A Dynamic Scheduling Technique to Optimize Energy Consumption by Ductless-split ACs

Abstract

The cooling systems contribute to 40% of overall building energy consumption. Each building has different cooling requirements based on its usage. There are two types of cooling systems, a ducted-centralized cooling system, and a ductless-split cooling system. To optimize the energy consumption of the ductless-split cooling system, we propose a Cooling-System Linear-Scheduling Algorithm (CLA). Besides optimizing, our technique satisfies two constraints, (a) maintaining the desired temperature in the entire room and (b) not executing any cooling system unit for a longer duration to increase its lifespan.We compare the energy savings by CLA with two techniques, the execution of all the ACs (AA) and a greedy algorithm (GA). AA maintains the desired temperature with the least deviation. The energy savings by GA serves as a benchmark as it consumes the least possible energy. The heat sources and external environment remain the same in a real-world environment. We use simulation to evaluate our proposed CLA with different external environments and heat sources. In a real-world setting, CLA saves up to 62% of energy compared to the cooling system’s execution when all the ACs are working. It saves up to 85% of energy consumption in the simulation environment. For real-world and simulation settings, CLA consumes the same energy as GA, which is the optimum. However, GA does not satisfy the second constraint of improving the lifespan of ACs. In both settings, CLA matches the desired temperature similar to that of AA and better than that of GA.