Search

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]

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]