Ebbs and Flows of Energy Systems (EFES)

Lead Research Organisation: Cardiff University
Department Name: Sch of Engineering

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.
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 decarbonisation 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

We have a project management structure to allow all investigators to pursue the most promising lines of research to
maximise impact. There are four important aspects to dissemination: the academic community, the distribution utilities, EV
manufacturers and the policy makers.
The research challenges are such that publication of results in international IET and IEEE conferences (such as the IEEE
Power Soc. General Meeting, CIRED and CIGRE), and ultimately in learned journals.
Two workshops will be organised by Cardiff University to publicise the emerging results of this consortium's work and to
discuss technical issues. The advisory companies will be closely involved in the progress of the work through project
meetings. The involvement of car manufacturer, DNOs and utility companies in the Advisory Board means a logical route to
exploitation exists.
Consortium members are already engaging with industry, government and end users through existing projects, and been
involved in organising and a diverse range of impact routes through working with regional and national governments,
commercial and not-for-profit organisations and advising on the setting of energy standards and regulations. This network
of engagements will continue and expand for informing the policy makers and industry about the findings and effective
knowledge exchange will be achieved. Prof. Nick Jenkins is directly involved with the Ofgem / DECC group on Smart Grids.
Consortium members have established formal and informal links with international collaborators in Europe and USA, and
opportunities for new connections are presented by COST Action "Autonomic Road Transport Support Systems."
Our project will be specifically developing demonstration case studies showing how EVs will impact the electricity systems,
which should be of great relevance to DNO. Contributions will continue to be made through Grid Code and Engineering
Recommendations revisions in the UK, and also through technology evaluation and demonstration.
Engagement in DECC/OFGEM Smart Grids Forum, Low Carbon Network Fund bids, Innovation Funding Incentive projects,
and the Energy Technologies Institute infrastructure programme, all provide the academics with pathways to impact. The
focus on tangible technological outputs, together with the informing context of case studies, provides a strong delivery
mechanism for communicating emerging technology options.
This project contributes to more cost effective integration of EVs and renewables along with reduction of CO2 emissions
and thus will benefit society at large.

Publications

10 25 50
 
Description Electric vehicles (EVs) have the potential to transform the way we use energy on a daily basis. Electricity demand across the UK varies depending upon the time of day and year. For example, peak electricity demand for the UK is between 4 and 7pm on a week day. This is because everyone has arrived home from work and turned on multiple appliances, causing a massive increase in electricity requirements to the National Grid. Currently this is supported by large fossil fuel power stations that run around the clock to anticipate any increase in the base demand. However, this additional demand could instead be provided through utilising the excess electricity stored in an EV or battery storage asset, redistributing the electricity across the local network and as such reducing the requirements on traditional power stations.
The project developed the following key technologies:
• Virtual Power Plant conceptual framework for enabling the coordination between EV, domestic storage, load and renewable generation, taking into account the technical, economical and communication requirements for acting as a VPP
• Local Energy Management System (LEMS) to control Electric Vehicle charging and Energy Storage Units within built environments
• VPP control algorithms for Peak shaving (flatten the demand profile of the building facility and reduce its peak); Triad avoidance (reduction the demand of building facility during triad peaks in order to reduce the Transmission Network Use of System charges) and Demand Side Response (enable the participation of the building manager in the grid balancing services market )
• Cloud-based deployment of Local Energy Management System
Exploitation Route The developed VPP could support the transition to a low carbon economy, by combining EVs, renewable generation and smart energy management.
The VPP developed is optimising the charging and discharging of electric vehicles to minimise CO2 emissions, costs and improve efficiency.
The VPP will allow residential and commercial customers to participate in demand response programs and help them in generating additional revenues.
The EVs owners could benefit from the storage services.When parked, the EVs battery can be used to let electricity flow to the electric distribution network and back, which has potential to provide around $4000 (£3274) per car, per year. This will have a significant impact in reducing the cost of operating an electric vehicle.
Sectors Education,Energy,Environment,Transport

URL http://www.cenex.co.uk/news/cenex-leading-installation-uks-first-domestic-vehicle-grid-unit/
 
