Introduction. The quality of dairy products is determined by the cumulative effect of energy parameters and temporal factors within the cooling process. Immediately after milking, prompt reduction of raw material temperature is required, followed by maintaining the specified thermal regime until the transportation or processing stage. Existing energy calculation methodologies applied to milk storage tanks fail to provide a comprehensive framework; it is essential to account for the passive thermal reserve, which is conditioned by the finite heat capacity of both the product and the containment structures, as well as the development kinetics of psychrotrophic microflora. Research indicates that the pre-cooling duration and the transition rate through the high-temperature zone critically influence product quality. Consequently, the evaluation criterion must be dynamic and based on sensor data. The objective of this study is to develop an energytechnological criterion that integrates thermal, microbiological, and electrical reserves to facilitate operational decisionmaking during power supply interruptions.

Materials and Methods. An energy-technological criterion has been proposed to evaluate the time reserve during power supply interruptions in a milk storage tank. The criterion incorporates three distinct components: a thermal reserve (con-ditioned by the thermal inertia of both the product heating and the containment structures); a microbiological reserve (determined by the dynamics of microflora growth, accounting for the initial bacterial load); and an electrical reserve (dependent on the capacity of the backup power source and the critical load level). The resulting composite indicator is compared with the forecasted power restoration time: if the forecasted duration exceeds the calculated reserve, emergency response actions are required. Model parameterization involves local identification of the tank’s thermal characteristics and calibration of microbiological dependencies based on empirical data.

Research results. An analysis of the temperature margin's sensitivity to key parameters was conducted; the dominant influence of the initial and limiting temperatures was established, driven by the narrow process window. The feasibility of reducing requirements for the thermal storage unit by increasing the passive thermal margin was demonstrated. Taking measurement uncertainty into account, a safety margin based on statistical estimation has been proposed. A dimensionless criterion has been developed to rank process risk zones and formulate an algorithm for management decisions. Model verification involves phased experimental measurements of thermal, electrical, and microbiological parameters, followed by an assessment of predictive accuracy.

Discussion and conclusion. The criterion integrates energy and process parameters, providing a transparent assessment of the reserve capacity. Priority measures depend on the limiting factor — whether thermal, microbiological, or electrical. The metric serves as a predictive indicator between laboratory analyses and is applicable to the multi-criteria optimization of costs and risks. Increasing model complexity is justified only if it reduces errors on independent data; otherwise, a simple, conservative model is preferable.