community aggregation - the value of local flexibility
TRANSCRIPT
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www.london.edu
Community Aggregation - The value of Local Flexibility
Dr. Jesus Nieto MartinSenior Research Fellow
Lisbon, 28th June 2018
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How electricity was delivered?
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Smart Grid
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Smart Grid Architectural Model
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LOW CARBON
TECHNOLOGIES
LOW CARBON GENERATION
• Limited capacity
• Passive design / operation
• Centralised Generation
• Limited Visibility
• One-way power flow
• Load centric design
• Reduced headroom
• Increased Intelligence / Active Management
• Distributed Generation
• Need for increased visibility
• Two-way power flows
• Utilisation centric design
N E T W O R K V I S I B I L I T YN E T W O R K V I S I B I L I T Y
Why is it an evolving sector?
DISTRIBUTION SYSTEM OPERATOR
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• Transition to a sustainable energy system
- Increase in intermittent generation
• Electrification of everything
- Growing electricity usage
- Electrification of transport and heat
• Distributed generation
- Small-scale generation in the distribution grids
Three Trends
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• Flexibility of demand should be exploited
- Demand and supply should both be used to balance
energy systems
• Aging networks operated to their limits
- Active distribution network management needed
• Control of large numbers of small units
- Too complex to use centralised top-down control
- Control paradigm shift needed
Three Challenges
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Our world is more complex and growing faster
than our control methods can handle
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Complex systems
• Highly interconnected
• Heterogeneous device-
human participation
• Extreme data
• Pervasive intelligence
• Increasing autonomy
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The move from Big Data to Distributed Control involves addressing:
• Large numbers of sensing and/or control end points
• High complexity
• Node heterogeneity
• Multiple scales of operation
• Pervasive computing /
autonomous nodes
• Wide geographical scope
The solutions must be:
Deployable, scalable, robust, resilient, and adaptable
From Big Data to Distributed Control
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• Some grid objectives:
- Reduce peak loads (lowers new capacity investments, enhances asset utilization)
- Enhance efficiency of wholesale markets and production
- Reduce impacts of transmission congestion
- Provide ancillary services, ramping, & balancing (especially in light of renewables)
• Some end-user objectives:
- Reduce energy bills
- Maintain requirements for comfort and business
- Increase net benefits of distributed generation and storage investments
• Some societal objectives
- Mitigate impacts from disasters
- Reduce environmental impact
Negotiate Multiple Objectives
with Distributed Control
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Planning vs Operations – Data driven models
Planning and Network
Development
Power System
Optimisation
Operational
Planning
Real-Time Operation (Including
Emergency)
Data Analysis
Ex-Post
Time
Scales
Long Term (1-5 years)
Midterm (1 month - 1 year)
Short Term (Intraday - 1 week)
Real Time (After Market
Closure, Including Emergency)
Post
Actions
Viewpoints Market Player Grid Optimiser
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The problem:
• Power production is shifting from centralize to more dispersed and distributed
deployments, and from entirely dispatchable forms to significantly intermittent
stochastic forms.
• Operating such a grid that powers economies with reliable and affordable electric
rates will require large amounts and new form of operational flexibility.
The opportunity:
• Provide this flexibility at reasonable cost whit distributed assets: continually
responsive loads, electrical &thermal storage. smart inverters, electric vehicle
chargers, etc.
• Transactive energy systems provide the control and coordination required to
actively engage customer-owned and third-party assets to provide this flexibility
through transparent, competitive means.
The problem and the opportunity
Transactive energy systems
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• Use market mechanisms to perform distributed optimization
- Reflect value in exchangeable terms (price)
- Effectively allocate available resources and services in real-time
- Provide incentive for investment on longer time horizon
• Use communications and automation of devices and systems as real-time
agents for market interaction
- Agents convey preferences and perform local control actions
- Engage in one or more markets to trade for services, e.g.,
Real-time energy, peak-shaving
System reserves
Transactive Energy
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• Engenders the voluntary collaboration of end-user assets through incentives
• Incentives must reflect actual grid values and constraints, to offer the end
user an equitable deal
• Decision-making to respond is kept at the end-user, participant level
• Automation conveniently takes care of the details
• Uses decentralized decision-making - scalable and sensitive to privacy
• "Virtual control" - negotiation feedback loop provides smooth, stable,
predictable response required by grid operators
• Allows end-user assets to compete on a level playing field, with each other
and traditional grid assets
Characteristics of Transactive Energy Systems
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Global energy goals cannot be met without changes in how we control complex systems
- Potential for substantial efficiencies in end-use systems with new controls
- More data and devices available
- New assets difficult to coordinate
- Existing controls antiquated
- Cyber-physical systems
- Growing "edge" computing resources
- Cloud computing becoming paradigm
- Existing security models challenged
Traditional centralized control approaches are a common weakness
Transactive Energy Conclusions
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www.london.edu
CEDISON: Community Energy Dynamic Solution with
Blockchain
A project funded by:
Primary hypothesis:
A distributed control approach is the most
efficient way to advance control theory to
address the challenges posed by large-scale
digitized infrastructure systems
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www.london.edu
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PenileeMilton
Craigend
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Impact on Tariff design
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n
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o Rapidly increasing number of new controllable devices within the archipelago with new
characteristics and impact on distribution networks as well as third party resources: ferry,
hydrogen plant...
o We propose a decomposition of distributed autonomous multi-level architecture
organised along: (1) substation/plant level; (2) local area/district level; (3) individual level.
o A multi-market phased approach:
Phased Stochastic multi-market clearings
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Preliminary conclusions
Aggregated trading strategy at community level would decrease
wind curtailment in the Orkney’s down to 30%
(vs 60-70% provided by the ANM)
Balancing at community level
decreases DUoS and Triads activation
Compelling measurable advantages of a
local balancing area:
• Congestion Management
• Coordination of heating strategies
• Smart charging of EVs
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"A set of economic and control mechanisms that allows the
dynamic balance of supply and demand across the entire
electrical infrastructure using value as a key operational
parameter.“
GridWise Architecture Council
An approach to responding to the change…
Transactive Energy
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