Energy systems modelling to support key strategic decisions in energy and climate change at regional scale

Renewable and Sustainable Energy Reviews 42 (2015) 394–414

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Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser

Energy systems modelling to support key strategic decisions in energy and climate change at regional scale Senatro Di Leo n, Filomena Pietrapertosa, Simona Loperte, Monica Salvia, Carmelina Cosmi National Research Council of Italy, Institute of Methodologies for Environmental Analysis—(CNR–IMAA), C.da S.Loja, 85050 Tito Scalo, PZ, Italy

art ic l e i nf o

a b s t r a c t

Article history: Received 3 April 2014 Received in revised form 29 September 2014 Accepted 12 October 2014

The evidence of relationships between climate change induced by greenhouse gases of anthropogenic origin, and energy-economic issues (inappropriate use of fossil fuels and technologies, uncertainty in fuels price and demand trends, etc.) asks for the adoption of a holistic approach in order to re-orient the anthropogenic activities’ system towards a configuration that harmonizes environmental protection, economic growth and security of energy supply. In this framework, energy system sustainability represents one of the major challenge the EU is facing and its implementation passes through a path of coordinate actions carried out by local governments in which objectives of sustainable development become integral part of strategic programming. The aim of this research is to provide local administrations with an analytical support tool to guide key strategic decisions in energy and climate planning on the medium-long term, assessing the possible role of local energy systems in the achievement of sustainable objectives at national/European scale. This paper focuses on the implementation of a partial equilibrium TIMES-generated model in a real case study, the regional energy system of Basilicata region (Southern Italy). First, it describes the adopted methodology. Second, it is provided a step-by-step description and characterisation of the reference energy system and the model’s data input which represents the first step for an in-depth knowledge of the present energy system on which to build effective and sustainable local energy and climate plans. & 2014 Elsevier Ltd. All rights reserved.

Keywords: Energy system analysis Regional energy planning Climate planning TIMES models generator Basilicata region

Contents 1. 2.

3.

n

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.1. The models generator and the user interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2. The reference energy system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2.1. Residential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2.2. Commercial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2.3. Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2.4. Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2.5. Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2.6. Electricity and heat production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2.7. Supply sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.3. The data files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 The Basilicata region energy system. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.1. Energy supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.1.1. Fossil fuels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.1.2. Renewable energy sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.1.3. Electricity and heat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3.2. Energy demand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.2.1. Residential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Corresponding author. Tel.: þ 39 971 427207; fax: þ 39 971 427271. E-mail address: [email protected] (S. Di Leo).

http://dx.doi.org/10.1016/j.rser.2014.10.031 1364-0321/& 2014 Elsevier Ltd. All rights reserved.

S. Di Leo et al. / Renewable and Sustainable Energy Reviews 42 (2015) 394–414

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3.2.2. Commercial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.2.3. Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.2.4. Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.3. Demand projection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 3.4. Air emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 4. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

1. Introduction

An integrated approach to climate and energy policy was adopted by the European Council in order to transforming Europe into a highly energy-efficient and low greenhouse-gas-emitting economy. With this in mind, the Energy Policy for Europe, adopted by the European Council on 9 March 2007, aims to increase the security of supply, to ensure the competitiveness of European economies as well as promote environmental sustainability and combat climate change. The ‘climate and energy package’ was agreed by the European Parliament and Council in December 2008 and became law in June 2009, creating pressure to improve energy efficiency which has been done through the EU’s energy efficiency action plan. In 2010, the European Commission revisited the implications of the different levels of ambitions (20% and 30% targets) of greenhouse gas emission reductions [1] and adopted the Communication “Energy 2020—A strategy for competitive, sustainable and secure energy” [2] which defines the energy priorities for the next 10 years and sets the actions to be taken in order to tackle the challenges of saving energy, achieving a market with competitive prizes and secure supplies, boosting technological leadership, and effectively negotiating with international partners. A key issue for achieving the EU and global climate change objectives but also to contribute to its innovation, jobs and growth agenda, is to accelerate the development and deployment of costeffective low carbon technologies. This is the main aim of the EC Strategic Energy Technology Plan (SET-Plan) [3] that, in the short term (2020), foresees the use in Member States of the low-carbon technologies available today or in the final stages of development, lowering their costs and improving performance as well as promoting pro-active support measures, with a 2050 vision towards complete decarbonisation (reducing 60–80% of GHGs) and the development of next-generation technologies. Implementing mitigation actions can have positive effects also in terms of air pollution control as it is widely demonstrated by numerous scientific studies [4–6]: For example, Jiang et al. [5] analysed how effective are energy-related policy measures, in particular, energy saving, in the simultaneous abatement of GHGs emissions and air pollution in their study on two Chinese big cities. The European Commission’s impact assessment for the Climate and Energy Package [7] indicated that reducing GHG emissions by 20% in 2020 reduces sulphur dioxide, nitrogen oxides and PM2.5 emissions by 10 to 14% compared to baseline emissions in the same year, contributing also to the objectives of the Protocol to abate Acidification, Eutrophication and Ground level Ozone (signed on November 30, 1999 in Gothenburg), as well as to the 2001/81 EC Directive (adopted on November 27, 2001) that introduced Emission Ceilings. In particular co-benefits of mitigation policies through energy efficiency in both the residential and commercial sectors can consistently improve local and regional air quality, particularly in large cities, contributing to improve public health (e.g. increased life expectancy, reduced emergency room visits, reduced asthma

attacks, fewer lost working days) and avoiding structural damage to private and public buildings [8]. A decisive step for translating the EU’s political directions into concrete actions is to work in the direction of promoting sustainable energy systems at local scale, focusing on the synergies between regional development and sustainable energy actions. In the latest years many developments have been carried out in EU policy as well as in the area of technical support for sustainable energy at the local and regional level. At the same time energy agencies and local authorities are collaborating more and more to increase their reactive capability of using European funding. Among the several initiatives carried out to help local authorities moving towards a more sustainable pattern of development, the Covenant of Mayors [9] has had an important role also in terms of urban climate planning. As a matter of fact signatory cities have to develop Sustainable Energy Action Plans (SEAP) to show how they intend to reach a 20% CO2 reduction by 2020 through a set of activities and measures, together with time frames and assigned responsibilities. Moreover the SET-Plan Smart Cities Initiative [10], launched in 2011, has the objective to create the conditions to trigger the mass market take-up of energy efficiency technologies in order to secure CO2 reductions. The focus is on cities that have committed themselves to create a more sustainable future, for instance adhering to the Covenant of Mayors, and that are willing to transform their buildings, energy networks and transport systems into those of the future, demonstrating transition concepts and strategies for a low carbon economy as well as the feasibility of going beyond the current EU energy and climate objectives—i.e. towards a 40% reduction of greenhouse gas emissions by 2020. In this framework Information and Communication Technologies (ICT) play a key role to foster energy efficiency at local and regional level. In Italy competence in the energy field is divided between Regions and State as result of the Reform of 5th Title of Italian Constitution. At regional level the Regional EnergyEnvironmental Plans (REEP) is the main tool aimed to support strategies and interventions in the energy field through the harmonization of all the relevant decisions concerning the local and regional scale. The REEP must contain measures on both energy supply and demand, evaluating different alternatives based on both conventional and non conventional energy sources, taking into account aspects related to territorial availability, cost-effectiveness, potentialities to boost local economy. At the same time also demand management is very important because the Region interventions are wide and rationalization of energy uses can provide consistent advantages at local level. All Italian Regions have finally approved their REEP, a tool provided more than 15 years ago. Although the Regions are key territorial areas for the achievement of the national targets, it would be necessary to balance distribution of the objectives by Region, setting emission reduction targets and renewable energy objectives in agreement with national commitments.

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Italy’s Budget Law 2008 (DL no. 208/2008) introduced the concept of “burden sharing” among regions, that is the decision to split among regions the duties to achieve the EU target set for Italy for a 17% share of renewable energy by 2020. Only in 2012 this Law was acknowledged by a ministerial decree [11] which set, in the particular case of Basilicata Region, an increase of the total share of thermal and electric energy produced by renewable energy sources in order to reach 33.1% of the gross final consumption within 2020. Besides, the Italian economic and financial programming document (DPEF) 2008–2011 introduced a CO2 emissions sharing mechanism among Regions. These provisions, aimed to give more responsibility to regions, were enforced by Law 13/2009, which established a burden-sharing criterion based on the European 2020 target [12]. In this case a ministerial decree has not been issued yet. Moreover, it should be pointed out a boost in energy and climate planning due to the Covenant of Mayors initiative: as of 20th March 2014, 2655 Italian towns and cities have signed up to the Covenant of Mayors [9]. Moving toward a low-carbon development path and smarter cities passes through a careful medium long-term analysis of local energy systems, assessing the related trends of greenhouse gas emissions and air pollution. In this framework, the implementation of sustainable energyenvironmental planning methods can contribute fundamentally to foster the diffusion of best practices at regional scale, testing their effectiveness in real test cases around Europe. Moreover, consensus building should be fostered among stakeholders in the promotion of effective sector-tailored mitigation options (e.g. renewable energy or energy efficiency) which should consider also the co-benefits in terms of air pollution reduction. On the other hand, the strong correlation between energy consumption and climate change variables [13,14] makes necessary the utilisation of energy-environmental models to support the definition of energy and climate strategies. This paper focuses on the implementation of a decision support tool for regional energy planning as well as to define comprehensive climate change mitigation strategies on the medium-term horizon. Section 2 focuses on the generally applicable methodology showing how it applies in a local case study (Basilicata region, Southern Italy). Section 3 describes in detail the data input of the energy model and how detailed data are derived from available statistics in order to provide a comprehensive overview of the present energy system which is the first step towards the definition of sustainable pathways.

