In the modern power system, transmission losses play an increasingly important role in determining the costs of transmission system operators, in particular in cross-border energy exchange. A variety of transmission losses calculation methods are present in scientific literature in recent years, but regularly neglecting the measurement uncertainty which is an important contribution in calculating the final cost of exchanged energy. Due to the significant cost of transmission losses in total costs, all transmission system operators are interested in discovering the probabilistic nature of transmission losses as a fundamental requirement for finding the fair method for transmission losses allocation. In this paper, transmission losses are simulated on 110 kV cross-border transmission line using an Adaptive Monte Carlo method. The probability density estimation procedure is performed by the non-linear least-squares method, using the Levenberg-Marquardt algorithm. The Gaussian, log-normal, Rayleigh, four-parameter beta, generalized trapezoidal and the sum of uniform and normal distribution are fitted and the quality of the distribution estimates is compared according to the corresponding values of the Kolmogorov-Smirnov statistic. Furthermore, an additional example presents a distribution fitting procedure on the zero-impedance data of the same transmission line.

The study presents the evolution of a measurement uncertainty concept from the traditional error approach up to modern calculation methods. First, a method based on the internationally accepted document Guide to the Expression of Uncertainty in Measurement is presented considering the conditions for its application and fundamental deficiencies. Next, the Monte–Carlo (MC) method, as an alternative, is presented together with an adaptive MC method. After a theoretical comparison between the latter methods, the practical calculation of a transmission line resistance is performed. The results show that the adaptive MC method is reliable, unlike the traditional approach, which shows a significant overestimation of the standard deviation owing to the non‐linearity of the mathematical model and associated distributions other than Gaussian.

This paper presents measurement uncertainty propagation through four basic photovoltaic cell models: One-diode model without resistances, with one resistance and with two resistances and two-diode model with two resistances. The expressions for the output current of all photovoltaic cell models is presented as a function of global irradiance G and temperature T. Next, the expressions for all fill factor parameters: short-circuit current, open-circuit voltage, current and voltage at the maximum power point, depending on the global irradiance G and temperature T are derived as well. For each parameter, Monte Carlo simulations to calculate the measurement uncertainty of the parameter are performed and the results were used as input values for the calculation of measurement uncertainty of fill factor. Practical calculations are performed in laboratory for renewable energy sources located on 45°32′ N and 18°44′ E. Final fill factor calculations are compared for three different module technologies.

Digital transformation of metrology is a holistic process that was started formally by the Joint Statement of Intent “On the digital transformation in the international scientific and quality infrastructure” signed by major metrology organisations in March 2022. With the digital transformation of metrology in motion, the questions of a seamless transition to digital representation while ensuring adherence to all the requirements of digital representation and maintaining a sustainable framework for future operations are just some of the challenges faced. To tackle these challenges, also within the concept of “more electrical world” (MEW), one technology is demonstrating high potential applicability as a possible candidate solution—blockchain technology, with its critical underlying properties (e.g., immutability, decentralisation, etc.) being fully compliant with the requirements of digital representation in metrology. Accordingly, this paper presents a blockchain-based concept for the digital transformation of the traceability pyramid for electrical energy measurement. The concept is developed in accordance with the goals of the Metroracle project. Based on the analyzed and presented state-of-the-art, the main contribution of the paper is the comprehensiveness of the concept, which encompasses the whole pyramid and describes all relevant processes and responsibilities of all stakeholders: measurement instrument (MI) owners, certificate issuers (National Accreditation Body (NAB), National laboratory (NL), Reference laboratory (RL)), MI manufacturers/developers, MI installers. The transformed pyramid is defined by Croatian metrology laws and regulations, but with smaller adjustments, it is applicable to other EU countries as well, and also to the traceability of other physical quantities, i.e., not to electrical energy only. Possible legal and technical issues are identified (amount of data, machine-readable standards and regulations, ensuring limited access, legal relevance of digital signature) and corresponding solutions presented, as well as further steps in our research and development within the Metroracle project.

This study deals with calculation of transmission line losses. Having in mind that this type of losses, besides the line load and the other external input quantities such as atmospheric conditions, strongly depends on measurement uncertainty as well, the issue can be considered through finding the most convenient approach in calculation of measurement uncertainty. In this respect, two approaches (methods) are the most common: traditional method based on the guide to the expression of uncertainty in measurement (GUM) and the adaptive Monte–Carlo method (AMC). The study reveals the main disadvantages of the GUM, which is so far considered as a most accurate method. The observed drawbacks of the GUM can be successfully overcome by using of the AMC method. The comparison between the methods is performed on 110kV cross‐border transmission line from Croatian Transmission System Operator Ltd. The results show the great difference in the estimated variances, i.e. GUM variances are significantly overestimated what results in incorrect transmission losses allocation procedure with respect to its final financial effect. The study confirms that the AMC method is likely to be more practically suitable method for transmission line resistance and losses calculation.

In a very short time, green marketing has become a new trend in the orientation of companies in the world, where it represents a new face of modern marketing theory and is the answer to the current consumer society. The aim of this paper is to study the consumer society, its characteristics and consequences on the community as a whole. The consumer today is no longer just a passive observer, but an active participant in the events - Such a role of the consumer in the modern market necessarily leads to a different marketing approach of companies. The conducted research aims to identify the green marketing concept and clarify the boundaries and elements associated with the new marketing concept. The research concluded that green marketing is the application of traditional marketing practices, putting environmental protection first as a priority when determining the elements of the marketing mix from product design, pricing, distribution and promotion. Also, it has been proven that green marketing is not limited to just one sector, but to world-leading experiences in almost all industrial branches.