Minimizing Operating Costs of Vapor Compression Equipment with Optimal Service Scheduling

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Dynamic programming was used to obtain optimal service schedules and costs for cleaning the condensers and evaporators of air-conditioning equipment. Results were obtained for a range of service and energy costs, characteristic fouling times, and equipment sizes for a single building and location. Minimum operating costs were compared with regular service intervals (representative of current practice) and a strategy where service is only performed when a constraint is violated (e.g., a comfort violation). It was found that optimal service scheduling reduced lifetime operating costs by as much as a factor of two over regular service intervals, and by 50% when compared to constrained only service. For practical implementation, a simple near-optimal algorithm for estimating optimal service scheduling was developed that does not require on-line forecasting or numerical optimization and is easily implemented within a micro-controller. Over the wide range of cases tested, the near-optimal algorithm gave operating costs that were within 1% of optimal. This technique could also be applied to other systems where performance degradations are important such as large chillers and power plants.