2. Methods The overall aim of this paper is to perform an analytic decision support tool for strategic planning in terms of energy, climate and environment, useful in assisting planners and local decision makers [15,16]. In particular, the energy system of Basilicata Region was modelled and analysed adopting the TIMES models generator platform [17] which allows to represent in detail the entire energy system, from primary sources to end-use technologies, and investigate possible development scenarios for the medium-long term (30–50 years) taking into account the evolution of some key variables (energy, environmental, economic) in order to identify sustainable strategies and policies. 2.1. The models generator and the user interfaces The TIMES (acronym of The Integrated MARKAL/EFOM System) is an energy, economic, environmental planning tool largely

utilized by numerous scientific communities worldwide to derive and study optimal energy-environmental scenarios at level of single Communities/Province/Region/State or in a multi-regions approach, analyzing in depth solutions for energy security, climate change mitigation and air pollution reduction on a medium-long time horizon. The TIMES has been developed in the recent years by ETSAP researchers [18] as the evolution of the MARKAL family of models [17] and the EFOM [19] from which it takes a full representation of the network of technologies, characterised by energy-economic and environmental parameters, and from the latter a detailed representation of energy flows among technologies [20]. At the same time, TIMES model holds specific features, that award it more flexibility respect to its forerunners. These new features include, for example, variable length periods, vintaged technologies, flexible inputs and flexible outputs for technologies, climate module, and endogenous energy trade between regions [20]. These peculiarities make the TIMES model a widely used tool for the optimization of complex energy systems and the analysis of possible future energy systems for which robust strategies can be derived in line with sustainable development goals. The data input of the TIMES model consists of a detailed representation of existing and future technologies in terms of technical-economic and environmental parameters and technology turnover (vintaging and technology learning). The best possible optimal configuration of the analyzed energy system is obtained minimizing the total discounted system’s cost under a set of exogenous constraints relatively to demands trend prevision, resources and technologies availability, caps on air pollutant emissions and policy vision, so that different development perspectives can be evaluated through scenarios building. The optimization is made on a medium-long term time horizon (usually from 20 to 50 years) divided into time periods of fixed or variable length. Scenario analysis allows comparison among different evolutions of energy system under a set of user constrains to evaluate impacts of different policies and price mechanisms by trade-off curves. TIMES is a tool for expert users, although it is fitted out with front-end (FE) and back-end (BE) user interfaces (VEDA-FE and VEDA-BE) that makes easier both handling data input and browsing the final results. The data input of the model is organized in a standard structure (templates) based on Excel spreadsheets, containing all the specific data that characterize technologies and energy/commodity flows. The VEDA-FE imports these data from the templates (one template for each economic sector included in the study, e.g. Residential, Commercial, Industry) and manages the energy system optimization based on a linear programming solver (General Algebraic Modeling System—GAMS [21]). The results of TIMES model are then imported into the VEDABE that organizes them in standard or user made tables, facilitating the analysis and comparison of the model’s results. This paper focuses on the TIMES-Basilicata which has been implemented taking benefit of the multi-region platform provided by the MONET Italy model [22]. Thanks to this modelling approach it will be possible to support the regional authority to formalize strategies in a manner consistent with a widely recognized and accepted methodology as well as to introduce in the future possible links and trades with other regional energy systems. In particular, starting from the MONET 20-region TIMES energy model, the Basilicata basic structure was further improved and detailed based on officially available data (such as those reported in the Regional Policy Plan for Energy and Environment—PIEAR [23], official statistics, and sectoral data sources). Moreover sector-specific studies were carried out in order to obtain a high level of disaggregation of final energy uses. The analysed time horizon goes from 2007 to 2030, covering a 28 years period (subdivided in 12 periods of two years each).

S. Di Leo et al. / Renewable and Sustainable Energy Reviews 42 (2015) 394–414

As described in detail in the following sections, a full representation and characterization of the whole regional energy system from an economy, technical and environmental point of view was provided for the Energy supply (primary energy extraction/import/export), Electricity and heat power generation as well as for all the end-use demand sectors (Residential, Commercial, Transport, Industry and Agriculture). An overview of the analysed final demands as well the related code and units are reported in Fig. 1.

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Each end-use was characterised by a case specific network of technologies. In particular:

 Space heating, water heating and space cooling were modelled

 

distinguishing between single “S” end-use (e.g. furnaces) and multiple “M” end-uses (e.g. dual boilers and heat pumps) (Fig. 2). Freezers, refrigerators, washing machines and dishwashing were represented according to their different energy class. Lighting included incandescent, halogen and compact fluorescent devices.

2.2. The reference energy system The structure of a TIMES-based model is usually described through the Reference Energy System, which represents production, transformation and use of various energy forms and the related network of technologies. In particular, the Reference Energy System of the TIMESBasilicata model includes the following sectors: Residential (RES), Commercial (COM), Agriculture (AGR), Industry (IND), Transport (TRA), Electricity and Heat Production (ELC) and Energy Supply (SUP). In the following paragraphs the reference energy system of the TIMES-Basilicata model is fully described sector-by-sector.

2.2.1. Residential Residential was modelled taking into account 13 end-use demands: space heating, water heating, space cooling, cooking, lighting, refrigerators, freezers, washing machines, tumble dryers, dishwashers, entertainment devices, services for the home, general services for buildings.

2.2.2. Commercial The representation of the Commercial sector was split in 14 end-uses: hotel space heating, hotel water heating, hospital space heating, hospital water heating, unmarketable other tertiary space heating, commercial centres space heating, other tertiary space heating, other tertiary water heating, other tertiary cooking, office equipments, air conditioning, refrigerators, lighting, other devices. For example, Fig. 3 represents the reference energy system of hotel space heating and water heating.

2.2.3. Agriculture Agriculture is modelled as a single generic technology (AGRI) with some fuels in input (AGAS—natural gas, AELC—electricity, AGPL—liquefied petroleum gas and AGSL—diesel) and an aggregated useful energy demand (DEMAGR) as an output (Fig. 4). In this case the useful energy demand is expressed in monetary terms (MEuro) representing the added value.

Fig. 1. Overview of the sector-by-sector demands and the related units.

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Fig. 2. Reference energy system of space heating (DRRISC) water heating (RESACS) and space cooling (RESRAF) demands in residential. Outputs of space heating (RRIS_) water heating (RACS_) and space cooling (RRAF_) devices are respectively space heating (RESRIS), water heating (RESACS) and space cooling (RESRAF) services, expressed in PJ. Dummy technologies (RDRISEDI0_, RDACSEM01, RDRAFEDI01) transform these commodities in end -use demand, respectively expressed in Mm2 (space heating and cooling) and in G-litres (water heating).

2.2.4. Industry Industry is modelled distinguishing among 10 sub-sectors, each of them corresponding to a single end-use demand: metallurgical, mechanics, food, textile and clothing, buildings materials, chemical and petrochemical, paper, other manufacturing, building and energy. Each end-use demand is represented as the output of a process powered by thermal energy and electricity. In turn the thermal energy is produced using fossil fuels (ICAR—coal, IOLI— fuel oil, IGSL—diesel, IGPL—liquefied petroleum gas, IAPP—other petroleum products and IGAS—natural gas) and biomass (IBIO). The only exception is the building industry which has in input only electricity and diesel. Fig. 5 represents, as an example, the reference energy system of the metallurgical sector (MET).

and one type of heat (IHET) are represented. Electricity is also imported from other regions (IMPELC0) at very high voltage. 2.2.7. Supply sector In TIMES-Basilicata the Supply sector is structured around “mining” processes from which both fossil and renewable energy carriers originates. Dummy technologies transform these carriers into sector-specific input fuels for Residential, Commercial, Agriculture and Industry (Fig. 8). On the other hand, in the transport sector these fossil and renewable fuels are used without further redenomination (Fig. 9). 2.3. The data files

2.2.5. Transport This sector includes public and private transport of passengers and road freight, distinguishing between specific services and routes (e.g. bus urban and extra urban routes, car urban / extra urban and long distance routes). The overall representation is provided in Fig. 6.

The time horizon analyzed by TIMES-Basilicata goes from 2007 to 2030, covering a 28-year period (subdivided into 12 periods of two years each). In particular, the structure of the TIMES-Basilicata is composed by three main sets of Excel spreadsheets:

 Seven base year templates, with reference to 2.2.6. Electricity and heat production The Electricity and Heat production sector includes power plants (public) and co-generative plants (public and private), both from fossil fuels and renewable sources (Fig. 7). In the reference energy system, four types of electricity (very high voltage—ELCP, high voltage—ELCA, medium voltage—ELCM, and low voltage—ELCD)



– Five end-use demand sectors (Residential, Commercial, Transport, Industry and Agriculture). – Electricity and heat power generation. – Energy supply (primary energy extraction/import/export). A database of new technologies ”Subres new techs” which is a virtual basket including the new technological options.

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Fig. 3. Reference energy system of hotel space heating (DCARIS) and water heating (DCAACS). CARI_ and CAAC_ technologies have as output space heating (COMARI) and water heating (COMAAC) services, expressed in PJ. Dummy technologies (CDARIEDI01 and CDAACEDI01) transform these commodities in end -use demands, both expressed in M-presences (space heating—DCARIS and water heating—DCAACS).

Fig. 4. Reference energy system of agriculture (AGRI). The end-use demands is expressed in terms of added value (MEuro) (DEMAGR).

 Scenario files which contain all the main coherent assumptions



necessary to build up alternative scenarios: future trajectories of demand (Demand Projections) and exogenous constraints (User Constraints). Emission factors related to greenhouse gases (CO2, CH4 and N2O) and local air pollutions (NOx, CO, VOC, PM10, SO2).

The data input is structured around three groups of elaborate Excel spreadsheets (Fig. 10): 1. Base year templates: the local energy system is modelled through six sector-by-sector “templates” which hold the data necessary to calibrate the energy flows of the base-year for the analysed sectors (COM: Commercial, RES: Residential, IND: Industry and Agriculture, TRA: Transport, ELC: Electricity and Heat production, and SUP: Energy Supply). In particular, these

spreadsheets contain the following information: base-year energy flows, technical and economic features of the existing technology stocks, transmission efficiencies. The representation of the base year is completed by the “Electricity Share (SHR)” template aimed to convert, through dummy technologies, the electricity at different levels of voltage into new electricity flows consumed in different industrial sectors and Agriculture. 2. Database of new technologies “Subres new techs”: new technological options are introduced and described by their technical and economic parameters distinguishing among Electricity Production (ELE), Heat Production (HET), Electricity and Heat Production (CHP), Residential (RES), Commercial (COM), Industry (IND) and Transport (TRA). 3. Scenario files: in order to build up alternative scenarios, different sets of coherent assumptions about the future trajectories of demand are defined (Demand Projections) as well as exogenous constraints (User Constraints). The characterisation of the Basilicata energy system is completed by a spreadsheet containing emission factors (both GHGs and local air pollutants) and through other files containing additional information to be used in further studies (e.g. external costs, life cycle inventory impacts).

