www.cranfield.ac.uk
Dynamic Investments in Flexibility Services for Electricity Distribution with Multi-Utility Synergies
Dr. Jesus Nieto-Martin
Professor Mark A. Savill
Professor Derek W. Bunn
40th IAEE International Conference
Singapore, 19th June 2017
2© Cranfield University 2016
Why do we need flexibility?
Source: Strbac, Imperial College
• Previous analysis shows significantly more investment is needed in absence of flexibility
• Flexibility can support a cheaper low-carbon generation mix to meet a given carbon reduction target
3© Cranfield University 2016
Real Options Valuation for Pricing Distribution Flexibility Services
• Understanding the role of flexibility is very complex and associated with a number of uncertainties:
• Evolution of future energy system • Projected cost and availability of different flexibility options
• Despite uncertainties, key investment decisions need to be made in the short-term but will have a lasting impact due to long lead times
• This creates the possibility for regret i.e. additional cost due to suboptimal myopic decisions
• Flexibility can provide option value – postponing decisions on larger investments until there is better information, hence reducing the need to make potentially high regret decisions
• A proposed approach is about quantifying the possible outcomes for a set of strategic choices, and then identifying choices of the outcome for decision makers
4© Cranfield University 2016
Real Options Valuation for Pricing Distribution Flexibility Services
DSO
DSO
5© Cranfield University 2016
Business Options for contracting Flexibility
© Cranfield University 2017
6© Cranfield University 2016
Milton Keynes, trials city
© Cranfield University 2017
7© Cranfield University 2016
Scenario Investment Model
Smart Grid trialed techniques
Dynamic Asset Ratings
Automated Load Transfer
Meshed Networks
Battery Storage
Distributed Generation
Demand-Side Management
http://www.westernpowerinnovation.co.uk/Falcon.aspx
8© Cranfield University 2016
Methodology: Bottom-up Meta-heuristics
9© Cranfield University 2016
Planning Flexibility Investments
10© Cranfield University 2016
SIM Interfaces and results
Inspector
20152010 2020 2025 2030 2035 2040 2045 2050
42
Affected assets
Select All Focus Inspect
Patch Status Asset
1 added 3-A
1 changed 3-B
1 changed 3-C
2 changed 3-D
3 deleted 3-E
3 deleted 3-F
Column 4
4-A
4-B
4-C
4-D
4-E
4-F
Actions
1 2
3
Current year: 2030
State Metrics Year% 2030$CML% 5234$
CI% 20$Losses% 300$
Avg.%Utilisation% 0.70$Avg.%Max%Utilisation% 0.75$
Load%Factor% 0.9$Cost% 123$
$
© Cranfield University 2017
11© Cranfield University 2016
A valuable source of learning: When Do Issues Occur?When do issues occur?
Project FALCON Closedown Dissemination Event
Initially a wider spread of days when issues occur – Winter Peak and Winter Weekday are most likely time for issues, some summer peak and other weekdays. Could reduce the number of days modelled. Weekends
© Cranfield University 2017
12© Cranfield University 2016
Data visualisation: SIM Expansion trees
13© Cranfield University 2016
MURRA: Combining ROV with SIM locational resolution
© Cranfield University 2017
14© Cranfield University 2016
*DECC: Department of Energy & Climate Change became part of Department for Business, Energy & Industrial Strategy in July 2016
Demand deterministic models
© Cranfield University 2017
Demand Scenarios Fuel efficiency Low Carbon heatWall
insulation
DECC 1 Medium High High
DECC 2 High Medium High
DECC 3 High High Low
DECC 4 Low Low Medium
15© Cranfield University 2016
Results – Short-term planning (2015-2023)
On the left DECC2, on the right DECC 4
Most demanding scenario requires 17% more of TOTEX
16© Cranfield University 2016
Results – Long-term planning (2015-2047)
On the left DECC2, on the right DECC 4
DECC2 scenario requires spending 14% more on TOTEX
17© Cranfield University 2016
Optimal Investment Strategy 2015-2023
18© Cranfield University 2016
Optimal Investment Strategy 2015-2047
Optimal Path All SIM All DSO All Outs All Agg All P2P
1 1.17 1.92 1.47 1.38 1.52
19© Cranfield University 2016
Myopic Investment Strategy 2015-2047
Sub-Optimal All SIM All DSO All Outs All Agg All P2P
1.19 1.33 1.81 1.39 1.36 1.41
20© Cranfield University 2016
Some learnings so far…
© Cranfield University 2017
• Voltage issues appear in 2015 by changing Electrical Vehicles and Heat Pumps clustering assumptions
• Discovery of overbuilt primary networks, better to sign locational flexibility contracts
• Benefits of meshing do not correlate to load
• Voltage issues appear only in DECC2 and DECC3 scenarios
• Smart intervention techniques make up a greater proportion of the number of interventions over longer timeframes
• Smart techniques do not create extra capacity in the system
21© Cranfield University 2016
