Abstract
Prerequisite for an efficient cooling energy system is the knowledge and optimal combination of different operating conditions of individual compression and free cooling chillers. The performance of cooling systems depends on their part-load performance and their condensing temperature, which are often not continuously measured. Recorded energy data remain unused, and manufacturers’ data differ from the real performance. For this purpose, manufacturer and real data are combined and continuously adapted to form part-load chiller models. This study applied a predictive optimization algorithm to calculate the optimal operating conditions of multiple chillers. A sprinkler tank offers the opportunity to store cold-water for later utilization. This potential is used to show the load shifting potential of the cooling system by using a variable electricity price as an input variable to the optimization. The set points from the optimization have been continuously adjusted throughout a dynamic simulation. A case study of a plastic processing company evaluates different scenarios against the status quo. Applying an optimal chiller sequencing and charging strategy of a sprinkler tank leads to electrical energy savings of up to 43%. Purchasing electricity on the EPEX SPOT market leads to additional costs savings of up to 17%. The total energy savings highly depend on the weather conditions and the prediction horizon.
Highlights
Generation of cold utility for industrial processes consumes about 9% of the net electricity in Germany, with similar trends in other countries, and an overall chiller energy efficiency ratio (EER) of less than two [1]
The results resultsofof predictive simulation-based optimization are compared in five scenarios
Table 3Summary summarizes the results for the comparison of the different prediction horizons, the influence of the ambient temperature, and the effect of purchasing electricity for a variable price
Summary
Generation of cold utility for industrial processes consumes about 9% of the net electricity in Germany, with similar trends in other countries, and an overall chiller energy efficiency ratio (EER) of less than two [1]. Cold utility systems encompass cooling towers (evaporative coolers), air coolers, and refrigeration. The ongoing digitization of many processes in the industry enables the potential to automate and optimize the operation of cold utility units. Coupled with an efficient and flexible utility system, a site can achieve substantially highier levels of system efficiency. Critical to this vision is linking sectors—e.g., process heating and cooling and electricity grid—combined with technologies, processes, and control systems to collect and analyze the data and implement complex energy optimization methods.
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