Modeling of photovoltaic power uncertainties for impact analysis on generation scheduling and cost of an urban micro grid

In electrical systems, the main objective is to satisfy the load demand at the least cost without having imbalance between generation and consumption. Thus, the uncertainty of photovoltaic (PV) power production must be considered in generation planning of a power system. In this paper, we develop a modeling method of this uncertainty to consider it into the generation scheduling. The optimal generation scheduling in an urban microgrid is made by taking in consideration the operating reserve provision under stochastic characteristics of PV power prediction. By considering a prescribed risk level of unbalancing, a dynamic programming algorithm sets the operational planning of conventional generators by solving a non-convex mixed-integer nonlinear programming model, so that the operational cost and available operating reserve can be calculated. Then, the effect of PV power uncertainty into the unit commitment is analyzed by considering PV forecast intervals with a 95 % confidence level. The unit commitment is then recalculated with new generator set points and the same criteria. Finally, variations of the targeted minimized costs and obtained OR is analyzed according to the uncertainty. (C) 2020 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.

Automated summary

This paper investigates the impact of photovoltaic power production uncertainty on generation scheduling in power systems, using a dynamic programming algorithm to solve a non-convex mixed-integer nonlinear programming model, and analyzing the cost and operational reserve variations due to PV power uncertainty.