Energiforsyning i Arktis – hvilken vej vælger Grønland? - Artek ...

Fig 1 shows the timeline of the proposed
market, which include the following basic
parameters:
• Operation Interval = Market Cycle = 5
minutes
• Performance based (no Activation
Requirement, Duration Requirement and
penalty)
• One-way price-signal based (no Market
Forward Time, Market Open and Closure
Time, no bid-auction procedures)
2.4. Technical Requirements of the
proposed market:
• 5-minute meters
Demand response programs usually require
more advanced meters than traditional
electromechanical meters These demand
response programs includes different pricing
mechanisms for customers such as Time of
Use (TOU) rate, Critical Peak Pricing (CPP),
Extreme Day Pricing (EDP), Extreme Day
CPP (ED-CPP), and Real Time Pricing (RTP)
Different from these demand response
programs, the proposed market/program
is aimed at providing real-time balancing
service rather than peak load reduction or
load shifting, although the proposed market/
program also uses ex ante determined prices
and intervals/periods at a more near realtime
basis The proposed market requires new
5-minute meters rather than the hourly or
longer interval meters in traditional demand
response programs
• End-user controllers based on price signal
Traditional demand response programs aimed
at peak load reduction/load shifting do not
necessary requires automatic controllers
Customers can respond to day-ahead given
prices manually In the proposed market,
controllers based on price signal are necessary,
at least to residential customers to respond
in real-time in short interval Compared to
traditional primary frequency control, the
new market control devices receive the price
signal rather than sensor the frequency By
using price signal, customers can decide and
configure their responsive prices The price
signal will also directly determine customers’
earnings (according to their response), which
will contribute to the efficiency of the market
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• Methods for calculating the price signals
A simple first step solution could base the
price signals on the wholesale real-time
balancing prices with considerations of local
congestion and loss reduction Take locational
marginal pricing (LMP) approach as an
example, broadcasting price = wholesale
price + locational multiplier + loss multiplier
However, an efficient price generating method
implies the requirement for forecasting the
end-users’ response before sending out
certain price signal Due to the large amount
of small end-users, aggregation effect will
result in high predictability and low forecast
error It will be difficult to estimate the exact
forecast error, but it might be lower than the
day-ahead load forecast error (usually 1-5%)
because of the more close-to-real-time
timeline, if provided with sufficient number of
customers and appropriate customer groups
• Broadcasting channels
System operator needs to broadcast the
price signals every 5 minutes to customers/
end-users Because (1) the communication is
one-way (2) data flow is just price signals (3)
the reliability requirement is not high, (i e
several customers failed to receive several
price signals will not influence the aggregated
response very much because of the large
amount of small users), broadcasting can be
based on common communication tools such
as internet and telecom There is no need
to establish new communication line or new
sending/receiving devices
3. Future work
In the future, we will focus on the interaction
between our proposed market and the
existing (energy/ancillary services) markets
at transmission (wholesale) level and
distribution (retail) level The authors believe
that with carefully designed market rules, tens
of thousands of such loads can deliver a wellbehaved,
stable and predictable balancing
support
4. Acknowledgements
This work is supported by the Hans Christian
Ørsted postdoctoral funding programme at
Technical University of Denmark, and the
EDISON project, funded by the Public Service
Obligation Programme, ForskEl (project
number 2009-1-0224)