(601c) Unit Commitment Operation of Energy Storage Systems: Comparison of Multi-Stage Stochastic Programming and Empc

Adeodu, O. - Presenter, Illinois Institute of Technology
Chmielewski, D. J., Illinois Institute of Technology
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. Previously, we have demonstrated that Economic Model Predictive Control (EMPC) can be used to approximate the scenario based multi-stage stochastic programming version of the economic dispatch problem. However, since operation of storage units is expected to be at a larger time scale, it is more appropriate to consider a Unit Commitment (UC) type framework. Within this framework the multi-stage, stochastic program will contain mixed integer variables, accentuating the need for a more computationally attractive operating policy. In this work, the head-to-head comparison between EMPC and the scenario based solution is extended to the UC framework in an effort to validate the adoption of more tractable EMPC-based methods for the optimal sizing and placement of storage units.