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In recent years, there has been an increasing urgency among energy-intensive companies to find innovative ways of mitigating the negative financial impacts of rising fuel and electricity prices. Consequently, companies are exploring new technological solutions to lower electricity costs, such as investing in their own power generation sources or storage systems. In this context, this article presents a data-driven optimization-based framework to manage and optimize the operation of a hybrid energy system within industries characterized by substantial power requirements. The framework encompasses several key aspects: electricity generation, self-consumption, storage, and electric grid interaction. The case of an energy-intensive company specializing in wood processing and office furniture production is evaluated. This study explored two system configurations of hybrid energy systems within an energy-intensive company. The result of the analyzed case shows that the system's flexibility is enhanced by its ability to store energy, resulting in electricity cost savings of nearly 72% and total operating cost savings of 20%. [ABSTRACT FROM AUTHOR]

The volatility of raw material prices and the rising prices of CO2 emission allowances when using fossil fuels to produce electricity and heat are still relevant problems for owners of generating units. The decision-making tools are used in the fuel purchase process. However, these tools should also consider environmental issues. The article’s main objective is a quantitative analysis of the potential for reducing costs associated with supplying and using hard coal in public power plants as a result of considering the costs of environmental protection and CO2 emission allowances in the process of planning this fuel supply. A mathematical model was developed to optimize the supply of hard coal for the power industry. The tool and elaborated research scenarios made it possible to calculate and analyze the impact of considering the costs of emissions of harmful substances into the environment and CO2 emission allowances on the planning of coal supplies and the reduction of costs related to acquiring and using coal by public power plants. The calculation results were presented on the example of the Polish power sector. The model’s results confirm that the appropriate selection of coals, taking into account the quality parameters determining the amount of emissions of harmful substances, reduces the amount of these emissions and the total costs of acquiring and using coal in electricity production. However, depending on the considered scenario, the scale of this impact varies. The results of the optimization of coal supplies to power plants and their proper interpretation may constitute an important contribution to making management decisions in energy companies. [ABSTRACT FROM AUTHOR]

Investments in the development of the district heating system require a thorough analysis of the technical, economic, and legal aspects. Regarding the technical and economic context, a mathematical model of the district heating system has been proposed. It optimizes both the technical and economic aspects of the function and development of a district heating system. To deal with non-linearities, the developed linear programming model is divided into three phases: flow, thermal, and pressure. Therein, non-linear dependencies are calculated between the linear optimization phases. This paper presents the main assumptions and equations that were used to calculate the parameters of the heating system, along with the optimal level of heat production, the flow rate of the heating medium in the heat nodes and edges of the network graph, the heat, power, and temperature losses at each edge, and the purchase costs of heat and its transmission. The operation of the model was tested on a real-world district heating system. The case study results confirm that the model is effective and can be used in decision support. The economic results of the model, before the calibration process, were 3.6% different from historical values. After the calibration process, they were very similar to the real data—all percentage deviations were within 1%. [ABSTRACT FROM AUTHOR]

Background: In recent years, the introduction of single-cell RNA sequencing (scRNA-seq) has enabled the analysis of a cell's transcriptome at an unprecedented granularity and processing speed. The experimental outcome of applying this technology is a M × N matrix containing aggregated mRNA expression counts of M genes and N cell samples. From this matrix, scientists can study how cell protein synthesis changes in response to various factors, for example, disease versus non-disease states in response to a treatment protocol. This technology's critical challenge is detecting and accurately recording lowly expressed genes. As a result, low expression levels tend to be missed and recorded as zero - an event known as dropout. This makes the lowly expressed genes indistinguishable from true zero expression and different than the low expression present in cells of the same type. This issue makes any subsequent downstream analysis difficult. Results: To address this problem, we propose an approach to measure cell similarity using consensus clustering and demonstrate an effective and efficient algorithm that takes advantage of this new similarity measure to impute the most probable dropout events in the scRNA-seq datasets. We demonstrate that our approach exceeds the performance of existing imputation approaches while introducing the least amount of new noise as measured by clustering performance characteristics on datasets with known cell identities. Conclusions: ccImpute is an effective algorithm to correct for dropout events and thus improve downstream analysis of scRNA-seq data. ccImpute is implemented in R and is available at https://github.com/khazum/ccImpute. [ABSTRACT FROM AUTHOR]

