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Item type:Publication, Access status: without files , Distribution grid state assessment for control reserve provision using boundary load flow(2019-06); ; With the increasing expansion of wind and solar power plants, these technologies will also have to contribute control reserve to guarantee frequency stability within the next couple of years. In order to maintain the security of supply at the same level in the future, it must be ensured that wind and solar power plants are able to feed in electricity into the distribution grid without bottlenecks when activated. The present work presents a grid state assessment, which takes into account the special features of the control reserve supply. The identification of a future grid state, which is necessary for an ex ante evaluation, poses the challenge of forecasting loads. The Boundary Load Flow method takes load uncertainties into account and is used to estimate a possible interval for all grid parameters. Grid congestions can thus be detected preventively and suppliers of control reserve can be approved or excluded. A validation in combination with an exemplary application shows the feasibility of the overall methodology.Publicationtype: Conference Paper124 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A distribution system state estimation for an efficient integration of electric vehicle charging infrastructure into low-voltage gridsDue to political reasons, a growth in the usage of electric vehicles (EV) is expected for the coming years. The consequenceis an increasing amount of EV charging operations, where the charging devices are mainly connected to the low-voltagelevel of the distribution grid. A high simultaneity factor of the charging processes together with inherent high and constantload demands can lead to a higher stress on grid assets and in extreme situations to violations of grid operation constraints.For a resolution of this problem, direct load management represents a favorable instrument in the view of distributionsystem operators. An efficient load management scheme, which acts on the loads only in critical grid situations, demandsa grid state estimation of high accuracy. A deteriorating factor for the estimation quality in low-voltage grids is the verylow-availability of real-time measurements.This work presents a methodology for implementing an accurate state estimation scheme for low-voltage grids, withoutthe need for real-time measurements and solely based on historical smart meter data. For the realization of the objective,the methodology consists of the synthesis of two concepts. The first concept implements a state estimation algorithmfor low-voltage grids using three-phase line models. In order to handle the low-availability of real-time measurementdata, a concept for the generation of pseudo-measurements flanks the first concept. Hereby, neural networks trained withhistorical smart meter data are used to estimate the real-time load behavior of household loads.A series of exemplary simulations in a typical low-voltage grid from the city of Hamburg proves the applicability of thedeveloped concept.Publicationtype: Conference Paper253 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Ensuring the reliability of control reserve from renewable energiesIn the future, wind and solar power plants must also be able to provide control reserve, whereby the challenges of participating in the control reserve market particularly consist in maintaining the high level of reliability required for the provision. This paper presents a methodology for the calculation of the maximum offerable amount of control reserve which can be provided by a spatially distributed pool of wind and solar power plants. This is done under consideration of the adherence to a given reliability level. A probabilistic approach is chosen, which models the stochastic dependencies of the forecast errors with the copula-theory. The methodology is compared with alternative calculation methods on the basis of an exemplary pool consisting of 32 plants. Finally, the amount of offerable control reserve is examined with a variation of the reliability target.Publicationtype: Conference Paper225