Efficient solution of many-objective Home Energy Management systems

Home Energy Management systems have become an essential tool on pursuing an efficient energy consumption besides the implantation of demand response programs in residential consumers. This kind of systems have evolved from a single-objective paradigm, in which only the electricity bill was concerned, to many-objective frameworks that involve different targets such as grid supporting programs or user convenience premises. From the computational point of view, many-objective optimization problems are more challenging than single-, and multiple-objective ones due to higher computational burden and the necessity of advanced tools capable to reach a compromise solution among objectives. This paper tackles this issue by developing an efficient but effective stochastic many-objective solution framework based on Mixed Integer Linear Programming formulation. The new proposal is based on lexicographic optimization and scalarizing functions, thus allowing to distinguish one of the targets as the most important one. This feature makes the new approach very suitable for Home Energy Management systems in which the energy cost is normally the most important objective while other goals can be considered secondary. The developed tool is validated on a standard home layout benchmark considering up to six typical objectives. The results obtained put on manifest the effectiveness and efficiency of the developed approach.

Automated summary

This paper presents an efficient stochastic many-objective solution framework based on Mixed Integer Linear Programming formulation, which is suitable for Home Energy Management systems focusing on energy cost. The validation on a standard home layout benchmark demonstrates the effectiveness and efficiency of the proposed approach.