New optimization models to solve the distribution system planning problem in the context of active networks

Abstract

The integration of renewable energy resources and new technologies in future electricity distribution networks requires planning methodologies that accurately consider the uncertainty associated with the output power from the renewable sources and the demand growth. To that aim, novel optimization methodologies for the multi-period expansion planning problem of distribution systems will be developed in this project. The proposed methodology is a specialized tool to support the network operator decisions in the planning of the future distribution grid. Traditional network assets (feeders and substations), as well as new assets, e.g., renewable/conventional distributed generators and storage systems will be included within the expansion planning, considering the influence of new technologies such as electric vehicles.Regarding the network characteristics, the mathematical models will include convex versions of the AC power flow equations, which will be obtained by using convex relaxation techniques or linear approximations. In addition, stochastic and robust programming approaches will be employed to deal with the uncertainties of demands and renewable sources. The mathematical formulation will be implemented in the mathematical modeling language AMPL and the solutions will be assessed using Monte Carlo simulations.