Analysis of an Optimized Milk Cooling Controller for Dynamic Electricity Pricing Tariffs

Abstract

Abstract. The aim of this study was to quantify the financial benefits resulting from the application of a model predictive controller to a milk cooling plant in a Dynamic Electricity Tariff scenario. The model predictive controller was based on a load shifting algorithm for an ice storage system. The financial benefits produced by implementation of this controller over the current state of the art in ice bank load shifting control was simulated in a day ahead real time electricity pricing forecast environment. This real time electricity price was inferred from the cost of electricity in the Irish wholesale market. Multiple ice bank charge levels were simulated in order to quantity the performance of the two control methods for varying operating conditions such as; ambient temperature and milk cooling load. A milk production model was employed for milk yield profiling and load simulation. Both economic and energy saving benefits were found by simulating the operation of the model predictive controller for a dynamic electricity pricing tariff. The monetary savings achieved for high ice bank charges were low, but as the desired charge level was dropped the savings potential increased. This resulted in fluctuating cost saving as the cooling load is based on a seasonal variation. It was found that the benefits produced by the model predictive controller depended on the sizing of the ice bank, the electricity pricing profile and the milk cooling load. An overall mean cost saving of 6.1% was produced over a full milking season.