Ebbs and Flows of Energy Systems (EFES)

Lead Research Organisation: University of Warwick
Department Name: WMG

Abstract

This project builds upon the Ebbs and Flows of Energy Systems feasibility study (31737-230167) and demonstrates the
development, impact and business potential of a Virtual Power Plant (VPP) integrating: building energy management;
renewable electricity generation, electric vehicles and battery storage systems. The project will manage the electricity use
of a range of sites, from single properties through to large commercial premises. The proposed management system uses
algorithm based predictive control to enable and optimise the active utilisation of multiple electric vehicle and domestic
storage batteries as an energy storage and generation resource. The project will demonstrate VPP functionality,
aggregating the disparate energy distributed energy resources to provide wider network ancillary support services, such as
peak shaving. This will reduce variability in electricity demand levels, cost and CO2 emissions, plus improve the UK grid
security of supply.
The Warwick university contribution will be a new energy system model that quantifies energy storage, performance and
degradation for a vehicle battery system when exercised under real-world driving and charging/discharging conditions
(Vehicle-to-Grid: V2G). This model will reinforce the capability of the industrial partners in areas of energy system design
and evaluation. A comprehensive understanding of energy storage performance and degradation will also be of great value
to energy providers - it will further support the creation of business models that promote the use of renewable sources of
energy integrated with local storage.
Energy storage is one of the eight great technologies identified by the government to propel the UK to future growth (David
Willetts MP, Policy Exchange, 2013). The RCUK Review of Energy in 2010 highlights that R&D into energy storage has the
potential to yield high levels of de carbonisation beyond 2030. The TSB (Energy Supply Strategy, 2012) states that battery
related R&D within the energy and transport sectors is a UK priority that will benefit from public investment.

Planned Impact

Consortium Partners
The primary impact from the Warwick contribution will be a new energy system model that quantifies energy storage,
performance and degradation for a vehicle battery system when exercised under real-world driving and
charging/discharging conditions (Vehicle-to-Grid: V2G). This model will reinforce the capability of Potenza Technology for
energy storage system design and the ability of the lead partner Cenex to provide leading guidance and consultancy
service to both private and public electric and hybrid vehicle fleet operators, domestic consumers and energy providers. A
comprehensive understanding of energy storage performance and degradation will be of great value to energy providers - it
will further support the creation of business models that promote the use of renewable sources of energy integrated with
local storage.
Wider UK Supply Chain
Innovations in integrated battery system manufacture and use will spill-over from the transport sector and energy sectors
with impact to other, high-value, industries (e.g. the built environment and air/rail transport). Embedding the researcher
within the High Value Manufacturing (HVM) Catapult and the National Automotive Innovation Campus (NAIC) (see
Pathways to Impact) will ensure broad engagement with a diverse range of stakeholders, including SMEs and technology
start-ups. The proposed research will reduce the commercial risk for energy storage development; opening the market to
new entrants and stimulating innovation. The PI and researcher will exploit their various networks - WMG HVM Catapult,
IIPSI (International Institute for Product and Service Innovation - Warwick), Niche Vehicle Network (Potenza Technology),
Vehicle fleet operators and energy providers (Cenex) to ensure that the research deliverables are disseminated through a
range of means to UK companies and SME's.
Professional Training
The research milestones will feed directly into the syllabus content of professional educational programmes (at Masters
level) on alternative propulsion, energy systems, complex electrical networks, systems modelling and simulation and digital
verification (e.g. the Science Engineering and Manufacturing Technologies Alliance (SEMTA) Advanced Skills Accreditation
Scheme (ASAS) programme). Companies will benefit from staff with improved knowledge and skills, with the potential to
stimulate shorter-term impact in the commissioning, design and manufacture of new energy storage technologies.
Public
The wider public will better appreciate the value and role of engineering and manufacturing science when addressing
international societal challenges. Students at the WMG Academy for Young Engineers will benefit from a structured
programme of learning (focussed on key STEM subjects), based around state-of-the-art facilities and real-world problems.
Information from the project will be disseminated on a WMG website. The website will facilitate a centralised repository for
relevant open source data and open source WMG publications. Research publications and data will also be shared with
Cardiff University for inclusion in their project website for local public engagement.
Social
Reduced domestic energy bills through the adoption plug-in vehicles (through the increased use of Vehicle-2-Grid, V2G).
Greater accessibility of Electric Vehicles within the UK as purchase price falls and OEMs explore integrated service models
of mobility and energy supply (related to improved battery management).
Environmental
The headline environmental benefit through this project is the reduction in CO2 derived from the use of integrated V2G;
where at scale, a 6% average daily balancing contribution to grid services would equate to at least 12 million tonnes of
CO2 saved nationally by 2020.