3. The Basilicata region energy system Basilicata is a small region of the Southern Italy, with 591,338 inhabitants (2007) [24], which covers an area of 9992 square kilometres, representing only the 3.3% of the Italian surface. Basilicata is bounded to the west by Campania, to the north and

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Fig. 5. Reference energy system of the metallurgical industrial sector (MET). The INDMET process is fed by thermal energy (IHETMET) and electricity (ELC) and produces metallurgical demand (DEMINDMET) as an output. Demands (such as DEMINDMET) are expressed in added value (MEuro).

Fig. 6. Reference energy system of the transport sector. Technologies representing the public transport of passengers are: buses (TD_BUS) and trains (TD_ELC_) whereas the private transport of passengers is modelled including cars (TD_A_), motorcycles (TDBENM00) and road freight (trucks TD_MER). End-use demands include urban buses (DTPMUB), extra urban buses (DTPMEB), road freights (DTMERC), urban cars (DTPMUA), extra urban cars (DTPMEA), long distance cars (DTPMLA), motorcycles (DTPMMO), passenger trains (DMTPAS), freight trains (DMTMER). Demands are expressed in Mpass/km (passengers transport) and Mt/km (freight transport). Dummy technologies (CONVSMUA, CONVSMEA and CONVSMLA) transform the unit of measure from M-cars/km to M-pass/km.

east by Puglia and to the south by Calabria and has two small seaboards, on Tyrrhenian Sea (to the west) and on Ionian Sea (to the south-east) (Fig. 11). The territory is prevailingly mountainous (46.9%), with only 8% of plain area, and 20% of total surface is wooded area. Due to its various territories, the Region enjoys a varied climate that spam from continental climate with rigorous and humid winter and

warm and dried summer, to Mediterranean climate on coastal areas and neighbouring areas with a mild winter and hot summer. The regional territory is interested by two National Parks: the Pollino National Parks, established in 1993, between Basilicata and Calabria with 171,132 ha (of which 88,650 ha in Basilicata) and the most recent Appennino Lucano-Val d’Agri-Lagonegrese National Park, instituted in the 2010, that covers 68,996 ha.

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Fig. 7. Reference energy system of the electricity and heat production. The modelled technologies include: hydroelectric plants (EBAHYDR_), wind plants (EBAWINRIA), waste plants (EBARIFRI_, photovoltaic plants (EBASOLRI1) and natural gas plants (ELCGNA). Electricity and heat are split and consumed by different industrial sub-sectors through dummy technologies (chemical and petrochemical SHARE_ICPC, metallurgical SHARE_IMET, other manufacturing SHARE_IAMA, paper SHARE_ICGR SHARE_IEDI, building materials SHARE_IMCV, textile and clothing SHARE_ITAB, food SHARE_IAGR, mechanics SHARE_IMEC, building and energy SHARE_IENA, Commercial SHARE_TER, Agriculture SHARE_AGR, Transport SHARE_TRA and Residential SHARE_RES).

Basilicata Region is split into two provinces: Province of Potenza and Province of Matera. Potenza is also the regional capital. Situated 819 m above sea level, with an area of 174 km2, the city is the highest regional capital and one of the highest provincial capitals in Italy (second only to Enna, Sicily). Basilicata, after Valle d’Aosta, is the Italian region with the lowest population density, with about 60.8 inhabitants per square kilometres respect to the 201.2 inhabitants per sq.km, that is the average Italian density of population. This is mainly due to the prevalently mountainous morphology of the territory and to a low economic growth. The GDP of Basilicata is about 18,900 Euro per inhabitants, slightly higher than the average value in Southern Italy (17,300 Euro per inhabitants), but consistently lower than the national average GDP (26,000 Euro per inhabitants) (Table 1). Local economy is based prevalently on agriculture, and in particular on cereal, potato, vine and olive growing. Industry is specialised in alimentary production, artificial fibre production, non-metallic mineral processing and chemical production. In the North of the Region the largest Italian carmaker (FIAT) has an important industrial pole. Tourism is increasing involving mainly coastal areas, but it is still under the national average. Basilicata is strongly dependent on electricity import, in fact in 2007 51% of inland consumption was imported from the neighbouring regions [25]. The energy system of Basilicata Region is described in the following paragraphs, focusing both on the supply side and the sector-by-sector demand.

3.1. Energy supply Regional primary energy production deals mainly with fossil fuels extraction, notably natural gas until 1995 and, afterwards (from 1996), oil extracted in the oilfield of Val d’Agri area (in the South-West of the Region) which has became the main endogenous resource. The gross inland oil extraction over a 15-year period has increased from 446 ktoe in 1990 to 5446 ktoe in 2005, thanks to the constant increase of oil exploitation. Table 2 resumes the trend of gross inland primary energy production from 1990 to 2005, pointing out the strong rise of oil extraction from 2001, the increasing utilisation of natural gas and renewable energy sources (boosted by national and regional incentives) and the absence of solid fuel mineral deposits [23].

3.1.1. Fossil fuels Despite of its small size, Basilicata holds the most large oil reservoir of continental Europe with a large quantity of crude oil and natural gas extracted from its underground (actually about 80,000 barrels per day and 3 million of m3 per day [26]). These oil extraction activities are located in the Val d’Agri area, characterised by a significant natural environment, recognised by the institution of the Appennino Lucano-Val d’Agri-Lagonegrese National Park. In particular, as reported in Fig. 12, in 2012 the extraction of crude oil was 4042 kt that represent 75% of the total oil extracted in Italy and 82% of the overall onshore production [26].

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Fig. 8. An example of reference energy system for the Supply sector consisting of mining processes (DISP_) and dummy technologies (INFRES_, INFCOM_, INFIND_ and INFAGR_) which transform the energy vectors in inputs for end-use sectors (residential—RES, commercial—COM, agriculture—AGR, industry—IND).

At present in Val d’Agri 25 oil wells are in operation, fulfilling about 10% of the national demand of crude oil. These amounts are pre-treated at the local Oil Centre of Viggiano and subsequently carried by a 136 km oil pipeline to the Taranto refinery, in the neighbouring Puglia region where it is further transformed in petroleum products. Besides reservoir oil, in Basilicata there are also remarkable quantities of gas reservoirs. Indeed, respect to onshore fields, Basilicata is the Italian region with the highest quantitative of mined gas (in 2012 1293,506,618 standard m3, 52% of the total national onshore gas extraction [26]). On the other hand, as mentioned before, no deposit of solid fuels is located in the regional territory.

3.1.2. Renewable energy sources A privileged position for solar energy (with a 40 degree northern latitude), orographic conditions favourable for producing wind power, the presence of several rivers and streams, many woodlands and agriculture fields make Basilicata an ideal place for the exploitation of multiple renewable energy sources. Nevertheless only in the last decade, also thanks to an effective national financial support scheme, there has been a strong growth of renewable energy production in Basilicata, as discussed in the following.

The PIEAR [23] sets the targets of maximum capacity increase from renewable sources by 2020 as summarised in Table 3.

3.1.2.1. Solar. Photovoltaic (PV) cells enable the direct conversion of sunlight into electricity. This is one of three main solar active technologies, along with concentrating solar power (CSP) and solar thermal collectors for heating and cooling (SHC). PV technologies are expanding very rapidly due to effective supporting policies, of which the most important is a feed-in tariff scheme called “Energy bill”, as well as to the recent dramatic cost reductions [27]. The Basilicata territory is characterized by favourable potentials of irradiation in terms of local climatic conditions and latitude. A GSE elaboration on ENEA data derived by the Italian Atlas of solar radiation [23] shows promising potentials of irradiation in almost all the regional territory, most of it offering values of about 4 kWh/(m2 day), with higher values in the coastal areas as well as on the Pollino mountains and Matera hills. PV is a commercially available and reliable technology with a significant potential for long-term growth in the Basilicata region, with a total installed power of 1762 kW, as reported in Table 4. According to the regional energy plan [23], PV will be further exploited to fulfil 5% of the regional electricity consumption in 2020, increasing to 11% in 2050.

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403

Fig. 9. Reference energy system of the supply sector as concerns transport fuels.

Fig. 10. Overview of the data input structure of TIMES-Basilicata.

In the last few years, large centralized PV power systems, mostly at the multi-megawatt scale, were built in Basilicata to feed local and regional electricity grids. In 2007, the model base year, there were only four PV plants larger than 20 kW and the most widespread technologies were those building-integrated.

This is mainly due to the incentive given for this kind of investment by the Italian Energy Bill and, on the other hand, by the lack of guidelines on transforming rural areas at regional scale. Another solar active technology, whose application could be very promising in Basilicata, is provided by solar thermal collectors

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Fig. 11. Localisation of Basilicata region.

Table 1 Demographic indicators and GDP per inhabitants. [24].

Basilicata region Province of Potenza Province of Matera Italy

No. of inhabitants (2007)

Area (sq km)

Population density (inhabitants/ sq km)

GDP per inhabitants (2007)

591,338 387,818 203,520 59,131,287

9,726 6,389 3,330 293,893

60.8 60.7 61.1 201.2

18,900 19,200 18,300 26,000

for heating and cooling (SHC). In the last few years a large number of solar collectors have been installed on the roofs in order to satisfy hot water demand or to integrate the existing heating systems especially in the residential sector. There is a consistent potential for a larger penetration of these technologies in the actual market.

