Development and assessment of renewable energy policy scenarios by 2030 for Bulgaria

Accepted Manuscript Development and assessment of renewable energy policy scenarios by 2030 for Bulgaria

Angel Nikolaev, Popi Konidari PII:

S0960-1481(17)30392-0

DOI:

10.1016/j.renene.2017.05.007

Reference:

RENE 8770

To appear in:

Renewable Energy

Received Date:

08 May 2016

Revised Date:

01 April 2017

Accepted Date:

01 May 2017

Please cite this article as: Angel Nikolaev, Popi Konidari, Development and assessment of renewable energy policy scenarios by 2030 for Bulgaria, Renewable Energy (2017), doi: 10.1016/j. renene.2017.05.007

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ACCEPTED MANUSCRIPT

Highlights    

A policy scenario with an average ambition for renewables is proposed. The scenario results in 28 % renewable energy share in 2030. The scenario has high political acceptability and feasibility of implementation. The scenario has above average environmental performance.

ACCEPTED MANUSCRIPT

Development and assessment of renewable energy policy scenarios by 2030 for Bulgaria

1 2 3 4

Angel Nikolaev

5 6

Faculty of Economics and Business Administration, Sofia University “St. Kliment Ohridski”

7

Dr. Popi Konidari

8 9

Head of Climate Change Policy, Energy Policy and Development Centre, national and Kapodistrian University of Athens Abstract

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

The Bulgarian target for Renewable Energy Sources (RES) by year 2020 is to achieve 16% share of energy from RES in gross final energy consumption. The so far recorded data show that the country will exceed it. The question that emerges is what new RES target the country can set up for the following decade up to 2030. This target needs to be in consistency with the obligations of Bulgaria as an EU member state for the 2030 framework for climate and energy policies, but also with its national priorities and needs. This paper aims to identify the most feasible level of ambition up to year 2030 for the Bulgarian renewable energy policy taking into consideration the national framework. Two research tools are used for this purpose, the modeling tool LEAP and the multi-criteria evaluation method AMS. LEAP simulates three developed scenarios aiming to different RES targets for 2030 supported by different policy mixtures. LEAP outcomes and official information are used as inputs to AMS. The AMS outputs allow the identification of the most appropriate scenario for the country. Conclusions concern under which conditions each policy mixture is feasible along with discussion on policy recommendations for its improvement.

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Keywords: Renewable energy Policy scenarios Bulgaria

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1

Introduction

As an EU Member State, Bulgaria is committed to the European Union (EU) climate policy targets for 2020, adopted by the EU Parliament on December 17, 2008, namely 20% reduction of EU greenhouse gas emissions compared to year 1990, 20% reduction of primary energy consumption compared to projections for year 2020, and 20% share of renewable energies in EU energy consumption by 2020. Directive 2009/28/EC regarding the promotion of RES sets mandatory EU Member State targets for their overall share in gross final consumption of energy and in transport by year 2020. For Bulgaria, the target is 16% share of RES in gross final energy consumption in 2020 (based on 9.4% share in 2005). This target includes 20.8% share of electricity from RES in gross final consumption of electricity, 23.8% share of heating and cooling from RES in gross final consumption of energy for heating and cooling, and 10.8% share of energy consumption in the transport sector [1]. As an EU Member State the country will need to contribute to the more ambitious targets that the EU is intended to set and proceed with the post 2020 era and under the framework of the set into force Paris Agreement. A reduction in Greenhouse Gas (GHG) emissions by 40% below the 1990 level, requires an EU-wide binding target for renewable energy of at least 27%

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[2] share of gross final energy consumption. Bulgaria will need to re-examine its RES policy and maybe adopt a new RES target in consistency with this commitment. In the 2014 study of the Vienna University of Technology (VUT) in cooperation with the Energy Economics Group (EEG), the Bulgarian RES targets for year 2030 were calculated taking into consideration also the different levels of ambition on EU scale in terms of 2030 RES share in the gross final energy demand. For Bulgaria, the proposed targets were: 23% for a 30% EU level of ambition ie 30% RES share of the gross final energy demand by 2030, 26% for a 35% of EU level of ambition, 29% for 40% and 32% for 45% [3]. For a 40% reduction in GHG emissions, Bulgaria is expected to undertake a target of 31% share of RES in gross final energy consumption [4]. Another 2014 study of the Bulgarian Electricity System Operator reviewed two scenarios for the Electricity from Renewable Energy Sources (RES-E) integration to the grid in 2020 and 2030. According to the ambitious scenario RES-E reaches 31.0% of the total final electricity consumption in 2030. That scenario is based on the accelerated introduction of innovative technologies to mitigate the impact of the intermittent generation, such as electrical transport, accumulators, responsive demand, and pump storage. The less ambitious scenario assumes limited new technologies and it results in 28.4% RES-E share in 2030 [5]. The work presented in this paper distinguishes in this area for the following reasons. There is a very limited number of published papers about the Bulgarian RES policy. They mainly concern a specific type of RES (geothermal, biogas, hydropower) [6, 7, 8] but not the whole RES sector and its relevant policy mixture or the set targets. Another group of papers includes Bulgaria in a group of EU countries that are examined for the effectiveness of: i) a specific policy instrument such as the feed-in tariffs in 26 European Union countries [9]; ii) specific support policy strategies for RES (Feed-in Tariffs (FITs), quota based on tradable green certificates) [10]; or the convergence of a group of policy instruments: support policy types over the last decade (feed-in tariffs, premiums, tradable green certificates, tax incentives, investment grants and financing support for specific technologies (wind, biomass, PV) [11] or just part of a review regarding the combination between primary and secondary instruments for RES-E support [12]. Also, there are papers in which the EU Member States are examined as a group regarding the support mechanisms for the penetration of RES (investment support, FITs, Tradable Green Certificates, fiscal and financial measures) [13, 14]. Therefore, there are no papers in which the Bulgarian RES policy as a total is examined alone and not in a group of countries under a forward-looking perspective. This paper covers this gap and focuses on the identification of the most suitable policy mixture for the promotion of RES in Bulgaria. For the determination of this policy mixture two research tools are used: the LEAP model and the multi-criteria evaluation method AMS. Brief presentation of the two tools and of the approach are quoted in Section 3. The scenarios and their evaluation are discussed in Section 4. Section 5 includes the discussion of the outcomes and the respective policy recommendations based on them.

85 86 87

1.1 The Bulgarian framework for RES The dynamics of the primary energy supply, final energy consumption, and RES consumption in Bulgaria is shown in Figure 1.

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Fig.1: Dynamics of the primary energy supply, final energy consumption, and RES consumption in Bulgaria. Source: [15] The figure shows a moderate variance of the primary energy supply, a relatively stable final energy consumption, and increase of the RES contribution. The 2015 structure of the final energy consumption is shown on Figure 2.

