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Merit Order of Grid Optimizing Measures for a Sustainable Grid Planning and Efficient Solar Integration

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Merit Order of Grid Optimizing Measures for a Sustainable Grid Planning and Efficient Solar Integration Merit order of grid optimizing measures for a sustainable grid planning and efficient solar integration Simon Köppl, Andreas Zeiselmair, Alexander Bogensperger, Mathias Müller, Michael Hinterstocker, Florian Samweber Forschungsstelle für Energiewirtschaft (FfE e.V.), Forschungsgesellschaft für Energiewirtschaft mbH Research Center for Energy Economics Munich, Germany framework, a methodology was developed to assess the The integration of solar power leads to new challenges techno-economical potential of these measures which is especially in distribution grids. A wide variety of grid described in this paper. optimizing measures with different technical and economic characteristics is available. Therefore, a consistent II. SCENARIOS FOR FUTURE GRID DEVELOPMENTS methodology to analyze the effects of different measures in First of all, scenarios of future developments in the representative exemplar grids especially with high German energy supply were defined, reflecting different photovoltaic penetration is necessary. This paper describes a possible changes in the upcoming decades. Based on a possible option to derive a merit order of grid-optimizing systematic and transparent scenario process, five scenarios measures for distribution grids in regions with diverse energy mixes and grid structures. were developed. The aim of this process was to derive scenarios as heterogeneous as possible but always Keywords: simulation, grid planning, grid optimizing considering realistic and consistent framework conditions in measures, distribution grids order to get a robust evaluation of the gom on distribution and transmission grid level. This includes the general I. INTRODUCTION framework of the energy economy but also consumption and The pending extensive reconstruction of grid supply factors. The analysis shows, not only supply and infrastructure is not only a technical challenge. Planning and demand, but also the intelligence of the future grid realization is caught in a field of tension between infrastructure as well as the potential influence and economical and socio-political interests. Under the heading accessibility by system operators are relevant for the impact Merit Order Grid-Expansion 2030 (German: “Merit Order and effectiveness of gom. After all, the following five Netz-Ausbau 2030” – MONA 2030) 1 , a comparison of MONA scenarios were derived (see also the comparison of measures and technologies for grid optimization is currently the critical descriptor in the different scenarios in Figure 1): carried out at the Research Center for Energy Economics Reference scenario (FfE). The goal of this project is to derive a ranking like a The reference scenario reflects the current political and merit order for all relevant grid-optimizing measures (gom) regulatory conditions and provides a reference base for all and technologies. other scenarios. The influence of the system operators stays Depending on future developments in the areas supply, unchanged. Considering low acceptance regarding demand, technologies, grid requirement and the economic innovative measures, no gom based on devices inside of households are available. 1 Centralized scenario The project MONA 2030 (funding code 03ET4015) is co- The centralized scenario is dominated by an increasing funded by the German Federal Ministry of Economic influence of transmission system operators. This goes along Affairs and Energy through the funding initiative with an increased acceptance for major infrastructure “Zukünftige Stromnetze”. 16 project partners from the projects. The given possibility of a directed regional energy (e. g. system operators) and automotive industry development of renewable energy generation is essential, support the research project through the provision of data too. Nevertheless, the penetration of gom available on and individual practical experience. The research is carried household level is still low and not available for grid out by the “Forschungsstelle für Energiewirtschaft e.V.” in stabilization. cooperation with the industrial partners. Further information of the project are provided at Distribution grid scenario http://www.ffe.de/en_mona In contrast to the prior scenarios, the distribution grid scenario shows an increased influence of distribution system operators. Since the focus is drawn to small scale PV on the representative results the components, especially PV generation side, the provision of grid services through systems, are randomly allocated. Once the grid prosumers and small facilities is significantly higher. This characteristics are set, the dynamic simulation for each time goes along with a high acceptance of data provision and step (range from 5 seconds up to 1 hour) at each grid adaption of the prosumers’ usage behavior. Therefore all connection point (gcp) starts. Phase-specific electricity gom at household level are available to the system operator. flows and therefore residual and reactive power loads at each gcp are calculated. Based on this data the OpenDSS Prosumer scenario load flow calculation is executed and the voltage level for In the prosumer scenario, the influence of system each gcp is calculated as a result. The results can be either operators stays unchanged. Prosumers accept no external evaluated using overall load flows or by examining the interference with their usage behavior or privacy. In following not admissible operating conditions: contrary the focus is given to the optimization of own consumption, mainly by small scale PV-plants. For grid • Cable or transformer overload stabilization there are no gom available at household level. • Exceedance of the voltage tolerance band Conservative scenario Finally the resulting impact of the implemented gom can The conservative scenario is closely connected to a be evaluated by their effect on reducing these forbidden reduced economic growth along with the adjustment of conditions or by generally improving of the grid state. political goals regarding the share of renewable energy, efficiency and electric mobility to a lower level. To illustrate the functionality of GridSim in detail, the Furthermore, the CO 2 and fuel prices stagnate. The influence following chapters outline the generation of representative possibilities of system operators stay low. This results in a base grid topologies, the metamorphosis into realistic type lack of gom available at household level. grids as well as the assessment of the grid capacity and the effect of grid optimizing measures. TSO influence A. Base grid topology Degree of Acceptance for major decentralization infrastructure projects In a first step, the initial data of hundreds of real grids, provided by the participating distribution system operators, Possibility of directed Tendency towards regional are clustered to create typical base-grids, representing optimization of own development of renewable consumption energy common distribution grid topologies. In order to select these representative topologies, Tendency towards DSO influence individual grids are extracted from the underlying grid data small PV-plants and are subsequently analyzed and evaluated to identify Acceptance for data similar topologies and features. This evaluation yields Market penetration provision and adjusted home storage systems several criteria that describe the grids, such as number of usage behavior Grid services by connection points, number of grid branches, mean and prosumers and small- maximum length to a connection point and mean and scale facilities maximum resistance to a connection point. The values of Centralized Distribution grid Prosumer Reference- & conservative every grid for these criteria are calculated from the available scenario scenario scenario scenario data and are eventually normalized. Figure 1: Overview of the MONA scenarios according to selected This allows to group various grids with similar critical descriptors (the outer ring illustrates a high value) properties by hierarchical clustering. At the beginning of the process, each grid is considered as one cluster. Starting from The scenarios lead to a different availability and that, the distance between every pair of clusters is specifications/dimensioning of the gom which result in a determined, interpreting the criteria as dimensions of an varying merit order for every scenario. Euclidean space. Afterwards, the two clusters with minimal III. INPUT DATA FOR GRID MODELLIING distance are combined in a new cluster. In the first step, these two clusters each consist of one single grid. Later in In order to assess the technological potential of the gom the clustering process, clusters of several grids are various simulations are conducted by using the FfE tool compared. In this case, the distance between two clusters is “GridSim”. GridSim is a modular simulation tool for defined as the maximum distance between the grids in the detailed 3-phase calculations of distribution grids with high clusters. The combination of the two nearest clusters is penetration of decentralized generation. It is therefore repeated until the distance exceeds a certain threshold. This appropriate to analyze many different future development threshold value defines the “similarity”, which is required to scenarios with high share of solar power in the distribution group grids in a cluster. grids /FFE-14 15/. Moreover, new additional components like electric vehicles, power-to-heat and storage units can be This process yields several clusters of similar grids. implemented. On the basis of the open source load
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