3.1.2.2. Wind. The regional government recognises onshore wind energy as the most mature of all the available renewable technologies, producing electricity and preventing at the same time the release of greenhouse gases from other energy sources. Thus wind is expected to contribute heavily to the challenging targets set on renewable energy, benefitting also from the incentive (feed in tariffs) introduced by the national government in order to encourage the uptake of renewable energy by guaranteeing a price for energy generated from renewable sources such as wind energy. The wind plant installed capacity was 156 MW in 2007 (compared to the 2714 MW capacity totally installed in Italy) and 279 MW in 2010 (5797 MW in Italy) [28]. On the basis of the maps reported in the Italian Wind Atlas [29], the Basilicata region is characterized by a discrete availability of wind although distributed in an irregular way on the territory. In particular, while the average wind speed is generally higher than 6–7 m/s, some areas are characterized by a speed higher than 7 m/s with some peaks from 8 to 9 m/s. These

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Table 2 Regional production of primary energy sources in ktoe [23]. 1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Solid fuels Crude oil Natural gas Renewable sources

– 70 334 42

– 64 355 80

– 75 392 54

– 156 313 63

– 219 289 68

– 271 305 70

– 395 370 100

– 568 385 75

– 485 333 77

– 535 298 81

– 837 319 66

– 1109 367 88

– 2638 584 91

– 3263 691 146

– 3370 689 169

– 4386 883 177

Total

446

499

521

532

576

646

865

1028

895

914

1223

1564

3313

4099

4227

5446

However, despite these first interesting analyses, more detailed studies are necessary in order to obtain the maps of geothermal resources and to estimate the potential use of this energy in the region.

Fig. 12. Oil and natural gas production in Basilicata [26].

Table 3 Renewable energy targets by 2020. Renewable energy source Wind Solar and photovoltaic Biomasses Hydroelectric Total

Share (%)

Electricity production (GWh/year)

Targets of installed capacity (MWe)

60 20

1374 458

981 359

15 5 100

343 114 2289

50 48 1438

Table 4 Number of plants supported by the first energy bill and became operational in March 2, 2009 [23]. Class of power (kW)

Power plants (no.)

Installed power (kW)

1:20 20:50 50:1000

49 23 2

489 1039 234

Total

74

1762

areas are located along the Apennine dorsal, especially in the North of the region.

3.1.2.3. Geothermal. Geothermal energy is provided by the continuous conduction of heat from the core of the planet and its surface originated by its temperature differential. In Basilicata, some geophysical surveys have been carried out to characterize the stratigraphycal and structural setting and to better understand the deep water circulation system in specific areas. In particular, near Venosa, there are some deep water wells characterized by a water conductivity of about 3 mS/cm and a temperature of about 35 1C. By several methods and techniques, a horst saturated with salted water and an anomalous local gradient of 60 1C/km was identified [30], which is exactly twice the average value of 30 1C/km.

3.1.2.4. Biomass. The forest resources are the historical energy source for excellence, by virtue of the widespread use of firewood for heating and cooking. Woody biomass is mainly produced by forest use, but also from dedicated crops and as a residual material of industrial processes (the so-called “untreated biomass”). Concerning the Basilicata region, the most recent study on biomass resources and their potential use is represented by RAMSES [31], an interregional program among the regions of Basilicata, Campania and Calabria, aimed at the use of lignocellulose biomass at small and medium scale. The quantification of the availability of biomass residues, resulting from the forest use, is of fundamental importance at the regional level, having Basilicata region a high value of woodiness coefficient approximately equal to 35.6%, that represents the ratio between the area covered by forest and the total one [32]. The residues obtained by lignocellulose agricultural wastes are mainly derived by the annual and periodic maintenance of tree crops (olive trees, orchards and vineyards). At regional level it can be observed a predominance of olive groves, with 33,190 ha, equivalent to 57% of the total area occupied by woody crops, whereas the cultivation of citrus and orchards represents 36% (23,129 ha). In the region, there are about 560 wood processing companies whose dimensions are very small. In the following table the amounts of wood biomass coming from these activities are reported. Table 5 provides quantitative data on the surfaces covered by woody biomass in Basilicata and the amounts of residuals from agriculture, forests and wood processing companies. 3.1.2.5. Hydroelectrical. Electricity production, through the use of the gravitational force of falling or flowing water, has been the first renewable energy used in the region, which is very rich of water and has a highly developed and strategic system of water infrastructure. For this reason, water bodies with the highest potential are already equipped with dams and hydroelectric plants of medium and large dimensions. However, there is still an exploitable hydropower potential in the region through the installation of run of the river power plants, able to exploit marginal resources with minimal impact on the ecosystem. At now there are 128 MW of installed capacity in eight power plants where the most significant contribution is given from pumped storages (122 MW) and only a little capacity refer to run of the river hydroelectric plants. 3.1.3. Electricity and heat The Region is heavily dependent on imported energy from neighbouring regions with particular reference to electricity. In fact, to satisfy an annual total consumption of 2931 GWh (4959 kWh per capita), it needs an import of 1625 GWh. Thermal power plants are powered by fossil fuels for a total of 290 MW and 1048 GWh of net production and are characterized by an efficiency

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Table 5 Estimate of biomass for energy purposes in Basilicata [31]. Surfaces covered by woody biomass [sq km]

9992

Forest harvesting residues [quintals]

137,510

Residues of the wood processing companies [quintals]

25,709

Residuals from agricultural practices Olive residues [quintals]

Vineyards residues Orchards residues Total [quintals] [quintals] [quintals]

1626,317

130,373

2290,032

533,343

Table 6 Regional energy consumption in 2007 (PJ) (CNR-IMAA elaboration on PIEAR [23], ENEA statistics [34] and ISTAT data [35]). Wood and other solids Residential Commercial Industry Agriculture Transport

0.29 – 0.44 – –

Total

0.73

Natural gas 5.02 2.135 6.30 0.04 0.06 13.56

LPG

Diesel

Fuel oil

Other petroleum products

0.24 0.138 0.24 – 0.25

0.38 0.239 0.27 2.01 10.54

0.002 0.038 1.43 – –

– – 1.98 – 6.07

1.84 2.02 6.28 0.26 0.1

0.87

13.44

1.47

8.05

10.50

level below the national average, being quite old installations. The installed capacity of cogeneration plants is 73% of total thermoelectric power plants. The most important plant is the combined cycle technology of FIAT-Serene (100 MW). Regarding the electricity production from renewable sources, the main contribution is given by wind power plants with a net production of 262 GWh and 155.5 MW of installed capacity. In 2002 the first eight wind turbines, with a total capacity of 5.3 MW, came into operation, while in 2006 other 28 wind turbines, with a total capacity of 23.8 MW, were added. In particular, the wind farm of Vaglio di Basilicata, active from October 2003, consists of 20 three-bladed wind turbine, each of 0.6 MW for a total installed capacity of 12.3 MW. In Montemurro it was built a wind farm with a total capacity of 29.08 MW. Other wind farms, with significant capacity and in operation before 2007, are located in Avigliano (13.2 MW), Forenza (23.76 MW) and Maschito (15.84 MW). Hydroelectricity production is of 227 GWh with an installed capacity of 128 MW. Most of the production belongs to the Italy’s largest power company (ENEL Production), which in Basilicata has three hydroelectric plants for a total capacity of 123 MW: the hydro power plant located in the Agri basin which utilises the water reservoir provided by the Pertusillo Lake and has been operating since 1963 with a capacity of 39 MW; the Castrocucco hydropower plant located in the municipality of Trecchina, operating from 1973 with a power of 83 MW, and the run of river power plant of Caolo, located in the municipality of Tramutola, with a capacity of 0.692 MW. Furthermore with the introduction of the “energy bill” there has been an increase in the obtainment of permits for the installation of photovoltaic systems. Starting from 0.8 MW of installed capacity and 0.5 GWh of electricity production in 2007, PV systems reached 330 MW of capacity installed and 402 GWh of electricity production in 2012 [25]. In the small municipality of Calvello a small biomass thermal plant has been operational since 2006 with a nominal power of 220 kW, feeding a district heating network of about 200 m [33]. This plant provides heat for a multi-sports complex (950 m2) and the related changing rooms (100 m2). The plant is fed with wood chips, produced by the periodic cutting of local forests. 3.2. Energy demand In 2007 Industry, Transport, Residential and Commercial energy uses accounted respectively for 47%, 29%, 13% and 8% of the energy consumption in Basilicata.

Electricity

Heat

Total

– 0.0003 10.62 – –

7.77 4.57 27.56 2.31 17.02

10.62

59.23

An overview of the regional energy demand by sector and energy sources is reported in Table 6, whereas detailed information on data sources and methods used for obtaining these values are provided in the following paragraphs. 3.2.1. Residential The residential energy consumption represents 14% of the total regional consumption and is in line with the national sectoral sharing (18%) [34]. In particular, natural gas is the prevalent fuel utilised in this sector, accounting for 64% (5.02 PJ) of the total energy consumption, also thanks to a widespread distribution of gas grids on the regional territory, followed by electricity (24%, that is 1.84 PJ), petroleum products (8%, 0.63 PJ) and a small percentage of renewable sources (4%, 0.29 PJ), including wood and solar for water heating [23]. Modelling, in detail, the whole Basilicata energy system requires highly detailed information on the breakdown of residential energy use by fuels and end use categories (space heating, water heating, cooling, etc.). Starting from the aggregated energy balance of the Regional Energy Environmental Plan [23] and referring to the breakdown of the Italian energy consumption of petroleum products in the Residential sector (39% LPG, 61% diesel and 0.3% fuel oil [34]) as well as using other national statistics on the population and households [35], some elaborations were made to obtain the requested breakdown of the energy consumption by fuel (Table 7). The next step dealt with computing the detailed breakdown of energy consumption among end use categories: space heating, water heating, cooking, cooling, refrigeration, washing machine, dishwasher, lighting, and other electric uses (Table 8). In particular, electricity was split among end use categories [36], whereas other fuels were disaggregated on the basis of the average Italian breakdown per energy uses [34]. 3.2.2. Commercial The commercial sector is modelled through six sub-sectors: Hotels, Hospitals, Unmarketable Other Tertiary (health facilities, public administration offices and schools), Shopping Malls, Other Tertiary (restaurants and cafeterias, bars, banks and insurance, communications) and obliged electrical use. In 2007, the commercial sector consumed 0.461 PJ of oil products and 2.135 PJ of natural gas [24], while the total electricity consumption was 2.021 PJ [36]. Starting from these values and

