This paper proposes a new mode of cyber-physical attack based on injecting false commands, which poses an increasing risk to modern power systems as a typical example of Cyber-Physical Systems (CPS). Such attacks can trigger physical attacks by driving the system into vulnerable states. To address the critical issues arising from this new mode, we define an inverse-community (IC) in power flow distribution and evaluate it using inversemodularity. To identify the most vulnerable state of the IC that represents the inherent vulnerability of the system, we employ a full malicious power dispatch problem. We also analyze an example of the proposed mode, where a partial malicious power dispatch that maximizes inverse-modularity is combined with physical attacks aimed at disconnecting vulnerable IC boundary lines, making cascading failures highly likely. To demonstrate the potential impact of this coordinated cyber-physical attack, we use the IEEE-118 and IEEE-300 bus systems for simulation. The results show the effectiveness of this attack strategy and provide a new perspective to analyze cyber-physical security issues in modern power systems.

The development of energy infrastructure is crucial for the fulfilment of multifaceted European Union (EU) policy objectives in the energy field. The EU’s support to projects is financial, technical, and political, and explicated through a series of legislative acts. This opinion aims to provide an overview of the main energy policy initiatives introduced in recent years (or soon to be introduced) and their impact on European energy infrastructure development. Examples include the revision of the Trans-European Networks for Energy, funding mechanisms to foster sustainable investments in renewable energies, and the EU taxonomy on sustainable activities. We also discuss possible future improvements of EU policy and regulatory frameworks on energy with the aim of supporting an efficient achievement of the European Green Deal objectives.

Interoperability becomes a key issue for smart grid systems, as the interaction between diverse components needs to lead to a normal system operation. In this paper, we test interoperability issues with respect to home automation. In particular, interaction of a home energy management system (HEMS) is examined with an external actor for home/building remote control. We show the importance and the feasibility of remotely controlling domestic loads from outside the house premises, which can be crucial for energy saving operations, such as demand response. The Smart Grid Architecture Model (SGAM) is used, where the different actors are depicted. The interoperability testing methodology for smart grids, developed by our unit, is followed in order to design the necessary tests and execute them. For the experimental part, we develop an HEMS in our lab along with a Home Automation End Device (HAED), used to transform two normal plugs, and consequently, normal loads into smart ones, thus creating a system for home automation and control. The described configuration is only one possible configuration out of the available ones existing in the market for home automation. LabVIEW programming is used in order to realize the actual explicit demand response program through remote load control and scheduling. The results show that explicit demand response can be achieved by an external actor with success and interoperability is preserved.

The contributions of this article include a new concept, a new question, and a new method. This article proposes the concept of functional community, which is different from conventional topological community. Functional community is defined with two meanings: (1) tighter internal coupling for better efficiency within the same community; (2) more internal transmission from source to sink nodes within the same community. Then a new question about how to detect functional communities in power grids is analyzed, and most existing algorithms are not applicable. Therefore, a new method is put forward. Corresponding to meaning 1, electrical coupling strength (ECS) is defined to replace conventional adjacency matrix; corresponding to meaning 2, power supply strength is defined and integrated with ECS to form the newly defined electrical functional strength. Based on these two changes, we apply the proposed power supply modularity as a benchmark to evaluate any partitioning of power grids. Moreover, the Newman fast algorithm is modified with power supply modularity maximization to detect functional communities in power grids. The capability of the proposed partitioning method is demonstrated via the IEEE-118, IEEE-300 bus systems, and an Italian power grid. We argue that the conventional topological modularity may exaggerate the community characteristics of power grids and is inferior to the power supply modularity in detecting some functional features in communities. The work can also give inspiration to other engineering networks for functional communities.

