Operation of Grid Scale Energy Storage Systems: Comparison of Multi-Stage Stochastic Programming and Empc

It is widely recognized that a major concern with renewable energy is the fact that wind and solar sources are non-dispatchable. That is, the power produced from renewable sources is dependent on environmental conditions and is likely uncorrelated with the power demand from load centers. While fossil based sources are dispatchable and currently have the ability to respond to the full range of consumer loads, the additional range imposed by renewable sources is expected to exceed the dispatch capability of these fossil plants at the point of 20% renewable power. Thus, many have advocated the use of massive energy storage systems to provide the additional level of dispatch capability required to maintain grid solvency.

Due to the uncertainty of consumer demand as well as that of renewable generation, the problem of optimal placement of these storage units within the grid along with the selection of equipment sizes must be formulated as a stochastic program. However, rather than being a fairly simple two-stage stochastic program, the dynamics imposed by the storage devices requires the formulation to be of the far more challenging multistage class. Due to the computationally intense nature of multistage stochastic programming, many have advocated the use of Economic MPC. The objective of this work is to provide a head-to-head comparison of feedback policies generated from multi-stage stochastic programming and EMPC. This comparison of policies provides a validation of EMPC based equipment design procedures.