Developing a time based electricity tariff.
Teich, Tobias ; Roessler, Falko ; Szendrei, Danny 等
Abstract: The research project "Low Energy Living"
pursues the aim to create a techno-economic system to increase the
energy efficiency in a network of lodgers, housing societies and
providers (for example of electric power, thermal energy, natural gas or
water). The necessary cross-linking and the use of different housing
technologies like smart meters, heating and security installations for
building automation with housekeeping and multimedia equipment is called
intelligent living or, to be precise, smart home. These applications are
connected and regulated by the established EIB/KNX field bus via
electric cables, radio, double wire line or Ethernet. The technological
basis for smart homes was developed to a great extent recently and is
available at the market. Nevertheless, the potentials of these
technologies aren't utilized to the full. Currently the housing
technology and automation is deployed in commercial and public used
large-scale buildings. In contrast to this the utilization of modern
building technology in the living area is just at the beginning. For
this reason, the target is to integrate intelligent building bus
engineering and their automation on the basis of a demonstration object.
Key words: smart metering, smart home, electricity tariff
1. INTRODUCTION
One subfield of the research project deals with the development of
a variable electricity tariff for the local customers. The following
article explains the pricing mechanism in Germany's energy market.
Particularly with regard to the progressive liberalization of that
market it covers the possibilities for creating variable tariff models.
Existing concepts were discussed and as a result a new concept for
implementation within the research project "Low Energy Living"
must be developed. The target is to smooth the load profile. This gives
the opportunity to reduce the annual electricity costs for each
electricity consumers.
2. PRICE FORMATION
Until the liberalization in 1998 the German electricity prices were
based on the average costs of production. Currently the calculated price
for the end customers is derived from the purchase price on the European
Electricity Exchange (EEX) plus taxes, duties, network access charges
and distribution costs. The individual shares in the total electricity
price were shown in Figure 1.
The purchase price is given by the intersection of the supply and
demand function, which were generated via the different bids. The bids
of the other bidders cannot be consulted. The thus formed equilibrium
price is determined for each hour of the following day. All consumers,
who are willing to pay this price, can be served. The purchase price
occupies the biggest part of the total electricity price.
The other parts like taxes are regulated by law and cannot be
influenced by the energy suppliers. For designing a variable tariff
model the price fluctuations on energy market must be passed on to
customers. As seen in Figure 2, the purchase price is fluctuating very
strongly in the course of day.
[FIGURE 1 OMITTED]
[FIGURE 1 OMITTED]
3. LITERATURE OVERVIEW
To make it possible to classify the concept for a variable tariff
model presented in Chapter 4 it is necessary to explain two existing
concepts.
3.1 Locational Pricing, Nodal Pricing
The concept of Locational Pricing respectively Nodal Pricing is
respected as the ideal model in literature. The basis of this approach
is the modeling of the electrical system considering different economic
and technical specifications. Each producer and all greater load centers
represent a single node. In addition all technical and economic
performance indicators were determined either by a market mechanism or
by a query. This model is used in the sense of the maximization of the
economic total utility. Thereby each node represents its own submarket
in which a price for electricity along with the fee for grid usage is
determined. By optimizing the model it is possible to use each currently
available line and to juice the most cost-effective kin of generation
and provision of electricity. Due to the large number of producers and
consumers such a model is too complex for a realization in Europe or
especially in Germany.
3.2 The "Eckenflirder Tariff"
One of the first German projects concerning the displacement of
consumption profiles is the research Project "Dynamische
Stromtarife und Lastmanagement" which was carried out between 1994
and 1996. In a field trial 1000 randomly chosen households were
analyzed. Their consumption was charged by a variable, continuously
adjusted tariff. The basis of that experiment was the Peakload Pricing
Model, which follows the course of marginal costs of producing
electricity to determine the price function. As a result the load
profile was smoothed by about 10 %. Along with that, electricity costs
could be reduced by about 4,4 %. The one-off costs for the necessary
equipment and additional infrastructure were amortized within three
years. On the basis of inquiries of the participants a high customer
satisfaction and acceptance could be proved.