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water, the electricity and natural gas consumptions are very similar (respectively 0.096 PJ and 0.083 PJ), whereas petroleum products are much less consumed (0.004 PJ).

applying the national consumption shares [37], it was derived the Commercial breakdown in energy uses resumed in Table 9. This detailed prospect of energy uses in Commercial shows that 87% of electricity is mainly used for “forced electrical purposes”, including lighting (33% of the total electricity use), office equipment (17%), air conditioning (13%), other services (16%) and refrigerators (8%). Lower amounts of electricity were utilised by space heating (2%) and water heating (4%). On the other hand, natural gas is the fuel most widely used for space heating (1.822 PJ), followed by petroleum products (0.450 PJ) and electricity (0.148 PJ). As concerns domestic hot

3.2.2.1. Hotels. The energy demand of space heating and water heating in hotels is linked to the number of admissions per year, estimated as 1.88 Mpresences in 2007 [38]. To meet this demand, a total useful energy of 0.062 PJ for space heating and 0.087 PJ for water heating was required. The energy demand of space heating (0.071 PJ) was estimated considering an annual energy consumption of 2.5 MWh/(roomyear) and a total number of 7913 rooms. As concerns water heating, the total energy demand (0.114 PJ) was assessed considering a consumption of 4 MWh/(room-annually). As shown in Table 9, space heating utilises mostly natural gas (77%) and diesel (15%), with a lower use of LPG (6%) and electricity (3%). For water heating, electricity is the most used fuel (68%), together with natural gas (31%).

Table 7 Regional energy consumption by fuel in 2007 (PJ) (IMAA elaboration on PIEAR data [23]). Regional energy consumption by fuel (PJ) Natural gas Renewable sources

5.02 0.29

Breakdown in TIMES-Basilicata (PJ)

Electricity

1.84

Natural gas Wood Thermal solar LPG Diesel Fuel oil Electricity

Total

7.77

Total

Petroleum products 0.63

5.02 0.29 0.002 0.24 0.38 0.002 1.84 7.77

407

3.2.2.2. Hospitals. The estimation of the energy demand of hospitals was related to the number of beds (0.0019 Mbeds, [39]), to which corresponds a request of 0.092 PJ of useful energy for space heating and 0.0095 PJ for water heating. With regards to space heating a specific fuel consumption of 13.5 Gcal/ (number of beds-year) [40] was taken into account, providing a total consumption of 0.105 PJ, whereas a specific consumption of

Table 8 Regional energy consumption in 2007 (PJ) (CNR-IMAA elaboration on PIEAR data (2005) [23] and ENEA statistics [34]). Wood

Natural gas

LPG

Diesel

Fuel oil

Thermal solar

Electricity

Total

3.053 1.301 0.67 – – – – – –

0.136 0.07 0.07 – – – – – –

0.3053 1.301 – – – – – – –

0.002 – – – – – – – –

– 0.002 – – – – – – –

0.038 0.258 0.072 0.051 0.312 0.181 0.067 0.244 0.607

3.84 1.659

Cooking Cooling Refrigeration Washing machine Dishwasher Lighting Other electric uses

0.291 – – – – – – – –

Total residential

0.29

5.02

0.24

0.38

0.002

0.002

1.84

7.77

Space heating Water heating

0.051

Table 9 Energy consumption in Commercial sector 2007 (PJ) (CNR-IMAA elaboration on PIEAR data [23] and ENEA statistics [33]). Heat

Natural gas

LPG

Diesel

Fuel oil

Electricity

TOTAL

Water heating Cooking Forced electric purposes Office equipments Air conditioners Refrigerators Lighting Other devices

– – – 0.085 – – 0.0003 0.0003 – – – – – – – – – – – –

0.090 0.055 0.035 0.006 0.081 0.004 1.467 1.467 0.041 0.041 0.452 0.178 0.043 0.230 – – – – – –

0.005 0.004 0.001 0.016 0.006 0.0001 0.108 0.108 0.003 0.003 0.015 0.006 0.001 0.008 – – – – – –

0.011 0.011 0.001 – 0.016 0.00006 0.207 0.207 0.006 0.006 – – – – – – – – – –

– – – 0.011 – – 0.081 0.081 0.002 0.002 – – – – – – – – – –

0.079 0.002 0.077 0.118 0.002 0.0085 0.042 0.042 0.001 0.001 0.130 0.100 0.010 0.020 1.758 0.346 0.271 0.156 0.671 0.315

0.185 0.071 0.114 0.085 0.105 0.013 1.906 1.906 0.054 0.054 0.597 0.285 0.055 0.258 1.758 0.346 0.271 0.156 0.671 0.315

Total commercial

0.0003

2.135

0.138

0.239

0.083

2.021

4.597

Hotels Space heating Water heating Hospitals Space heating Water heating Unmarketable other tertiary Space heating Shopping centres Space heating Other tertiary Space heating

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0.15 toe/(number of beds-year) [40] was utilised in the case of water heating, obtaining a total consumption of 0.013 PJ. 3.2.2.3. Unmarketable other tertiary. Dealing with the part of tertiary which not include the sale of goods but refers to schools, public administration and health facilities, the main energy demand consists of space heating and it is calculated on the basis of the total area of buildings (4.067 Mm2), of which 0.0108 Mm2 health facilities [41], 3.069 Mm2 public administration [42] and 0.988 Mm2 schools [35]. In the case of health facilities (public and private), an annual energy consumption of 165 kWh/(m2-year) was considered [43], taking into account the presence of 115 clinics on the territory for a total of 11,300 m2 [44]. The same assumption (165 kWh/m2-year) was made for the annual energy consumption of governmental buildings, covering a total area of 3.07 Mm2 [42]. On the other hand, a specific heat consumption of 44.18 MJ/m3 was adopted to estimate the annual energy consumption of schools [43]. In this case the total volume adds up figures of lower primary schools, primary schools, higher primary schools, high schools and university buildings accounting for 2.67 Mm3 [35]. Based on these assumptions the natural gas consumption for space heating is 1.467 PJ (77% of the total consumption of Unmarketable other tertiary), of which 0.005 PJ for health facilities, 1.373 PJ for public administration buildings and 0.089 PJ for schools. The total consumption of diesel is 0.207 PJ (11%), of which 0.001 PJ for health facilities, 0.194 PJ for public administration buildings and 0.013 PJ for schools. Smaller is the contribution of other fuels: LPG (6%), fuel oil (4%) and electricity (2%). 3.2.2.4. Shopping centres. Shopping centres include supermarkets, department stores, specialized mega stores, hypermarkets and minimarkets which cover in Basilicata a total area of 92,269 m2 [45]. Using specific unitary consumption factors for different types of shopping centres [46] it was possible to calculate the total energy consumption for space heating. To split this consumption among the different fuels utilized, the following percentages of final energy consumption per fuel in Tertiary were applied according to the Regional Energy Environmental Plan: natural gas (76%), followed by diesel (11%), LPG (6%), fuel oil (4%) and electricity (2%). 3.2.2.5. Other tertiary. This sub-sector deals with the final energy consumption of bars and restaurants, banks, insurances and communications activities and it refers to space heating, domestic water heating and cooking. Demands are expressed in Mega-employees. As for space heating and domestic hot water demands, it was considered a total number of 10,583 employees (2459 in restaurants and canteens, 1060 in bars, 2185 in banks and 4879 in the insurance industry [47]), while for cooking, the total number of employees was 3519 (working in restaurants, cafeterias and canteens). The total energy consumption was split among water heating (10%), space heating (39%) and cooking (51%) [46]. In order to satisfy the space heating and hot water demands, there were used respectively 0.178 PJ and 0.043 PJ of natural gas, 0.100 PJ and 0.010 PJ of electricity, 0.006 PJ and 0.001 PJ of LPG. Cooking needed 0.230 PJ of natural gas, 0.020 PJ of electricity and 0.008 PJ of LPG. 3.2.3. Industry The PIEAR energy balance [23] reports that the overall energy consumption of the regional Industry is 18.6 PJ with a larger use of gaseous fuels (7.2 PJ), electricity (6 PJ) and oil products (4.8 PJ) and 0.6 PJ of renewable sources. As previously discussed in Section 2.2.4, the RES for Industry adopted in this model requires a desegregation of energy

consumption per each economic activity (sub-sector) which is not provided by any official data source and was, therefore, evaluated ad hoc as follows: – Industrial data derived by the Italian National Energy Balance [48] were re-aggregated according to the MONET [22] structure of sub-sectors, as described in Table 10. – The official data on the number of employees per each economic activity [49] was re-aggregated accordingly to these 10 industrial sub-sectors (Table 10). – Taking into account national figures on industrial energy consumption and the related number of employees, it was obtained the average national consumption per employee for 2007, broken down by energy source. These values were used to obtain a first estimate of the regional consumption of the industry by sub-sector (Table 11).

This estimate resulted to be undersized compared to the reference values [23], showing a total consumption of 12.5 PJ compared to 18.6 PJ (444 ktoe), mainly due to an underestimation of the power consumption considering the average national values. It was therefore necessary to correct electrical consumption using the regional sectoral data [25] and calibrate the remaining industrial consumption per energy source to the PIEAR 2005 data [23]. Consumption of Industry in Basilicata resulting from these procedures are summarised in Table 12 and were introduced in the data input of TIMES-Basilicata. Filling in the model template for Industry passed through the definition of average efficiencies of thermal power generation from industry (IHET) by fuel and the estimation of the consumption of thermal energy by sub-sector (except for Construction, which uses mainly liquid fuels) as reported in Table 12. Finally comparing the thermal energy consumption (IHET) with the electricity consumption (IELC) there were obtained the “shares” among the two energy carriers by industrial sub-sector (Table 13). It should be noticed that in the case of Building (EDI) there is not thermal energy consumption but only diesel and electricity consumption.