The article contains the results of research on transient heat and mass transfer processes occurring in a honey dehydrator with the capacity of 30 kg of honey with closed air circulation with volumetric flow rates Va = 0.01–0.03 m³s−1. The research was carried out different rotational speeds of the honey mixer ns = 120-270 rpm, without and with preheating of the honey. The article presents heat and mass balance equations for the considered process of honey dehydration, the values of heat transfer and mass transfer coefficients between honey and air were determined. The values obtained are respectively α = 5-25 Wm−2 K−1, β = 0.001–0.035 kg m−2s−1. The reduction of mixer speed from ns = 270 rpm tons = 120 rpm was accompanied by an increase in average heat and mass transfer coefficients of approx. 30% and 52%, respectively. The tripled volumetric flow rate of air(Va1/Va2 = 3) resulted in an increase in heat and mass transfer coefficients – on average by 80% and 140%, respectively. Preheating the honey allows to increase the amount of removed water by 30%. The paper presents the general dimensionless expressions allowing for the calculation of heat and mass transfer coefficients. [ABSTRACT FROM AUTHOR]

For much of the last two decades, the Central and East European (CEE) economies have experienced a deep structural reform, moving away from a socialist economic system towards a market economy. The political situation of the second half of the 20th century had a significant impact on the economic development and competitiveness of these transition countries, when compared with their Western European counterparts. A vast number of studies have been conducted to analyze the structural changes required for resource-dependent economies to achieve long-term development and to understand the synergies between commodities and diversification. Yet, the dynamics of resource extraction and the resource dependence of regions that have experienced periods of sustained levels of growth have largely been overlooked, especially the Central and Eastern European region. In this context, this article presents an analysis of the level of resource dependence of six countries which joined the European Union between 2004 and 2007. Using data spanning from the year 2000 to 2017, we calculate the Extractives Dependence Index (EDI) of six former Soviet satellite nations and one former Soviet state. Our results indicate that the commodity structure of trade in the six countries which joined the European Union has changed considerably. These countries have reduced their economic dependence on extractive resources by developing their high value-added and technology-intensive sectors. Our findings also reveal that Poland experienced the highest decrease in EDI scores among the six CEE countries. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical model of the heat and mass transfer processes for a rotary-spray honey dehydrator with a heat pump and a closed air circuit. An analytical calculation model, based on the energy balance equations of the dehydrator and heat pump, was used to model the transient dehydration process of honey in a dehydrator. The presented article includes a different approach to modelling both the dryer and the heat pump assisting the drying process. The novel quality of this study lies in the use of original equations to determine the heat and mass transfer coefficients between honey and air and using an actual model of a cooling unit to model the honey dehydration process. The experimentally verified calculation algorithm enables an analysis of the effects of air flow rate, mixer rotation speed, and cooling unit power on the efficiency of the drying process. The dehydrator calculation model was used to minimize the drying time by selecting the optimal evaporative temperature values of the cooling unit. For fixed mixer speed and air flow rates, optimal values of evaporation temperatures allow for 8–13% reduction in honey drying time and an increase in the specific moisture extraction rate (SMER) by 4–32%. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has caused changes in electricity demand and, consequently, electricity consumption profiles. Given the rapid changes in energy prices, it is significant from the perspective of energy companies, and forecasting consumed energy volume. A necessity for accurate energy volume planning forces the need for analyzing consumers' behaviors during the pandemic, especially under lockdowns, to prepare for the possibility of another pandemic wave. Many business clients analyzed in the paper are economic entities functioning in sectors under restrictions. That is why analyzing the pandemic's impact on the change in energy consumption profiles and volume of these entities is particularly meaningful. The article analyzes the pandemic and restrictions' impact on the total change of energy consumption volume and demand profiles. The analysis was conducted basing on data collected from a Polish energy trading and sales company. It focused on the energy consumption of its corporate clients. Analyzed data included aggregated energy consumption volumes for all company's customers and key groups of economic entities under restrictions. The analysis demonstrates the influence of pandemic restrictions on energy consumption in the group of business clients. Significant differences are observable among various sectors of the economy. The research proves that the largest drops in energy consumption are related to shopping centers and offices. Altogether, the restrictions have caused a 15–23% energy consumption drop during the first lockdown and a maximum 11% during the second against expected values. [ABSTRACT FROM AUTHOR]

