Integration of energy storage into electrical power systems

  • Integration of energy storage into electrical power systems
INTERREG VA Storage Platform for the Integration of Renewable Energy (SPIRE 2)

Proposed Project Title:

  • Integration of energy storage into electrical power systems

Principal Supervisor(s):
  • Prof. D John Morrow, Dr Robert J Best, Dr Amy Liu and Dr Aoife Foley


Project Description:

Queen’s University Belfast has a number of PhD opportunities on topics related to the integration of energy storage into electrical power systems. These are funded by the Storage Platform for the Integration of Renewable Energy (SPIRE 2) INTERREG VA, a collaborative project led by Ulster University with Strathclyde University and Dundalk Institute of Technology as the other academic partners.

Project 1: Big Data Analytics for Small Scale Energy Storage

Ireland has adopted a renewable power generation target stipulating that 40% of electricity will be produced from renewable sources by 2020. In order to achieve such ambitious targets Ireland is expected to have 6000 MW of wind power generation installed by 2020. With an all-island peak system demand of circa 7000 MW and min load of circa 2000 MW wind could, at times, theoretically supply all of system demand. However, the variability and uncertainty associated with wind power generation and the nature of the technology creates operational challenges, such that in practice there are limitations to the instantaneous wind power penetration permitted. In such an environment, new, more intelligent tools are needed by the power system operator to deal with the increased challenges.

This project will highlight the commercial drivers for small scale energy storage such as EV and consumer owned small scale batteries, which are connected to the distribution grid. The positive and negative impact of such autonomous connections will be assessed with regard to system stability and levels of renewable power that can be integrated into the power system.

Smart integration methods will be proposed that will maximise the benefits of such connections to power system stability and subsequently help facilitate integration of high levels of renewable generation to the grid. A "big data" approach will be adopted, utilising real energy storage data, demand data, and system operational data, to analyse the limits of power system operation.

Project 2: Energy arbitrage with PV Generation and EV Charging

The uptake of PV generation at domestic level, largely due to renewable incentives, is giving rise to technical challenges in the operation of the distribution system with significant generation infeed during the day when load it typically small.  Additionally, form an owner/operators point of view there is presently a 3 fold financial benefit of using units generated on site as opposed to exporting to the grid.  The objective of this project will be to explore the role of battery storage (~10 kWh) at the domestic level, charging via PV and then discharging when there is sufficient load with the premises.  With the anticipated uptake of EVs, this provides one such load suitable for energy arbitrage.

This project will also seek to model an area of distribution network and to explore the technical challenges associated with significant deployment of these new generation and load technologies and the extent to which energy arbitrage has the potential to alleviate such problems.

Project 3: Storage to augment the capability of thermal plant

With the ever increasing penetration of stochastic renewable generation there are greater demands upon thermal plant to offer greater flexibility than ever before.  The purpose of this project is to investigate the role of storage added to a thermal power station to provide hybrid plant operation. The project will make use of Phasor Measurement Unit data captured from the existing 10 MW battery energy storage facility at AES Kilroot. AES are the primary industrial collaborator on this PhD.

The project will explore two related themes:

  • Onsite storage services to improve power plant reliability and operability: This theme will investigate the potential for storage to benefit the thermal plant through a range of bespoke onsite services not necessarily remunerated by the market. This includes the use of the storage inverter to mitigate onsite voltage fluctuation, integration with the thermal generator’s excitation system to improve stability during faults, and methods of improving plant efficiency and lessen maintenance by reducing demands on the thermal plant.

  • Power plant flexibility enhancement through storage: The second theme will investigate the ability of the storage-augmented thermal plant to provide a superior suite of system services. This includes offering lower minimum output, higher maximum output, and enhanced ramp rates, start-up and shut-down capabilities. In addition, inertia, frequency response, and reserve services could be provided more effectively in combination.  It may prove possible to introduce new system services that are only made possible by the hybrid plant.

 

Project 4: A market analysis of customer-connected mass energy storage (MES)

Energy storage is needed to ensure the continued growth of variable renewable energy and act as the catalyst for the decarbonisation of heating and transport loads and the decentralisation of energy production. The drivers behind the change in energy production, shipping and are government policy and targets sustainable energy transition. However, there are many regulatory, policy and economic uncertainties to MES deployment at the residential and commercial level.

MES from a behind-the-meter market perspective can offer services such as flexibility and convenience (e.g. back-up, load shifting, islanding and quality) for generating companies (genco), customers and prosumers along the energy chain in addition to hedging against prohibitive regulatory changes (e.g. demand charges and tariff structures), carbon charging and mothballing of fossil fuel generators. However, the technical and economic value of these services is not fully understood, qualified or quantified with regard to modular MES.

This project seeks to provide one of the first behind-the-meter electricity market analyses of customer-connected distributed modular MES to provide a realistic business model that maps, designs and studies new commercial opportunities to meet government decarbonisation and energy policy targets by establishing technical, regulatory and market frameworks and requirements.

 


Academic Requirements:

A minimum 2.1 honours degree or equivalent in Electrical and Electronic Engineering or relevant degree (e.g. Computer Science, Mechanical Engineering, Civil Engineering and or Mathematics/Physics) is essential. A strong mathematical background is also highly desirable, in addition to a keen interest and career aspirations in in power systems and energy systems.

Candidates applying from countries where the first language is not English must produce evidence of their competence through a qualification such as IELTS or TOEFL score. For a list of English Language qualifications accepted by the School and University please see the following link:
http://www.qub.ac.uk/International/International-students/Applying/English-language-requirements/


General Information:

These studentships will comprise Home/EC tuition fees and an annual stipend of £20,000 for a period of up to 3 years subject to satisfactory progress and are tenable from 1st January 2018.  Non-EU candidates will be considered for partial fees funding and stipend.

Applicants must apply electronically through the Queen’s online application portal at: https://dap.qub.ac.uk/portal/

Further information available at:  http://www.qub.ac.uk/schools/eeecs/Research/PhDStudy/


Contact details:

Supervisor Name: Prof. D John Morrow, Dr Robert J Best, Dr Amy Liu and Dr Aoife M. Foley
Address:

Queens University of Belfast
School of EEECS,
Ashby Building,
Stranmillis Road,
Belfast
BT9 5AH

 

Email: dj.morrow@ee.qub.ac.uk, r.best@qub.ac.uk, x.liu@qub.ac.uk & a.foley@qub.ac.uk
Tel: +44 (0)28 9097 4060 / 4159 / 4112 / 4492  


Deadline for Submission of Applications is 18 Dec 2017


For further information on Research Area click on link below:

http://www.qub.ac.uk/research-centres/EPIC/