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Fig.2: 2015 structure of the final energy consumption by fuel in Bulgaria. Source: [15]

96 97 98 99 100 101 102 103 104 105 106 107 108 109 110

The figure presents the dominant role of petroleum products and electricity in the 2015 final energy consumption. The sector with the highest final energy consumption is transport (35%), followed by industry (29%), households (23%), and services and others (13%) [15]. The Bulgarian energy sector is dependent on energy imports. In 2015, 35.4 % of the primary energy supply relied on imports and this was attributed mainly to the high dependence on imported crude oil and gas. The country has large lignite production (4.81 Mtoe) and limited production of brown coal (0.29 Mtoe), natural gas (0.16 Mtoe), and crude oil (0.03 Mtoe) [16]. The share of renewable energy in the gross final energy consumption during the period 20102015 is shown in Table 1. This table also demonstrates the increase of RES share during this period, which is attributed to the increase of all three sectoral shares: Heating and Cooling from RES (RES H&C), RES-E, and RES in the Transport sector (RES-T). The following tables 2, 3, and 4 show that the increase of these three shares is driven by the higher use of renewables, while as indicated in figure 1, the final energy consumption remains relatively stable. Table 1: Sectoral and overall shares of energy from RES. Source: [17] (2010-2014 data); [16] (2015 data)

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ACCEPTED MANUSCRIPT 2010

2014

2015

24.9%

27.5%

29.2%

28.3

28.6

RES-E

12.7%

12.9%

16.1%

18.9%

18.9

19.1

RES-T

1.0%

0.4%

0.3%

5.6%

5.3

6.5

14.1%

14.3%

16.1%

19.0%

18.0%

18.2%

Table 2: Total actual contribution (installed capacity, gross electricity generation) from each RES-E technology in Bulgaria. Source: [17] (2010-2014 data); [16] (2015 data)

Hydro

2010

2011

2012

2013

2014

2015

MW ktoe MW ktoe MW ktoe MW ktoe MW ktoe MW

ktoe

3048 353 3108 354 3181 363 3203 368 3219 372 3219

486

Geothermal

0

0

0

0

0

0

Solar

25

1

154

9

1013

70

Tide, wave, ocean

0

0

0

0

0

0

0

0

0

0

0

0

Wind

488

52

541

69

677

89

683

105

700

112

700

125

Biomass

10

3

11

5

14

6

34

10

40

17

54

21

TOTAL

0

0

0

0

0

1020 117 1026 108 1029

3571 409 3814 436 4885 528 4940 599 4985 608 5002

0 119

751

Hydro power is traditionally the most important RES-E technology in the country, however the sharp increase of solar PhotoVoltaic (PV) and wind capacities (see table 2) makes these technologies substantial contributors too. Table 3: Total actual contribution (final energy consumption) from each RES-H&C technology in Bulgaria (ktoe). Source: [17] (2010-2014 data); [16] (2015 data) RES-H&C Technology Geothermal (excl. heat pump) Solar Biomass - Solid biomass - Biogas - Bio liquids Renewable energy from heat pumps Total

120 121 122 123 124

2013

24.4%

Types of RES

114 115 116 117 118 119

2012

RES-H&C

Overall RES share

111 112 113

2011

2010 33 10 884 883 1 0 38 964

2011 33 14 944 943 1 0 42 1033

2012 33 15 1005 1005 0 0 47 1101

2013 33 19 1010 1010 0 0 64 1127

2014 33 20 963 961 2 0 65 1081

2015 33 22 1046 1043 3 0 66 1167

The quick growth and large share 28.6% in 2015) of RES-H&C in the heating and cooling sector can mainly be attributed to the large scale use of solid biomass for heating, mainly in households (table 3). Table 4: Total actual contribution from each RES-T technology in Bulgaria (ktoe). Source: [17] (2010-2014 data); [16] (2015 data) RES-T technology Bioethanol / Bio-ETBE Biodiesel

2010

2011 0 0

0 0

2012 2013 in ktoe 0 8 0 96

2014 15 96

2015 50 126

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ACCEPTED MANUSCRIPT Hydrogen from renewables Renewable electricity Others Total

0 7 0 7

0 8 0 8

0 6 0 6

0 7 0 111

0 9

0 9

120

185

125 126

Following RES-T negligible contribution the period 2010-2012, it increases sharply (table 4), due to the increased biofuel blending obligations [18].

127 128 129 130

1.2 Renewable Energy Potential

131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156

The results of the most recent studies on the technical potential of RES in Bulgaria are presented in Table 5. Table 5: Estimation on technical potential of RES in Bulgaria. Renewable source Technical potential, in ktoe Hydropower 1290 [19] Geothermal energy 18 [19] Geothermal energy using injection technologies 331 [19] Solar PV 1066 [20] Solar thermal >6396 [20] Tidal and sea wave energy no assessment Wind energy 12000 [20] Solid biomass 1524 [19] Biogas 280 [19] Liquid fuels 366 [19]

1.3 Policy instruments The main existing policy instruments and rules-influencing mechanisms for RES-promotion in the country are: – Obligatory RES-E purchase: Electricity transmission and distribution companies are obliged to purchase all RES-E and electricity from Combined heat and power (CHP) [21]. – PPAs: The obligatory purchase of RES-E is under Power Purchase Agreements (PPAs) with a term of: 20 years for geothermal, biomass, and solar energy; 12 years for wind energy, and 15 years for hydropower plants with capacity of up to 10 MW and other RES [18]. – Feed-in tariffs (FIT) combined with Quotas: The Energy and Water Regulatory Commission (EWRC) sets annually FIT and quotas for grid-connected RES-E installations. The FIT for RES-E are determined according to the typical production costs for the technology, plus addition. The FIT are fixed for the whole PPA period. The RES-E quotas are set for the next 12 months, based on the country progress towards the renewable energy targets of the National Renewable Energy Action Plan (NREAP) [18]. In this relation, and due to the experienced negative impact of the increased RES-E on the electricity system and electricity prices, since the introduction of quota mechanism in 2012, the annual RES-E quotas were set to zero, except for the small-scale biomass plants [20, 58]. – Certificate of origin: RES-E is recognized by this certificate, issued by EWRC. It certifies the producer, amount of generated electricity, period of production, production plant and its capacity [44]. – Priority access to the grid: Electricity transmission and distribution companies are obliged to expand their capacity to integrate RES installations and to connect them to the grid by priority. Connection costs are paid by the RES-E producer [18].

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Transport fuel blending obligations: Companies trading transport fuels are obliged to sell conventional fuels mixed with bio-fuels. They have to follow a schedule for the gradual increase of the bio-fuel share until 2020 [18]. - Green Investment Scheme (GIS): The Bulgarian Government can sell Assign Amount Units (AAU) and use the income from them for increasing the use of RES (specifically biomass utilization) technologies [22]. The Bulgarian National Renewable Energy Action Plan (NREAP) - the main document to ensure the achievement of the national RES targets – includes 38 planned measures to promote RES and provides estimated trajectories for both the shares of renewable energy consumption in heating and cooling, electricity, and transport, as well as the development of renewable energy capacities until 2020 [1]. The planned measures have partially been adopted in the legislation.

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2

170 171 172 173 174 175

2.1 Approach

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-

Methodology

As aforementioned, two research tools are used for this paper. The modeling tool, LEAP, which is necessary for understanding the time development of the scenarios, and the evaluation multi-criteria method, AMS, that will allow to understand which of the developed scenarios (and its respective policy portfolio) is the most suitable one for the Bulgarian case. The next paragraphs present these tools.

