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This paper analyzes the development of the European electricity transmission network for different policy scenarios at the horizon 2050. We apply a bottomup techno-economic electricity sector model to determine transformation scenarios of the European electricity sector. It has a very detailed spatial disaggregation that allows for a fine representation of domestic and international electricity flows and transmission expansion. The cost-minimizing mixed-integer model calculates investments for time steps of ten years. The model results indicate that network requirements are lower than generally assumed. The largest share are domestic upgrades, rather than country interconnectors. Most investments (20bn EUR) occur in the near future, by 2030 the latest. Only the high-mitigation scenarios require large additional network investments. The timing and location of investments differ, depending on generation scenarios and cost assumptions for interconnectors. The results indicate that carbon emission reduction targets alone provide insufficient information for long-term network planning. [ABSTRACT FROM AUTHOR]

This paper proposes a set of digitalisation indicators focused on measuring the different digital capabilities and infrastructure of electricity distribution systems, as opposed to previous indicators which have mainly focused on performance and quality of service aspects. The indicators are classified according to the pillars of digitalisation: sensor and actuator, connectivity, data processing, and digital culture. They are use-case-agnostic and do not require a huge amount of information. In addition to this, three possible new applications of these indicators for distribution system operators and regulatory authorities are identified and discussed. The extensive use of these indicators in Europe could allow the development of fruitful collaborations between distribution system operators, allow the identification of cause–effect relations between grid performance and digital infrastructure, and improve the replicability of innovative smart grid solutions. However, this will only be possible if regulators promote the adoption of the proposed indicators and the dissemination of their results. • Smart grid indicators are required by European Directive 2019/944. • Indicators on sensors/actuators, connectivity, data processing, and digital culture. • Indicators to provide an overview of the distribution grid. • Indicators to study relation between performance and digital infrastructure. • Indicators to generate information for the replicability of solutions. [ABSTRACT FROM AUTHOR]

This paper investigates the current state of market integration among European electricity day-ahead spot prices. In our empirical analysis we utilize a large sample of hourly spot prices of 25 European markets for the period 2010Jan01/01h- 2015Jun30/24h and combine it with other relevant data such as hourly interconnector capacities and the existence of market coupling. Firstly, empirical results from cointegration analysis indicate that market integration increased from 2010 to 2012 but then declined until 2015, despite the introduction of market coupling in many markets. Secondly, we empirically assess error correction after price shocks and reach the conclusion that markets' strength of the error correction mechanism is rather modest. In general, our findings suggest that the integration among European electricity markets has a large potential for improvements from additional capacity investments and further promotion of market coupling. [ABSTRACT FROM AUTHOR]

The ultra-wideband wireless personal area networks are expected to be most commonly employed in desktop environments. This paper presents a measurement campaign conducted on a typical office desk. A pair of omnidirectional UWB antennas and a vector network analyzer were used to measure the impulse responses over a frequency range spanning from 6 GHz to 8.5 GHz, in accordance with the UWB regulations in Europe. The coherence bandwidth and the rms delay spread are calculated from the measurement results. A significant correlation between these wideband parameters is found, but only at higher correlation thresholds. [ABSTRACT FROM AUTHOR]

Increasing numbers of very small generators are being connected to electricity distribution systems around the world. Examples include photovoltaics (PV) and gas-fired domestic-scale combined heat and power (micro-CHP) systems, with electrical outputs in the region of 1 to 2 kW. These generators are normally installed within consumers' premises and connected to the domestic electricity supply network (230 V single-phase in Europe, 120 V in North America). There is a growing need to understand and quantify the technical impact that high penetrations of such generators may have on the operation of distribution systems. This paper presents an approach to analyzing this impact together with results indicating that considerable penetrations of micro-generation can be accommodated in a typical distribution system. [ABSTRACT FROM AUTHOR]

The interdependence of electricity and natural gas is becoming a major energy policy and regulatory issue in all jurisdictions around the world. The increased role of gas fired plants in renewable-based electricity markets and the dependence on natural gas imports make this issue particular important for the European energy market. In this paper we provide a comprehensive combined analysis of electricity and natural gas infrastructure with an applied focus: We analyze three different scenarios of the long-term European decarbonization pathways, and analyze the interrelation between electricity and natural gas markets on investments in the long run and spatial aspects in the short run. [ABSTRACT FROM AUTHOR]

Abstract: Large scale integration of wind energy poses new challenges to the European power system due to its stochastic nature and often remote location. In this paper a multivariate uncertainty analysis problem is formulated for the integration of stochastic wind energy in the European grid. By applying copula theory a synthetic set of data is generated from scarce wind speed reanalysis data in order to achieve the increased sample size for the subsequent Monte Carlo simulation. In the presented case study, European wind power samples are generated from the modeled stochastic process. Under the precondition of a modeled perfect market environment, wind power impacts dispatch decisions and therefore leads to alterations in power balances. Stochastic power balances are implemented in a detailed model of the European electricity network, based on the generated samples. Finally, a Monte Carlo method is used to determine power flows and contingencies in the system. An indicator is elaborated in order to analyze risk of overloading and to prioritize necessary grid reinforcements. Implications for the Swiss power grid are investigated in detail, revealing that the current system is significantly put at risk in certain areas by the further integration of wind power in Europe. It is the first time that the results of a probabilistic model for wind energy are further deployed within a power system analysis of the interconnected European grid. The method presented in this paper allows to account for stochastic wind energy in a load flow analysis and to evaluate deterministic indicators, such as the N −1 criterion, on a probabilistic basis. Thus, it constitutes an important extension of deterministic models. [Copyright &y& Elsevier]

