Multiple objective Particle Swarm Optimization approach to enable smart buildings-smart grids

This paper proposes an effective method for improving the flexibility of buildings as electrical loads to support the distribution grid operation. The buildings energy consumption is the result of the operation of the energy systems that are there to support its operation. As the buildings main purpose is to provide a safe environment, a great part of the buildings energy demand come from the operation of the comfort systems. Furthermore, the aim is always to use as less electrical energy as possible. In this paper, two conflicting objectives, i.e. maximization of comfort and minimization of energy consumption, are optimized to provide a Pareto optimal solution, taking into account the low voltage network operation. A Weighted Aggregation Approach is used in a combination with Particle Swarm Optimization to find this Pareto optimal. The model is tested on a low voltage distribution test feeder, and different weights are used to tune the flexibility of the building.