This paper presents a novel benchmark system for the simulation of low-voltage networks. Two different versions are provided for dynamic simulations over short time intervals and for power flow studies over longer time horizons. The model description is accompanied by a comprehensive open-source documentation in order to facilitate the utilisation, tuning and expansion of the model by external users. This documentation includes the model implementation files in a Matlab/Simulink environment and a detailed description of the network and its components according to the PreCISE methodology. Finally, the model is extensively tested in simulation, considering two distinct test cases from the Erigrid 2.0 test case library.

AbstractThis chapter presents the evolution of EU energy policy, examining how concepts of inclusiveness and justice in energy have been progressively included in relevant energy policy documents. It discusses how EU energy policy has evolved to acknowledge the importance of the individual as well as the collective dimension of energy for an inclusive green transition. Recognizing the challenges linked to the translation of these concepts into concrete actions, the chapter elaborates a socio-energy system approach that can help in making visible important aspects of the energy transition that would go unrecognized in other analytical approaches that focus mainly on the technological side. There is an increasing awareness that the European Green Deal and other political initiatives for a sustainable future require not only technological change but also careful attention to the social implications of the transition. The chapter applies the proposed approach to smart metering technologies, discussing how the technology-centric view of the energy system is framed around the average consumer or early-adopter, leaving vulnerable groups and those living in energy poverty underrepresented. A socio-energy approach also challenges the predominant use of purely quantitative results such as energy or cost savings to evaluate the successfulness of initiatives tackling inclusiveness and fairness (e.g. energy poverty). Social outcomes of energy policy choices and technology arrangements need to be better investigated and accompanied by innovative ways to measure their success. The proposed socio-energy approach offers a way of including wider societal implications of the energy transition in the design of energy policies and in their implementation.

The worldwide spread of the COVID-19 pandemic in 2020 forced most countries to intervene with policies and actions—including lockdowns, social-distancing and smart working measures—aimed at mitigating the health system and socio-economic disruption risks. The electricity sector was impacted as well, with performance largely reflecting the changes in the industrial and commercial sectors operations and in the social behavior patterns. The most immediate consequences concerned the power demand profiles, the generation mix composition and the electricity price trends. As a matter of fact, the electricity sectors experienced a foretaste of the future, with higher renewable energy penetration and concerns for security of supply. This paper presents a systemic approach toward assessing the impacts of the COVID-19 pandemic on the power sector. This is aimed at supporting decision making—particularly for policy makers, regulators, and system operators—by quantifying shorter term effects and identifying longer term impacts of the pandemic waves on the power system. Various metrics are defined in different areas—system operation, security, and electricity markets—to quantify those impacts. The methodology is finally applied to the European power system to produce a comparative assessment of the effects of the lockdown in the European context.

Cross-border electricity interconnections are important for ensuring energy exchange and addressing undesirable events such as power outages and blackouts. This paper assesses the performance of interconnection lines by measuring their impacts on the main reliability and vulnerability indicators of interconnected power systems. The reliability study is performed using the sequential Monte Carlo simulation technique, while the vulnerability assessment is carried out by proposing a cascading failures methodology. The conclusions obtained show that highly connected infrastructures have simultaneously high reliability and limited robustness, which suggests that both approaches show different operational characteristics of the power system. Nevertheless, an appropriate increase in the number and capacity of the interconnections can help to improve both security parameters of the power supply. Seven case studies are performed based on the IEEE RTS-96 test system. The results can be used to help transmission system operators better understand the behaviour and performance of electrical networks.

This paper proposes an assessment framework for the deployment of citizen energy communities (CECs) in cities using meta-data assisted clustering techniques. It elaborates a top-down approach that aims at capturing the “built intelligence” at the city level in order to specify the number of CECs in a given city. Specific types of CECs are proposed and the main sources of meta-data to assist the assessment of CECs are identified. The paper also provides a case study for clarification. We focus on the electricity vector among the several energy carriers covering energy consumption needs in cities. The resulting CECs are supposed to function in grid-tied mode. Specific focus is given to photovoltaic systems (PVs) as the main source of renewable energy generation in CECs.

