14th International Conference on the European Energy Market - EEM17, Dresde (Alemania). 06-09 junio 2017
Resumen:
In recent years, power systems have been watching important advancements related with Plug-in-Electrical Vehicles (PEVs), Demand Side Management (DSM), Distributed Generation (DG), Microgrid and Smart Grid installations that directly affect distribution networks while impacting indirectly on Transmission studies. These changes will lead to an extra flexibility on the transmission-distribution boundary and to a significant modification of the load patterns, that are an essential input to planning studies. In this scope, this paper describes a multiyear Transmission Expansion Planning (TEP) solved by Evolutionary Particle Swarm Optimization (EPSO) and incorporating the impact of solar DG penetration. The primary substation load profiles and the solar generation profiles are taken into account on the planning problem. The numerical simulations were conducted using the IEEE 24 bus reliability test system in which the planning horizon is 3 years and the load growth is 2.5 % per year. If demand and solar DG peaks are coincident, then the liquid demand seen by the transmission network gets reduced enabling a reduction of investment costs. In the tested cases, these peaks were not coincident so that the optimal expansion plan remains unchanged even though the injected power from DG is large. This stresses the fact that solar DG may not on an isolated way contribute to alleviate the demand seen by transmission networks but should be associated with storage devices or demand side management programs.
Palabras clave: Multiyear Transmission Expansion Planning, AC – Optimal Power Flow, Solar DG, Evolutionary PSO
DOI: 
https://doi.org/10.1109/EEM.2017.7981850
Fecha de publicación: junio 2017.
Cita:
Vilaça, P., Tomé Saraiva, J.P., Transmission system planning considering solar distributed generation penetration, 14th International Conference on the European Energy Market - EEM17, Dresde (Alemania). 06-09 junio 2017.
IIT-17-266C
