Development of a Solar PV Energy Assessment Tool for EG-Audit Ltd.

Chemical & Biological Engineering.

Student Name:

Daniel Owen

References

Supervisor Names: 2016

Dr Alan Dunbar

& Kevin Aylward

0

4000

8000

12000

16000

20000

Life

tim

e P

rofi

t (£

) ● Primary solar solution providers

● Secondary solar solution providers

● Not-for-profit organisations

Introduction

As of February 2016, microgeneration FiT rates fell to 4.4p/kWh

from 12.5p/kWh[2]. This project investigated the effects of this

change upon the financial payback for PV systems in the UK.

The nationwide roll-out of SMART meters in 2020 will

dramatically affect the export payments for future PV

installations[1]. Therefore, by calculating the actual export

versus self-consumption ratio for a property, the developed

tool will possess a higher level of accuracy.

EG-Audit supplied electricity metering data for

six case study properties that were analysed for the

development of an impartial solar assessment tool.

Rival solar assessment tools were analysed using an example property

to identify any notable variances in results and result presentation methods.

Analysis Method

Excel was used to develop the solar

assessment tool from data supplied by

the MCS and solar insolation variable

relationships from scientific publications.

Excel was used to identify electricity usage

trends from the metering data supplied by EG-

Audit for the six case studies.

[1] Gans, W. et al. (2013) Smart meter devices and the effect of feedback on residential

electricity consumption. Energy Economics, 36(1), pp. 729-743.

[2] Gauke, D. (2015) Budget 2015. London, HM Treasury.

[3] Jardine, C. (2015) Solar Photovoltaic Panels. In: I. Staffell. et al. (Eds.) Domestic

Microgeneration: Renewable and Distributed Energy Technologies, Policies, and Economics.

Oxon, Routledge. pp. 179.

Rival Calculator Results

Case Study Results

The predicted profits ranged from £4,000 to £18,000. The primary

solar solution providers displayed a clear bias for overestimation.

Feed-in Tariff Generation Payments

SUN

Export Tariff What you sell to the grid

Self-Consumption Electricity savings

£

Bi-directional

Meter

Future Revenue Stream Results*

52.8%

30.9%

16.3%

£

*as a proportion of

total income. .

kWh

/ho

ur

Time of Day

Commercial Usage

Residential Usage

4kWp Generation

Average Daily Energy Curves used

to calculate Actual Export Ratios

Future Development Gather further historical usage data from outside the

North West to create average usage trends for all areas of the UK.

Research the potential of reducing the reliance of the tool

upon the MSC supplied insolation data; instead, utilising observed

relationships between solar insolation levels and the variable factors.

Conclusions Average UK payback period for PV

systems will increase by 32.5% under

new legislation (using 2015 efficiencies).

Inputs and results overlooked by the

rival calculators, but included in EG-Audit’s

assessment tool, are listed below;

On average, the summer

months accounted for 53.8%

of total annual export for the

properties analysed.

Winter 0.1%

Spring 33.3%

Summer 53.8%

Autumn 12.8%

Average Seasonal Export as a

Proportion of Total Annual Export All six case studies were found to

export well below the 50%

assumption applied by the UK

government for export payments[3];

ranging from 5.5% to 21.2%.

Developed Solar

Assessment Tool

UNIQUE INPUTS UNIQUE RESULTS

Area Classification Actual Export Ratio

Property Classification Electricity Usage Trends

Degradation Rate Energy Payback Time

Maintenance Costs Generation Trends

Electricity Inflation Environmental Results