Interoperability is a challenge for the realisation of smart grids. In this work, we first present an interoperability testing methodology, which is substantial to perform interoperability tests for the smart grid. To show its applicability and facilitate its comprehension, we present an example by applying it on a Demand Side Management (DSM) use case. The DSM use case is chosen because it is a major topic for modern grids and it involves the participation of many actors. The tutorial exemplifies the interactions among those actors. The Smart Grid Architecture Model SGAM framework is used, where the mapping of the use case is presented along with the Message Sequence Chart (MSC). Then we describe the profiling of the equipment, relevant technical information and standards, which form the basis for the design and execution of the interoperability tests. We focus on the technical part of the interoperability testing; therefore, attention is focused on the information and communication layer. We present how the interoperability tests should take place and we analytically show the respective Test Cases (TC). The verdict of the test should be either PASS or FAIL. The paper shows how to successfully use the methodology for interoperability testing on a specific use case, whereas its applicability can be extended to any smart grid interoperability use case.

The interest in modeling the operation of large-scale battery energy storage systems (BESS) for analyzing power grid applications is rising. This is due to the increasing storage capacity installed in power systems for providing ancillary services and supporting nonprogrammable renewable energy sources (RES). BESS numerical models suitable for grid-connected applications must offer a trade-off, keeping a high accuracy even with limited computational effort. Moreover, they are asked to be viable in modeling for real-life equipment, and not just accurate in the simulation of the electrochemical section. The aim of this study is to develop a numerical model for the analysis of the grid-connected BESS operation; the main goal of the proposal is to have a test protocol based on standard equipment and just based on charge/discharge tests, i.e., a procedure viable for a BESS owner without theoretical skills in electrochemistry or lab procedures, and not requiring the ability to disassemble the BESS in order to test each individual component. The BESS model developed is characterized by an experimental campaign. The test procedure itself is framed in the context of this study and adopted for the experimental campaign on a commercial large-scale BESS. Once the model is characterized by the experimental parameters, it undergoes the verification and validation process by testing its accuracy in simulating the provision of frequency regulation. A case study is presented for the sake of presenting a potential application of the model. The procedure developed and validated is replicable in any other facility, due to the low complexity of the proposed experimental set. This could help stakeholders to accurately simulate several layouts of network services.

Demand response services and energy communities are set to be vital in bringing citizens to the core of the energy transition. The success of load flexibility integration in the electricity market, provided by demand response services, will depend on a redesign or adaptation of the current regulatory framework, which so far only reaches large industrial electricity users. However, due to the high contribution of the residential sector to electricity consumption, there is huge potential when considering the aggregated load flexibility of this sector. Nevertheless, challenges remain in load flexibility estimation and attaining data integrity while respecting consumer privacy. This study presents a methodology to estimate such flexibility by integrating a non-intrusive load monitoring approach to load disaggregation algorithms in order to train a machine-learning model. We then apply a categorization of loads and develop flexibility criteria, targeting each load flexibility amplitude with a corresponding time. Two datasets, Residential Energy Disaggregation Dataset (REDD) and Refit, are used to simulate the flexibility for a specific household, applying it to a grid balancing event request. Two algorithms are used for load disaggregation, Combinatorial Optimization, and a Factorial Hidden Markov model, and the U.K. demand response Short Term Operating Reserve (STOR) program is used for market integration. Results show a maximum flexibility power of 200–245 W and 180–500 W for the REDD and Refit datasets, respectively. The accuracy metrics of the flexibility models are presented, and results are discussed considering market barriers.

Based on current policy targets, projections, and expectations, electricity is set to play a central role in the European Union's (EU's) economy. The ambitious goals of decarbonization and energy-efficient actions include decreasing greenhouse gas emissions by 40% in 2030 and 95% in 2050 down to below 1990 levels, increasing the renewable energy share to at least 27% of final energy consumption in...