2.2 LEAP The Long range Energy Alternatives Planning system (LEAP) - developed by the Stockholm Environment Institute - is a widely-used tool for energy policy and climate change mitigation assessment. It can be used to: i) track energy consumption, production, resource extraction, and GHG emissions in all economic sectors [23]; ii) create models of different energy systems and iii) support a wide range of modeling methodologies on the: a) energy demand side (bottom-up, end-use accounting techniques to top-down macroeconomic modeling); b) supply side (powerful accounting and simulation methodologies for modeling electric sector generation and capacity expansion planning) [23]. It is the most appropriate tool for developing RES scenarios for Bulgaria because it: i) is a predominantly bottom-up tool, which is the better choice for less developed countries [24]; ii) is simple to use and transparent [25]; iii) has relatively low data input and high data flexibility; iv) has a considerable number of significant applications that are presented in its web-site [25], v) is free of charge for a wide group of users (ie students in an accredited academic institution (college, university or school); non-profit organizations (NGOs), not-forprofit governmental agencies, and academic organizations, all based solely in a developing country [25]).

2.3 AMS

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AMS is the combination of three standard multi-criteria methods: Analytical Hierarchy Process (AHP), Multi-Attribute Utility Theory (MAUT) and Simple Multi-Attribute Ranking Technique (SMART) [26]. It consists of four steps:

197 198 199 200

i) creating the criteria-tree; ii) determining weight coefficients for criteria/sub-criteria; iii) grading the performance of policy instruments/policy mixtures under a criterion/subcriterion;

201 202

iv) collecting the previously produced grades and forming the aggregate grade for each evaluated policy instrument/mixture.

203

The necessary consistency and robustness tests are performed within the relevant steps [26, 27].

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The method has been used in similar study cases. The weight coefficients of the criteria/subcriteria are calculated (step ii) by the user. Here the values of previous works with very good results for the performed consistency test are used [26]. Its main advantage for the Bulgarian case is that if for any of the sub-criteria there are no available and credible data then the user can proceed with judgements based on any available information and assign a grade for the judgement.

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3.1 Concept of scenarios

Scenario modeling

The concept for developing the scenarios was to understand the synthesis of different policy mixtures that support respectively the achievement of different RES targets for Bulgaria, but are adopted under the same feasible, expected energy demand. For setting this same feasible, expected energy demand (constraint) the authors looked at the most recent Reference scenario (REF2016) for Bulgaria [28]. Basic key assumptions and results of that scenario for years 2020 and 2030 are presented in Table 6. These assumptions were used for the developed in this paper scenarios. Table 6: Key assumptions and results in the Bulgarian Reference scenario [28]. 2020 2030 Population 6 951 984 6 454 556 GDP, mln EUR, at constant 2013 prices 45 135 53 485 Final energy consumption, in ktoe, i.e: 9 481 9 652 - industry 2 794 2 790 - transport 3 050 3 138 - services 1 265 1 291 - households 2 371 2 433

219 220 221 222 223 224 225 226 227 228 229 230 231 232

Three scenarios for the Bulgarian RES policy were developed: I) the RED scenario which is a business-as-usual scenario, with its policy mixture synthesized by the existing and planned RES policies, implemented and officially expressed until 31st December 2015. 2015 was selected, because it is the most recent year with available statistical energy data. The name RED as selected to express current Renewable Energy Direction (RED) of the country. II) the GREEN scenario which is a scenario of ambitious RES development with the necessary policy mixture for supporting such a target. The name GREEN was selected to express the path towards a low carbon direction. III) the BLUE scenario which is a scenario of a moderate level of ambition towards RES development; it includes additional policies compared to RED, but without the most costly ones of GREEN. The name BLUE was selected since the blue color is used to synthesize the color GREEN and this scenario has similar characteristics with the GREEN one. Each of the scenarios is explained below, but following the order RED, BLUE and GREEN according to their ambition level of RES targets.

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Additionally, the following costs were considered for all of these three scenarios:

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   

Capital costs of electricity and heat transformation processes; Variable and fixed operational and maintenance costs of electricity and heat transformation processes; Costs of primary (coal, biomass, etc.) and secondary (electricity imports/exports, biofuels, etc.) energy resources; Costs of demand-side energy technologies in all demand sectors. For simplification purposes no costs have been specified for technologies that are identical in all scenarios - this concerns mainly the electricity use technologies (electricity demand is equal in all scenarios) and the cost of vehicle fleet (vehicles using traditional fuels can use blended fuels with biofuels).

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Information about the aforementioned costs were drawn from the National Statistical Institute [16], EWRC documents [57], the Intergovernmental Panel for Climate Change (IPCC) Assessment reports [29], and United States Energy Information Administration [30]. The above cost categories make up all internalized costs. The externality costs are not included, because the applied evaluation method AMS does not necessarily require the presentation of externalities in monetary terms. All cost figures are based on 2015 (or earlier, if not available) data and future cost developments were not considered.

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3.2 Scenario characteristics and assumptions RED scenario

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The RES policy mixture of this scenario includes the previously presented policy instruments in section 1.3. The planned ones as aforementioned are those quoted in the NREAP and are the following [1]: - Regulatory standards

257 258 259 260 261 262

o

-

programme for the gradual replacement of electricity and fossil fuels for heating and hot water purposes so that all public buildings by 2020 will be heated by biomass and other RES to the fullest extent possible. Gradual increase of the share of biomass fuels and support for the transition to the respective heating equipment, as a part of the programs supporting low income families.

Economic instruments

263 264

o

Developing rules and using financial resources from the Emission Trading Scheme (ETS) for investments in RES;

265 266 267

o

Financing projects through the Energy Efficiency and Renewable Sources Fund, which provides technical assistance combined with soft loans and/or financial guarantees (this is an existing instrument, which apparently is planned to continue);

268 269

o

Development of a support scheme for the use of RES in the: i) industry and ii) residential sector;

270 271

o

Development of a support scheme for local heating systems based on renewable energy in residential and public buildings;

272

o

Tax incentives for investments in energy generation from RES for household purposes.

273

For this scenario the following assumptions were adopted:

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a) RES-E capacity is assumed to remain the same as it was in 2015. This is justified by the decisions of the Regulator to set zero quota for new RES-E (see section 1.3). This results in 20.0% RES-E share in 2030 electricity consumption.

277 278 279

b) RES-H&C share is assumed to slightly increase until 2020, reaching 30.2%, in relation to the already planned policy instruments. During the period 2021-2030, its share is considered to remain unchanged.

280 281 282 283

c) RES-T is assumed to reach 10.8% in 2020, according to the NREAP [1]. This is supported by the annual renewable fuel blending obligations, set out in the Energy from Renewable Sources Act [18]. During the period 2021-2030 the RES-T share is expected to remain unchanged at 10.8%, given the absence of new policies.

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Based on the above assumptions, LEAP calculations resulted to 22.8% RES share in the 2030 gross final energy consumption.

