There are different MV grid concepts with regard to mode of operation and protection system layout. The increasing installation of DG raises the question if the currently used concepts are still optimal for future power systems. We present a methodology that allows the automated calculation and comparison of target grids within different concepts. Specifically, we consider radial grids, closed ring grids and grids with switching stations. A target grid structure is optimized for each of those grid concepts based on geographical information. To model a realistic planning process, compliance with technical constraints for normal operation, contingency behaviour and reliability figures are ensured in all grid concepts. We present a multiphase approach to solve the optimization problem based on an iterated local search meta-heuristic. We then economically compare the grids with regards to CAPEX and OPEX for primary and secondary equipment, to analyse which concept leads to the most overall cost-efficient target grids. Since the methodology allows an automated evaluation of a large number of grids, it can be used to draw general conclusions about the cost-efficiency of specific concepts. The methodology is applied to 44 real MV grids spanning about 4800km of lines, for which the results show that a radial grid structure is overall cost efficient compared to grid topologies with switching stations or closed rings even in grid areas with a large DG penetration. The contribution of this paper is threefold: first, a comprehensive methodology to compile automated target grid plans under realistic premises is presented. Second, the practical applicability of the approach is demonstrated with a large scale case study with a high degree of automation. And third, the results of the case study allow to draw conclusions about the techno-economical differences of different MV grid concepts.

Since failure of high- to medium-voltage (MV) transformers affect a large number of consumers, they are usually built with a redundancy to guarantee service restoration in the case of a single contingency. The redundancy can be provided by a backup transformer or by transferring the load to a neighbouring substation in case of failure. While a load transfer allows for more efficient use of transformers in normal operation, it also requires the MV network to be dimensioned with redundant transmission capability for the contingency case. In this study, the authors present their approach to determine if it is profitable in the long term to remove a backup transformer in intrinsically safe substations and handle resupply with load transfer to neighbouring substations instead. To this end, they compare the cost of the necessary network expansion to the costs of a backup transformer. They introduce an iterated local search algorithm for the calculation of emergency switching plans as well as expansion of the MV network. The methodology is applied to a large real MV network group, where reinforcing the network to allow a load transfer is cost efficient compared with the existing backup transformer in three of four substations.

This study is addressing the issues regarding reduction in the necessary network expansion by taking flexibility options into account. If a certain amount of the annual energy from renewable generation is curtailed, the expansion of the power grid can be reduced. This study presents a comparison of the necessary expansion of a high-voltage distribution grid (110 kV) under consideration of different curtailment approaches for renewable energy sources. Here, the necessary expansion is calculated, if a static or a dynamic curtailment is applied and then compared with the calculations without any curtailment mechanism. The curtailment methods are tested using a probabilistic expansion planning method based on the calculation of probabilistic load flow.

This paper presents an adaption of stochastic load profile modeling for application in distribution grid simulations. Such load profiles are necessary for network expansion planning as well as for state estimation in case of unavailable measurements. Relevant properties of the synthetic load profiles generated by Markov chain-based approach and a linear regression model will be adapted by a denormalization for using in smart grid simulations. First, a briefly explanation of the used profile modeling approaches will be given and the resulting weak points will be demonstrated. In relation to this, the denormalization process for the adoption of the synthetic profiles will be presented. The validation of the proposed method will be carried out by the comparison of the relevant properties for smart gird simulations before and after the denormalization. The results of this evaluation are contributed to assess potential fields of application of the synthetic profiles presented in this paper.

This paper presents a new efficient way to integrate the (n−1)-security into modern probabilistic network expansion planning. Therefore, a method is presented for an (n−1)-secure probabilistic load flow based on AC distribution factors. For the simulation of multiple segment outages, a new mathematical description is presented. The presented method is able to handle the islanding of single nodes within the calculation. Afterwards, a linearization is presented using the superposition theorem and Newton Raphson load flow calculations. A new linearization of the power flow is used to consider reactive power flows. Based on this, AC line outage distribution factors can be calculated using the normal operation state of the grid. The analyzed sensitivity of the distribution factors to the load and generation scenario is low. Therefore, the linearized method shows a good congruency. Additionally, the proposed method identifies correctly the worst case conditions in massively reduced computation time. A comparison between the (n−1)-secure probabilistic method and today’s deterministic planning methods show that the high penetration of renewable energy sources leads to an under dimensioning of the grid.

This paper presents different new formulations of dynamic optimal power flow for power feed-in curtailment of RES that are applicable in distribution grid planning. Therefore, a method for dynamic curtailment is presented using AC distribution factors and afterwards optimized using linear programming. The optimal power flow formulations minimize the annual curtailed energy under the boundary condition of a maximum active power flow, the annual curtailed energy and the combination of both. The results on a 5 bus test system show that overloading of lines can be prevented using dynamic curtailment with a small amount of curtailed energy. Therefore, the optimal power flow formulations can be used by distribution system operators to plan their grid using different ways to increase the hosting capacity of renewable energy sources.

