Integrated Techno-Economic Power System Planning of Transmission and Distribution Grids

Müller, Ulf; Schachler, Birgit; Scharf, Malte; Bunke, Wolf-Dieter; Günther, Stephan; Bartels, Julian; Pleßmann, Guido

doi:10.3390/en12112091

Cited by 34 publications

(21 citation statements)

References 30 publications

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“…The spatial allocation of consumption and generation is of great importance in the modeling of energy systems and has been used, for example, in studies on grid expansion [31]. Voronoi polygons around the substations of the high-voltage network were also used for modeling the distribution network areas in [32].…”

Section: Distribution Grid Model and Dso Substation Allocationmentioning

confidence: 99%

Substation Related Forecasts of Electrical Energy Storage Systems: Transmission System Operator Requirements

et al. 2020

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The growth in volatile renewable energy (RE) generation is accompanied by an increasing network load and an increasing demand for storage units. Household storage systems and micro power plants, in particular, represent an uncertainty factor for distribution networks, as well as transmission networks. Due to missing data exchanges, transmission system operators cannot take into account the impact of household storage systems in their network load and generation forecasts. Thus, neglecting the increasing number of household storage systems leads to increasing forecast inaccuracies. To consider the impact of the storage systems on forecasting, this paper presents a new approach to calculate a substation-specific storage forecast, which includes both substation-specific RE generation and load forecasts. For the storage forecast, storage systems and micro power plants are assigned to substations. Based on their aggregated behavior, the impact on the forecasted RE generation and load is determined. The load and generation are forecasted by combining several optimization approaches to minimize the forecasting errors. The concept is validated using data from the German transmission system operator, 50 Hertz Transmission GmbH. This investigation demonstrates the significance of using a battery storage forecast with an integrated load and generation forecast.

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Section: Distribution Grid Model and Dso Substation Allocationmentioning

confidence: 99%

Substation Related Forecasts of Electrical Energy Storage Systems: Transmission System Operator Requirements

et al. 2020

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“…In the open_eGo (open_eGo repository: https://github.com/openego) project, the osmTGmod approach was enhanced by the coverage of the high voltage level (110 kV). When both the high and extra high voltage levels of the German transmission grid are considered, the number of nodes in the osmTGmod grid topology amounts to more than 11,000 [15] nodes.…”

Section: General Differences In the Grid Model Derivation Approaches mentioning

confidence: 99%

“…Open source grid models have already been used for power flow calculations, yielding realistic results [13][14][15][16]. However, those models are not validated yet and differ in their structure.…”

mentioning

confidence: 99%

Comparison of Open Source Power Grid Models—Combining a Mathematical, Visual and Electrical Analysis in an Open Source Tool

Heitkoetter¹,

Medjroubi²,

Vogt³

et al. 2019

Energies

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Power grid models are important in relation to several topics and applications, especially the modelling, optimisation and extension of electrical grids. The significance of grid models is heightened by the increase in renewable energy generation and the challenges associated with its integration into the power grid. However, despite their crucial importance, grid models have generally not been made publicly available for scientific studies or technical analyses. Little information has been published about either the details and methods used in the derivation of these models, or their input and output data. Recently, several projects were initiated in an effort to address this by developing open source grid models and associated data. These projects used different approaches and methods, but most are based on the OpenStreetMap database. The goal of this paper is to compare the different available grid models on the basis of the structure and derivation methods used. Therefore, a novel combination of a graph-theoretical, Geographic Information System (GIS)-based and power-related comparison level is introduced using the open source tool AutoGridComp, which was developed by the authors. The grid models considered in this study are the Scientific Grid Model (SciGRID), GridKit and open street map Transmission Grid Model (osmTGmod) models for Germany.The goal of energy system modelling is to model and simulate energy systems using different scenarios, as well as analysing their impact and results. This field gained increasing interest due to the integration of renewable energy sources in the energy supply, motivated by environmental, political and economic factors [1,2]. Energy system models constitute powerful tools, which help policyand decision-makers to understand the effects and implication of policies on future energy systems. The insights provided by energy models are the subject of many technical papers, studies and reports, for example dealing with the cost of renewable energy [3], the stability of the German transmission network [4] and the Ten-Year Development Plan for the European transmission network [5].

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“…The author of [20] presents a time-series-based method to minimize development costs and shows optimization results for a one-year time horizon using twenty-four representative days. Time-series-based planning methods allow the integration of the time dependency of RES and loads in power system planning, leading to substantial cost savings in comparison to the worst-case method [21]. However, most of the time-series-based strategies considering curtailment focus on a single future year without recommending a possible transformation path to the grid power system planner [22].…”

Section: Introductionmentioning

confidence: 99%

Multi-Year High-Voltage Power System Planning Considering Active Power Curtailment

Schäfer

Braun

2020

Energies

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Integrating active power curtailment (APC) of renewable energy sources (RES) in power system planning reduces necessary investments in the power system infrastructure. In current target grid planning methods, APC is considered by fixed curtailment factors without considering the provided flexibility to its full extent. Time-series-based planning methods allow the integration of the time dependency of RES and loads in power system planning, leading to substantial cost savings compared to the worst-case method. In this paper, we present a multi-year planning strategy for high-voltage power system planning, considering APC as an alternative investment option to conventional planning measures. A decomposed approach is chosen to consider APC and conventional measures in a long-term planning horizon of several years. The optimal investment path is obtained with the discounted cash flow method. A case study is conducted for the SimBench high-voltage urban benchmark system. Results show that the time-series-based method allows for reducing investments by up to 84% in comparison to the worst-case method. Furthermore, a sensitivity analysis shows the variation in total expenditures with changing cost assumptions.

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Integrated Techno-Economic Power System Planning of Transmission and Distribution Grids

Cited by 34 publications

References 30 publications

Substation Related Forecasts of Electrical Energy Storage Systems: Transmission System Operator Requirements

Substation Related Forecasts of Electrical Energy Storage Systems: Transmission System Operator Requirements

Comparison of Open Source Power Grid Models—Combining a Mathematical, Visual and Electrical Analysis in an Open Source Tool

Multi-Year High-Voltage Power System Planning Considering Active Power Curtailment

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