The European Commission has set a target of establishing an integrated Europe-wide electricity market for day-ahead and intraday transactions. However, there are still many open questions on the potential benefits of a Europe-wide intraday market integration and the harmonizing market rules. This paper intends to provide a precise insight into the potential impacts of EU policies regarding integrating electricity markets on market efficiency and on different market players with the aim of supporting policy makers to increase the penetration of renewables in a cost efficient manner. In this paper, we investigate and compare the current option of regional intraday electricity market with the option of an integrated Europe-wide one, with reference to the three European test cases with high renewable penetration: the Iberian electricity market including Spain and Portugal, the Italian electricity market including Italy and Slovenia, and the electricity market of Germany. We consider two 2030 scenarios: (i) the regional/local intraday electricity market, and (ii) the integration of the current regional intraday market of the test cases into a single intraday market in Europe. The two scenarios are modelled through stochastic Monte Carlo simulation, considering uncertainty on electricity demand, wind and solar power. The performance of the intraday market under the two options are compared in terms of generation cost, electricity prices, producer’ surplus, and load expenditure inside the European test cases. The simulation results lead to the conclusion that integrating to a Europe-wide intraday electricity market is not advantageous for power producers inside the European countries with high share of variable renewable generation, in terms of annual generation surplus. However, from the customers’ point of view, intraday market integration is beneficial, leading to lower cost to loads. Furthermore, it is shown that the flexibility provided by the installed capacity of hydro pumped-storage generators within Europe, by 2030, eliminates the planned curtailment of renewable energy sources in day-ahead and intraday markets and confines the impact of market integration on the market performance indicators.

The modernization of the distribution grid requires a huge amount of data to be transmitted and handled by the network. The deployment of Advanced Metering Infrastructure systems results in an increased traffic generated by smart meters. In this work, we examine the smart meter traffic that needs to be accommodated by a real distribution system. Parameters such as the message size and the message transmission frequency are examined and their effect on traffic is showed. Limitations of the system are presented, such as the buffer capacity needs and the maximum message size that can be communicated. For this scope, we have used the parameters of a real distribution network, based on a survey at which the European Distribution System Operators (DSOs) have participated. For the smart meter traffic, we have used two popular specifications, namely the G3-PLC–“G3 Power Line communication” and PRIME–acronym for “PoweRline Intelligent Metering Evolution”, to simulate the characteristics of a system that is widely used in practice. The results can be an insight for further development of the Information and Communication Technology (ICT) systems that control and monitor the Low Voltage (LV) distribution grid. The paper presents an analysis towards identifying the needs of distribution networks with respect to telecommunication data as well as the main parameters that can affect the Inverse Fast Fourier Transform (IFFT) system performance. Identifying such parameters is consequently beneficial to designing more efficient ICT systems for Advanced Metering Infrastructure.

A new methodology for real-time management and control of smart grids is proposed. It exploits the full benefit of a multi-directional communication between all stakeholders in order to regularly provide efficient operations in case of emergency. The unique feature of the proposed methodology is that the techno-economic demands imposed by a policy and the environmental/social constrains are preserved at all times without the need for artificial, disclosed or hidden economic subsidies or other incentives. The Dynamic Management and Control of Smart Energy Grids (McSEG) approach takes into consideration the policy priorities and the parameters that could potentially affect the policy and formulate precise indicators that could be used to evaluate compliance in a transparent way. The grid-management decisions are taken dynamically based on the priorities set by the policy makers and the regulators. The method enables the interoperability between distributed energy service suppliers in the electricity grid with different technologies. In this way the competition could be realised in a transparent and fair manner.

This paper proposes an Absolute Scoring Scheme for interoperability testing purposes. The scheme has been created in the context of a Demand Side Management test case aiming to examine the capability of different components of interest to interoperate with each other. Here, the interoperability of smart meters with data concentrators has been studied. The Scoring Scheme proves to be more precise with a larger set of devices. The SGAM framework has been followed for the proper mapping of components, communication protocols and information models used. This work can contribute to enhancing the quality of interoperability testing activities in order to support industrial stakeholders.