The paper investigates the competitiveness of the Polish hard coal mining sector as a fuel source for heat and power generation. The main objective of the study is to make a quantitative assessment of the impact of the price relationship between domestic and imported steam coal on the consumption of domestic fine coal in the Polish heat and power generation sector. For this purpose, a long-term mathematical model of the Polish steam coal market is employed and scenarios that mimic the relationship between domestic and imported steam coal prices is developed. The following results are analysed: ?? the volume of total domestic steam coal consumption under the scenarios analysed, ?? the absolute difference in domestic steam coal consumption under the scenarios analysed in comparison with the scenario 0%, ?? the total imported and domestic steam coal consumption in the period analysed. In addition, the results were depicted in cartograms in order to present the distribution of domestic and imported coal consumption in the various regions of Poland. The results of the study indicate that the supply of steam coal in Poland can be completely covered by domestic mines when the price of domestic coal is from -40% to -20% lower than that of imported coal. For the remaining scenarios, the consumption of imported coal increases and reaches its highest value in the scenario +40%, in which imported coal covered of 71% of total steam coal consumption in Poland over the period. The conclusions presented in this paper provide valuable findings and policy insights into the competitiveness of domestic mines and management of domestic production both in Poland and other countries in which power generation systems are mostly dominated by coal. [ABSTRACT FROM AUTHOR]

This paper conveys some of the results of a research project involving the design and tests of biomimetic underwater vehicle which is intended for implementation of intelligence, surveillance and reconnaissance tasks. The research presented in this paper is based on the theoretical and practical study. All major subsystems of the robot are specified and briefly described. The mechanical design is based on modular structure. Two types of modules, dry and wet, are specified. The major parts of the tail module were checked with the use of the finite element method. Moreover, hardware and software parts of robot's control subsystem and Simulink model of static depth regulator are briefly presented. The final part presents main parameters and basic functionality of the built biomimetic underwater vehicle. [ABSTRACT FROM AUTHOR]

The concept of risk is well known in the energy sector. It is normally recognized when it comes to price and cost forecasting, annual production calculation, or evaluating project lifetime. Nevertheless, it should be pointed out that the quantitative evaluation of risk is usually difficult. The discount rate is the only parameter reflecting risk in the discounted cash flow analysis. Therefore, knowledge of the discount rate along with the major components affecting its level is of fundamental significance for making investment decisions, capital budgeting, and project management. By referring to the standard coal-fired power generation projects the authors of the paper tackle the analysis of the composition of discount rate for onshore wind farm technologies in the Polish conditions. The study was carried out on the basis of a typical (hypothetical) onshore wind farm project assessed at the feasibility stage. To enable comparisons and discussions, it was assumed that the best reference point for such purposes is the real risk-adjusted discount rate, RADR, after-tax, in all equity evaluations (the 'bare bones' assumption); that is because such a rate reflects the inherent characteristics of the project risk. The study methodology involves the a priori application of the discount rate level and subsequently—in an analytical way—calculation of its individual components. The starting point for the analysis of the RADR's composition was the definition of risk, understood as the product of uncertainty and consequences. Then, the risk factors were adopted and level of uncertainty assessed. Subsequently, using the classical sensitivity analysis of IRR, the consequences (as slopes of sensitivity lines) were calculated. Consequently, risk portions in percentage forms were received. Eventually, relative risks and risk components within cost of equity were assessed. Apart from the characteristics of the discount rate at the feasibility stage, in the discussion section the study was supplemented with an analogous analysis of the project's cost of equity at the operating stage. [ABSTRACT FROM AUTHOR]

In recent years, a growing number of enterprises have taken different steps to reduce the energy consumption and carbon emissions of information and communication technology (ICT) assets. Because of the expansion of digitalization and the need for rapid access to information, enterprises have been compelled to optimize the location and utilization of their ICT hardware. In this context, this paper presents a novel method based on a mixed-integer linear programming approach for optimizing the physical location and task allocation of printing devices in office floor plans considering the power usage of the ICT assets, the costs related to the purchase and service of the individual devices, operating costs, and distance between employees and printing devices. The applicability of the proposed model is illustrated using the case study of a company with 100 functional departments located in several office buildings across Poland. The results reveal that the model guarantees the execution of all printing tasks and satisfies the functionality requirements expressed by the users of the workstations. Moreover, the selection of more energy-efficient printing devices leads to a considerable reduction in electricity consumption, related not only to the direct operation of these devices but also to their modes of operation (work, idle, or sleep). Such results also bring tangible effects in reducing carbon dioxide emissions, which is particularly important for businesses operating in countries where fossil fuels still dominate the energy mix. [ABSTRACT FROM AUTHOR]