Transcript Imperial College London

FUTURE FM Project Overview
Dr Salvador Acha
Departments of Civil & Chemical Engineering
Agenda
Research Group
Future FM Overview
Modelling UK Electricity Prices
Urban Energy Systems Research Group
Background:
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Multi-disciplinary group
Identifying trade-offs from holistic analysis on energy supply-chains,
infrastructure and technologies
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Led by Prof Nilay Shah and Prof John Polak
Expertise on modelling urban energy systems
Design & operation analysis of organisations, cities, countries, etc.
Projects funded by bp, Sainsbury’s, EDF, EPSRC, EU, etc.
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Future FM Objective and WPs
• Objective: improve energy performance of non-domestic
buildings by focusing on analysing multiple data streams
that are captured by systems embedded in these sites
• Work Packages:
WP0 – Virtual Test Bed Development
WP1 – Data mining for FM
WP2 – Model Design Through Global Sensitivity Analysis
WP3 – Smarter Control Algorithms for FM
WP4 – New business plans for building management
• Partners
Modelling UK electricity prices
• UK consumers face rising electricity costs
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Projected +50% rise from 2011 to 2020
Costs and policies guaranteeing security of supply
Billing structure is complex and evolving
Customers need knowledge to make informed decisions
2011
2020
Source: Npower
Modelling UK electricity prices
Concept
Budget (%)
Stakeholder
Feature
Comment
Fee
1
Supplier
Fixed
Negotiated at tender
BSUoS
2
Grid Operator
HH settlement
Daily set tariff to recover cost from running the system
DUoS
10
DNOs
Fixed & temporal
Fees agreed with regulator, varying region, connection, and RYG
TNUoS
5
Grid Operator
Temporal
Demand zones reviewed annually, cost based on Triad days
Dloss
3
DNOs
Temporal
LLF established to account for losses in distribution systems
Tloss
1
Arbitrator
HH settlement
TLF are used to allocate losses in transmission system
RO
12
Government
Fixed annually
Funds transition towards meeting carbon reduction (e.g. Wind)
FiT
3
Government
Fixed annually
Funds small scale renewables (e.g. PVs)
CCL
5
Government
Fixed annually
Tax on business from using carbon intensive electricity
CfD
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Government
Fixed annually
Mechanism to replace RO and fund renewables
CM
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Government
Fixed annually
Payment vehicle to guarantee security of supply/back-up
AAHEDC
0.1
Government
Fixed annually
Support to reduce distribution costs in Scotland (Hydro)
CRC
0.25
Government
Fixed annually
Carbon tax for businesses based on electricity and gas use
NBP/Market
Forward/Spot UK electricity
Agreements can be bilateral,
OTC, or exchanges
• 56Modelling
Non-domestic
prices
Commodity
Modelling UK electricity prices
• Modelling Non-domestic UK electricity prices
• Full year HH spot prices, 14 DNO regions and 27 TSO zones
2014 UK Spot Price Summary
DUoS Map
Source: Elexon, OFGEM & National Grid
Modelling UK electricity prices
• Modelling Non-domestic UK electricity prices
Modelling UK electricity prices
• 5 year outlook
• London and South East < expensive
• North England > expensive
Most
Expensive
Least
Expensive
UKPN - London
NP - Yorkshire
Source: OFGEM
Some thoughts
• Comprehending energy bills is a complex task
• Updates on energy markets and policies is key
• Regional real-time prices of electricity allows us to
assess carefully cost reduction investments and hence
define best practice on managing buildings/assets
• Energy cost foresight allows stakeholders to develop
long term investment plans
Thank You
WP0
Virtual Test Beds
• Objective: Simulate indoor thermal
environment and HVAC performance of
case study buildings
WP2&3
WP1
Data Mining for FM
• Objective: Understand HVAC performance and detect faults
using data gathered from FM logs, BMS, and occupational
data collected
WP3
WP2
Model Design Through Global Sensitivity Analysis
• Objective: Apply global sensitivity analysis to HVAC systems
to identify most important parameters and develop reduced
order models
WP3
WP3
Smarter Control Algorithms for FM
• Objective: Feed WP1&2 into a model predictive control
strategy for test bed buildings
WP4
New Business Plans for Building Management Services
• Objective: Review business models that provide added value
to building owners and operators, while enhancing services
offered by energy service/BMS providers