1. Technische Universität München
Lehrprobe - Einführung in Smart Grids
Dr. Martin Sachenbacher
Technische Universität München
Institut für Informatik
http://www.in.tum.de/energieinformatik
14. Mai 2012
M. Sachenbacher
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2. Technische Universität München
Electricity Grid Basics
Producers
Consumers
Conventional
Industry
Power Plants
Households
Pumped-
Renewable storage Plants
Energy
Storage
14. Mai 2012
M. Sachenbacher
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3. Technische Universität München
Electricity Grid Assumptions
Guiding Principle: Production follows consumption
Basic Assumptions:
Production is deterministic and fully controllable
Consumption is well-understood stochastic process
Mass effects ensure smooth consumer behavior
Grid state is observable (frequency, voltage)
Thus, good prediction and a bit of fine-tuning do the job
Control energy that be subtracted or added to the grid; mostly,
pump storage
This was the case for several decades, but now situation
changes rapidly
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5. Technische Universität München
Electricity Grid in Germany: Fundamental Changes
Absolute priority given to (microgenerated) renewable power
Financial incentives for renewable power above market price
Decision to phase out nuclear power after Fukushima incident
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M. Sachenbacher
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6. Technische Universität München
Challenges from Integrating Renewable Power
Wind and solar power have much higher volatility, and this
volatility is largely uncontrollable
Production is now turning into a stochastic process as well
Volatility may exceed the available control energy
Need mechanisms for grid stabilization
14. Mai 2012
M. Sachenbacher
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7. Technische Universität München
Renewable Power affects Grid Stability
Incident on September 6, 2010
Drastically more solar power in the grid than predicted before
Germany at 12 p.m.: Surplus of 7 GW
Entire negative control energy exhausted (- 4.3 GW)
Imported emergency reserve from neighboring countries (- 2.8 GW)
to avoid black-out
Number of manual interventions
EWE in 2009: < 1 per week
EWE in 2011: > 1 per day
Bundesnetzagentur during winter 2010/11: 39
Bundesnetzagentur during winter 2011/12: 197
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M. Sachenbacher
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8. Technische Universität München
What can be done?
Producers
Consumers
Conventional
Industry
Power Plants
Households
Pumped-
Renewable storage Plants
Energy
Storage
14. Mai 2012
M. Sachenbacher
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11. Technische Universität München
Basic Elements of Demand-Response Systems
Short-range and medium-range prediction
techniques for
Electric power demand
Solar and wind generated electric power
Grid capacity and potential grid bottlenecks
Voltage stability, especially for last mile
Measurement and logging infrastructure for
state of grid components
Techniques to group elastic customers into
clusters, and orchestrate their behavior
Decision support systems for effectuating
demand-response mechansims
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M. Sachenbacher
12. Technische Universität München
Decentralized Grid Management
Frequency-based distributed control strategy (EN 50438) enforced
for microgenerators in Germany in 2007
Must shut off the output if observed frequency overshoots 50.2 Hz
However, observation delays can lead to critical oscillations
Source: [Berrang et al. AVACS 2012]
no delay
10s delay
14. Mai 2012
M. Sachenbacher
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13. Technische Universität München
Decentralized Grid Management
Improved control strategy proposed by VDE (VDE-AR-N 4105)
Linear increase/decrease of output per minute by 10%/40%,
if frequency is observed below/above 50.2Hz
Avoids oscillations, but may overshoot target frequency
Source: [Berrang et al. AVACS 2012]
no delay
10s delay
14. Mai 2012
M. Sachenbacher
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14. Technische Universität München
Decentralized Grid Management
Control strategy analogous to internet transmission protocol (TCP)
proposed by [Berrang et al. 2012]
Additive increase/multiplicative decrease of output per minute by
10%/0.67, if frequency is observed below/above 50.2Hz
Highly dampened version of on/off-controller behavior
Source: [Berrang et al. AVACS 2012]
no delay
10s delay
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M. Sachenbacher
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