Table 10 Reorganisation of Industrial sub-sectors according to the MONET structure and derivation of the breakdown of employees among subsectors in Basilicata. NEB classification MONET classification

Code

No. of employees (2007) Italy (ISTAT)

No. of employees (2007) Basilicata (CNR-IMAA elaboration)

Iron and steel Non ferrous metals Mechanic Food and drink Textile Building materials

Metallurgy Mechanic

MET MEC

803,671 745,581

3,853 9,632

Food and drink Textile Building materials Chemical and petrochemical Paper

AGR TAB MCV

450,263 608,524 240,053

4,955 1,485 2,399

CPC

417,300

1,998

CGR

210,740

731

975,053 1,985,235 284,720

6,020 18,696 3,604

6,721,140

53,373

Glass–ceramics Chemical Petrochemical Paper Other industries Buildings Mining Total

Other industries AMA Buildings EDI Energy and eater ENA

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Table 11 Energy consumption of Industry in Basilicata (CNR-IMAA elaboration on MSE [45], ISTAT [49] and TERNA [25] data) (Legend: ICAR: coal for industry; IBIO: biomass for industry, IOLI: fuel oil for industry, IGSL: oil for industry, IGPL: LPG for industry, IAPP: other petroleum products for industry, IGNA: natural gas for industry, IELC: electricity for industry). Metallurgy Ind. (MET)

Mechanic Food and Ind. (MEC) drink Ind. (AGR)

Textile and clothing Ind. (TAB)

Building material Ind. (MCV)

Chemical and petrochemical Ind. (CPC)

Paper Ind. (CGR)

Other manufacturing Ind. (AMA)

Building (EDI)

Energy and Total water (ENA)

0.00 0.00 0.04 0.01 0.02 0.00 0.67 1.48

0.00 0.00 0.42 0.13 0.08 0.05 1.82 1.38

0.00 0.00 0.50 0.04 0.04 0.00 1.01 0.59

0.00 0.00 0.04 0.01 0.00 0.00 0.14 0.27

0.00 0.58 0.28 0.05 0.12 2.21 2.02 0.68

0.00 0.01 0.25 0.01 0.01 0.16 0.82 0.66

0.00 0.00 0.05 0.01 0.00 0.00 0.42 0.08

0.00 0.00 0.15 0.02 0.01 0.00 0.32 0.13

0.00 0.00 0.00 0.04 0.00 0.00 0.00 0.02

0.00 0.00 0.02 0.02 0.00 0.00 0.02 1.00

0.00 0.59 1.74 0.33 0.28 2.42 7.24 6.28

Total 2.21

3.88

2.17

0.46

5.94

1.91

0.56

0.62

0.06

1.07

18.87

ICAR IBIO IOLI IGSL IGPL IAPP IGNA IELC

Table 12 Average efficiencies and thermal energy consumption (IHET) for industry and fuel (CNR-IMAA elaboration on MONET data [22]). Average efficiency

ICAR IBIO IOLI IGSL IGPL IAPP IGNA

1.30 1.33 1.22 1.22 1.18 1.22 1.15

Total

Thermal energy consumption in Industry (PJ) Metallurgy (MET)

Mechanic (MEC)

Food and drink (AGR)

Textile and clothing (TAB)

Building material (MCV)

Chemical and Paper petrochemical (CPC) (CGR)

Other manufacturing (AMA)

Energy and water (ENA)

Total

0.00 0.00 0.03 0.00 0.01 0.00 0.58

0.00 0.00 0.34 0.11 0.07 0.04 1.59

0.00 0.00 0.41 0.04 0.03 0.00 0.88

0.00 0.00 0.03 0.01 0.00 0.00 0.12

0.00 0.43 0.23 0.04 0.10 1.81 1.76

0.00 0.00 0.20 0.01 0.01 0.13 0.71

0.00 0.00 0.04 0.00 0.00 0.00 0.37

0.00 0.00 0.13 0.01 0.01 0.00 0.28

0.00 0.00 0.01 0.02 0.00 0.00 0.02

0.00 0.44 1.43 0.27 0.24 1.98 6.30

0.63

2.15

1.35

0.16

4.38

1.06

0.41

0.42

0.05

10.66

Table 13 Share between electricity and thermal energy in industrial sectors (CNR-IMAA elaboration). Metallurgy (MET)

IELC 0.70 IHET 0.30

Mechanic (MEC)

Food and drink (AGR)

Textile and clothing (TAB)

Building Chemical and material (MCV) petrochemical (CPC)

Paper (CGR)

Other manufacturing (AMA)

Energy and water (ENA)

Metallurgy (MET)

0.39 0.61

0.30 0.70

0.63 0.37

0.13 0.87

0.16 0.84

0.23 0.77

0.40 0.60

0.95 0.05

0.38 0.62

Table 14 Circulating vehicles by type of fuel and emission standard for the year 2007 (CNR-IMAA elaboration on ISTAT data) and fuel consumption by vehicle type.

Stock of circulating vehicle Gasoline Gasoline and LPG Gasoline and methane Diesel Methane

Euro 0

Euro 1þ Euro 2

Euro 3þ Euro 4 o sup.

Motorcycles

Buses

Freight

63,280 3,351 357 13,242 –

81,231 4,405 856 50,641 –

40,136 476 309 77,173 –

29,126 – – – –

– – – 1789 30

1,764 – – 37,308 –

1.62 – 1.57 –

0.76 0.31 2.27 0.05

0.21 – – –

– – 0.72 0.01

0.36 – 3.89 –

Fuel consumption by vehicle type (PJ) Gasoline 1.33 LPG – Diesel 0.42 Methane –

3.2.4. Transport In 2005, the transport sector was responsible of 29% of the total regional energy consumption (13.74 PJ). Most of the consumption refers to diesel (9.05 PJ), followed by gasoline 4.32 PJ and with a small consumption of LPG (0.31 PJ) and electricity (0.06 PJ).

Jet fuel and biodiesel consumption is totally absent, while the use of natural gas for vehicle is still negligible. In TIMES Basilicata the transport demand is modelled distinguishing among private and public transport of persons and goods. In Table 14 the stock of cars (broken down per category: pre-Euro,

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Following this scenario, many demands related to the evolution of population were analysed considering decreasing trends over the considered time horizon (2007–2030). The only exception is represented by the electric use demands, for which the trend was derived by the Basilicata Region module of the MONET model (2004–2030) [22], carrying out some adaptation procedures to make comparable the MONET model prevision in 2007 with the statistical values available for the same year, which represents the base year of TIMES-Basilicata. On the other hand, for those demands of commodities characterised by the availability of historical trends logarithmic regressions were applied in order to estimate their trends on the analysed time horizon. The resulting demands are summarised in Tables 16–19, which refer respectively to Residential, Commercial, Transport, Industry and Agriculture sectors.

Euro 1–2, Euro 3–4) and other circulating vehicles is reported with reference to the year 2007. The annual average distances were derived by national literature [50], whereas average fuel consumption by type of fuel [51] and emission standards [52] were considered in order to estimate the efficiencies expressed in Mpass-km/PJ. Also maximum annual paths, useful life, the minimum share of use and CO2 emissions were estimated. As regards public transport and transport of goods, it was estimated the stock of buses and trucks starting from regional statistics. In Table 14 fuel consumption by vehicle type are reported. 3.3. Demand projection To estimate the demand projection on the entire time horizon (2007–2030), it was necessary to identify appropriate demand drivers and use statistical tools and trends coming from previous studies. A key demand driver is the regional population projection was provided by the National Institute for Statistics of Italy (ISTAT) [35] in three different levels of estimates: low, medium and high. For this study it was chosen to adopt the central scenario as the demand driver for the regional population projection which estimates a population reduction of about 10% in 2030 respect to 2007 (Table 15).

3.4. Air emissions For each sector, the average emissions factors of the main greenhouse gases (CO2, CH4 and N2O) and local air pollutants (SO2, NOx, VOC, CO and PM10) were introduced based on national databases [52,53]. In order to represent the sectoral emissions, the

Table 15 Projection population—central scenario [35]. Year

2007

2010

2014

2018

2022

2026

2030

Population

590,528

586,799

578,462

567,519

555,700

543,598

531,495

Table 16 Residential sector—demand projection.

DRRISC (space heating) DRACSA (water heating) DRERAF (space cooling) DRAUCO (cooking) DREASB (cloth drying) DRECON (freezer) DREENT (entertainment) DREFRI (refrigerator) DREILL (lighting) DRELAB (cloth washing) DRELAS (dishwashing) DRESCA (services for the home) DRESGE (general services)

Unit

2007

2010

2014

2018

2020

2024

2026

2030

Mm2 Gl Mm2 Munit Gcycles Gl PJ Gl Glum Glav Gcycles PJ PJ

18.79 11.17 1.46 0.22 0.0008 0.013 0.42 0.048 3.617 0.037 0.015 0.095 0.075

19.98 11.10 2.00 0.22 0.0011 0.015 0.46 0.050 3.721 0.039 0.017 0.099 0.080

21.70 10.95 2.88 0.23 0.0017 0.017 0.52 0.052 3.820 0.043 0.022 0.106 0.088

23.54 10.98 3.89 0.24 0.0025 0.019 0.57 0.054 3.872 0.047 0.028 0.114 0.098

24.51 11.11 4.45 0.24 0.0032 0.021 0.62 0.055 3.886 0.049 0.031 0.118 0.108

24.82 11.34 5.58 0.25 0.0048 0.024 0.67 0.058 3.905 0.053 0.039 0.127 0.120

24.97 11.44 6.15 0.25 0.0057 0.025 0.68 0.059 3.911 0.055 0.044 0.132 0.122

25.29 11.64 7.22 0.26 0.0086 0.029 0.73 0.061 3.910 0.060 0.055 0.142 0.137

Table 17 Commercial sector—demand projection.

