Extrapolating Household Load Data

Vortrag im Rahmen der 15th IAEE European Conference im September 2017 in Wien

The integration of renewable energies is one of the major issues the energy sector is facing nowadays. In a system mainly supplied by conventional power stations, which are highly reliable in terms of time-dependent utilization, the principle of production following demand can easily be upheld. In a system which is characterized by a high degree of fluctuating feed-in, generation adequacy can either be reached by installing overcapacities on the supply side or by installing vast amounts of storage units, which allow for the bridging of temporal discrepancies between the demand and supply of electricity.

The realization of these solutions seems unlikely because both solutions can lead to a surge in system costs. Hence, means of user-situated flexibility start moving into the centre of attention. This shall lead to a maxim where no longer production simply follows consumption, but consumption is also triggered by feed-in given by the conversion of non-dispatchable energy sources.

Due to a fragmented and widespread distribution of energy production from renewables, a smart grid can help to control the system by enabling communication between all types of system elements. Such infrastructure is costly and not in all cases economically advantageous. A cost-benefit analysis of the Federal Ministry of Economics and Technology in Germany has concluded that the installation of smart meters in new and renovated buildings and in households/small businesses with a consumption superior to 6,000 kWh/a should be executed [1].

According to that, the Act on the Digitisation of the Energy Transition [2] has been adopted by the Bundestag in 2016. Within it, the Act of Metering Point Operation [3] has been issued. It decrees that from 2017 onwards, consumers with more than 10,000 kWh annual consumption and from 2020, users consuming more than 6,000 kWh/a have to be equipped with smart meters. Thus, only a share of the consumers in the grid are monitored, which results in incomplete system coverage.

Given the fact that most of the units producing electricity from renewable sources are situated in lower voltage levels of the electrical grid and new devices with high-level energy consumption like electric vehicles (EVs) or heat pumps are brought into the system, the supply situation in lower grid levels becomes more and more uncertain as standard load behaviour cannot be assumed. As in the German grid area-wide measurements are only conducted down to the 110 kV-level, most of the actions in the lower levels go unnoticed.

With consumers more and more evolving to prosumers who interact with the electric system, knowledge about events taking place in lower grid levels become more and more important. As the consumption of households and their load profile has a major influence on lower grid levels, distribution network operators can benefit from knowledge of the load situation. Therefore, it is important, that the development of the German power grid towards a smart grid will take a huge step forward, when the rollout of smart meters in Germany is carried out from 2017.

As not all consumption will be measured, a method which allows aggregating selected household data to a reliable network load at different levels of the grid is required. This will help distribution network operators, energy providers and transmission network operators in forecasting their load situation. The presented approach thus aims to achieve a representative network load without knowledge of all household load data, as displayed in Figure 1.

extrapolation of single load data

Figure 1: Extrapolation of single load data to line load data and to grid area data

This paper is a result of research in the project “C/sells – Das Energiesystem der Zukunft im Sonnenbogen Süddeutschlands – BASISmbH – Bayerische Systemintegration von Solarenergie” support code: “03SIN120” – fundet by the Fedeal Minestry for Economic Affairs and Energy.

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