A multi-agent approach to the optimization of Intelligent Buildings Energy Management

Abstract

The existing installations in buildings form a specific kind of mazes that are overcome by factors that are dedicated to them (heat, water, electricity, etc.) The present systems attempt to distribute sources in such buildings to the receivers as well as they can. The most sophisticated ones are based on the Building (Energy) Management Systems, i.e. BEMS located in modern intelligent buildings. The article proposes a new approach to the existing grids with the ant colony optimization (ACO). ACO agents are effective in overcoming existing grids. But they do need modification of their standard algorithms or parsed grids for energy savings. These questions constitute the hypothesis taken under examination. The expected solution is a challenge for different ACO techniques with an evolutionary or aggressive approach taken into consideration. Different opportunities create many latent patterns to recover, evaluate and rate. They can be recovered in nondeterministic polynomial time, but they occur as NP-hard problems, so they can consume a lot of time to be solved. It is extremely important to formulate more aggressive ways to find an approximation of the optimal pattern within an acceptable time frame. The options taken under examination show that there are a few interesting approaches to accelerate the ACO and reveal a solution in real time. In the article the results are presented as the results of the research.