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Demand Response (DR) systems are gaining momentum in the EU energy markets albeit based on fragmented standards that, as a result, hinder interoperability. These discrepancies necessitate the introduction of a semantically enriched umbrella framework that will allow DR systems to exchange and consume data transparently, an issue that is currently unaddressed. Furthermore, to support semantically interoperable DR architectures, a multi-layer compliance testing framework is required that will examine and quantify the technical, syntactic and semantic properties of individual DR systems. In this work, the aforementioned gaps in the literature are addressed by, first, introducing an OpenADR-based semantic enrichment component. According to the guidelines of the Smart Grid Architecture Model (SGAM) framework, a concrete evaluation procedure of this component is presented, which allows for a step-by-step syntactic and semantic testing. Following the identification of the instruments composing the testbed and the equipment/links under test at SGAM’s communication and information layers, the Basic Application Interoperability Profiles (BAIOPs) are defined and their involved steps are described. Experiments demonstrate the validity of the presented methodology, while also evaluating the introduced component.

The cybersecurity analysis of Smart Grid in a holistic manner is an extremely difficult challenge. Especially since a lot of systems and technologies are integrated under the same umbrella. In our paper we illustrate the complexity of the current Smart Grid infrastructure, by presenting the ICT communication requirements as depicted in the Smart Grid Architecture Model. Moreover we propose a specific testbed where we illustrate that in order to provide a satisfactory level of security for the Advanced Metering infrastructure requires a complete analysis of the IT systems and the communication channel. The Advanced Meter Infrastructure interoperability and connectivity are fundamental components in the implementation of Smart Grid, principally for distributed energy resources. The security assessment of the cyberphysical systems found in Critical Infrastructures (CI) requires advanced experimental facilities and methodologies. In this work, an Advanced Metering Infrastructure (AMI) has been deployed in our lab facilities. For this purpose, a small scale system has been built and tested, which represents a real end-to-end system from the control center to the customers’ smart meters.

Narrowband Power Line Communication (NB-PLC) plays a key role in the deployment of smart grid, since it is a widely spread technology for smart grid applications and systems, like the Advanced Metering Infrastructure (AMI) system. In this paper, we study the characteristics of the NB-PLC channel and noise. A method is proposed to estimate the occurrence and duration of the dominant category of noise, the periodic impulsive noise, which greatly degrades the signal quality. A technique is proposed to mitigate the noise effect, with the use of Luby Transform (LT) codes. The proposed scheme exploits the features of the dominant noise on the NB-PLC channel and mitigates its effect especially in highly noisy environments. An estimation algorithm of the burst time occurrence and its duration is introduced. The system can estimate these parameters with an accuracy in the range of 10−4 and it can work even without channel state information. The proposed scheme is compared to two popular NB-PLC technologies, namely the PRIME and G3-PLC, whereas the results show that it can be very effective under severe noise conditions.

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&ndash, 245 W and 180&ndash, 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.

The distribution system is a key part of the electricity chain. It links bulk production with end consumers. Recently, radical changes have taken place in every segment of the power industry. These are calling for a changing role of the Distribution System Operators (DSOs) in Europe. This report provides a clear picture of the features of distribution grids in Europe, on the way they are operated and how far DSOs are from the paved provisions proposed in the recent Electricity Directive of the European Commission., JRC.C.3-Energy Security, Distribution and Markets

The active involvement of residential consumers in smart home initiatives is a key topic for the realization of the smart grid. In this paper we propose a method to accomplish residential remote load scheduling and control through a novel algorithm realized with a LabVIEW interface. Therefore, LabVIEW programming is used in order to transform two normal plugs into smart ones. The status of each plug (on/off) is defined beforehand by the end user through a user friendly interface. Each step of the program contains information regarding the status of the controllable plug and its duration. The program can start and end at any time and its duration can be fixed by the user. We created a testbed to apply the proposed method to a lab experiment, where two load consumption profiles have been used and the respective energy diagram has been derived. The results show that this technique is effective for load scheduling and control, since it can determine the exact time moments of the loads operation. The method can be applied not only to smart home and home energy management applications but also to applications where remote control is required by external actors outside the house premises. The concept is shown to remain the same.

