Abstract:The ongoing shift towards a more decentralized and renewable energy system in Germany requires extensive modifications to existing grids and their operating principlesespecially at the distribution level. Furthermore, the integration of e-mobility will have a significant effect on distribution grids. Smart distribution systems are one way of handling these new supply scenarios. Hence, a self-sustaining monitoring and control system for LV-grids has been developed. It monitors the power flow situation and is ab… Show more
“…A decentralized system for LV-grid automation has been developed and tested in several LV-grids within Germany [1], [2]. The concept of the system is shown in Fig.…”
Section: B Lv-grid Automation Systemmentioning
confidence: 99%
“…Power flow calculation for LV-grids with a sparse sensor environment is a new challenge involving online monitoring of the grid state with scarce measurement data, resulting in an under-determined system of equations. Moreover, power flows at the LV-level cannot be assumed to be symmetric like at MV-level and above but are asymmetric and require phaseselective treatment [2].…”
Section: Lv-grid State Identificationmentioning
confidence: 99%
“…nodal voltages and branch currents for each phase within the entire LV-grid. The algorithm consists of two main components [2]: -a power flow algorithm, adapted and optimized for phase-selective calculation of power flows in LVgrids considering possibly asymmetric system load -a predictive algorithm for estimating loads and feedins based on sparse measurement data to compensate for the lack of information caused by the sparse sensor environment…”
Section: Lv-grid State Identificationmentioning
confidence: 99%
“…The calculation is executed consecutively for each element of the topology catalogue. The facultative elements of the grid's measurement topology do not enter into these calculationsthey are preserved for the next step of the technique [2]. Now, after a unique grid state estimate has been attributed to all elements of the topology catalogue, the deviation of the preserved facultative measurements from the values provided by the estimated grid state is calculated and stored in an error vector for each element of the topology catalogue [7].…”
“…Two different control strategies have been developed based on the 3-stage model [2]. In contrast to other approaches, the control process is solely performed by the LV-grid MCS within the secondary substation [11].…”
Section: B Direct and Optimized Control Strategiesmentioning
The ongoing shift towards more decentralized and renewable energy systems requires extensive modifications to existing grids and their operating principles -especially at the distribution level. Besides conventional grid enhancements, smart distribution systems are one way of handling these new supply scenarios and allow for maintaining voltage quality and capacity utilization constraints. The present paper describes an autonomously operating LV-grid automation system that is able to monitor the power flow situation within the LV-grid and to control the grid if necessary by using different actuators. It has been tested within several LV-grids in Germany. Both core modules of the system, the state identification module and the control module, are in the spotlight of this paper.
“…A decentralized system for LV-grid automation has been developed and tested in several LV-grids within Germany [1], [2]. The concept of the system is shown in Fig.…”
Section: B Lv-grid Automation Systemmentioning
confidence: 99%
“…Power flow calculation for LV-grids with a sparse sensor environment is a new challenge involving online monitoring of the grid state with scarce measurement data, resulting in an under-determined system of equations. Moreover, power flows at the LV-level cannot be assumed to be symmetric like at MV-level and above but are asymmetric and require phaseselective treatment [2].…”
Section: Lv-grid State Identificationmentioning
confidence: 99%
“…nodal voltages and branch currents for each phase within the entire LV-grid. The algorithm consists of two main components [2]: -a power flow algorithm, adapted and optimized for phase-selective calculation of power flows in LVgrids considering possibly asymmetric system load -a predictive algorithm for estimating loads and feedins based on sparse measurement data to compensate for the lack of information caused by the sparse sensor environment…”
Section: Lv-grid State Identificationmentioning
confidence: 99%
“…The calculation is executed consecutively for each element of the topology catalogue. The facultative elements of the grid's measurement topology do not enter into these calculationsthey are preserved for the next step of the technique [2]. Now, after a unique grid state estimate has been attributed to all elements of the topology catalogue, the deviation of the preserved facultative measurements from the values provided by the estimated grid state is calculated and stored in an error vector for each element of the topology catalogue [7].…”
“…Two different control strategies have been developed based on the 3-stage model [2]. In contrast to other approaches, the control process is solely performed by the LV-grid MCS within the secondary substation [11].…”
Section: B Direct and Optimized Control Strategiesmentioning
The ongoing shift towards more decentralized and renewable energy systems requires extensive modifications to existing grids and their operating principles -especially at the distribution level. Besides conventional grid enhancements, smart distribution systems are one way of handling these new supply scenarios and allow for maintaining voltage quality and capacity utilization constraints. The present paper describes an autonomously operating LV-grid automation system that is able to monitor the power flow situation within the LV-grid and to control the grid if necessary by using different actuators. It has been tested within several LV-grids in Germany. Both core modules of the system, the state identification module and the control module, are in the spotlight of this paper.
The new German energy strategy-the so-called Energiewende-is mainly based on the large scale implementation of volatile renewable energy sources, like onshore wind and photovoltaic. As a consequence there are two tasks to be done. The first, time-based one is to keep the power balance between the fluctuating generation and consumption. This has to be managed by the implementation of a smart market which is coordinating flexible conventional power plants, demand side and-in future-storages. The second, location-based task is to manage the new high power and volatile load flows in the grids. The utmost challenge will occur in the distribution grid. By far the most of the new generation units will be connected there. In order to solve this challenge in an economic way the technical reserves of the existing grid have to be used. This means the transition from a static dimensioned grid to a dynamically operated grid. This approach is based on the availability of on-time load flow information and active load flow management. In general such a grid is a so-called "smart grid". A very promising concept-called iNES-with a high strategic potential has been developed and implemented in Frankfurt.
This paper describes new planning principles for rural low voltage networks, which have to be significantly expanded due to the required integration of distributed energy resources. The planning principles focus on the optimized use of innovative technologies (like feed-in management and voltage controller) in order to lower the total costs of necessary network reinforcement. In order to derive these planning principles technical and economical results of multiple concrete and representative low voltage distribution networks are compared. By means of cluster analyses, dependencies between the supply tasks and the most suitable innovative technologies are examined. As a result 6 planning principles are presented and discussed as a basis for a company-specific strategic orientation for planning of low voltage networks.
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