  This paper analyzes different models for evaluating investments in Energy
Storage Systems (ESS) in power systems with high penetration of Renewable
Energy Sources (RES). First of all, two methodologies proposed in the
literature are extended to consider ESS investment: a unit commitment model
that uses the System States (SS) method of representing time; and another one
that uses a representative periods (RP) method. Besides, this paper proposes
two new models that improve the previous ones without a significant increase of
computation time. The enhanced models are the System States Reduced Frequency
Matrix (SS-RFM) model which addresses short-term energy storage more
approximately than the SS method to reduce the number of constraints in the
problem, and the Representative Periods with Transition Matrix and Cluster
Indices (RP-TM&CI) model which guarantees some continuity between
representative periods, e.g. days, and introduces long-term storage into a
model originally designed only for the short term. All these models are
compared using an hourly unit commitment model as benchmark. While both system
state models provide an excellent representation of long-term storage, their
representation of short-term storage is frequently unrealistic. The RP-TM&CI
model, on the other hand, succeeds in approximating both short- and long-term
storage, which leads to almost 10 times lower error in storage investment
results in comparison to the other models analyzed.