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BLUE scenario Its assumptions reflect average ambition towards renewable energy. The following assumptions were adopted for this scenario:

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a) RES-E follows the less ambitious RES-E scenario (28.4% RES-E in 2030) of the Electricity System Operator (see section 1) [5]. In addition to the policy instruments in RED, this scenario assumes higher RES-E quotas for grid-connected installations, backed by adequate FIT, and more stimuli for private off-grid RES-E (tax incentives, grants, soft loans, guarantees). b) RES H/C share is assumed to increase at a rate that is average of the rates applied in the other two scenarios, reaching 37.8% in 2030. It is considered that, compared to RED, additional financial support (tax incentives, grants, soft loans, guarantees) is available for private RES H&C and there are higher obligations for the public buildings to use RES H&C. c) RES-T dynamics until 2020 is identical to RED (10.8% in 2020) and the values after 2020 slightly increase to reach 12.5% RES-T share in the transport energy consumption by 2030. The reason for assuming limited increase is the high costs of both biofuels and electric vehicles. The main measures to reach the target are financial incentives for switch to electric transport and respective level of the fuel blending obligations.

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Compared to RED, additional soft measures are considered, including information, advice, training, labelling, and others. According to LEAP calculations, the above assumptions resulted in 28.0% overall RES share in 2030.

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GREEN scenario GREEN is based on an ambitious policy towards the promotion of RES reaching 31% share of RES in 2030. This share is based on the Enerdata study (reviewed in section 1) in view of the fulfilment of the national GHG obligations [4].

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The following assumptions were adopted for this scenario:

313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330

a) RES-E development follows the ambitious RES-E penetration scenario (31% RES-E in 2030) of the Electricity System Operator [5]. The policy instruments considered to reach this share, in addition to the ones in RED, are high quotas for grid-connected installations, backed by attractive FIT, and largely available stimuli for private off-grid RES-E. b) RES-H&C is assumed to reach 45.5% in 2030. This substantial increase is justified by the rapid historical growth (3.9% on average during the period 2010-2015) and the introduction of largely available incentives RES-H&C investments with longer payback period and obligations for use RES H&C in almost all public buildings. c) RES-T is assumed to grow until 2020, according to the NREAP [1] and similarly to the other scenarios reaches 10.8% share in 2020. However, due to the active support policy, the RES-T share will continue to increase until 2030. In order to reach 31% total share of renewables in 2030, the RES-T share in 2030 need to be 14.2%. This target can be considered ambitious enough in view of the high biofuel and electric transportation costs. The considered policy instruments are introduction of relatively ambitious transport fuel blending obligations, in combination with incentives for the use of electric vehicles. In addition to the above policies, it is assumed that substantial soft measures (information, advice, training, etc.) are implemented.

331

Table 7 presents the three scenarios and exhibits their differences.

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Table 7: Presentation of the three scenarios according to their characteristics. Characteristics

Scenarios RED

BLUE

GREEN

Assumed shares for RES in 2030 -

Overall RES share in final energy consumption

22.8%

28.0%

31.0%

-

RES-E share in electricity consumption

20.0%

28.4%

31.0%

-

RES- H&C share in H&C consumption

30.2%

37.8%

45.4%

-

RES-T share in electricity consumption

10.8%

12.5%

14.2%

Policy packages -

Obligatory RES-E purchase

X

X

X

-

PPAs for RES-E

X

X

X

-

FIT combined with Quotas for RES-E

no new quota

quotas ensuring 28.4% RES-E in 2030, backed by adequate FIT

quotas ensuring 31.0% RES-E in 2030, backed by adequate FIT

-

Priority access to grid for RES-E

X

X

X

-

Transport fuel blending obligations (RES-T)

Obligations ensuring 10.8% RES-T

Obligations ensuring 12.5% RES-T

Obligations ensuring 14.2% RES-T

-

GIS

X

X

X

-

Obligations for public buildings to use RES H&C, supported by relevant grants

-

Stimuli for private RES H&C and off-grid RES-E (tax incentives, grants, soft loans, guarantees)

-

Emission Trading Scheme

-

Soft measures (information, advice, training, labelling)

coverage of 50% coverage of 70% of buildings of buildings limited to the existing and planned ones

coverage of 90% of buildings

additional stimuli substantial for the most cost- additional stimuli effective technologies

X

X

X

limited

moderate coverage

large scale coverage

333 334 335 336 337

3.3 LEAP outcomes The total final energy consumption is equal in all scenarios, but the structure of the demand by energy carrier is different. These structures in RED, BLUE, and GREEN are shown respectively in Figures 3, 4, and 5.

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338 339

Fig.3: 2030 Structure of final energy consumption in RED scenario.

340 341

Fig.4: 2030 Structure of final energy consumption in BLUE scenario.

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Fig.5: 2030 Structure of final energy consumption in GREEN scenario. It can be observed that the final energy consumption structure is similar in the three scenarios and the main differences concern biomass and natural gas consumption. Although the

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electricity share is identical in all scenarios, the RES-E share is quite different, as specified in section 3.2. Similarly, the RES H&C share in the final consumption of heat (from central systems) is the highest in GREEN and the lowest in RED, in line with section 3.2 assumptions. The 2030 global warming potential in all scenarios is shown in table 8.

350 351

Table 8: 2030 one-hundred-year global warming potential by branch and scenario In Million metric tons CO2 eq. RED

BLUE

GREEN

Demand

14.03

12.98

11.93

Transformation

51.72

43.31

41.19

Total

65.74

56.29

53.12

352 353

As expected, in GREEN the global warming potential is the lowest, while in RED it is the highest one.

354

The total 2030 costs (excluding externalities) are presented in table 9.

355

Table 9: 2030 total costs

356

In Million Euro RED Demand equipment cost

BLUE

GREEN

203

197

191

Transformation

2 549

2 512

2 588

Resources (fuel)

4 270

4 219

4 166

Total

7 022

6 928

6 945

357 358 359 360 361

Resources have the highest share among all costs. In RED the costs are higher compared to the other scenarios, mainly due to the higher resources cost. The higher transformation costs in GREEN scenario are partly balanced by the lower resource and demand equipment costs. The costs in BLUE are the lowest and the table indicates that this can be attributed to the costeffective energy transformation mix.

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4

363 364

The procedure starts from step iii) as explained above. The scenarios are evaluated against the described criteria/sub-criteria.

365

Criterion 1: environmental performance

366 367 368

Direct contribution to GHG emission reductions: The scenario with the highest penetration of RES contributes more to GHG emissions reduction. The necessary data is available from the LEAP outcomes (Table 8). Grades are shown in Table 11 with all AMS outcomes.

369 370 371 372

Indirect environmental effects: the total amount of the total environmental effects is provided by LEAP outcomes (Table 10). Table 10: Emissions for CO, NOx, Non Methane Volatile Organic Compounds, SO2 (LEAP Outcomes in Mt) in year 2030 RED Effects BLUE GREEN 1.00 Carbon Monoxide 1.01 1.03 0.17 Non Methane Volatile Organic Compounds 0.16 0.16 0.23 Nitrogen Oxides 0.20 0.20 0.26 Sulfur Dioxide 0.18 0.17 1.66 Total 1.55 1.56

AMS Evaluation

373 374

Criterion 2: Political acceptability

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Cost efficiency: This criterion is based on the internalized total costs of the three scenarios, including primary energy carriers, transformation, and demand-side energy utilization technologies. These are LEAP outcomes (see Table 9).

