Search

The German energy transition is a new challenge for the energy supply grid. Distribution grid operators are particularly affected, especially since 90 % of the regenerative decentralized generation plants are installed at the distribution grid level. This change can lead to massive voltage band violations and equipment overloads. In principle, these problems can be solved by conventional grid expansion or smart grid solutions. In addition to economic reasons, Smart Grid solutions offer further advantages over conventional grid expansion, such as real-time monitoring of the grid state or problem handling using flexibility mechanisms - also with regard to the use of market-grid interactions. This article describes the added value of smart meters in the integration of regenerative decentralized generation plants with a focus on solar. The Smart Meter Gateway offers a tariff application case for the recording of feed-ins with a resolution of 15 minutes, which are transmitted cyclically, in order to fulfil the specifications for the integration of solar systems between 30 and 100 kilowatts in particular. In addition, this article illustrates how market participants can use the smart meter to map their business models in addition to grid-based control. The aim is to increase the integrability of renewable energy plants or storage facilities by means of flexibility mechanisms. The controllable systems provide a flexible share of the output on the market. In addition, artificial intelligence methods for photovoltaic power forecasting are presented within the framework of grid condition estimation, which result in a minimization of switching operations. [ABSTRACT FROM AUTHOR]

This paper describes a method to identify the optimal position for stationary storage systems in a low voltage direct current (LVDC) traction network with non-receptive power sources and photovoltaic systems. The peculiarity of such a system is that there is no possibility of transferring any energy back into the adjacent medium voltage AC grid. This behavior comes with its own challenges and depends on innovative solutions to increase stability and efficiency. For this purpose, a storage system is planned to be integrated into the network structure. A method for optimized location identification will subsequently be introduced and demonstrated using an LVDC traction network simulation. The simulation consists of a DC power flow (PF) algorithm, a PV simulation and trolleybus movement simulations. These different components are explained and the storage positioning method introduced. The first results of this approach are presented and will be discussed. [ABSTRACT FROM AUTHOR]

In the course of the ongoing transformation of the energy supply towards a renewable and decentralized system, the share of volatile renewable infeeders, as well as high power consumers like plug-in electric vehicles (PEVs) in the German distribution grid is steadily increasing. Challenges in that context are likely to manifest mainly through asset overloads in urban distribution grids. Since charging processes of PEVs rarely require the maximum charging power over the entire parking time, they offer a high level of flexibility, which may be used to counteract grid overloads via controlled charging. Therefore, comparatively expensive grid enhancement could be avoided. Additionally, the integration of renewable energy sources could be supported by exploiting the PEVs' charging flexibility (i.e. to match volatile infeed). A further increase in added value may be achieved through a suitable energy procurement strategy at the spot market for energy, which should also take into account forecast deviations. In this paper a procurement optimization strategy for a car park with 40 PEV charging stations and decentralized infeeders is presented. In that context an automated temporal shift of the PEV charging power is carried out several times in order to adapt the charging schedule to the relevant energy prices and occurring forecast deviations. The corresponding grid-related power limit is constantly adhered to. [ABSTRACT FROM AUTHOR]

In the course of the ongoing transition of the energy supply towards a renewable and decentralized system, the number of electric vehicles in Germany is also increasing. The growing number of electric vehicles is an important part of the energy transition, along with the expansion of decentralized generation facilities. While there is sufficient measurement technology available at the transmission grid level to calculate the state of the grid and the calculation algorithms focus more on the redundancy of the measured values and their measurement errors, there is hardly any measurement technology available below the 110 kV level. As a result, the observability of mediumvoltage and low-voltage grids is severely restricted. This situation is historically conditioned and can be traced back to the power supply by means of central large-scale power plants. This paper highlights the added value of smart meters in the context of the integration of electromobility. Furthermore, it will be presented how the combination of smart meters and decentralized distribution grid automation systems can cost-efficiently increase the transparency in the grid. Within this framework, an intelligent Smart Meter Converter is presented, which provides the decentralized grid automation system with scenario-specific Smart Meter data in a usable form. The advantages and relevance of such a module in the context of digitization and industry 4.0 will be highlighted. Based on this, first steps for the practical realization of an intelligent Smart Meter Converter will be presented. [ABSTRACT FROM AUTHOR]

This contribution presents two different grid serving coordination mechanisms for the control of charging stations based on a multi agent approach. In the first coordination mechanism the agents control autonomously and in the second coordination mechanism the agents create a collaborative controls strategy by negotiation and interaction. In addition, the structure of the multi agent system is discussed and the control modelling of a charging station is described. Finally, the stability of the control mechanisms are critically analysed. [ABSTRACT FROM AUTHOR]

