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Allocation of Annual Electricity Consumption and Power Generation Capacities Across Multiple Voltage Levels in a High Spatial Resolution

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Allocation of Annual Electricity Consumption and Power Generation Capacities Across Multiple Voltage Levels in a High Spatial Resolution International Journal of Sustainable Energy Planning and Management Vol. 13 2017 79–92 Allocation of Annual Electricity Consumption and Power Generation Capacities Across Multiple Voltage Levels in a High Spatial Resolution ! ""! # $%" !! "# ABSTRACT Keywords: The electrical energy system is in transition. There is continuing expansion of renewable Energy consumption; generation, which causes a spatial and temporal shift of energy flows at different voltage levels Geospatial analysis; of the power grid. On the consumption side, demand patterns are expected to change. The limited Open data, Power generation; availability of data with high spatial resolution hinders independent and transparent assessments. In view of this, the research project open_eGo is developing methods focusing on electricity URL: networks and open-science principles. In this work, electricity demand and power generation are dx.doi.org/10.5278/ijsepm.2017.13.6 allocated to their corresponding voltage levels and network nodes. By combining data on municipal boundaries with Voronoi cells we created catchment areas for each substation. On the demand side, OpenStreetMap data is used for mapping different demand sectors. We show that a consistent data set can be produced in a high spatial resolution using geographical data processing. Our results apply to Germany but the methodology can be adopted to other countries or regions where sufficient open data is available. 1. Introduction The research project open_eGo is a response to these challenges [8]. It is developing an open-source grid Due to pollution and the increasingly visible effects of planning toolbox named eGo. This toolbox works from climate change, various countries are turning from extra-high to low voltage levels of the power grid to conventional power generation to renewable energy [1]. determine the optimal network and storage topology. In In Germany, the transformation in power generation order to properly identify and locate the need for technology has already changed the geographical and electricity grid extension at different voltage levels, temporal distribution of electricity production. The multilayer power flow simulations are performed. At the increasing share of decentralised power generation same time, such simulations could assist in the analysis of challenges the grid [2, 3]. The existing system was not the effects of decentralisation. High resolution data sets of designed to support a large share of power generation in energy consumption, power generation and the existing distribution networks. The number of redispatch grid infrastructure are compiled and made available. operations by transmission system operators (TSO) has In addition to status-quo analysis of the German been increasing in the short term [4, 5], while long-term electricity system, future scenarios up to a fully renew- solutions such as grid extension have been delayed [6, 7]. able electricity system are considered in the research * Corresponding author: email address: [email protected] (Ludwig Hülk) International Journal of Sustainable Energy Planning and Management Vol. 13 2017 79 Allocation of Annual Electricity Consumption and Power Generation Capacities Across Multiple Voltage Levels in a High Spatial Resolution project. The scope of this study is the identification of in Section 2.2. In Section 2.3, corresponding grid areas relevant substations between voltage levels and the are created for each substation. To identify and locate allocation of demand and generation data to these energy consumption, the creation of the load areas is network nodes. The creation of grid topology models [9] explained in Section 2.4, followed by the method to and the generation of time series [10, 11, 12] within the allocate installed capacities and sector-wise annual grids are not part of this article and are addressed in [13, consumption data to each load area in Section 2.5. 14]. In the following sections, we describe our methods for identifying substations (transmission substations and 2. Methods transition points) and allocate annual electricity consumption and power generation capacities through 2.1. General areas we generate (high voltage grid districts and In this study, all methods are combined but can also be medium voltage grid districts). The low voltage applied separately if necessary. All steps make use of infrastructure located inside the identified load areas is the following voltage-level classification based on the not considered. German three-phase electric power grid, see Figure 1. Several publications [15, 16, 17, 18, 19] implemented The grid is divided by voltage level into an extra-high an allocation of generation and demand. The spatial voltage (EHV), high voltage (HV), medium voltage resolutions differ due to differences in the guiding (MV), and low voltage (LV) grid [24, 25]. The rare case research questions. The method presented here achieves of 60 kV has been assigned to HV since its principal a higher spatial resolution, as the results must be suitable function is regional transmission, similar to 110 kV. In for calculations in the distribution grid comparable to addition, there is a single-phase AC power grid for [20]. A high spatial resolution is necessary when railway operations (HVrail with 110 kV) which we simulating medium and low voltage grid levels. Further, disregard. The direct transformation from EHV to MV is there are more than 880 distribution system operators in uncommon in the German electricity grid and is not Germany [5]; as a result, a uniform digital data set on the taken into account. medium- and low-voltage grid levels is not available. In open_eGo, substations connecting EHV and HV Although developing a data set based on publicly grids are called transmission substations and sub- available sources covering all voltage levels is chal- stations between transmission and distribution level lenging, an open-source approach is possible thanks to (HV-MV) are defined as (power) transition points of the data from governmental authorities and the public electricity grid while distribution substations connect database OpenStreetMap (OSM) [21]. Generally, open- the LV grids. The transition points are of central source and open data increase transparency in scien- tific and public discussion and allow reproducible validations and comparisons [22, 23]. We develop Grid Substation Catchment Area methods for generating these data sets based on open- source software and under the strict use and compliance EHV of open data. This makes it possible for others to use and ≥ 220 kV further develop our method, the generated data or just Transmission High voltage substation grid district parts thereof. The research questions that we intend to HV address and answer are: 110 kV 1. What methods can be developed in order to grid Transmission Transition point Medium voltage allocate electricity generation and consumption grid district across multiple voltage levels in a high spatial MV resolution? 1 – 35 kV 2. What is the added value of the developed Distribution Low voltage methods? substation grid district 3. Is it possible to conduct such research using only LV Distribution grid < 1 kV open-source software and open data? After a brief introduction to the general conventions Figure 1: Simplified scheme of voltage levels of our method, we describe the processing of substations Figure by Ludwig Hülk / CC BY SA 4.0 80 International Journal of Sustainable Energy Planning and Management Vol. 13 2017 Ludwig Hülka, Lukas Wienholt, Ilka Cußmann, Ulf Philipp Müller, Carsten Matke, Editha Kötter importance to the eGo-tool since they are the smallest 2.2. Substations unit for power flows carried out at the transmission grid To identify relevant substations, similar to [30], we apply levels and at the same time considered as slack nodes methods of the SciGRID model [31] to derive an OSM- from the distribution grid perspective. An area based power dataset for EHV and HV. Apart from the associated to only one transition point and its transition points we identify transmission substations in corresponding medium voltage grid will further be order to allocate industrial consumers in Section 2.5. The called grid district. These catchment areas are used for complete process starting from the raw data set and collecting electrical energy consumption and electrical ending with valid substation data is visualised in Table 1. generation associated to each substation at the different Due to the inhomogeneous data quality in OSM (see voltage level. Section 2.1), we cannot only consider substations In the open_eGo project and in this study in particular, mapped as a surrounding area by data type way, but also the data from OSM is of great importance because it have to consider substations mapped by data type node influences the implementation and the outcome of the and in the case of EHV substations also by data type power data allocation [9]. OpenStreetMap is an open relation. In addition, we assume that substations have database project which collects and publishes data missing or incomplete voltage information indicating a mapped by its numerous users. Data in OSM is crowd- connection to the respective voltage level. sourced by conventions instead of strict rules [26]. There In order to find valid transmission substations and are three general data types in OSM: nodes (points), ways transition points, substations are identified that contain (lines or polygons), and relations (structures).
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