Publications

10 25 50
 
Description Renewable energies are a key pillar of power sector decarbonisation. Due to the variability and uncertainty
they add however, there is an increased need for energy storage. This adds additional infrastructure
costs to a degree that is unviable: for an optimal case of 15 GWof storage by 2030, the cost of
storage is circa: £1000/kW. A promising solution to this problem is to use the batteries contained within
electric vehicles (EVs) equipped with bi-directional charging systems to facilitate ancillary services such
as frequency regulation and load balancing through vehicle to grid (V2G) technologies. Some researchers
have however dismissed V2G as economically unviable claiming the cost of battery degradation is larger
than arbitrage. To thoroughly address the viability of V2G technologies, in this research project we develop a
comprehensive battery degradation model based on long-term ageing data collected from more than
fifty long-term degradation experiments on commercial C6/LiNiCoAlO2 batteries. The comprehensive
model accounts for all established modes of degradation including calendar age, capacity throughput,
temperature, state of charge, depth of discharge and current rate. The model is validated using six
operationally diverse real-world usage cycles and shows an average maximum transient error of 4.6% in
capacity loss estimates and 5.1% in resistance rise estimates for over a year of cycling. This validated,
comprehensive battery ageing model has been integrated into a smart grid algorithm that is designed to
minimise battery degradation. We show that an EV connected to this smart-grid system can accommodate
the demand of the power network with an increased share of clean renewable energy, but more
profoundly that the smart grid is able to extend the life of the EV battery beyond the case in which there
is no V2G. Extensive simulation results indicate that if a daily drive cycle consumes between 21% and 38%
state of charge, then discharging 40%e8% of the batteries state of charge to the grid can reduce capacity
fade by approximately 6% and power fade by 3% over a three month period. The smart-grid optimisation
was used to investigate a case study of the electricity demand for a representative University office
building. Results suggest that the smart-grid formulation is able to reduce the EVs' battery pack capacity
fade by up to 9.1% and power fade by up to 12.1%.
Exploitation Route New Innovate UK and EPSRC funded projects, eg through Faraday Challenge Calls. Commercialisation of the algorithms through third-party SMEs and through engagement with the Catapult network.
Sectors Energy,Environment,Transport

 
Description This research, for the first time, suggests that electric vehicle battery life may be extended when connected to the grid. This research received considerable national and international attention, including a BBC Radio Interview (The Ends Report - 09/2017) and invited presentations at Hawaii Natural Energy Institute (08/2017), Chinese Academy of Science (01/2018) and the Energy Storage & Battery Expo (2018) in Abu Dhabi (01/2018). Broader Media interests include (11/2017): Science Newsline; Web India 123; Environmental News Network and Energy Central. This work has underpinned our invitation to join new consortiums funded by Innovate UK as the models are applied at higher TRL.
First Year Of Impact 2017
Sector Energy
Impact Types Societal,Policy & public services

 
Description Innovate UK V2G Demonstration Programme
Amount £3,800,000 (GBP)
Organisation Innovate UK 
Sector Public
Country United Kingdom
Start 04/2018 
End 03/2021
 
Title Battery Degradation Model 
Description Model to predict long term battery degradation 
Type Of Material Computer model/algorithm 
Year Produced 2017 
Provided To Others? Yes  
Impact Comprehensive battery degradation model based on long-term ageing data collected from more than fifty long-term degradation experiments on commercial C6/LiNiCoAlO2 batteries. The comprehensive model accounts for all established modes of degradation including calendar age, capacity throughput, temperature, state of charge, depth of discharge and current rate. The model is validated using six operationally diverse real-world usage cycles and shows an average maximum transient error of 4.6% in capacity loss estimates and 5.1% in resistance rise estimates for over a year of cycling. This validated, comprehensive battery ageing model has been integrated into a smart grid algorithm that is designed to minimise battery degradation. 
 
