Abstract
Power system operation and planning studies face many challenges with increasing of renewable energy sources (RESs) penetration. These challenges revolve around the RESs uncertainty and its applications on probabilistic forecasting, power system operation optimization and power system planning. This paper proposes a novel and effective criterion for uncertainties modeling of the RESs as well as system loads. Four sorting stages are applied for the proposed uncertainty cases reduction. Added to that, it proposes three different uncertainty reduction strategies for obtaining different accuracy and speed options. The proposed reduction strategies are tested on medium and large scale distribution systems; IEEE 69-bus and 118-bus systems. The obtained results verify the effectiveness of the proposed criterion in uncertainties modeling in distribution systems with acceptable level of accuracy.
Highlights
Many electrical power system studies are concerned with uncertainty modeling especially those which based on renewable energy sources (RES) such as photovoltaic (PV) and wind turbines (WT)
Three different reduction case strategies are applied to the new criterion to obtain the appropriate accuracy and speed
The proposed reduction strategies lead to a 99% reduction in the uncertainty cases for one year, which is sufficient for effective modeling with an acceptable level of accuracy
Summary
Many electrical power system studies are concerned with uncertainty modeling especially those which based on renewable energy sources (RES) such as photovoltaic (PV) and wind turbines (WT). There are some uncertainties that can not be modeled possibilistically or probabilistically, a hybrid method can be used combining the merits of the two techniques [19]. In [24], The uncertainty of two wind profile and system load demand is simplified and modeled using three dimension scenarios based probabilistic method. In [25], a reduced set of scenarios were introduced for representing the uncertainties of WT, PV and load demand in optimal planning of active distribution grids. Worst case scenario uncertainty based model was incorporated with robust control problem of RES [27]. The main issue of the pre-mention uncertainty reduction studies is that it considered as a trade-off problem because the modelling accuracy is inversely proportional to the time consumed [28]. Three different strategies are introduced for offering different degrees of simplicity and accuracy depending on the considered uncertainty cases
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