phd dissertation presentation v 2.4

ROBERT HICKEY

Cost Modelling for Improving

Energy Efficiency

PhD Dissertation

Defense

Robert HickeyJune 4th, 2015 | PhD Dissertation

Anthropogenic climate change (APG) may be the biggest challenge facing humanity;

Knowledge of the potential negative consequences of continued emissions levels have not stimulated action on a large enough scale to adequately address it;

A major reason given for inaction is that measures to address APG may result in economic harm to economies;

There is some evidence that energy efficiency measures can reduce greenhouse gas emissions while delivering economic and social benefits.

Why was this topic chosen?


Thesis Hypothesis

As a result of the age of the majority of the residential building stock in Bulgaria, and the relatively high levels of energy poverty, it was hypothesised that improving energy efficiency in the country though basic residential building envelope retrofits could have significant economic benefits for citizens while simultaneously reducing Bulgaria’s production of greenhouse gases;

It was also hypothesized that existing financial outlays for improving energy efficiency in the country would not be sufficient to meet stated emissions reductions targets or capture the benefits of these basic building envelope retrofits.


Forecasting greenhouse gas emissions for Bulgaria between 2015 and 2020;

Calculating the costs (as a percentage of GDP) to achieve different levels of emissions reductions from these forecasts, using three emissions abatement cost models;

Calculating the possible level of greenhouse gas emissions abatement from basic building envelope retrofits and the theoretical costs for doing so according to the models;

Comparing this possible abatement amount and costs to real-cases;

Determining the current financing available for energy efficiency measures in residential buildings;

Calculating the level of emissions that could be reduced with this financing if it was used similarly to the real cases and if it was used optimally according to the abatement cost models.

How was this investigated?


Thesis SUMMARY

BEGINEnergy Policy in EU and

BG

Calculating

Emissions for 2020

Carbon Abatement Cost Models

Available Financing

for EE

The Human Element

ENDPolicy

Implications

Q&A

THE CASE FOR EE

MEASURES

I

MTDS. EMISSIONS & ABATEMENT

COSTS

II

REAL CASES OF EE IMP

IV

RETROFIT COST CALC.

III

MAIN FINDINGS

V

LIMITATIONS

VI

Compare Models

and Cases

THE CASE FOR EE MEASURESAs of 2013, Bulgaria had the most energy intense economy of the twenty-eight member states of the European Union, and high relative levels of energy poverty.

I


A McKinsey study from 2008 highlights that “depending on how new low-carbon infrastructure is financed, the transition to a low-carbon economy may increase GDP growth in many countries”;

The energy intensity in Bulgaria increased between 2009 and 2011 (kg of oil equivalent per 1 000 EUR) which was possibly linked to the global financial crisis – although between 2011 and 2013 the energy intensity has decreased by 13.5%. Nevertheless, Bulgaria’s energy intensity is still the highest in the EU-28;

Data for Bulgaria, from 2009, reveals that 93.8% of residential housing in Bulgaria was built before 1990 when energy efficiency codes were relatively weak.

The Case for Energy Efficiency Measures


3.91%

17.26%

26.95%

18.73%

14.70%12.25%

5.41%

0.79%

1946-1960

1919 - 1945

1971 - 1980

1991 - 2000

Up to 1919

1981 - 1990

Since 2001

1961 - 1970

Source: European Union Statistics on Income and Living Conditions

Residential Buildings in Bulgaria by Period of Construction


Data from the 2011 Census in Bulgaria showed that 15.5% of households in Bulgaria had outside thermal insulation, while 29% have low-energy windows or doors;

Energy consumption in the residential sector in Bulgaria is characterized by the consumption of low efficiency renewable energies (i.e. firewood) and electricity. According to National Statistical Institute data from 2013, in Bulgaria, 34.1% of all households used wood as a main heating source, 28.6% used electricity, 19.81% used coal, 16.37% used central heating, and .68% used gas. Thus EE measures could help reduce the need to burn these low efficiency fuels;

Energy efficiency in buildings can aid in the alleviation of energy poverty, as thermal comfort not affordable for many households in the country.

The Case for Energy Efficiency Measures


Percentage of Population "Unable to Keep House Adequately Warm"

2010

9.5

66.5

2011

9.8

46.3

2012

10.8

46.5

EUROPEAN UNION AVERAGE BULGARIA

Source: European Union Statistics on Income and Living Conditions


NAME OF DOCUMENT TARGET

Third National Action Plan on Climate Change

61,864 kt CO2e emissions by 2020 with “scenario with existing measures”. (-7.8%

compared to 2005)54,578 kt CO2e emissions by 2020 with

“additional measures” (-18.7% compared to 2005)

Energy Strategy of the Republic of Bulgaria till

2020

Save 5.8 million toe of primary energy in comparison with a reference BAU scenario in

2020

First National Energy Efficiency Action Plan

2008-2010 (2007)

627 Ktoe of energy savings in final energy consumption by 2016

ENERGY AND EMISSIONS TARGETS IN POLICY DOCUMENTS

These is also a need to meet the energy saving targets laid out in a number of policy documents.