378 379 380 381 382 383

For simplification purposes, grid costs are not considered. The scenarios are characterized by different electricity generation mix and this would result in different grid-related costs. An upper threshold for reasonable grid costs is estimated to be around 40% for the share of intermittent generation capacity in 2030. Beyond this share, costly additional preventive measures will have to be taken in order to guarantee power system stability [31]. In all scenarios, the intermittent generation (being part of RES-E) is notably below 40%.

384

Grades are shown in Table 11 with all AMS outcomes.

385 386 387 388

Dynamic cost efficiency: Utilization of scientific and technological expertise for developing energy solutions is low and the country relies largely on foreign import and know-how in terms of green technologies [32]. The government has failed to promote technological innovation through the provided stimulus to RES (RED scenario) [32].

389 390 391 392

Although solid biomass is used for heating mainly in primitive installations, there is almost no consumers’ demand for more advanced installations [33]. Large-scale hydro power remains the main RES in electricity generation, but according to experts, its technical and economic potential is already fully exploited [34].

393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425

Furthermore, the low dynamic cost efficiency of the current RES policy mix is justified from the following: i) The National Programme for Reforms 2007-2009 had a long list of priorities which included energy-saving technologies and not RES [35]. A few years later the National Strategy of Scientific Research to 2020 (adopted by Parliament in 2011) listed the development of green and eco –technologies among five priority areas for research development in Bulgaria [35]. ii) According to the Bulgarian ‘Energy Strategy until 2020’ [36] financial support for research will be sought ‘through facilitation of investors’ access to scientific development works, specialized credit lines and facilities from European funds and programs’. No further action was undertaken for this. iii) the country has the lowest R&D intensity in the EU and ranks the lowest in the EU on private R&D investment as a share of GDP [35, 37]. The same situation remains under the GREEN scenario, but due to increased financial support, there might be an improvement and innovative technologies will be supported. The BLUE scenario is characterized by less financial support compared to the GREEN one, but slightly more than in the RED. Grades based on the above information: RED – 5, BLUE – 6, GREEN – 7 Competitiveness: The country ranked for year 2012 in the 39th position regarding attractiveness in RES investments, for 2013 in the 35th position, for 2014 in the 36th position and in 2016 and 2015, it was not included in the list of the forty most attractive countries for RES investments [38, 39, 40, 41, 42, 43]. This situation shows that the currently implemented policy mixture of the RED scenario does not attract RES investments. The reasons are the following: i) Energy from RES is still considerably more expensive compared to energy produced from conventional sources [36]. Additionally, due to the low purchasing power of Bulgarian households (five times less than the EU-27 average) the local commercial (non-government or stimulus-related) market is very limited [32]. ii) Grid connection limits competitiveness. EWRC estimated in 2009 that connecting RES in the next 4-5 years period, would require EUR 100–120 million [43]. iii) Investors have not embarked on major projects due to the lack of experience in large investments [43]. On the other hand, there was strong development of the renewable heating sector mainly due to low-cost biomass options [45]. Additionally in 2012, Bulgaria had the world’s tenth highest growth rate of new wind energy power plants and only that year 712 MW of installed solar capacity was added to the national energy mix [47]. This growth was attributed largely to the

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ACCEPTED MANUSCRIPT 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475

adoption of the feed-in tariff for RES-E [47]. Furthermore, there is still potential to exploit RES, particularly biomass [47]. The situation is slightly better for the other two scenarios, since there are there is stimuli for private RES H&C and off-grid RES-E for encouraging and facilitating the potential RES investors (see Table 7). Grades based on the above information: RED – 5, BLUE – 6, GREEN – 6 Equity: Bulgarian households are concerned about the social burden of energy bills, especially under an ongoing financial crisis. They are unprepared for bills of more expensive electricity and only 17% of them indicate willingness to pay extra for clean energy, under a modest increase (of up to 10%) in their electricity bills [32]. Low-income Bulgarian households (i.e. well over half of them) support cheaper, albeit “dirtier”, energy such as wood for heating, which is the cheapest source of energy [32]. On the contrary one third of the Bulgarian businesses are willing to pay higher prices for RES-E [32]. Regarding consequences on employment in the RES sector, there are limited data provided by reports of Eurobserver. These demonstrate that the direct employment in the wind energy subsector was 900 in 2009 and 3000 in 2010, while direct jobs created in the PV subsector were 130 in 2009 and 350 in 2010 [34]. However, in 2010 employment in the Bulgarian energy production sector (through use of RES), as a percentage share of total employment in the country, was below 0.2 % and one of the lowest in the EU [46]. The situation is similar for all three scenarios since no relevant to these raised issues policy instruments were included. Grades based on the above information: RED – 5, BLUE – 5, GREEN – 5 Flexibility: Influencing mechanisms (soft loans, subsidies etc) for the promotion of RES are currently limited. Under the RED scenario, RES projects are financed predominantly by private investors and commercial banks, i.e.: i) The European Bank for Reconstruction and Development distributed loans of up to €2.5 million and granted up to 15% of the disbursed loan through the Bulgarian Energy Efficiency and Renewable Energy Credit Line (BEERECL) programme upon the completion of the project (January 2014) and on the basis of verification by an independent energy expert [47, 48]. ii) EU-funded Operational Programmes finance RESE and RES-H projects both in the public and private [47, 48, 49]. iii) The Bulgarian Energy Efficiency and Renewable Sources Fund provides soft loans and financial guarantees for a variety of RES-E and RES-H projects. Building owners are facilitated in using RES technologies in buildings through a system of tax incentives [49]. There are no other incentives for the RES heating sector [50]. The situation under the GREEN scenario is more flexible compared to the other two due to more financial incentives/support (stimuli, see table 7). On the other hand, because of stricter quota obligation, higher obligations for ensuring a specific share of RES-T, the scenario with the highest quota ie the GREEN scenario is the least flexible one considering these. Grades based on the above information: RED – 5, BLUE – 6, GREEN – 6, Stringency for non-compliance: RES-E and RES-H are driven mainly by incentives (e.g. feedin tariffs for RES-E, subsidies, soft loans, etc.) and market forces. In case that end suppliers do not off take the RES-E as they are obliged to do so, will face a penalty ranging from BGN 20,000 (appr. EUR 10,200) up to BGN 1,000,000 (appr. EUR 510,000) [51]. The penalty for non-compliance for RES-T fuel blending obligation is BGN 200,000 (appr. EUR 102,000) [51]. The situation is similar for all three scenarios. Grades based on the above information: RED – 5, BLUE – 5, GREEN – 5 Criterion 3: Feasibility of implementation

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ACCEPTED MANUSCRIPT 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496

Implementation network capacity: Under the RED scenario, the Bulgarian Implementation Network (IN) for the promotion of RES is rather limited. The policy in the area is developed by the Ministry of Energy (MEE), while the regulatory role is taken by the EWRC. The availability of information is characterized as negative [50, 52]. Technological infrastructure and particularly the national grid require upgrading as already aforementioned. Bulgaria is still far from achieving specific grid quality and management capacity for promoting RES [53]. Lack of transparency in decision making after public discussions and/or hearings is observed since statements, opinions or notes of suggestions do not seem to be taken into account [50]. Due to a more ambitious scenario such as the other two, the situation is expected to be improved assuming that due to the additional financial support the IN will be reinforced with skills and entities. Otherwise, the current IN can not secure the implementation of the policy packages either of BLUE or GREEN scenario. Grades based on the above information: RED – 5, BLUE – 7, GREEN – 7

497 498 499 500

The licensing procedure is differentiated by installed capacity (procedure lasts less than 9 months for rooftop PVs of several kW and the lead time of the licensing procedure for installed capacity over 5 MW is over 1 year) [54]. EWRC has most of the main responsibilities for the implementation of RES projects which creates administrative burden [55].

