an interesting subject for researchers as well. In recent years, significant research efforts have been devoted to the development of methods for identification of the faulted area to assist utility operators in expediting service restoration, and consequently reducing outage time and relevant costs. Considering today's wide variety of distribution systems, a solution preferred for a specific system might be impractical for another one. This paper provides a comparison framework which classifies and reviews a relatively large number of different fault location and outage area location methods to serve as a guide to power system engineers and researchers to choose the best option based on their existing system and requirements. It also supports investigations on the challenging and unsolved problems to realize the fields of future studies and improvements. For each class of methods, a short description of the main idea and methodology is presented. Then, all the methods are discussed in detail presenting the key points, advantages, limitations, and requirements

Innovative Higher Education Approaches for Power System Courses

Higher education plays a crucial role in modern society and in emerging energy systems, due to the rising complexity of the phenomena and the interplay among various layers (physical, cyber, social and economic). To cope with this context, universities need to develop new visions and tools for education and training. Real-time simulation (RTS) is emerging as a novel and effective approach to analyzing power system aspects, and this characteristic can be effectively used in power system courses. Hence, after the presentation of the basics about the RTS, the paper will show the advantages of employing RTS for teaching activities. Finally, two examples of didactic activities involving RTS at Politecnico di Torino will be presented. In fact, RTS is part of both multi-disciplinary projects (where students with different backgrounds can face the issues affecting the protection and control of power systems) and the course “Electrical systems and safety”, where RTS is used to study the behavior of voltage transformers in saturation

Remote Hardware-In-the-Loop Measurement System for Electrolyser Characterization

© 2019 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 redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The installation of facilities replicating the realworld condition is often required for carrying out meaningful tests on new devices and for collecting data with the aim to create realistic device model. However, these facilities require huge investments, as well as areas where they can be properly installed. In this paper, we present a test infrastructure exploiting the concept of Remote Power Hardware-In-the-Loop (RPHIL), applied for characterizing the performances of a 8kW Proton Exchange Membrane (PEM) electrolyser installed at the Hanze University of Applied Sciences in Groningen (The Netherlands). The electrolyser is subjected to different test conditions imposed both locally and remotely. The results show that this measurement procedure is effective and can open new perspectives in the way to share and exploit the existing research infrastructure in Europe

Predictive methods of electricity price: An application to the Italian electricity market

Price forecasting is a crucial element for the members of the electricity markets and business decision making to maximize their profits. The electricity prices have an impact on the behavior of market participants, and thus, predicting prices for generation companies, and consumers is essential for both the short-term profits in the Day-Ahead, Intra-Day and Ancillary markets, and the long-term benefits in the future planning, investment, and risk management. Therefore, participants in the electricity market need to accurately and effectively predict the price signal to manage market risk. In this paper, different forecasting models have been compared, and the most promising ones have been employed to forecast the short term Italian electricity market clearing price for achieving forecasting accuracy. In particular, simulations are performed for four principal regression methods, including Support Vector Machine, Gaussian Processes Regression, Regression Trees, and Multi-Layer Perceptron. The performance of predicted models is compared through several performance metrics, including MAE, RMSE, R, and the total number of percentage error anomalies. The results indicate the SVM is the best choice for forecasting the electricity market price on the Italian case study