While official forecasts of emissions in 2020 and 2030 exist for Bulgaria in public documents, we wanted to construct our own emissions baseline;

Additionally, the National Energy Efficiency Action Plans are based on assumptions that did not hold true in the years after baseline emissions estimates were constructed.

Forecast of emissions was calculated, but why?

Source: Own Table Using Data from First National Energy Efficiency Action Plan 2008-2010, Eurostat – Final Energy Consumption by Sector, and SPSS

METHODS FOR CALCULATING EMISSIONS AND ABATEMENT COSTS

II


Emissions projections for Bulgaria, through 2020, must be accurately determined and used as a baseline against which potential emissions reductions resulting from EE measures can be calculated. Some of the calculation logic for the targets in the National Energy Efficiency Action Plans linked emissions rates and energy consumption directly to the GDP growth rate. This approach is appeared overly simplistic;

William Cline (American economist and Senior Fellow at the Peterson Institute for International Economics) deploys an approach that considers population growth rates, changes in per capita income, changes in the rate of energy efficiency, and changes in the carbon intensity of energy production over a defined period of time in helping to construct such a baseline.

Calculating Emissions Baseline in 2020


Developing Emissions Projections

CALCULATING POPULATION

GROWTH

WHERE Nt IS EQUAL TO THE POPULATION

IN YEAR t, No INDICATES THE

REFERENCE YEAR, n IS THE GROWTH RATE OF THE POPULATION.

CALCULATING REAL GDP PER CAPITA

WHERE Qt IS THE GDP PER CAPITA IN 2005 PPP DOLLARS IN YEAR t, Qo IS THE REFERENCE YEAR,

AND g IS THE GROWTH RATE OF

PER CAPITA INCOME.

CALCULATING OUTPUT PER UNIT OF

ENERGY

WHERE Λt EQUALS THE OUTPUT PER UNIT OF ENERGY

(ENERGY EFFICIENCY) IN YEAR t, Λ0 IS THE

REFERENCE YEAR AND w IS THE ANNUAL

RATE IN INCREASE IN ENERGY EFFICIENCY.

ENERGY PER UNIT OF CARBON DIOXIDE

WHERE Yt EQUALS THE ENERGY PER UNIT OF CARBON DIOXIDE (CARBON

EFFICIENCY) IN YEAR t, Y0 IS THE

REFERENCE YEAR AND c IS THE ANNUAL RATE OF INCREASE IN CARBON EFFICIENCY

OF ENERGY.

1 2 3 4

𝑁𝑡=𝑁0𝑒𝑛𝑡 𝑞𝑡=𝑞0𝑒

𝑔𝑡 𝜆𝑡=𝜆0𝑒𝑤𝑡 𝛾𝑡=𝛾0𝑒

𝑐𝑡

Using Cline Equation


Using these equations, Cline shows how emissions in year t can be approximated by multiplying the population in year t, times real GDP per capita in year t, divided by output per unit of energy in year t, times energy per unit of carbon dioxide as

The percentage rise or fall of the value of this equation between year 0 and year t is equivalent to the percentage rise or fall of emissions between these years;

How will change over time is directly proportional to how will change over time;

Thus, to calculate emissions in year t (or Et), we need to know emissions in the base year as well as:



Developing Emissions Projections

CALCULATING POPULATION

GROWTH

USING THIS FORECAST UNTIL 2020 (DAMPENED

TREND MODEL), WE FIND THAT n=-.73% BETWEEN 2015 AND

2020

CALCULATING REAL GDP PER CAPITA

USING THIS FORECAST UNTIL

2020 (BROWN MODEL), WE FIND

THAT g=3.95% BETWEEN 2015 AND

2020

CALCULATING OUTPUT PER UNIT

OF ENERGY


2020 ( ARIMA MODEL), WE FIND

THAT w=6.6% BETWEEN 2015

AND 2020

ENERGY PER UNIT OF CARBON

DIOXIDE


2020 (HOLT MODEL), WE FIND

THAT c=-.48% BETWEEN 2015

AND 2020

1 2 3 4

Using Cline Equation



𝐸𝑡=𝐸𝑜𝑒¿ ¿

The last official figure for emissions levels in Bulgaria from the Europe Environmental Agency was from 2012 and reported as 61,045.626 kt CO2e. When applying the forecasted average annual rate of change between 2015 and 2020 we find that in the 8th year after 2012 – 2020, that

𝑁 8=61,045.626 𝑒− .029∗ 8

𝑁 8=48,405.89

Source of the EstimationOwn Calculation

Based on the Cline Model

EU Energy, Transport and GHG Emissions –

Trends to 2050: Reference Scenario

2013

Second National Action Plan on

Climate Change

Third National Action Plan on

Climate Change (Scenario with

additional measures)

Third National Action Plan on

Climate Change (Scenario with

Additional Measures)

Emissions in 1000t CO2 equivalent in

202048,406 55,000 89,000 61,864 54,578



Using this baseline emissions estimate and three cost models (CRED Model, RICE Model, EMF-22 Model) we find the following costs for various levels of emissions cutbacks in Bulgaria in 2020.