501 502 503 504

Insufficient support for RES is attributed to the administrative incapability to formulate and implement policies [53]. Administrative delays are frequently observed in the process of connecting RES to the grid [53]. Administrative deficiencies are linked with corruption regarding public procurement and permit issuing procedures [53].

505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520

This situation is expected to be improved under the other two scenarios since they are more ambitious compared to the RED one. Grades based on the above information: RED – 5, BLUE – 7, GREEN – 7.

Administrative feasibility: Under the RED scenario, administrative procedures are mentioned by stakeholders as complex and lengthy since investors need various certificates, permissions, and licenses issued by different authorities [52]. 5-15 is the average number of authorities involved directly or indirectly in the RES-E licensing/permitting procedure, while 9-24 months is the average lead time for the overall RES-E authorization procedure including grid connection [54].

Financial feasibility: Several EU-funded operational programs and other financial sources are available, as mentioned above. Due to the more ambitious RES targets in GREEN and BLUE, additional financial support is expected to back-up these targets. Since the financial resources are not secured by the described policy packages (through revenues from other types of policy instruments (ie taxes, fees, levies or penalties) these two scenarios have a weaker performance against this sub-criterion compared to RED. Grades based on the above information: RED – 5, BLUE – 4, GREEN – 3. AMS results The AMS results, calculated according to the methodology of Konidari and Mavrakis [26, 27], are presented below. Table 11 AMS results for each scenario Criteria Direct contribution to GHG emission reductions (0.833) Indirect environmental effects (0.167)

RED 0.000 0.000

Scenarios BLUE 62.38 16.70

GREEN 83.300 15.18

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ACCEPTED MANUSCRIPT Environmental performance (0.168) – A Cost efficiency (0.474) Dynamic cost efficiency (0.183) Competitiveness (0.085) Equity (0.175) Flexibility (0.051) Stringency for non-compliance (0.032)

0.000 0.000 3.583 2.039 5.833 1.212 1.133

13.285 47.300 5.675 3.230 5.833 1.919 1.133

16.545 38.746 8.992 3.230 5.833 1.919 1.133

Political acceptability (0.738) – B

10.184

48.038

44.172

5.133 9.651 5.424

12.884 24.224 3.397

12.884 24.224 2.179

Feasibility of implementation (0.094) – C

1.900

3.807

3.693

Total (A+B+C)

12.084

65.015

64.525

Implementation network capacity (0.309) Administrative feasibility (0.581) Financial feasibility (0.110)

521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557

Sensitivity analysis The robustness of the results is tested with sensitivity analysis through two cases [26, 27]. In the first case, one of the three weight coefficients of the criteria increases by a certain percentage, a second one decreases by the same percentage and the third is adjusted properly to these changes. In the second case, one of the three weight coefficients – again for the criteria – remains stable, another one increases gradually and the third is adjusted again due to these changes. In both cases the increase continues until there is a change in the order of the ranking. Also, the changes occur as long as each weight coefficient is less than 1 and more than 0. Therefore, for the first case, the ranking remains the same for: i) an increase by 8.0% to the first weight coefficient (for environmental performance) and the same decrease to the second one (for political acceptability) (values for weight coefficients: 0.181 (environmental performance) – 0.678 (political acceptability) – 0.140 (feasibility of implementation)); ii) an increase by 13% to the second weight coefficient and the same decrease for the first weight coefficient (the values: 0.165 – 0.833 – 0.001); iii) an increase of the first weight coefficient by 13% and an equal decrease for the third one (the values: 0.190 – 0.728 – 0.082); iv) 26% increase of the second one and same decrease for the third one (the values: 0.001 – 0.930 – 0.070); v) 95% increase of the third weight coefficient and the same decrease in percentage (23%) for the first (the values: 0.008 – 0.808 – 0.183); vi) 2.8% increase for the value of the third weight coefficient over the same decrease for the second one (values: 0.191 – 0.711 – 0.097). For the second case, the ranking remains the same for: i) 12% increase for the first weight coefficient with the third one stable (the values: 0.190 – 0.718 – 0.094); ii) 16% increase for the first weight coefficient and stable value for the second one (the values: 0.195 – 0.738 – 0.067); iii) 12% increase for the second weight coefficient and stable value for the first one (the values: 0.168 – 0.827 – 0.005); iv) 81% increase for the third weight coefficient and stable value for the first one (the values: 0.168 – 0.662 – 0.170); v) 22% increase for the second weight coefficient, stable value for the third one (the values: 0.006 – 0.900 – 0.094); vi) 175% increase for the third one, stable value for the second one (the values: 0.004 – 0.738 – 0.259).

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The second criterion is more sensitive due to the higher value of its weight coefficient, but the ranking is robust for the majority of the changes and for rather high increases. Additionally, there are three policy mixtures/packages compared which makes it more sensitive for this criterion compared to the case of a larger number of evaluated cases, while a higher percentage was not acceptable due to the limitation of the acceptable range of values (lower limit-0, upper limit-1) [27].

564 565 566 567 568 569 570 571 572 573 574 575

5

576 577 578 579 580 581

Considering that the 2020 national RES target is only 16%, BLUE’s 27.6% (increased by 72.5%) overall RES share for 2030 is very likely to exceed a possible national RES target (either binding or indicative) set at EU level in line with the EU policy and under the Paris agreement [2, 56]. Compared to RED, the BLUE scenario is expected to have a more effective implementation network, including more transparent and accessible information and more investments.

582 583 584 585 586 587

Furthermore, BLUE’s share of RES is below the 31% share identified by Enerdata study (Enerdata, 2014) as the most appropriate to achieve as the set 2030 GHG reduction target (40%). In the context of GHG reduction target, it would be valuable to expand the research made in this paper, by covering a much wider range of policies affecting the amount of GHG emissions and understanding the contribution of RES in the reduction of Bulgarian GHG emissions.

588 589 590 591 592 593

The outcomes indicate that if the financial issues related to target groups and IN are faced properly, Bulgaria will be able to accept a more ambitious target compared to the current situation. The combined outcomes of LEAP and AMS may indicate another scenario - if applied again as being the most appropriate one due to following shortcomings that this study encountered and which need to be considered in future research:

594 595 596 597 598 599 600 601 602 603 604 605 606 607

Discussion and conclusions

The work under this paper identified as the most feasible level of ambition up to year 2030 for the Bulgarian renewable energy policy, after taking into consideration the national framework, the BLUE scenario. Out of the three the BLUE scenario (with moderate ambition) has the best overall performance compared to the other two after the application of the AMS method and the use of LEAP outcomes in combination with available information. It is worth mentioning that although the GREEN scenario (high level of ambition) scored in most of the sub-criteria the same with the BLUE scenario, it was not the most appropriate solution in total for the Bulgarian framework. This outcome can mainly be attributed to the cost-efficiency and financial feasibility of BLUE, when compared to the other two policy mixtures. The BLUE scenario involves cost-efficient fuel switch to RES, while it avoids the costliest RES technologies of GREEN.



There is no official statistical data at national level about the costs of energy demand and transformation technologies capacity.  A recent GDP forecast, including GDP distribution per sector, is needed by 2030.  There are no electricity capacity plans beyond 2020 and no information is available about the expected time of phasing-out of the existing electricity capacities after 2020.  There are no studies estimating the marginal RES utilization costs in the country.  There are no assessments of what may be the Government’s and society’s financial costs and revenues of implementing the current renewable energy policy. Additionally, there are no such estimations about the planned (by 2020) policy. However, based on the currently available data and information, BLUE is a realistic and feasible scenario (realistic due to the moderate level of ambition and feasible de to the human potential). The Paris Agreement requires joint efforts between the countries, but it is bottomup structured when compared to the Kyoto Protocol. This element offers countries the

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flexibility to set by themselves the targets that they can accomplish. Bulgaria can explore its options and conclude to the targets that serve better its priorities and needs.

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References [1] Ministry of Economy, Energy, and Tourism (MEET). 2011a. Resubmitted National Renewable Energy Action Plan (NREAP) drawn up in accordance with the template for national renewable energy action plans as set out in Directive 2009/28/EC of the European Parliament and of the Council. [2] European Commission, 2014b. 2030 climate and energy goals for a competitive, secure and lowcarbon EU economy. Available at: http://europa.eu/rapid/press-release_IP-14-54_en.htm [3] VUT and EEG, 2014. 2030 RES targets for Europe – a brief pre-assessment of feasibility and impacts. Authors: Gustav Resch, Christian Panr, Andre Ortner. Compiled with the European Intelligent Energy Europe project KEEPONTRACK. At: http://www.keepontrack.eu/contents/publicationsscenarioreport/kot--2030-res-targets-for-europe.pdf [4] Enerdata, 2014. Costs and benefits to EU Member States of 2030 Climate and Energy targets. At: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/285505/costs_benefits_e u_states_2030_climate_and_energy_targets_enerdata_report.pdf [5] Energy and Water Regulatory Commission (EWRC). 2012a. Decision № Ц-018 from 28.06.2012. Available at: http://www.dker.bg/files/ download /res-c018-12.pdf [6] Black Sea Energy Research Centre (BSERC). 2014. Energy balance forecast of Bulgaria by 2030 – annually, and by 2050 – every 5 years. Contract 103/13.02.2014 of the Ministry of Economy and Energy. [7] Bottero Marta, 2013. Sustainability assessment of large dams: the case of a hydropower plant in Bulgaria Management of Environmental Quality: An International Journal, Vol. 24 No. 2, pp. 178-198 [8] Zahariev A., Penkov D. & Aladjadjiyan A., 2014. Biogas from Animal Manure – Perspectives and barriers in Bulgaria. Biology 4(5), pp. 709-719. [9] Jenner Steffen, Groba Felix, Indvik Joe, 2013. Assessing the strength and effectiveness of renewable electricity feed-in tariffs in European Union countries. Energy Policy 52, pp. 385-401. [10] Haas Reinhard, Panzer Christian, Resch Gustav, Ragwitz Mario, 2011. A historical review of promotion strategies for electricity from renewable energy sources in EU countries. Renewable and Sustainable Energy Reviews 15, pp. 1003-1034 [11] Kitzing Lena, Mitchell Catherine, Morthorst Poul Erik, 2012. “Renewable energy policies in Europe: Converging or diverging?”. Energy Policy 51, pp. 192-201. [12] Del Rio Pablo, Mir-Artigues Pere, 2014. “Combinations of support instruments for renewable electricity in Europe: A review”. Renewable and Sustainable Energy Reviews 40, pp. 287-295. [13] Patlitzianas Konstantinos, Karagounis Konstantinos, 2011. “The progress of RES environment in the most recent members states of the EU”. Renewable Energy 3: 429-436 [14] Poncet S. 2006. The Long Term Growth Prospects of the World Economy: Horizon 2050. CEPII, Working Paper No 2006-16. Available at: http://www.cepii.fr/anglaisgraph/workpap/pdf/2006/wp0616.pdf [15] National Statistical Institute (NSI). 2017a. Overall energy balance sheet 2011, 2012, 2013, 2014, 2015. http://www.nsi.bg/sites/default/files/files/data/timeseries/Energy4.1_en.xls [16] National Statistical Institute (NSI). 20142017b. Energy Balance 2015s 2012. http://www.nsi.bg/sites/default/files/files/publications/EB_Publ_15.xlshttp://www.nsi.bg/sites/default/fi les/files/data/timeseries/Energy4.1.xls [17] Ministry of Energy. 2015. Third National Report on Bulgaria’s Progress in the Promotion and Use of Energy from Renewable Sources. Available at: https://ec.europa.eu/energy/en/topics/renewableenergy/progress-reports [18] Energy from Renewable Sources Act, SG 35/3.05.2011, last amendment SG 10065/618.0812.20142015 [19] Ministry of Economy, Energy, and Tourism (MEET). 2009. Forecast document [20] Black Sea Regional Energy Centre (BSREC), 2012. Assessment of the wind and solar energy potentials in Bulgaria and policy recommendations for their promotion. FP7 project: ENVIROGRIDS [21] Energy Act, State Gazette (SG) 107/9 December 2007, last amendment SG105/30.12.2016. http://lex.bg/laws/ldoc/2135475623 [22] Environment Protection Act, SG 91/25.09.2002, last amendment SG 12/03.02.2017 http://lex.bg/laws/ldoc/2135458102