Description The project helped the general public to engage with new technologies like Electric Vehicles V2G units allowing batteries to be used for storage and generally have a better understanding of potential benefits this technology could bring to the consumers. The engagement of the general public with V2G new technology was facilitated through a number of workshops. Liana Cipcigan gave evidence at National Assembly for Wales, Economy, Infrastructure and Skills Committee "EV charging in Wales", November 2018.
First Year Of Impact 2017
Sector Environment,Transport
Impact Types Policy & public services

 
Description Welsh Government
Geographic Reach Local/Municipal/Regional 
Policy Influence Type Participation in a advisory committee
URL http://gov.wales/topics/businessandeconomy/creating-a-sustainable-economy/low-carbon-vehicle-expert-...
 
Description Decarbonising Transport through Electrification, a Whole System Approach (DTE)
Amount £915,857 (GBP)
Funding ID EP/S032053/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 08/2019 
End 08/2022
 
Description National Grid collaboration
Amount £213,675 (GBP)
Organisation National Grid Transco 
Sector Private
Country United Kingdom
Start 05/2018 
End 10/2019
 
Title Data supporting "Predicting the energy demand of buildings during triad peaks in GB" 
Description A model-based approach is described to forecast triad periods for commercial buildings, using a multi-staged analysis that takes a number of different data sources into account, with each stage adding more accuracy to the model. In the first stage, a stochastic model is developed to calculate the probability of having a "triad" on a daily and half-hourly basis and to generate an alert to the building manager if a triad is detected. In the second stage, weather data is analysed and included in the model to increase its forecasting accuracy. In the third stage, an ANN forecasting model is developed to predict the power demand of the building at the periods when a "triad" peak is more likely to occur. The stochastic model has been trained on "triad" peak data from 1990 onwards, and validated against the actual UK "triad" dates and times over the period 2014/2015. The ANN forecasting model was trained on electricity demand data from six commercial buildings at a business park for one year. Local weather data for the same period were analysed and included to improve model accuracy. The electricity demand of each building on an actual "triad" peak date and time was predicted successfully, and an overall forecasting accuracy of 97.6% was demonstrated for the buildings being considered in the study. This measurement based study can be generalised and the proposed methodology can be translated to other similar built environments. 2 datasets are provided (in .xlsx file format) with the data used in this publication. File "input_data.xlsx" contains the triad peak demand data, the building energy demand data and the weather data in separate tabs. These data were used as inputs to the model described in this publication. The Triads are the three half-hour settlement periods with highest system demand and are used by National Grid to determine charges for demand customers with half-hour metering and payments to licence exempt distributed generation. The triad peak demand data contain information about the dates, times and magnitude (in MW) of the 3 demand peaks of GB electricity system demand from 1990 to 2014. The building energy demand data is the daily energy consumption of 6 commercial buildings in Manchester in kWh for the years 2012-2013. The weather data are daily values of 10 weather attributes for the years 2012-2013. The attributes are: 1. Cloud Total Amount (in octas) 2. Cloud Base (in DM) 3. Wind Mean Speed (in knots) 4. Hourly Mean Wind Direction (in degrees) 5. Max Gust (in knots) 6. Air Temperature (in degrees Celsius) 7. Rainfall (in mm) 8. Hourly Global Radiation (in kj/sq.meter) 9. Relative Humidity (in %) 10. Sunshine Hours (in %) File "output_data.xlsx" contains the model results, as presented in this publication. The Mean Absolute Percentage Error (MAPE) data, Mean Absolute Error (MAE) data, triad forecast data and power demand forecast data are presented in separate tabs. The MAPE and MAE data (in %) are the forecast accuracy evaluation indices for the 11 different forecast scenarios and 6 buildings (as described in the paper). The triad forecast data are the probability values (absolute) calculated with the triad probability assessment model described in the paper. Data from three different cases are provided, the daily interval case, the 5-day interval case and the half-hourly interval case. The power demand forecast data contain information about the actual maximum power demand (in KW) and the forecasted maximum power demand (in KW) in each one of the considered commercial buildings. 
Type Of Material Database/Collection of data 
Year Produced 2017 
Provided To Others? Yes  
 
