In this paper, it has been implemented a code able to provide the optimal energy generation of an isolated power system, which for this study case it is represented by Tenerife, an island situated in Spain. The optimization algorithm has been developed using CVXPY, which is an open-source-based on Python capable of modeling a language for convex optimization problems. Tenerife power system can be represented as a Dynamic Virtual Power Plant (DVPP) which includes conventional and renewable power plants. In the first scenario, it has been assumed that the electricity needed to satisfy the demand in Tenerife has been produced using three power sources, coal, wind, and PV. In the second scenario, in addition, it has been included a battery energy storage system (BESS) and it has been chosen the lithium-ion technology for the battery. The aim of this study is to obtain the renewable capacity, BESS size, and hourly renewable generation which minimize the total cost of the DVPP. Several different possibilities have been discussed, in particular focusing on the influence of renewable penetration on the solution. This has been done considering the European environmental policies and targets for 2030 and 2050 that the European Union has developed to tackle the climate change. Furthermore, it has been discussed the influence of the BESS capital expenditures (CAPEX) on the solution, considering that the battery cost is strongly decreasing over the years. Finally, the ramp-rate control for coal, wind, and PV power plants has been implemented, which limits how quickly a plant can change its output. This has been done because power quality and network stability can be harmed by a short-term fluctuation in the power generated by grid-connected power plants with a significant size.

Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant