DIT PhD Project
Supervisor name & contact details: / Name: Dr. Brian Keegan & Dr.Keith SunderlandResearch Centre: / Applied Intelligence Research Centre
Dublin Energy Lab
Research Centre website: /
Supervisors Publication List: /
Title of the Project: Smart Control of Microgeneration for Mutual Load Stabilisation
Project Summary: Microgeneration can be classified as a grid connected energy capacity for electricity generation up to a maximum rating of 11kW when connected to the three phase portion of the distribution grid. Microgeneration is the production of heat or power on a very small scale, when compared to the outputs of a typical fossil-fuelled power station. Unlike these large power stations which are often located hundreds of miles away from where the power is needed, microgeneration systems use the power where it is made. This means they are potentially much more efficient, as transmission and distribution losses are virtually eliminated. One might argue that economies of scale are such that the benefits to the electricity networks arising from their connection is offset by the associated complexities involved in managing their contributions. Indeed, the output intermittency from these technologies, due to the variability of the associated primary resources involved, presents significant challenges for distribution network operators (DNOs). However, when one considers increasing population migration to urban centres, diverse, sustainable, robust and controllable electricity networks are inevitable requirements for future society. These smarter networks could include domestic and commercial prosumers contributing individually and collectively towards this goal. The main technologies used in microgeneration consist of wind turbine wind energy conversion (WEC) and solar photovoltaic (PV) systems. Generally, a prosumer is a consumer that can also produce electricity. The benefit to individual prosumers is to offset electricity demand through installed generation capacity. There is no communication between neighbouring microgeneration equipment. It can be shown that electrical network tolerance needs to be maintained to ensure delivery of a high efficiency electrical supply. This research proposes to develop a smart communication system between microgeneration equipment which would benefit the local grid by taking advantage of plant during periods of high performance. The communication system should utilise predictive meteorological data based on local sensor data as well as temporal performance analysis.
Please indicate the student requirements for this project:
2.1 grade or higher in Computer Science or Electrical Engineering discipline. The applicant will preferably have good knowledge of software development, networking, algorithm design and electrical power systems.