A probabilistic framework for unit commitment problem in deregulated markets with high penetration of wind and solar power

As a matter of fact, the soaring penetration of distributed energy resources (DERs), mainly those harvesting renewable energies (REs) such as wind and solar, is concomitant with environmentally friendly concerns. This type of energy resources are innately uncertain and bring about more uncertainties in the power system context, consequently, necessitates probabilistic analysis of the system performance. Unit commitment (UC) is a challenging optimization task which plays a crucial role in the daily operation of power systems, especially in deregulated power markets. The deterministic UC solution is used by the independent system operator (ISO) to run the system at its optimal operation point while on the contrary, the system parameters such as the load, wind and solar power are not fixed and vary ceaselessly, due to their inherent uncertainties. Therefore, the uncertainty analysis of the UC problem is an interesting issue. The two point estimation method (2PEM) is recognized as an appropriate probabilistic method to tackle with problems having uncertainties in their inputs. This paper develops a new methodology for probabilistic unit commitment (PUC) using the 2PEM to stochastically investigate on the UC problem. In order to justify the effectiveness of the proposed method, two case studies are examined using the suggested method.

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