This paper presents recent research conducted at the JRC Smart Grid Interoperability Lab and analyses key parameters that should be taken into consideration for the development of interoperable and sustainable electricity systems. Increasing energy efficiency aims at reducing the overall energy consumption and consequently lower the stress on the environment by using less energy. The first research activity illustrated is on the use of Advanced Metering Infrastructure as a gateway to improve Demand Response/Demand Side Management. The second one focuses on the use of photovoltaic in a low voltage distribution network and studies the effect of penetration in voltage unbalances. The last one addresses the power quality performance of electric vehicle chargers under low temperature conditions and provides hints for improvements. The paper underlines several factors that could affect the efficiency of systems towards making improvements that increase the stability of the relevant operations.

Smart grid interoperability is the driving force for integrating new components and technologies into the electricity grid of the future. Interoperability is an essential requirement for the smart grid allowing different subsystems and services to produce the expected results. Advanced metering infrastructure (AMI) plays an important role as it provides insights on load demand patterns. This paper proposes an Absolute Scoring Scheme for supporting interoperability testing activities. The Scoring Scheme aims at quantifying the capacity of components of interest, i.e. Data Concentrators (DCs) and Smart Meters (SMs) to interoperate. The larger the pool of devices tested the more accurate and reliable the scoring scheme turns to be; creating a reliable big picture of the assessed market of components. A Test Verdict Tracing Scheme supporting interoperability testing activities is proposed too. This work has been developed at the Smart Grid Interoperability Laboratory (SGI Lab) of the Joint Research Centre of the European Commission.

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.

Interoperability is a challenge for the realisation of smart grids. In this work, we apply the methodology for interoperability testing and the design of experiments developed at the Smart Grids Interoperability Laboratory of the Joint Research Centre of the European Commission on a simple use case. The methodology is based on the Smart Grid Architecture Model (SGAM) of CEN/CENELEC/ETSI and includes the concept of Basic Application Profiles (BAP) and Basic Application Interoperability Profiles (BAIOP). The relevant elements of the methodology are the design of experiments and the sensitivity/uncertainty analysis, which can reveal the limits of a system under test and give valuable feedback about the critical conditions which do not guarantee interoperability. The design and analysis of experiments employed in the Joint Research Centre (JRC) methodology supply information about the crucial parameters that either lead to an acceptable system performance or to a failure of interoperability. The use case on which the methodology is applied describes the interaction between a data concentrator and one or more smart meters. Experimental results are presented that show the applicability of the methodology and the design of experiments in practice. The system is tested under different conditions by varying two parameters: the rate at which meter data are requested by the data concentrator and the number of smart meters connected to the data concentrator. With this use case example the JRC methodology is illustrated at work, and its effectiveness for testing interoperability of a system under stress conditions is highlighted.

This paper provides a study of the smart grid projects realised in Europe and presents their technological solutions with a focus on smart metering Low Voltage (LV) applications. Special attention is given to the telecommunications technologies used. For this purpose, we present the telecommunication technologies chosen by several European utilities for the accomplishment of their smart meter national roll-outs. Further on, a study is performed based on the European Smart Grid Projects, highlighting their technological options. The range of the projects analysed covers the ones including smart metering implementation as well as those in which smart metering applications play a significant role in the overall project success. The survey reveals that various topics are directly or indirectly linked to smart metering applications, like smart home/building, energy management, grid monitoring and integration of Renewable Energy Sources (RES). Therefore, the technological options that lie behind such projects are pointed out. For reasons of completeness, we also present the main characteristics of the telecommunication technologies that are found to be used in practice for the LV grid.

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.

Current decarbonisation goals have, in recent years, led to a tremendous increase in electricity production generated from intermittent Renewable Energy Sources. Despite their contribution to reducing society’s carbon dioxide (CO2) emissions they have been responsible for numerous challenges that the current electricity grid has to cope with. Flexibility has become a key mechanism to help in mitigating them. Real-time informed consumers can offer the needed flexibility through modifying their behaviour or by engaging with Demand Side Management (DSM) programs. The latter requires the intervention of several actors and levels of communication management which makes this task difficult from an implementation perspective. With this aim we built and tested a small scale system in our lab which represents a real end-to-end system from the consumer to the energy provider. We programmed the system according to the Object Identification System (OBIS) specification to obtain consumers’ consumption through smart meters with high frequency (one minute). This allows remote control of their appliances in order to reduce the total neighbourhood consumption during critical time periods of the day (peak time). These results and the realisation of a realistic end-to-end system open the way to more complex tests and particularly to the possibility of benchmarking them with other lab tests.