4. RECOMMENDATIONS FOR CONFIGURING A VARIABLE TARIFF MODEL
Due to the economic crisis of the last years and the associated
output drops, sales of the electricity suppliers have declined. The aim
must be to introduce variable tariff models to preserve the customer
base on the one hand and on the other hand to support the acquisition of
new customers. It is necessary to implement incenitives for energy
savings in the existing Peak load times
The technical and political restrictions within our research
project:
* intelligent Smart Meter technology: the entire energy consumption
of a house or a fiat becomes totally transparent for customers
* dynamic tariff model cannot be calculated, because the local
energy supplier purchases the electricity not a the day-ahead market
To reduce the procurement costs, the electricity supplier must
smooth the load profile at all. The following figure (Number 3)
indicates the load peaks in Zwickau.
After the evaluation, different zones were surrendered. For example
the highest demand for electricity is in the evening hours. The purchase
price can be used as reference value. Following the load profile it is
necessary to implement various price leaps within one day. Within our
research project we make the suggestion to implement 4 tariff times:
* Peak load time between 10a.m. and 2p.m.
* Major time between 8 and 10 a.m. and between 6 and 8 p.m.
* Low-peak time between 6 and 8 a.m. and between 2 and 6 p.m.
* Off-peak time between 8 p.m. and 6 a.m.
The price to be paid by the consumers is graded as follows:
* peak load time 100 %
* major time 80 %
* low-peak time 70 %
* off-peak time 50 %.
As a result of a forecast calculation it could be possible to save
about 5 % in comparison to previous electricity bill. The premises of
these computations are that the load profile could be smoothening by
about 8 % and that the annual electricity consumption is up to 2000 kWh
annually.
Another starting point to reduce cost for suppliers and customers
is the automation of accounting through standard ERP Software. To
increase the image of the electricity suppliers and to enhance
transparency about the customers' energy consumption, a web based
information platform will be developed. Initial drafts are seen in
figure 4.
[FIGURE 2 OMITTED]
[FIGURE 4 OMITTED]
5. CONCLUSION
This article gives a short impression into the topic of designing
variable tariff models in the electricity sector. The presented
calculation example should examine possibilities for the introduction of
such tariffs. In a further step, the practical implementation should be
a priority.
6. REFERENCES
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In: Energieeffizienz in Wohngebauden, GUC Verlag, 978-3-934235-89-2,
Chemnitz
Morovic, T., Pilhar, R., Mohring-Huser, W. (1998). Dynamische
Stromtarife und Lastmanagement Erfahrungen und Perspektiven Kassel:
Institut fur Solare Energieversorgungstechnik (ISET)
Schober, D., Weber, C., Ziegler, D. (2008). Zusammensetzung der
Strompreise in Europa." Endbericht; Studie im Auftrag des BDEW,
Universitat Duisburg-Essen, Lehrstuhl fur Energiewirtschaft, Duisburg
Schwab, A.J. (2009) Elektroenergiesysteme: Erzeugung, Transport,
Obertragung und Verteilung elektrischer Energie, Springer-Verlag, Berlin
Heidelberg
Schittek, W. (2008). Strom--Fit fur die Zukunft? Dynamischer
Strompreis und virtuelle Sekunddrregelung, Verlag Grrich &
Weiershauser, Marburg
Wawer, T. (2007) Konzepte fur ein nationales Engpassmanagement im
deutschen Ubertragungsnetz, In: ZfE Zeitschrift fur Energiewirtschafi 31
(2007)
*** (2010) http://www.zev-energie.de/pdf/geschaeftsbericht/
geschaeftsbericht_2009.pdf Geschaftsbericht zum 31.12.2009 der Zwickauer
Energieversorgung, Accessed on: 2010-10-19