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Between 2018 and 2023 the penetration rate of electricity smart meters in the European Union (EU) is expected to grow from approximately 44% to 71%. The unprecedently rapid development of smart metering (SM) as an ICT-enabled technological novelty is progressing in a complex, multi-actor innovation system, which is strongly driven by EU-level institutions and policies. This paper presents the comprehensive Technology Innovation System (TIS) analysis of electricity SM development in the EU, with a focus placed on regulatory aspects. The article identifies the key elements of the SM innovation system (technologies and infrastructures; actors and networks; institutions and policies) and characterises their interaction based on an in-depth desk research and a critical assessment of regulations, statistics and primary and grey literature sources (e.g., market reports). The main enablers and barriers for EU-level SM TIS development are studied. The major driving force for EU-level SM TIS is the clear, yet evolving vision of EU-level actors for the SM deployment, founded on the grounds of energy conservation and empowerment of customers. On the other hand, the major inhibitor is the insufficient regulatory framework for roll-outs at the level of a Member State, which does not fully ensure interoperability, data protection and security standards or organisational effectiveness.

The wireless sensor network is gaining significant attention because of its ubiquitous deployability nature. In general, the role of the wireless sensor network is remarkable in smart city applications for data sensing, collecting, and transmitting. Advanced metering infrastructure is an automatic system for the reading of electricity consumption by individual users. The reading of data from meters normally communicated over a wireless medium. Apart from collecting and sensing, routing is one of the major attributes in the AMI network. Successful communication is possible when the link and node are in the proper state. In this paper, we propose a fault-tolerant routing mechanism named Grid Topological Routing scheme to provide an efficient route in case of encountering a faulty path. The simulation shows better performance against the Routing Protocol for Low-Power and Lossy Networks and Ad-Hoc On-Demand Vector algorithm in terms of power consumption and packet delivery ratio. This model is explicitly designed for the smart grid in India.

The study analyzes pro-environmental attitudes and behaviors of residents in the mountainous regions of Małopolska regarding energy saving and transportation. The main objective was to determine the extent to which environmental awareness, vehicle technical condition, and driving style translate into actual energy-efficient behaviors. The research was conducted using a quantitative method among 423 respondents from six mountain districts of Małopolska, based on a proprietary questionnaire and statistical analysis employing non-parametric tests, correlation coefficients, and principal component analysis. The results indicate that respondents most frequently declare simple pro-environmental actions such as waste segregation and energy saving, while less often engaging in activities requiring higher effort or investment, such as eco-driving or limiting car use. Women exhibit higher environmental sensitivity and greater support for ecological regulations, whereas men tend to focus on the technical aspects of vehicle maintenance. The most pro-environmental attitudes and motivations to switch to low-emission vehicles are observed among individuals aged 25–44. The findings confirm that demographic factors significantly differentiate eco–energy-saving orientations, and that environmentally friendly transport behaviors are closely linked to everyday energy-saving practices.

Quality of power supply in power distribution systems requires continuous measurement using power quality analyzers installed in the grid. The paper reviews the published methods for optimal location of metering points in distribution systems in the context of power quality metering and assessment. Three methods have been selected for detailed analysis and comparative tests. It has been found that utilization of the methods is possible, but their performance varies highly depending on the test grid’s topology. Since the methods rely on the state estimation approach, their performance is strictly related to observability analysis. It has been found that standard observability analysis used for typical state estimation problem yields ambiguous results when applied to power quality assessment. Inherited properties of the selected methods are also analyzed, which allows for the formulation of general recommendations about optimal selection of metering points in a distribution system.

Renewable Energy Sources (RES) have been gaining popularity on a continuous basis and the current global political situation is only accelerating energy transformation in many countries. Objectives related to environmental protection and use of RES set by different countries all over the world as well as the European Union (EU) are becoming priorities. In Poland, after years of a boom in photovoltaic (PV) installations, the Renewable Energy Sources Act has been amended, resulting in a change to the billing system for electricity produced by individual prosumers. The change in the billing method, also in pursuance to the provisions of EU laws, has contributed to the inhibition of the PV installation market for fear of energy prices and investment payback time. In this paper, by using the Net Present Value (NPV) method, three mechanisms of billing of electricity from prosumer micro-installations—based on the net-metering principle and net-billing principle (using monthly and hourly prices)—have been analysed. Particular attention has also been paid to the aspects of electricity self-consumption and energy storages, which play a significant role in the economy of PV installations in the net-billing system.

