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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]

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]

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]