  Pumped storage hydro units (PSHU) are great sources of flexibility in power
systems. This is especially valuable in modern systems with increasing shares
of intermittent renewable resources. However, the flexibility from PSHUs,
particularly in the real-time market, has not been thoroughly studied. The
storage optimization in a real-time market hasn't been well addressed. To
enhance the use of PSH resources and leverage their flexibility, it is
important to incorporate the uncertainties, properly address the risks and
avoid increasing too much computational burdens in the real-time market
operation. To provide a practical solution to the daily operation of a PSHU in
a single day look-ahead commitment (LAC) and real-time market, this paper
proposes two pumped storage hydro (PSH) models that only use probabilistic
price forecast to incorporate uncertainties and manage risks in the LAC and
real-time market operation. The price forecast scenarios are formulated only on
PSHUs that minimizes the computational challenges to the Security Constrained
Unit Commitment (SCUC) problem. Numerical studies in Mid-continent Independent
System Operator (MISO) demonstrate that the proposed models improves market
efficiency. Compared to traditional stochastic and robust unit commitment, the
proposed methods only moderately increase the solving time from current
practice of deterministic LAC. Probabilistic forecast for Real Time Locational
Marginal Price (RT-LMP) on PSH locations is created and embedded into the
proposed stochastic optimization model, an statistical robust approach is used
to generate scenarios for reflecting the temporal inter-dependence of the LMP
forecast uncertainties.
