This study focuses on the problem of the efficient energy management of an independent fleet of freight electric vehicles (EVs) providing service to a city multi-floor manufacturing cluster (CMFMC) within a metropolis while considering the requirements of smart sustainable electromobility and the limitations of the power system. The energy efficiency monitoring system is considered an information support tool for the management process. An object-oriented formalization of monitoring information technology is proposed which has a block structure and contains three categories of classes (information acquisition, calculation algorithms, and control procedures). An example of the implementation of the class “Operation with the electrical grid” of information technology is presented. The planning of the freight EVs charging under power limits of the charging station (CS) was carried out using a situational algorithm based on a Fuzzy expert system. The situational algorithm provides for monitoring the charging of a freight EV at a charging station, taking into account the charge weight index (CWI) assigned to it. The optimization of the CS electrical load is carried out from the standpoint of minimizing electricity costs and ensuring the demand for EV charging without going beyond its limits. A computer simulation of the EV charging mode and the CS load was performed. The results of modeling the electrical grid and CS load using the proposed algorithm were compared with the results of modeling using a controlled charging algorithm with electrical grid limitations and an uncontrolled charging algorithm. The proposed approach provides a reduction in power consumption during peak hours of the electrical grid and charging of connected EVs for an on-demand state of charge (SOC).
Determining the energy consumption level is one of the stages of energy efficiency monitoring facilities. The aim of the article is to adapt the energy baseline to the operating conditions of the facility in accordance with the ISO 50000 Standards requirements. The methodology for determining the energy baseline was proposed to achieve the goal. The three-stage procedure for forming a set of relevant variables of the energy baseline, which allows taking into account the significance of variables, the possibility of their measurement, controllability and control, and the procedure for constructing a multifactorial model of the optimal structure for determining the energy baseline are the main scientific results. This methodology was applied to a boiler house of a district heating system. Relevant variables were formed using a three-stage selection of factors that influence the gas consumption efficiency of the boiler house. Combinatorial algorithm of the group method of data handling was used for gas consumption simulation. The search for models of optimal complexity was performed in six classes of basic functions. The selection of better structures of the mathematical model was realized based on the criteria for its appropriateness (regularity, unbiasedness criterion, Schwartz, determination coefficient) and accuracy of the forecast using the morphological criterion. As a result, a multifactor mathematical model of optimal structure was obtained. The percent forecasting error did not exceed 1%. The significance of the results lies in the fact that the proposed methodology can be applied to any facility.
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