Optimal power system expansion planning including renewable plants, storage systems and ac short-term operation constraints using time-series synthesis and clustering: application in medium-size peruvian power systems

Abstract

One of the main challenges the Peruvian Electric System faces is the coordinated expansion of generation capacity and transmission to supply the demand requirements in the medium and long-term. Likewise, this process occurs in a context in which non-conventional renewable technologies such as solar photovoltaic (PV) and wind have experienced considerable cost reductions, which, added to the short development times that they entail, make them the ideal candidates to carry out the expansion of generation capacity. However, it is found that the country currently lacks the tools to carry out medium and long-term expansion planning considering these new technologies. Thus, this thesis presents 1) a methodology to synthesize hourly time series of solar PV and wind generation anywhere in the country, 2) a technique to reduce (cluster) the dimension of planning problems, and 3) an optimization model for the expansion of an electric power system that considers the operation of renewable plants, energy storage systems, and the AC short-term constraints. The results obtained show that these three proposals together make up a complete planning framework that allows evaluating different power systems in a context of scarcity of information, taking care of short-term validity of medium and long-term solutions, and achieving a correct trade-off between the technical and economic benefits of the solutions, versus the operating and investment costs of the decisions.