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Pumped storage hydro units (PSHU) are great sources of flexibility in powersystems. This is especially valuable in modern systems with increasing sharesof intermittent renewable resources. However, the flexibility from PSHUs,particularly in the real-time market, has not been thoroughly studied. Thestorage optimization in a real-time market hasn't been well addressed. Toenhance the use of PSH resources and leverage their flexibility, it isimportant to incorporate the uncertainties, properly address the risks andavoid increasing too much computational burdens in the real-time marketoperation. To provide a practical solution to the daily operation of a PSHU ina single day look-ahead commitment (LAC) and real-time market, this paperproposes two pumped storage hydro (PSH) models that only use probabilisticprice forecast to incorporate uncertainties and manage risks in the LAC andreal-time market operation. The price forecast scenarios are formulated only onPSHUs that minimizes the computational challenges to the Security ConstrainedUnit Commitment (SCUC) problem. Numerical studies in Mid-continent IndependentSystem Operator (MISO) demonstrate that the proposed models improves marketefficiency. Compared to traditional stochastic and robust unit commitment, theproposed methods only moderately increase the solving time from currentpractice of deterministic LAC. Probabilistic forecast for Real Time LocationalMarginal Price (RT-LMP) on PSH locations is created and embedded into theproposed stochastic optimization model, an statistical robust approach is usedto generate scenarios for reflecting the temporal inter-dependence of the LMPforecast uncertainties.

A Computational Efficient Pumped Storage Hydro Optimization in the Look-ahead Unit Commitment and Real-time Market Dispatch Under Uncertainty