The transition toward sustainable energy in Arctic and subarctic regions requires innovative approaches that account for both the unique geographical conditions and the economic and policy challenges associated with isolated power systems. This study examines how net energy metering (NEM) and net billing schemes influence distributed solar photovoltaic (PV) adoption and financial performance among utilities in Alaska’s Railbelt. The Railbelt, which supplies power to three-quarters of the state’s population, remains heavily reliant on natural gas and exhibits limited renewable penetration compared to other arctic regions. Using a stochastic risk-based modeling framework with Monte Carlo simulations and the Bass diffusion model, the analysis estimates the 15-year financial impacts of different NEM adoption scenarios on utilities. Results show that while NEM drives PV adoption through higher compensation for exported generation, it also increases potential revenue losses for utilities compared to net billing. Policy innovations like those introduced in Alaska’s House Bill 164 (HB 164), which establishes a reimbursement fund to mitigate utility revenue losses, indicate that regulatory work is being designed to balance distributed generation incentives with economic sustainability. This work provides a baseline for understanding how a policy framework influences both utility and consumer economics in terms of NEM and solar PV adoption in Arctic and subarctic systems.

The aim of this paper is to present the transformation of the network tariff system in Slovenia using a comprehensive assessment methodology for the techno-economic evaluation of electricity costs for households. The novelty of the proposed approach lies in the combined assessment of the previous and new network tariff systems, explicitly accounting for power-based network tariff components, time-block-dependent charges, and different support schemes for household photovoltaic systems, including net metering and credit note-based schemes. The results show that the transition from an energy-based to a more power-based network tariff system, introduced primarily to mitigate congestion in distribution networks, is not inherently disadvantageous for consumers and prosumers. When tariff structures are appropriately designed, the new framework can support efficient grid utilization and maintain favorable conditions for prosumers, particularly those integrating battery storage systems. Overall, the proposed methodology provides a transparent and robust framework for evaluating the economic impacts of network tariff reforms on residential consumers and prosumers, offering relevant insights for tariff design and the development of future low-carbon household energy systems.

With the high proportion of new energy and power electronic equipment access in the construction of new power systems, the dynamic volatility of the grid signal is stronger, which poses a serious challenge to accurate metering. To address this problem, this paper starts with the analysis of the electric energy metering algorithm principle. Firstly, the measurement characteristics of the Moving average algorithm and the Non-overlapping algorithm are compared. Secondly, on the basis of studying the steady-state signal metrology power metering error of the two algorithms when there is an active power threshold, the metrology ability of the two algorithms to dynamic signal is further analyzed. The conclusion is drawn that the threshold will cause the metrology power metering error of the moving average algorithm. The non-overlapping algorithm has a certain probability of power metering error. Finally, by designing different input signals, the moving average and non-overlapping algorithms are tested, respectively, to verify the effectiveness of the analysis. The research results of this paper can provide ideas for the research and analysis of dynamic metering algorithms of energy meters.

Capacitor voltage transformer (CVT) out-of-tolerance is one of the main factors causing power metering losses. In order to accurately predict CVT errors and avoid losses caused by CVT out-of-tolerance in a timely manner, this paper proposes a CVT error prediction algorithm based on the DenseNet-GRU network. This method uses CVT historical error data and environmental parameters as data samples to establish DenseNet-GRU Error prediction model achieves accurate prediction of CVT errors. In order to verify the effectiveness of the model, experimental comparisons were conducted with error prediction models established by similar algorithms. The results showed that the average absolute percentage error, root mean square error, and coefficient of determination of the prediction results of the DenseNet-GRU model were optimal and had higher prediction performance. The accuracy and robustness provide ideas and support for subsequent CVT error prediction research work.