Basic Building Envelope Retrofit Cost Calculations

III


Following the calculation of total emissions in 2020 and the theoretical upper limit of possible emissions abatement (before costs turned infinite), the McKinsey Marginal Abatement Cost Curve for Eastern Europe was scaled down to reflect this theoretically possible emissions abatement level of 37.26 Mt CO2e in Bulgaria (before costs tuned infinite) with the with the specific abatement possible (.87 MtCO2) from basic building retrofits of building envelopes noted.

Basic Building Envelope Retrofits Cost Calculation


By overlaying the cost models with the cost curve above (the details of how this was done can be seen in the dissertation itself), the following costs for abating this .87 MtCO2 were calculated and can be seen in the table below;

Clearly, all of these costs are extremely low, which is due to the fact that, in these models, the cost savings resulting from conserved energy makes the costs for basic envelope abatement essentially free.

Available Cost Calculation

McKinsey Bottom-Up Approach

CRED Model RICE Model EMF-22 Model

-49.48€ million (2005 Euros)

$11,247,197 2005 USD $5.335,913.71 2005 USD $26,879,744.66 2005 USD


This result seemed like it was too good to be true, and since whenever something seems too good to be true, it probably is, we wanted to cross check these theoretical models with real cases of building envelope retrofits in the country;

There is a plethora of academic literature which shows that it is common for renovated buildings to be used in ways that reduce or eliminate the benefits of the retrofit (i.e. that the retrofits are not done correctly, that increases in energy use result because more benefit is now derived from such use, or that consumers may pursue EE measures only when they want to consume more);

Data from a survey of Bulgarian and other European citizens was also analyzed and showed that around 9.8% of the 102 Bulgarian’s would not be willing to reduce their personal consumption compared to 6.6% of 1026 European citizens from 11 European countries;

Thus, would these calculated benefits really result from basic envelope building retrofits?

Basic Building Envelope Retrofits Cost Calculation

Real Cases of Energy Efficiency Retrofits

IV


Three real cases of building envelope retrofits were investigated to determine how the abatement costs, calculated using the cost models and McKinsey estimates, compare with reality.

It was found in these multi-family blocks that around 50% of total emissions could be abated using insulation of external walls, insulation of the roof, insulation of the floor, and changing of existing wooden and metal doors and windows to insulated PVC doors and windows. However, the renovation costs per M2 were much higher than in the McKinsey estimate.

In the McKinsey estimate, the renovation package included improving building air tightness by sealing baseboards and other areas of air leakage; weather strip doors and windows; insulate attic and wall cavities, add basic mechanical ventilation system to ensure air quality – but not changing windows and doors. It was assumed that this would result in a 15-25% heating savings potential and up to 10% cooling savings – so much less that was experienced in the actual renovations.

Real Cases Energy Efficiency Retrofits


We determined how much financing is available for energy efficiency in Bulgaria to determine how much carbon could theoretically be abated according to the cost models and how much could be abated if it was used in the same way as in these real cases

Available Financing for Energy Efficiency

Фонд „Енергийна ефективност и възобновяеми източници“ /

ENERGY EFFICIENCY AND

RENEWABLE SOURCES FUND

Оперативна програма

„Иновации и конкурентоспособнос" 2014 - 2020 / Operative program

"Innovation and competitiveness“

НАЦИОНАЛНА ПРОГРАМА ЗА ЕНЕРГИЙНА

ЕФЕКТИВНОСТ НА МНОГОФАМИЛНИ

ЖИЛИЩНИ СГРАДИ 2015 -

2016 г. / National Programme for

energy efficiency of multifamily buildings

ОП „Региони в растеж 2014-

2020“ / Operative program "Regions in development"

2014 - 2020

Програма BG04 "Енергийна

ефективност и възобновяема

енергия" - Грантова схема BG

04-04-05 - BG04 PROGRAMME

ENERGY EFFICIENCY AND

RENEWABLE ENERGY

67,800,000 лв. 516,502,700 лв.

Divided by the 7 years of the

program: 73,786,100 BGN

1,000,000,000 лв.



435,954,507 лв.



31,293,280 лв.


