Numerical methods for optimization problems arising in energetic districts

This paper deals with the optimization of energy resources management of industrial districts, with the aim of minimizing the customer energy bill. Taking into account real time information on energy needs and production and on energy market prices, a cost function is built that should be minimized. Here we focus on the solution of the arising nonlinear constrained optimization problem. We describe the two solvers that have been employed for its solution: a Sequential Linear Programming and a Particle Swarm Optimization