Title Impact of Optimised Distributed Energy Resources on Local Grid Constraints 
Description The impact of optimised distributed energy resources investment decisions in Distributed Energy Resources Customer Adoption Model (DER-CAM) were tested on the connecting network grid constraints. The test case study was a mid-rise apartment. Electricity demand data (weekdays, peak days and weekend days) for the mid-rise apartment used in the paper can be accessed from https://building-microgrid.lbl.gov/projects/how-access-der-cam . The output from the DER-CAM model is read by a MATLAB script and send to a text file for power flow analysis in NEPLAN software, NEPLAN is a power system analysis software (http://www.neplan.ch/). The output of the power flow analysis is plotted as voltage profiles (available as: voltage_profiles.xlsx) for three day-types (week, peak, weekend) each representing the 12 months of the year (24 × 12 = 288. Data points standings is available as: data_points.xlsx). Multiplying the data points by the three day-types gives a total of 864 data points for the power-flow in NEPLAN. The energy losses are plotted for the overall microgrid and is available as: energy_losses.xlsx). The microgrid network data is available as: microgrid_network.pdf. 
Type Of Material Database/Collection of data 
Year Produced 2017 
Provided To Others? Yes  
 
Title Optimal Battery Storage Operation for PV Systems with Tariff Incentives 
Description Optimisation models providing insights into the benefits of battery storage coupled to photovoltaic (PV) generation system are receiving attention recently. An electricity customer whose electricity demand is supplied by a grid connected PV generation system benefiting from a FiT incentive is simulated in this research work. The system is simulated with the PV modelled as an existing system and the PV modelled as a new system. For a better understanding of the existing PV system with battery storage operation, an optimisation problem was formulated which resulted in a mixed integer linear programming (MILP) problem. Data is available in .pdf and 2 .xlsx files. The pdf file named "AIMMS model formulation" describes the nomenclature and formulation (parameters, objective function, decision variables and constraints) of the AIMMS optimisation model. To run the optimisation model the .xlsx file named "input" is provided to be used as input data. The "input" file has 3 separate tabs (load, pv, and tou). The unit of the data "load" and "pv" tabs is in kW, while the unit of the data in the "tou" tab is in "pence/kWh". The "load" contains the half-hourly electricity demand of the customer while the "pv" tab contains the daily half-hourly photovoltaic power profile of the customer for a complete year. The data in the "tou" tab is the historical wholesale electricity tariff in pence/kWh. All the 3 tabs have the same data structure: The row heading describes each half-hour of the day (48 data points) while the column heading describes the date of each day of the year (365 data points). The output file in .xlsx is also provided. It contains 10 tabs. The data in each of the 10 tabs is the result of the optimisation model decision variables described in pdf file named "AIMMS model formulation". The structure of the "output_results.xlsx" is the same as described in the "input" file. 
Type Of Material Database/Collection of data 
Year Produced 2017 
Provided To Others? Yes  
 
Title Probabilistic wind-power forecasting model - case study datasets 
Description The file named "InputData.xlsx' is related to the wind power data used to train the model. The data consisted of half-hourly aggregated wind power values from wind farms across the Great Britain for the period of 01/03/2014-30/9/2014. Column headings are included to explain the variables. The file named "Outputs.mat' is related to model outputs. This file can be opened only if you have installed MATLAB at your system. Once opened, a file of type "struct" includes all the forecast for different cases. This file is divided into fields, each of them representing a different scenario. So, the fields are divided based on the: Number of Generated Forecasts; Number of Magnitude Classes used for the training process; The update frequency of the model (forecasting process). For example the file "Outputs.Num_Of_Forecasts1000.MagnitudeClasses10.UpdateFreq16" shows the generated 1000 weekly forecasts, when using 10 Magnitude classes for the training and updating the model every 16 half hours. Column headings are provided to help understand its column. The actual data are provided in order to compare the generated forecasts with them and evaluate the performance of the model. 
Type Of Material Database/Collection of data 
Year Produced 2016 
Provided To Others? Yes  
 