The German energy transition is a new challenge for the energy supply grid. Distribution grid operators are particularly affected, especially since 90 % of the regenerative decentralized generation plants are installed at the distribution grid level. This change can lead to massive voltage band violations and equipment overloads. In principle, these problems can be solved by conventional grid expansion or smart grid solutions. In addition to economic reasons, Smart Grid solutions offer further advantages over conventional grid expansion, such as real-time monitoring of the grid state or problem handling using flexibility mechanisms - also with regard to the use of market-grid interactions. This article describes the added value of smart meters in the integration of regenerative decentralized generation plants with a focus on solar. The Smart Meter Gateway offers a tariff application case for the recording of feed-ins with a resolution of 15 minutes, which are transmitted cyclically, in order to fulfil the specifications for the integration of solar systems between 30 and 100 kilowatts in particular. In addition, this article illustrates how market participants can use the smart meter to map their business models in addition to grid-based control. The aim is to increase the integrability of renewable energy plants or storage facilities by means of flexibility mechanisms. The controllable systems provide a flexible share of the output on the market. In addition, artificial intelligence methods for photovoltaic power forecasting are presented within the framework of grid condition estimation, which result in a minimization of switching operations. [ABSTRACT FROM AUTHOR]

The German energy transition is a new challenge for the energy supply grid. Distribution grid operators are particularly affected, especially since 90 % of the regenerative decentralized generation plants are installed at the distribution grid level. This change can lead to massive voltage band violations and equipment overloads. In principle, these problems can be solved by conventional grid expansion or smart grid solutions. In addition to economic reasons, Smart Grid solutions offer further advantages over conventional grid expansion, such as real-time monitoring of the grid state or problem handling using flexibility mechanisms - also with regard to the use of market-grid interactions. This article describes the added value of smart meters in the integration of regenerative decentralized generation plants with a focus on solar. The Smart Meter Gateway offers a tariff application case for the recording of feed-ins with a resolution of 15 minutes, which are transmitted cyclically, in order to fulfil the specifications for the integration of solar systems between 30 and 100 kilowatts in particular. In addition, this article illustrates how market participants can use the smart meter to map their business models in addition to grid-based control. The aim is to increase the integrability of renewable energy plants or storage facilities by means of flexibility mechanisms. The controllable systems provide a flexible share of the output on the market. In addition, artificial intelligence methods for photovoltaic power forecasting are presented within the framework of grid condition estimation, which result in a minimization of switching operations. [ABSTRACT FROM AUTHOR]

This paper describes a method to identify the optimal position for stationary storage systems in a low voltage direct current (LVDC) traction network with non-receptive power sources and photovoltaic systems. The peculiarity of such a system is that there is no possibility of transferring any energy back into the adjacent medium voltage AC grid. This behavior comes with its own challenges and depends on innovative solutions to increase stability and efficiency. For this purpose, a storage system is planned to be integrated into the network structure. A method for optimized location identification will subsequently be introduced and demonstrated using an LVDC traction network simulation. The simulation consists of a DC power flow (PF) algorithm, a PV simulation and trolleybus movement simulations. These different components are explained and the storage positioning method introduced. The first results of this approach are presented and will be discussed. [ABSTRACT FROM AUTHOR]

The scope of the following paper is a comprehensive analysis of how the grid state identification (GSI) is influenced by functional PV features, namely the orientation and the inclination. The grid state estimation is based on both a specific number of installed measurement devices and static grid information, such as the grid characteristics and the installed PV-power per node. This information is used to estimate substitute-values for the load flow calculation. However, the calculations suffer from inaccuracies due to the fact that several characteristics were approximated [1]. The grid state identification is supposed to be optimized by providing it with the most influential information next to the estimation of further insignificant values. In the existing Smart Grid System, PV features like orientation and inclination are neglected [1]. To increase the accuracy of the grid state identification these features can be implemented as additional information, which is why the considered information will be mentioned in future plant registry for upcoming PV-Systems. As a first step, the analysis investigates different PV- and gridproperties in order to demonstrate the potential additional benefits each value is able to provide. Furthermore, the use of the main features in the grid state identification process will be discussed. Each standard and additional value have to be implemented and configured. In summary, the paper presents the grid state identification functions as well as the use of important PV features to efficiently integrate a huge number of PV-Systems in a smart distribution grid. [ABSTRACT FROM AUTHOR]

Grid State Forecasting becomes more important in smart distribution grids, especially in context with the establishment of smart markets for solving local grid state violations. This document focuses on the influence and suitability of photovoltaic forecast for Grid State Forecasting. There for the Grid State Forecast algorithm, using two different photovoltaic forecasts, was analyzed. [ABSTRACT FROM AUTHOR]