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[23] Heaps, C.G., 20122016. Long-range Energy Alternatives Planning (LEAP) system. [Software version 20122017.0.5049] Stockholm Environment Institute. Somerville, MA, USA. www.energycommunity.org [25] Stockholm Environment Institute. 2017. LEAP website https://www.energycommunity.org/ (accessed 28.02.2017) [26] Konidari P., D. Mavrakis,. 2007. A multi-criteria evaluation method for climate change mitigation policy instruments, Energy Policy 35, pages 6235-6257. [27] Konidari, P. and D. Mavrakis, D. 2006. Multi-criteria evaluation of climate policy interactions. Journal of Multi-Criteria Decision Analysis 14:35–53. [28] National Technical University of Athens (NTUA). 2016. EU28: Reference scenario (REF2016): Summary report. Primes Ver. 4 Energy Model. E3M Lab. 20-07-2016. [29] Schlömer S., T. Bruckner, L. Fulton, E. Hertwich, A. McKinnon, D. Perczyk, J. Roy, R. Schaeffer, R. Sims, P. Smith, and R. Wiser, 2014. Annex III: Technology-specific cost and performance parameters. In: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [30] US EIA. 20132016. Updated Capital Cost Estimates for Utility Scale Electricity Generating Plants. Available at: https://www.eia.gov/analysis/studies/powerplants/capitalcost/pdf/capcost_assumption.pdf http://www.eia.gov/forecasts/capitalcost/pdf/updated_capcost.pdf [31] Lise Wietze, et al., 2014, Assessment of the required share for a stable EU electricity supply until 2050. Energy Policy 59(2013)904–913. [32] Mantcheva Denitza, Karaboev Stefan, Stefanov Ruslan, 2012. Green growth and sustainable development for Bulgaria: Setting the priorities. Friedrich Ebert Foundation- Office Bulgaria -Analyses, February 2012. Available at: http://library.fes.de/pdf-files/bueros/sofia/09016.pdf [33] Agency for Economic Analyses and Prognoses (AEAP). Vasilev D., Hadzhijski C. 2008. Long term effect of aging on the public finance in Bulgaria 2010-2050). Available at: http://library.birsbg.org/download.html?id=174 [34] Kirov Vassil, 2012. Public funding for green energy in a context of crisis – Country report (Bulgaria). Iss-BAS (Institute for the study of Societies and Knowledge). At: http://www.etui.org/content/download/11365/96105/file/6_Country+report+Bulgaria.pdf [35] European Commission, 2014a. Research and Innovation performance in EU Member States and Associated countries. Innovation Union progress at country level. Available at: http://ec.europa.eu/research/innovation-union/pdf/state-of-theunion/2014/iuc_progress_report_2014.pdf [36] Ministry of Economy, Energy, and Tourism (MEET). 2011b. Energy Strategy of the Republic of Bulgaria till 2020. State Gazette 43 from 7th June 2011. [37] European Commission, 2013. Research and Innovation performance in EU Member States and Associated countries. Innovation Union progress at country level. Available at: https://ec.europa.eu/research/innovation-union/pdf/state-of-theunion/2012/innovation_union_progress_at_country_level_2013.pdf [38] Ernst & Young, 2015. RECAI – Renewable Energy Country Attractiveness Index 48, October 2016. At: http://www.ey.com/Publication/vwLUAssets/EY-RECAI-48-October-2016/$FILE/EY-RECAI-48October-2016.pdf [39] Ernst & Young, 2015. RECAI – Renewable Energy Country Attractiveness Index, Issue 45, September 2015. At: http://www.ey.com/Publication/vwLUAssets/RECAI-45-September-15LR/$FILE/RECAI_45_Sept_15_LR.pdf [40] Ernst & Young, 2014. Renewable Energy Country Attractiveness Index (RECAI) – Issue 40, February 2014. Available at: http://www.ey.com/Publication/vwLUAssets/RECAI_40__February_2014/$FILE/EY_RECAI%2040_Feb%202014.pdf [41] Ernst and Young, 2013a. Renewable energy country attractiveness index. Issue 36. http://www.ey.com/Publication/vwLUAssets/Renewable_energy_country_attractiveness_indices_Febr uary_2013/$FILE/Renewable_energy_country_attractiveness_indices.pdf, Accessed on Dec. 12, 2013. [42] Ernst and Young, 2013b. Renewable energy country attractiveness index. Issue 38. http://www.ey.com/Publication/vwLUAssets/Renewable_energy_country_attractiveness_indices__Issue_38/$FILE/RECAI%20Issue%2038_August%202013.pdf, Accessed on Dec. 12, 2013.

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[43] Sarasa-Maestro J. Carlos, Dufo-Lopez Rodolfo, Bernal-Agustın L. Jose, 2013. Photovoltaic remuneration policies in the European Union. Energy Policy55, pp. 317-328 [44] Ordinance for issuing of certificates of origin for the electricity generated from RES, State Gazette (SG) G 10 / 6.02.2009, amended SG 85 / 29.10.2010. http://lex.bg/en/laws/ldoc/2135617067 [45] European Commission, 2015. Report from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions. Renewable Energy Report. Brussels, 15.6.2015, COM(2015) 293 final. At: https://ec.europa.eu/transparency/regdoc/rep/1/2015/EN/1-2015-293-EN-F1-1.PDF [46] Kujumdzieva Anna, Nedeva Trayana, Pankov Roumen, 2014. Green jobs in Bulgaria – National Analysis Report. Lifelong Learning Programme Leonardo da Vinci Transfer of Innovation Project Structuring of work related competences in chemical engineering, STRENGTH 2013-1-ES1-LEO0566726. At: http://www.greenstrength.eu/images/documents/public/report/strength_national_report_bg.pdf [47] UNDP, 2014. Renewable Energy Snapshot: Bulgaria. At: https://www.scribd.com/doc/224004846/Renewable-Energy-Snapshot-Bulgaria [48] KPMG, 2013. Investment in Bulgaria. At: https://www.kpmg.com/BG/en/IssuesAndInsights/ArticlesPublications/Brochures/Documents/2013Investment-in-Bulgaria-web.pdf [49] RES Legal, 2012. Renewable Energy policy database and support- RES Legal Europe. National profile: Bulgaria. At: http://www.res-legal.eu/no_cache/archive/?cid=264&did=375&sechash=304fa2cd [50] Ernst and Young, 2013a. Renewable energy country attractiveness index. Issue 36. http://www.ey.com/Publication/vwLUAssets/Renewable_energy_country_attractiveness_indices_Febr uary_2013/$FILE/Renewable_energy_country_attractiveness_indices.pdf, Accessed on Dec. 12, 2013. [51] Ministry of Economy and Energy. 2013. Second National Report on Bulgaria’s Progress in the Promotion and Use of Energy from Renewable Sources. Available at: http://ec.europa.eu/energy/renewables/reports/2013_en.htm [52] ECORYS, 2010. Assessment of non-cost barriers to renewable energy growth in EU Member States – AEON DG TREN No. TREN/D1/48 – 2008, http://ec.europa.eu/energy/en/topics/renewableenergy [53] Center for the Study of Democracy, 2011. “Green Energy Governance in Bulgaria,2011. AT А CROSSROADS”. Authors: Ruslan Stefanov, Denitza Mantcheva, Nikolay Tagarov, Dr. Dobromir Hristov, Valentina Nikolova, ISBN: 987-954-477-174-4, available at: http://www.mee.government.bg/doc_vop/Energy_Concept_ENG.pdf [54] Regional Centre for Energy Policy Research (REKK), 2013. Renewable Electricity Market Monitoring in the countries of the Danube region. At: http://www.danubeenergy.eu/uploads/files/publications/Renewable%20Electricity%20Market%20Monitoring%20in%20th e%20Countries%20of%20the%20DR.pdf [55] Ganev Peter, 2009. Bulgarian electricity market restructuring. Utilities Policy, 2009, vol. 17, issue 1, pages 65-75 [56] UNFCCC, 2015. The Paris Agreement https://unfccc.int/documentation/documents/advanced_search/items/6911.php?priref=600008831 [57] Energy and Water Regulatory Commission (EWRC). 2015. 2015 Decisions. Available at: http://www.dker.bg/docsbg.php?d=3&subD=114 [58] Energy and Water Regulatory Commission (EWRC). 2012b. Decision № EM1 from 29.06.2012. EM1/29.06.2012, EM2/28.06.2013, EM3/01.07.2014 Available at: http://www.dker.bg/files/download/res_moshtnosti_ZEVI.pdf

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