Keeping in mind the calculated level of emissions for Bulgaria in 2020 of 48,406 KtCO2:

Using this financing exactly the same way as it was used in the real cases would equate to a savings of 290 KtCO2 (.6%) annually following the completion of the refurbishment;

According to the CRED-Two Parameter Model 26,400 KtCO2, or a 54.5% cutback ( .0264 GtC02 or .0072 in GtC) could be abated by 2020 with this financing annually;

According to the Nordhaus RICE Model 27,890 KtCO2, or a 57.6% cutback (.02789 GtC02 or .0076 in GtC) could be abated by 2020 with this financing annually;

According to the EMF-22 Model 17,610 KtCO2, or a 36.4% cutback (.01761 GtC02 .0048 in GtC) could be abated by 2020 with this financing annually.

Compare Models And Cases

Main Findings

Based on an analysis of the findings a number of conclusions are given.

V


It appears that the energy efficiency retrofits in the three real cases, while beneficial in halving energy consumption and emissions, may not optimize the environmental benefits of the available financing for energy efficiency. It is speculated that this may be because these retrofits are deeper than would be environmentally optimal;

According to the McKinsey and cost models, 870 KtCO2 (.87 MtCO2) or 1.8% of emissions could be prevented from being emitted in 2020 at negative or near zero cost ;

Possible baseline emissions cutbacks with existing financing were calculated at between 36% to 57% if interventions were implemented in the most cost optimal way possible. This would easily achieve energy targets. There is a caveat here though that must be noted. The values for the constants in these cost curves were calculated as if action started in 2010, when initial research for this dissertation took place.

Main Findings


These findings point towards the idea that, while any building envelope retrofit would appear economically beneficial, the degree of this benefit is highly contingent upon the depth of the refurbishment – with basic refurbishments having faster payback periods and greater negative costs;

A thorough examination of all possible (or at least multiple competing) interventions would be one approach in ensuring that such financing is achieving its goals in a cost optimal way. For example, less intensive retrofits on a higher number of buildings, such as providing weather-stripping on doors and windows, and hiring knowledgeable technicians to install it, may be better placed than deep renovations and innovations like nearly zero-energy buildings. Further research would be needed to confirm or refute this;

Further consideration of this issue can reveal more complicated motivations for choosing a particular program or policy over another, and may reveal the social dimensions to energy policy. Just because an intervention is economically or environmentally beneficial does not necessarily mean that it is socially beneficial.

Policy Implications

Limitations

There are a number of assumptions and limitations in the study.

VI


The growth rate of the Bulgarian population, the growth rate of GDP per capita, the output per unit of energy, and the carbon efficiency of energy all have varying degrees of inherent uncertainty;

For the three cost models that were deployed, assumptions had to be made as to which cost parameters to use in each model;

It was assumed that McKinsey accurately included every possible carbon abatement intervention and did so in the correct order according to cost;

When trying to locate real case-based data to gain insights into the costs and benefits of energy efficiency interventions, there were limitations on the number of cases where raw data could be found;

It is only possible to roughly approximate the financial outlays that are available for energy efficiency improvements in Bulgaria;

There are some issues with the data from the survey of Bulgarian citizens in that it was not necessarily representative of Bulgarian society and/or the viewpoints held by Bulgarian citizens.

Study Limitations


The dissertation work was supported by two experts in the field of energy efficiency – one of these experts was the Chairwoman of the Management Board of the Sofia Energy Agency (SOFENA), Mrs. Nadya Nikolova-Deme. The other was provided by a researcher working at the Building Performance Institute Europe (BPIE) in Brussels, Mr. Francesco Mariottini.

Letters of Support


This research aims to illuminate how environmental benefits need not come at economic costs. However, reductions in emissions at the levels outlined here are extremely small compared to what is needed to keep global mean temperatures from rising by under 2˚ Celsius – the threshold under which the most serious negative affects of global warming can be avoided;

With global concentrations of CO2 now over 400 ppm, and without a slowdown of emissions in sight, the possibilities for keeping temperatures under 2˚ Celsius seem like somewhat of a dream.

World-renowned economist Jeffery Sachs said in a recent interview “If China and India continue to completely depend on coal as they are…if it’s true that the major parts of the world don’t participate, then it does not matter what you and I do and that is why we need a global understanding and a global agreement.”

Thus, if anything, I hope that this dissertation highlights that individual action, anywhere, can contribute to the solution, while benefitting individuals in the process.

Final Comments


[email protected]

TWITTERtwitter.com/rfhickey

LINKEDINbg.linkedin.com/in/hickeyrobert

Contact Me

You can find all dissertation related documents at: goo.gl/QTTv3N

Questions?

YOUTHANK

FOR COMING

phd dissertation presentation v 2.4

Documents

energy efficiency measures

emissions abatement

energy policy

energy intensity

level of emissions

high levels of energy

energy intense economy

ee measures