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Training demand response behaviour in the India power grid to optimise embedded solar energy usage

PhD project title: Training demand response behaviour in the India power grid to optimise embedded solar energy usage

Outline description, includinginterdisciplinary,intersectoral andinternational dimensions 

With a rapidly growing population, a power system 55% reliant on imported coal for electricity generation and an increasing
energy demand, India’s carbon emissions are cause for national and international concern. To curb this issue, the Indian power
sector has been shifting towards renewable power to ensure energy demand is met along with economic growth and
environmental sustainability. Solar energy represents an excellent opportunity for India to play a significant role in global
greenhouse gas emissions reduction. As India is the world's third largest producer and third largest consumer of electricity.
India has observed fast growth over the past few years in the power sector due to investment by government, private
organizations, as well as international financial agencies. Although a large-scale deployment of solar energy has been observed
in the Indian power sector. A massive problem of adequate energy procurement persists because of inefficient energy
consumption. This project will examine this problem with an aim to improve energy efficiency and reduction at peak load.
Others have looked at Energy Management Systems, ON/OFF and PID controls, Model Predictive Control and Markovian
control techniques in order to reduce peak load consumption and shift demand towards high productivity period. A low-cost
Demand Side Management (DSM) smart control is proposed in this research to monitor residential load in real time to analyze
consumption patterns. It will employ novel Bayesian ‘categorization’ techniques in response to demand. This will reduce local
grid congestion and afford consumers the opportunity to reduce their energy bills by accessing flexible Time of Use tariffs. This
pricing approach mechanism will train sustainable consumer behavior in response to energy prices. A further co-benefit of this
project will be a significant reduction in coal energy dependence from residential load, and thus a lowering of India’s carbon

Key words/descriptors Demand response, Decarbonisation, Bayesian, Tariff, India, Solar, Consumer, Controller

Fit to CITI‐GENS theme(s) Information Technology
Supervisor Information
First Supervisor: Dr. Aoife Foley (Reader)
Second Supervisor: Prof Jennifer McKinley
Third Supervisor: Ms Sorcha Schnittger

Name of non‐HEI partner(s) Scottish and Southern Electricity SSE, cf. LoS attached.
Contribution of non‐HEI partner(s) to the project:
They confirm that they will fund attendance at a European conference, provide supervision/expert
insight by their research team and placement. This is the intersectoral dimension.

The control aspects of the project will be carried out with SSE (cf. LoS attached). SSE confirm that they will host the student
on an industrial placement. This is the intersectoral dimension.

The international and interdisciplinary dimensions of the project are 1) the project will focus on India, 2) the second
supervisor will be Associate Professor Xi Lu from the School of Environment at Tsinghua University (cf. LoS attached) and
3) we are both invited members of ‘Asia-Pacific Network of Energy Think Tanks’ (APNETT). This think tank coordinated by
the United Nations Economic and Social Commission for Asia and Pacific (UN ESCAP) Energy Division which represents
policy makers, research institute and governments across Asia and the Pacific in shifting to a low carbon society. Professor Lu
has an existing project in India with Harvard University and Tsinghua. He has confirmed that he will also host the PhD
student at Tsinghua University (cf. LoS attached).

Research centre/School Bryden Centre/School of Mechanical & Aerospace Engineering with input from EPIC in EEECS
Subject area Energy Systems, Environmental Sciences