Optimal Electric Water Heater Sizing for Large Consumers using Techno-Economic Indicators

This article presents an algorithm developed to optimally determine the number and capacity of electric water heaters (EWHs) meeting the hot water needs of these structures. The optimization problem is treated as a multi objective problem with integer variables and is implemented using the particle swarm optimization (PSO) algorithm. The main objective is to achieve an optimum balance between satisfying users’ hot water needs and efficient cost management, particularly with regard to initial investment and maintenance expenditure. Three scenarios are addressed in this study, the first focuses on the investment and maintenance costs optimization by considering a minimum threshold of comfort for the hot water user; the second scenario favors the occupant comfort optimization, without worrying about the amount of the investment, while the third scenario seeks to establish a balance between these two contradictory objectives. To highlight the interests of the proposed optimization algorithm, its performances are compared to a conventional (and nonoptimal) solution, which consists of associating a small volume water heater with each element of the considered establishment. The simulations carried out under the Python environment show that compared to the conventional solution, the proposed algorithm ensures a reduction of 89.72% on the investment and maintenance costs, although a degradation of 6.6% is noted on the hot water user comfort.