语言表述
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In this context, several methodologies have been emerging for distribution grid management considering RES uncertainty. These methodologies are most often based on stochastic programming and robust optimization [5], [6].
Nevertheless, for a DSO, a more seemly output would be a single solution that is robust in all or a pre-defined percentage of the scenarios.
Current Management The mission of a DSO is to ensure the quality and continuity of supply levels imposed by the regulatory framework. In the past, technical problems such as overcurrent and voltage limit violation were mitigated by planning network investments and changing the network configuration to meet the loads. Presently, DSOs have additional flexibility in the network that allows solving the local technical problems in the operational domain, instead of solving them in a planning phase. The main benefits are investment deferral and reduced curtailment of DER. In the operating domain, the typical control actions are network reconfiguration, control of capacitor banks and activation, though on a very limited way, of non-firm connection contracts associated to industrial loads and some DER. Information about forecasts and corresponding uncertainty is not embedded in the current grid management functions.
- The vertices of the uncertainty set that are selected for the optimization process are represented by ΔP w(w,t,s) in the formulation. In addition, the number of vertices of the convex hull can increase significantly, when considering a large amount of intermittent resources, which can be intractable in the time frame of the DSO to solve the problem. Thus, algorithms to reduce the number of vertices can be considered. The recursive Douglas-Peucker algorithm [17] is based on polyline simplifications and can reduce the number of vertices that characterize the uncertainty set. An improved and speeding up version of the algorithm [18] can be used to significantly reduce the vertices of the uncertainty set。
([17] D. H. Douglas and T. K. Peucker, “Algorithms for the reduction of the number of points required to represent a digitized line or its caricature,” Cartogr. Int. J. Geogr. Inf. Geovisualization, vol. 10, no. 2, pp. 112–122,1973.
[18] J. Hershberger and J. Snoeyink, “Speeding up the Douglas-Peucker linesimplification algorithm,” in 5th International Symposium on Spatial Data Handling, 1992, pp. 134–143.)
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