DCARIS (hotel space heating) DCAACS (hotel water heating) DCHRIS (hospital space heating) DCHACS (hospital water heating) DCNRIS (unmarketable other tertiary space heating) DCCRIS (shopping centers space heating) DCORIS (other tertiary space heating) DCOACS (other tertiary water heating) DCOUCO (other tertiary cooking) DCEFRE (refrigerators) DCEAPU (office equipments) DCECAM (air conditioner) DCEILL (lighting) DCEPSE (other devices)

Unit

2007

2010

2014

2018

2022

2026

2030

Mattendances Mattendances Mbeds Mbeds Mm2 Mm2 Memployees Memployees Memployees PJ PJ PJ PJ PJ

1.88 1.88 0.0019 0.0019 4.07 0.092 0.013 0.013 0.0035 0.17 0.38 0.87 3.09 0.32

2.05 2.05 0.0019 0.0019 4.53 0.092 0.013 0.013 0.0035 0.19 0.46 0.99 3.34 0.35

2.31 2.31 0.0019 0.0019 4.47 0.091 0.015 0.015 0.0035 0.24 0.58 1.17 3.67 0.39

2.57 2.57 0.0019 0.0019 4.40 0.089 0.016 0.016 0.0034 0.29 0.72 1.39 4.02 0.43

2.84 2.84 0.0018 0.0018 4.31 0.087 0.017 0.017 0.0033 0.35 0.88 1.64 4.39 0.50

3.11 3.11 0.0018 0.0018 4.23 0.085 0.018 0.018 0.0033 0.42 1.06 1.91 4.78 0.52

3.37 3.37 0.0018 0.0018 4.15 0.084 0.019 0.019 0.0032 0.50 1.27 2.23 5.18 0.57

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Table 18 Transport sector—demand projection.

DTPMUA (urban car) DTPMEA (extra-urban car) DTPMLA (long distance car) DTPMUB (urban bus) DTPMEB (extra-urban bus) DTMERC (road freight) DTPMMO (motorcycles) DMTPAS (passengers trains) DMTMER (freight trains)

Unit

2007

2010

2014

2018

2022

2026

2030

Mpass-km Mpass-km Mpass-km Mpass-km Mpass-km Mt-km Mpass-km Mpass-km Mt-km

1260 3157 2813 489 734 2640 233 390 183

1277 3199 2850 501 752 2744 247 390 185

1284 3218 2866 508 762 2829 255 389 189

1284 3216 2865 510 765 2887 260 387 194

1280 3206 2856 511 766 2931 262 385 207

1274 3191 2843 510 765 2966 264 381 210

1267 3173 2827 508 763 2996 265 376 224

Table 19 Industry and agriculture sector—demand projection.

DEMINDMET (metallurgical) DEMINDMEC (mechanical) DEMINDAGR (food) DEMINDTAB (textile and clothing) DEMINDMCV (building material) DEMINDCPC (chemical and petrochemical) DEMINDCGR (paper) DEMINDAMA (other manufacturing) DEMINDEDI (building) DEMINDENA (mining) DEMAGR (agriculture)

Unit

2007

2010

2014

2018

2022

2026

2030

M-euro M-euro M-euro M-euro M-euro M-euro M-euro M-euro M-euro M-euro M-euro

66 251 106 55 79 29 25 138 394 68 568

67 253 107 55 79 30 25 139 396 69 532

64 241 102 53 76 28 24 133 378 65 539

61 232 98 51 73 27 23 128 364 63 543

59 225 95 49 71 26 22 124 353 61 547

58 220 93 48 69 26 22 121 345 60 550

57 215 91 47 67 25 21 118 337 58 553

Table 20 Average emission factors (kt/GW h) from electricity and heat production of the main greenhouse gases. kt/GW h

Coal

Natural gas

Fuel oil

Diesel

Biogas

Biomass

ELCCO2 ELCN2O ELCCH4

3.54E  01 2.88E  06 2.16E  06

2.02E  01 2.88E  06 2.16E  06

2.76E  01 5.90E  06 2.88E  06

2.64E  01 3.24E 06 2.70E 06

0 3.60E  07 3.60E  06

0 1.55E  05 6.48E  05

Table 21 Average emission factors (kt/GWh) from electricity and heat production of local air pollution. ELCSO2

ELCNOx

ELCPTS

ELCVOC

ELCCOX

Gas Gas Gas Gas Gas Gas Gas

Condensing steam cycle Gas turbine Combined cycle Steam cycle with repowered gas turbine Cogenerative combined cycle Cogenerative gas turbine Cogenerative condensing steam cycle

7.60E  05 7.60E  05 1.10E  04 1.10E  04 1.00E  04 1.10E  04 4.92E  04

1.85E  04 3.02E  04 1.64E  04 1.85E  04 1.64E  04 4.41E  04 1.85E  04

2.44E  05 3.58E  05 5.96E  06 2.44E  05 2.44E  05 3.58E  05 2.44E  05

0 1.11E  05 1.21E  05 0 1.21E  05 1.11E  05 0

5.04E  05 5.04E  05 5.04E  05 5.04E  05 5.04E  05 1.15E  04 5.04E  05

Oil Oil Oil Oil Oil Oil

Combined cycle Gas turbine Steam cycle with repowered gas turbine Condensing steam cycle Cogenerative steam cycle Condensing Cogenerative steam cycle

1.08E  03 2.28E  03 1.08E  03 7.56E  04 1.08E  03 7.56E  04

3.00E  04 2.96E  04 1.85E  04 3.00E  04 1.85E  04 3.00E  04

3.33E 05 7.39E  05 7.39E  05 7.39E  05 3.33E 05 7.39E  05

3.2E  07 4.48E  10 4.48E  10 4.48E  10 3.2E  07 4.48E  10

5.40E  05 5.40E  05 5.40E  05 5.40E  05 5.40E  05 5.40E  05

Coal Caol Coal

Condensing steam cycle Steam cycle Condensing Cogenerative steam cycle

2.28E  03 4.92E  04 2.28E  03

3.00E  04 3.33E  04 3.00E  04

5.54E  04 9.43E  05 5.54E  04

5.43E  09 5.43E  09 5.43E  09

3.24E 05 3.24E 05 3.24E 05

Diesel Diesel Diesel Diesel

Gas Turbine Internal Combustion Combined cycle Cogenerative combined cycle

1.08E  03 2.28E  03 1.08E  03 1.08E  03

3.00E  04 3.73E 03 3.00E  04 3.00E  04

1.34E  04 5.54E  04 5.54E  04 5.54E  04

1.5E  05 5.4E  08 5.4E  08 5.4E  08

6.12E  05 6.12E  05 6.12E  05 6.12E  05

Derived gas Waste Biomass Biogas

Combined cycle Incinerator

1.10E  04 1.08E  03 1.08E  03 0

3.21E  04 4.41E  04 2.25E  04 2.25E  04

2.44E  05 4.57E  05 4.57E  05 2.24E 05

0 1.63E  08 1.2E  08 6.72E  07

5.04E  05 3.53E  04 5.30E  03 4.28E  04

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S. Di Leo et al. / Renewable and Sustainable Energy Reviews 42 (2015) 394–414

commodities have been defined using the first three letters for indicating the sector, followed by the type of emission. So for example, commodities representing CO2 emissions from Residential are indicated as RESCO2. The average emission factors of greenhouse gases by combustion for electricity and heat production are related to the quantity of the used fuel, so they are expressed in kt/GWh (Table 20). As concern the main local air pollutants, the level of detail is higher distinguishing also the emission factors for typology of technology (Table 21). For electricity and heat production, the total suspended particulate (ELCPTS) is taken into account. For Commercial, Residential, Agriculture and Industrial sector (Table 22) the average emission factors of greenhouse gas (CO2, CH4, N2O) and local air pollution (NOx, SO2, CO, VOC and PM10) are related to fuel consumption, so they are expressed in kt/PJ consumed. As concern CO2, the emission factors are reported in the base year templates, while for the other pollutants, the emission factors are included in the appropriate emission factor file. The Transport sector was characterized taking into account the different typologies of vehicles. As concerns cars, the national database reports the emission factors (expressed in g/Mvehicles) for type of vehicle, fuel alimentation and also in function of extra urban (SMEA), long (SMLA) and urban (SMUA) distances. Therefore, the emission factors were associated to the commodities SMEA, SMUA and SMLA (Table 23), expressed in MVehicles per km, in order to calculate the emissions due to cars. For diesel buses the average emission factors are expressed in g/vehicle-km, distinguishing between urban and extra-urban distance (Table 24). In the emissions files, where emissions are

Table 23 Average emission factors (g/Vehicle-km) for cars (Legend: SMEA: no of vehicles per km for extra-urban distance; SMLA: no of vehicles per km for long distance; SMUA: no of vehicles per km for urban distance). Diesel

Gasoline not catalyzed

Gasoline— catalyzed

LPG

Methane

SMEA TRACO2 TRACH4 TRAN2O TRANOx TRASO2 TRACOX TRAVOC TRAP10

1.49E  01 1.30E  05 2.70E 05 8.10E  04 6.10E  05 3.53E  04 3.54E  05 1.71E  04

1.52E  01 5.11E  05 5.00E  06 2.14E  03 3.91E  05 8.44E  03 1.20E  03 3.70E 05

1.35E 01 2.47E  05 1.60E  05 2.38E  04 3.45E  05 1.18E  03 9.17E  05 1.70E 05

1.35E 01 3.37E  05 1.50E  05 2.01E  03 0 1.70E 03 5.34E  04 3.80E  05

1.24E 01 2.94E  05 1.47E  05 1.72E 03 0 1.66E  03 3.57E  04 3.80E  05

SMLA TRACO2 TRACH4 TRAN2O TRANOx TRASO2 TRACOX TRAVOC TRAP10

1.92E  01 5.39E  06 2.70E 05 5.45E  04 4.75E  05 4.22E  04 1.02E  04 1.21E  04

1.67E 01 3.46E  05 5.00E  06 3.31E  03 4.29E  05 4.81E  03 6.86E  04 3.70E 05

1.83E  01 1.59E  05 3.50E  05 4.97E  04 4.68E  05 4.17E  03 6.86E  05 1.70E 05

1.71E  01 2.40E  05 1.50E  05 2.39E  03 0 1.56E  02 3.35E 04 3.50E  05

1.56E  01 1.67E 04 1.46E  05 4.47E  03 0 8.79E  03 7.61E  05 3.50E  05

SMUA TRACO22 TRACH4 TRAN2O TRANOx TRASO2 TRACOX TRAVOC TRAP10

2.67E 01 9.05E  06 2.70E 05 9.28E  04 8.51E  05 1.19E  03 3.06E  04 3.07E 04

2.66E  01 2.61E  04 5.00E  06 1.70E 03 6.83E  05 3.68E  02 3.69E  03 4.70E 05

2.96E  01 2.85E  04 5.30E  05 5.48E  04 7.58E  05 1.68E  02 1.25E  03 1.80E  05

2.31E  01 1.09E  04 1.50E  05 1.43E  03 0 9.32E  03 1.81E  03 4.50E  05

3.45E  01 1.97E 04 1.69E  05 1.88E  03 0 1.84E  02 2.38E  03 4.53E  05

Table 22 Average emission factors (kt/PJ) from commercial, residential, agriculture and industrial sector. Coal COMCO2 COMCH4 COMN2O COMNOx COMSO2 COMCOX COMVOC COMP10 RESCO2 RESCH4 RESN2O RESNOx RESSO2 RESCOX RESVOC RESP10 AGRCO2 AGRCH4 AGRN2O AGRNOx AGRSO2 AGRCOX AGRVOC AGRP10 INDCO2 INDCH4 INDN2O INDNOx INDSO2 INDCOX INDVOC INDP10