Off-grid power systems are often used to supply electricity to remote households, cottages, or small industries, comprising small renewable energy systems, typically a photovoltaic plant whose energy supply is stochastic in nature, without electricity distributions. This approach is economically viable and conforms to the requirements of the European Green Deal and the Fit for 55 package. Furthermore, these systems are associated with a lower short circuit power as compared with distribution grid traditional power plants. The power quality parameters (PQPs) of such small-scale off-grid systems are largely determined by the inverter's ability to handle the impact of a device; however, this makes it difficult to accurately forecast the PQPs. To address this issue, this work compared prediction models for the PQPs as a function of the meteorological conditions regarding the off-grid systems for small-scale households in Central Europe. To this end, seven models—the artificial neural network (ANN), linear regression (LR), interaction linear regression (ILR), quadratic linear regression (QLR), pure quadratic linear regression (PQLR), the bagging decision tree (DT), and the boosting DT—were considered for forecasting four PQPs: frequency, the amplitude of the voltage, total harmonic distortion of the voltage ( T H D u ), and current ( T H D i ). The computation times of these forecasting models and their accuracies were also compared. Each forecasting model was used to forecast the PQPs for three sunny days in August. As a result of the study, the most accurate methods for forecasting are DTs. The ANN requires the longest computational time, and conversely, the LR takes the shortest computational time. Notably, this work aimed to predict poor PQPs that could cause all the equipment in off-grid systems to respond in advance to disturbances. This study is expected to be beneficial for the off-grid systems of small households and the substations included in existing smart grids. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates how the European electricity generation system can meet deep cuts in CO2 emissions until the year 2050 with special focus on national conditions for CCS. An 85% reduction in CO2 emissions until 2050 is imposed. The analysis is carried out with a techno-economic model (minimizing the system cost) including a detailed description of the present stationary European electricity generation system (power plants) and potential CO2 storage sites as obtained from the Chalmers Energy Infrastructure Database. The modeling puts a cap on CO2 emissions from the system which gives a price on these emissions, i.e. similar to the effect of the European Emission Trading Scheme (EU-ETS), which is the main policy instrument for controlling GHG emissions within EU. Emphasize is put on analyzing turn-over in capital stock of the existing power plant infrastructure, timing of investments and the infrastructural implications of large scale introduction of CCS on a regional perspective, including the effect of investing in new transmission capacity between member states. The work compares two scenarios, one used in a previous work with significant growth in electricity consumption and one assuming that energy efficiency measures are successfully applied in line with the recent EU energy policy package. The results show that it is possible to meet an 85% CO2 reduction target by 2050 at a cost of some 50 to 80 € /ton CO2 over the period up to 2050, but this will require large contributions from CCS and electricity from renewable sources (mainly wind and biomass). Yet, without significant energy efficiency measures it is questionable if such large investments in generation technologies are feasible. Thus, to reach an 85% reduction in CO2 emissions from the electricity generation system by 2050 is not a matter of choice between different technologies and energy efficiency measures but all of these are required and the crucial point is if there will be a high enough price on CO2 emissions. [Copyright &y& Elsevier]

We employ a detailed two-stage model to simulate the operation of the Central Eastern European electricity market and network. Implementing different cases of coordination in congestion management between national transmission system operators, numerical results show the beneficial impact of closer cooperation. Specific steps comprise the sharing of network and dispatch information, crossborder counter-trading, and multilateral redispatch in a flow-based congestion management framework. Efficiency gains are accompanied by distributional effects. Closer economic cooperation becomes especially relevant against the background of changing spatial generation patterns, deeper international integration of national systems, and spillovers of national developments to adjacent systems. [ABSTRACT FROM AUTHOR]

Empowered by the emergence of novel information and communication technologies (ICTs) such as sensors and high-performance digital communication systems, Europe has adapted its electricity distribution network into a modern infrastructure known as a smart grid (SG). The benefits of this new infrastructure include precise and real-time capacity for measuring and monitoring the different energy-relevant parameters on the various points of the grid and for the remote operation and optimization of distribution. Furthermore, a new user profile is derived from this novel infrastructure, known as a prosumer (a user that can produce and consume energy to/from the grid), who can benefit from the features derived from applying advanced analytics and semantic technologies in the rich amount of big data generated by the different subsystems. However, this novel, highly interconnected infrastructure also presents some significant drawbacks, like those related to information security (IS). We provide a systematic literature survey of the ICT-empowered environments that comprise SGs and homes, and the application of modern artificial intelligence (AI) related technologies with sensor fusion systems and actuators, ensuring energy efficiency in such systems. Furthermore, we outline the current challenges and outlook for this field. These address new developments on microgrids, and data-driven energy efficiency that leads to better knowledge representation and decision-making for smart homes and SGs. [ABSTRACT FROM AUTHOR]