Description Collaboration with Amrita University 
Organisation Amrita Vishwa Vidyapeetham University
Country India 
Sector Academic/University 
PI Contribution Joint EPSRC proposal "SEMACHAR: Socially-Driven Energy Modelling & Characterisation for Sustainable Urban and Rural Communities" addressed to the EPSRC UK-India Reducing Energy Demand in the Built Environment" addressed to the EPSRC UK-India Reducing Energy Demand in the Built Environment.
Collaborator Contribution Joint EPSRC proposal "SEMACHAR: Socially-Driven Energy Modelling & Characterisation for Sustainable Urban and Rural Communities" addressed to the EPSRC UK-India Reducing Energy Demand in the Built Environment" addressed to the EPSRC UK-India Reducing Energy Demand in the Built Environment.
Impact Joint EPSRC proposal "SEMACHAR: Socially-Driven Energy Modelling & Characterisation for Sustainable Urban and Rural Communities" addressed to the EPSRC UK-India Reducing Energy Demand in the Built Environment" addressed to the EPSRC UK-India Reducing Energy Demand in the Built Environment.
Start Year 2016
 
Description Collabortion with South Korea 
Organisation Yeungnam University
Country Korea, Republic of 
Sector Academic/University 
PI Contribution The Ebbs and Flows Energy Systems team initiated a collaboration with Yeungnam University for translating the Cloud-based Virtual Power Plant concept in the Korean power system. We developed a joint proposal "An Operation and Control Technology Platform for Distributed Energy Resources as Virtual Power Plant in Smart Grids (ETRUST)" addressed to the EPSRC KETEP Smart Grids calls in collaboration with Queen's University of Belfast which was not successful.
Collaborator Contribution The Korean partners Professor Ki-Yeol Shin, Professor Mo Chung and Professor Michael McAteer visited Cardiff University in 26-30 June to discuss future collaboration. Participation in the joint proposal "An Operation and Control Technology Platform for Distributed Energy Resources as Virtual Power Plant in Smart Grids (ETRUST)" .
Impact "An Operation and Control Technology Platform for Distributed Energy Resources as Virtual Power Plant in Smart Grids (ETRUST)" proposal.
Start Year 2015
 
Description Member in the Industrial Advisory Board 
Organisation National Grid Transco
Country United Kingdom 
Sector Private 
PI Contribution I was seconded at National Grid working in the Energy Insights department.
Collaborator Contribution A member of the Energy Insights department is acting in an advisory role. He advise my research team in the development of an algorithm for predicting the energy demand of buildings during triad peaks in GB.
Impact 10.1016/j.enbuild.2017.02.046
Start Year 2015
 
Description BSI Technical Committee 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Member of the BSI technical committee ESL/120 Electrical Energy Storage. Under the direction of the Standards Policy and Strategy Committee, the Technical Committee is responsible for standardization in the field of grid integrated EES Systems, focussing on system aspects on EES Systems rather than energy storage devices as well as investigating system aspects and the need for new standards for EES Systems. ESL/120 also focusses on the interaction between EES Systems and Electric Power Systems (EPS).
Year(s) Of Engagement Activity 2016
URL https://standardsdevelopment.bsigroup.com/committees/50254741#in-progress
 
Description Welsh Government Low Carbon Vehicle 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Policymakers/politicians
Results and Impact I was a member of the Low Carbon Vehicle expert steering group at Welsh Government. This group was established to advise and make recommendations on the Low Carbon Vehicle (LCV) sector in Wales and provide advice to Edwina Hart, Minister for Economy, Science and Transport at Welsh Government.
Year(s) Of Engagement Activity 2015
URL http://gov.wales/about/cabinet/cabinetstatements/previous-administration/2016/lowcarbonvehicles/?lan...
 
Description Workshop Manchester 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact Dissemination workshop "Delivering V2G Today - The Ebbs and Flows of Energy Systems Project" on 31st of October 2017. The workshop demonstrated and celebrated the project's three technologies developed, the Virtual Power Plant, the V2G unit and the V2G Gateway, to a wide audience of industry stakeholders, policymakers, potential users and other interested parties. The workshop offered a great opportunity to know how V2G has developed and what the future could hold for it in the UK.
Year(s) Of Engagement Activity 2017
URL https://www.eventbrite.co.uk/e/delivering-v2g-today-the-ebbs-and-flows-of-energy-systems-project-reg...