Description EV-elocity 
Organisation A.T. Kearney
Country United States 
Sector Private 
PI Contribution Processed customer usage data which will underpin the derivation of customer usage models. 2. Customer usage models which underpins the overall objective to understand user behaviour. 3. Processed battery degradation data which will provide understanding of causes, mechanism and effects of battery degradation. This data underpins the derivation of the degradation model as well as provides knowledge to partners. 4. Battery degradation models which severs the overall objective to understand impact of V2G cycling on EVs. 5. Detailed Economic model for V2G which will take into account system degradation, grid side requirements (e.g. energy supply/demand, costs, tariffs, etc.) and automotive side requirements (e.g. warranty, liability vehicle depreciation and recycling costs). Severs the overall objective to create a range of V2G business cases. 6. On-line decision-making algorithms that will demonstrate the models for virtual power plant (VPP) decision and optimal aggregation algorithms.
Collaborator Contribution WP 0 (Project Management; Lead: AT-Kearney). Deliverables include the monitoring and reporting of progress through the: 2nd- Level Plan, Exploitation Plan, Risk Register and financial governance. WP 1 (Business case modelling and case study identification; Lead: Cenex). Milestone (M1: month 7) - production of a series of business cases suitable for V2G installation that will lead to site specifications for the project. The final deliverable (D2.4) requires continuous data from the project, supported by M7 delivery). WP 2 (Investment Customer Scenario Creation; Lead: AT-Kearney). Milestone (M2: month 24) is the completion of investor portfolios based on business cases defined in WP 1. WP 3 (V2G hardware procurement; Lead: Cenex). Primary deliverable is the development of a clear purchasing framework for the project that will then be converted to a guidance document. Milestone (M3: month 9) is selection of the hardware supplier. WP 4 (Stakeholder engagement and customer identification; Lead: AT-Kearney). Milestone (M4: month 9) is the installation of all hardware required within the project. WP 5 (Software Platform Development; Lead: Slamjam). Milestone (M5.1: month 15) is full software platform launch, integrated with hardware installed at site. A key element of this WP is evaluation of software operation, which is not completed until month 35. WP 6 (Trading Requirements Development; Lead: Toto Energy). Milestone (M6: month 14) is delivery of a centralised scheduling strategy fully integrated with the software platform. WP 7 (Data collection and monitoring; Lead: Cenex). Milestone (M7: month 6) is creation of a data summary routine for all data collection.
Impact None Yet
Start Year 2018
 
Description EV-elocity 
Organisation Cenex
Country United Kingdom 
Sector Private 
PI Contribution Processed customer usage data which will underpin the derivation of customer usage models. 2. Customer usage models which underpins the overall objective to understand user behaviour. 3. Processed battery degradation data which will provide understanding of causes, mechanism and effects of battery degradation. This data underpins the derivation of the degradation model as well as provides knowledge to partners. 4. Battery degradation models which severs the overall objective to understand impact of V2G cycling on EVs. 5. Detailed Economic model for V2G which will take into account system degradation, grid side requirements (e.g. energy supply/demand, costs, tariffs, etc.) and automotive side requirements (e.g. warranty, liability vehicle depreciation and recycling costs). Severs the overall objective to create a range of V2G business cases. 6. On-line decision-making algorithms that will demonstrate the models for virtual power plant (VPP) decision and optimal aggregation algorithms.
Collaborator Contribution WP 0 (Project Management; Lead: AT-Kearney). Deliverables include the monitoring and reporting of progress through the: 2nd- Level Plan, Exploitation Plan, Risk Register and financial governance. WP 1 (Business case modelling and case study identification; Lead: Cenex). Milestone (M1: month 7) - production of a series of business cases suitable for V2G installation that will lead to site specifications for the project. The final deliverable (D2.4) requires continuous data from the project, supported by M7 delivery). WP 2 (Investment Customer Scenario Creation; Lead: AT-Kearney). Milestone (M2: month 24) is the completion of investor portfolios based on business cases defined in WP 1. WP 3 (V2G hardware procurement; Lead: Cenex). Primary deliverable is the development of a clear purchasing framework for the project that will then be converted to a guidance document. Milestone (M3: month 9) is selection of the hardware supplier. WP 4 (Stakeholder engagement and customer identification; Lead: AT-Kearney). Milestone (M4: month 9) is the installation of all hardware required within the project. WP 5 (Software Platform Development; Lead: Slamjam). Milestone (M5.1: month 15) is full software platform launch, integrated with hardware installed at site. A key element of this WP is evaluation of software operation, which is not completed until month 35. WP 6 (Trading Requirements Development; Lead: Toto Energy). Milestone (M6: month 14) is delivery of a centralised scheduling strategy fully integrated with the software platform. WP 7 (Data collection and monitoring; Lead: Cenex). Milestone (M7: month 6) is creation of a data summary routine for all data collection.
Impact None Yet
Start Year 2018