This paper presents a new approach for a dynamic curtailment method for renewable energy sources that guarantees fulfilling of (n-1)-security criteria of the system. Therefore, it is applicable to high voltage distribution grids and has compliance to their planning guidelines. The proposed dynamic curtailment method specifically reduces the power feed-in of renewable energy sources up to a level, where no thermal constraint is exceeded in the (n-1)-state of the system. Based on AC distribution factors, a new formulation of line outage distribution factors is presented that is applicable for outages consisting of a single line or multiple segment lines. The proposed method is tested using a planning study of a real German high voltage distribution grid. The results show that any thermal loading limits are exceeded by using the dynamic curtailment approach. Therefore, a significant reduction of the grid reinforcement can be achieved by using a small amount of curtailed annual energy from renewable energy sources.

This study proposes a new, fast and efficient method to identify worst-case conditions that result in a maximum loading of a particular line in active distribution grids. For this purpose, distribution factors are formulated based on the AC power flow equations and superposition theorem. Caused by the high penetration of volatile renewable energy sources, probabilistic methods are necessary in network expansion planning, since the predefined load and generation conditions are no longer suitable. The proposed rapid identification method is compared with the comprehensive probabilistic load flow (PLF) analysis in a real high-voltage distribution grid. The identified worst-case scenarios, using both approaches, differ slightly; nevertheless, the results of an in-line contingency analysis are quite similar to the PLF, which shows the applicability of the method. An additionally performed sensitivity analysis proves the high accuracy of the proposed approach.

Grid expansion planning requires detailed information regarding profiles of load and generation at all grid nodes considered in order to determine the resulting loading of system components. However, these profiles can have an extremely aggregated character in the high voltage grids, which can make it difficult to estimate the proper simultaneity between generation and load, especially if future scenarios are considered. In this paper, a new modeling approach for building synthetic load profiles for analysis of future high voltage grid expansion requirements is proposed. It is based on an autoregressive process, whereby climatic data are used to represent the correlation of the power infeed at each grid node with regard to the weather conditions over the area of the high voltage grid considered. A validation is performed using the data measured. Thus, a high number of profiles are calculated and the mean values are compared to the profiles measured. The validation shows good congruency.

One objective of grid planning for low voltage grids is to determine cable diameters of feeders. This usually involves simulating worst case scenarios to estimate peak loads, although the probability of such scenarios to actually occur is not known. Furthermore, today's grid planning needs to account for new technologies like dispersed generation and electric vehicles. A worst case approach, for example, would consider generation without any simultaneous load. However, in practical experience there is always a minimum load, which mitigates the effect of voltage rise due to generation. This publication presents a new approach to probabilistic grid planning under the consideration of risks of certain scenarios to occur. This methodology can help to plan grids more efficiently.

This contribution proposes a method to analyze the capabilities of low voltage grids to meet the demands of additional loads due to electric mobility. Probabilistic load models for both the domestic and electric vehicle loads are developed to give insight into the stochastic nature of load distribution and voltage bands. The results not only provide the maximum voltage deviations, but their probability of occurrence during a given period of time. With this information, a recommendation for future grid planning can be developed, which takes into account the increasing load caused by electric mobility. Furthermore, a load management system is proposed to reduce maximum load thus avoiding costs for increasing feeder capacities.

This paper presents procedures to handle time delays in a feedback control loop in which both measurement and control signals are sent through a network, where random time delays occur. Even when time stamps are utilized, for example, the control signal time delay still must be estimated. Using a Padé approximation and a Kalman filter, we can estimate the mean time delay. Furthermore, methods are described to estimate the time delay of every packet instead of the mean for the measurement channel, which greatly enhances the performance of the Padé approximation approach. This is done by matching the measurements to the expected measurements provided by the filter with maximum likelihood. The methods are applied to an inverted pendulum to assess performance.

The European electricity grid has faced significant changes over the past decades, inlcuding the interconnection of previously separated grids. This development has led to a phenomena called interarea modes where the frequencies of regions several hundred miles apart oscillate against each other. This paper elaborates on the possibilities of load control to oppose such instabilities. Using a simplified model of the European grid, it is shown that an additional controller attached to part of the load in the grid can, in principle, increase the damping of interarea oscillations. Various control approaches are examined and a statement for future usability is given.

AbstractDie elektrische Energieversorgung verändert sich dramatisch. Der Umbau des Kraftwerkparks, dezentrale Einspeisung und neue Verbraucher wie Elektroautos stellen das Stromnetz der Zukunft vor völlig neue Herausforderungen. Zum einen muss das Netz für die Fernübertragung ausgebaut werden. Die Energie wird zum Beispiel zunehmend von Windparks produziert, die weiter weg von den Verbrauchern stehen. Zum anderen muss das Netz der Zukunft Erzeuger, Speicher und Verbraucher intelligent verbinden. Dazu tragen auch intelligente Stromzähler bei, die seit dem 1. Januar 2010 in Neubauten und sanierten Altbauten eingesetzt werden müssen.