Biomass

0 3.20E  01 1.40E  02 8.00E  02 1.30E  02 7.50E þ 00 6.00E  01 2.61E  01

9.50E þ 01 1.50E  02 1.40E  02 1.25E  01 5.50E  01 9.17E  03 1.00E  02 4.40E  01

0 1.53E  02 3.50E  03 8.28E  02 3.55E  03 1.06E þ00 2.17E  01 3.50E  01

Diesel

Lpg

Petroleum products

6.93Eþ 01 7.00E  03 1.40E  02 5.00E  02 9.40E  02 2.00E  02 3.00E  03 3.60E  03 6.93Eþ 01 7.00E  03 1.40E  02 5.00E  02 1.80E  02 2.00E  02 3.00E  03 3.60E  03 6.93Eþ 01 1.20E  02 1.40E  02 1.30E þ00 9.40E  02 2.70E 02 8.80E  02 1.40E  02 6.93Eþ 01 2.00E  03 6.00E  04 7.00E  02 1.41E  01 1.00E  02 1.50E  03 6.70E 03

6.31E þ 01 1.00E  03 1.40E  02 5.00E  02 0 1.00E  02 2.00E  03 2.00E  03 6.31E þ 01 1.00E  03 1.40E  02 5.00E  02 0 1.00E  02 2.00E  03 2.00E  03 6.31E þ 01 1.00E  03 1.40E  02 5.00E  02 0 1.00E  02 2.00E  03 2.00E  03 6.31E þ 01 1.00E  03 1.40E  02 5.00E  02 0 1.00E  02 2.00E  03 2.00E  03

7.41E þ 01 3.00E  03 1.40E  02 1.50E  01 4.87E  01 1.60E  02 1.20E  02 5.87E  02 7.41E þ 01 3.00E  03 1.40E  02 1.50E  01 4.87E  01 1.60E  02 1.20E  02 5.87E  02

Fuel oil

7.41E þ01 3.00E  03 1.40E  02 1.60E  01 9.80E  01 1.00E  02 3.00E  03 2.12E  02

Other petroleum products

Natural gas

7.33Eþ 01 7.00E  03 1.40E  02 5.00E  02 2.00E  02 6.00E  02 3.00E  03 3.60E  03

5.61E þ 01 3.00E  03 3.00E  03 5.00E  02 0 2.50E  02 5.00E  03 6.70E 03 5.61E þ 01 3.00E  03 3.00E  03 5.00E  02 0 2.50E  02 5.00E  03 6.70E-03 5.61E þ 01 3.00E  03 3.00E  03 5.00E  02 0 2.50E  02 5.00E  03 6.70E 03 5.61E þ 01 5.00E  03 1.00E  01 1.00E  01 3.10E  04 1.00E  02 2.50E  03 1.70E  03

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Table 24 Average emission factors (g/Vehicle-km) for buses, motorcycles and trucks.

TRACO2 TRACH4 TRAN2O TRANOx TRASO2 TRACOX TRAVOC TRAP10

Diesel urban buses (g/vehicle)

Diesel extra-urban buses (g/vehicle)

Methane urban buses

Gasoline motorcycle (g/vehicle)

Diesel trucks (g/vehicle)

Gasoline trucks (g/vehicle)

9.16E þ 02 1.26E  01 3.00E  02 8.96E þ 00 1.76E  01 2.37E þ 00 1.15E þ 00 4.04E  01

5.70Eþ 02 5.10E  02 3.00E  02 3.71E þ 00 1.09E  01 1.03E þ00 6.58E  01 1.99E  01

5.61E þ01 (kt/PJ) 2.43E  06 (kt/Mpass) 8.48E  12 (kt/Mpass) 6.11E  02 (kt/PJ)

7.67Eþ01 2.14E  01 1.00E  03 3.00E  02 1.97E  02 1.47E þ 01 8.58E þ00 4.20E  02

5.70Eþ02 5.10E  02 3.00E  02 6.31E þ 00 1.09E  01 1.94E þ 00 9.70E 01 5.02E  01

4.68E þ02 1.10E  01 6.00E  02 7.26E þ 00 1.90E  02 5.21E þ01 5.16E þ00 4.88E  01

3.91E  04 (kt/Mpass) 3.06E  02 (kt/PJ) 9.17E  04 (kt/PJ)

associated to final demands (Mpass-km), they are converted in kt/Mpass-km considering the average number of passengers for vehicle. Instead for methane buses the average emission factors were derived from the NEEDS-Italy model [37] and expressed in kt/PJ consumed in the case of CO2, VOC, NOx and PM10 and in kt/Mpass-km for CH4, N2O and CO. As concern motorcycles and trucks (Table 24), the average emission factors are expressed in g/vehicle-km by national database [52,53] and then converted in kt/Mpass-km.

4. Conclusions This research dealt with the implementation of a regional energy system model based on the TIMES platform which is widely used in Europe and in other OECD countries to support energy and greenhouse gas reduction policies at local, national and supranational scale. The main aim was to set up a flexible and comprehensive representation of the local energy system for Basilicata region (Southern Italy) rooted in a national multi-regional model (MONET) with a twofold objective: to support the regional authority to formalize strategies in a manner consistent with a widely recognized and accepted methodology and to derive effective strategies for reaching the national energy and climate targets through regional burden sharing. To this end, this paper describes in detail how to implement from scratch an energy system model through building up the reference energy system and characterizing it from an economic, technological and environmental point of view. In fact, the definition of the reference energy system and the energy model’s database is a challenging step in energy system analysis and also a prerequisite base of knowledge for policy making. In particular, the study aimed at providing a methodological guidance to energy analysts and planners in order to overcome the common lack of reliable and desegregated data at regional scale which represents a main weak point. In fact, as concerns Italy the most recent energy balances focusing on the regional scale refer to 2008, and the situation is even worst at provincial and municipal scale, where data on energy consumption owned by different authorities are often aggregated and seldom updated. In this framework the selection of suited proxy variables represents a crucial issue to estimate reliable end-use consumption by sector for the base year (on the basis of data commonly available at larger scales, e.g. national) as well as to obtain sound projections over the considered time horizon. The implementation of the Basilicata region model is therefore aimed at illustrating the basic steps necessary to build the model’s data input, selecting proxy variables to downscale national data at local level as well as managing properly the scarce available data from local sources. In this application both supply (electricity and heat production) and demand (Commercial, Residential, Transport,

Industry and Agriculture) as well as the electricity transmission and distribution network were modelled considering also their contribution in terms of local air pollutant and greenhouse gas emissions. Moreover, starting from the year 2007 (the model’s reference year, for which the most recent data were available at local scale) the demand projections to 2030 by sector were carried out selecting appropriate demand drivers to build up the baseline scenario (“Business as Usual”). The next step will deal with the calibration and analysis of the baseline scenario to individuate the optimal mix of technologies and fuels that fulfil the energy demand on the basis of the current policy framework and the definition of alternative future scenarios. Another important step will be the evaluation of the possible development of the Basilicata Region energy system under different boundary conditions (energy, technology, socio-economic and environmental) in order to identify the drivers towards a low carbon economy.

Acknowledgements The TIMES-Basilicata model was implemented on the basis of the multi-region structure of the MONET—Multiregional Energy System Model in the framework of an Agreement between CNRIMAA and RSE (Research on the Electrical System S.p.A., former ERSE S.p.A.), 2010. The authors also want to express their gratitude to the two anonymous reviewers for their highly valuable comments. References [1] Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions. Analysis of options to move beyond 20% greenhouse gas emission reductions and assessing the risk of carbon leakage {SEC(2010) 650} /n COM/2010/0265 final n/; 2010. [2] Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions. Energy 2020—a strategy for competitive, sustainable and secure energy. {SEC(2010) 1346}/n COM/2010/0639 finaln/; 2010. [3] Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions. Energy Technologies and Innovations. {SWD(2013) 157 final} {SWD(2013) 158 final}nCOM/2013/0253 finaln/2013. [4] Liu F, Klimont Z, Zhang Q, Cofala J, Zhao L, Huo H, et al. Integrating mitigation of air pollutants and greenhouse gases in Chinese cities: development of GAINS-City model for Beijing. J Cleaner Prod 2013;58:25–33. [5] Jiang P, Chen Y, Geng Y, Dong W, Xue B, Xu B, et al. Analysis of the co-benefits of climate change mitigation and air pollution reduction in China. J Cleaner Prod 2013;58:130–7. [6] Selvakkumaran S, Limmeechokchai B. Energy security and co-benefits of energy efficiency improvement in three Asian countries. Renewable Sustainable Energy Rev 2013;20:491–503. [7] Joint impact assessment on the package of implementation measures for the EU’s objectives on climate change and renewable energy for 2020. 23 Jan 2008 —SEC (2008) 85. Available from: 〈http://ec.europa.eu/clima/policies/package/ docs/sec_2008_85_ia_en.pdf〉 [cited 24.03.2014].

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