Conceptualizing sustainable development of conventional power systems in developing countries – A contribution towards low carbon future

Energy 126 (2017) 112e123

Contents lists available at ScienceDirect

Energy journal homepage: www.elsevier.com/locate/energy

Conceptualizing sustainable development of conventional power systems in developing countries e A contribution towards low carbon future A. Merzic a, *, M. Music a, Z. Haznadar b a

Public Enterprise Elektroprivreda of Bosnia and Herzegovina, Department for Strategic Development, Vilsonovo Setaliste 15, 71 000 Sarajevo, Bosnia and Herzegovina Faculty of Electrical Engineering and Computer Science, Zagreb University, Department of Fundamentals of Electrical Engineering and Electrical Measurement, Unska 3, 10000 Zagreb, Croatia

b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 4 March 2016 Received in revised form 7 February 2017 Accepted 4 March 2017 Available online 9 March 2017

A transition plan for conventionally structured generation portfolios dominantly based on coal fired plants has been offered through four models. The models are primarily focused on elevated penetration of facilities based on intermittent renewable sources and CO2 emission reduction by at least 20% compared to the initial state, accordingly addressing balancing output power variation problems and social aspects of the considered society. These models are:

Keywords: Conventional power system CO2 emission reduction Developing countries Intermittent renewable energy sources Low carbon future Sustainable transition model


Flexible generation portfolio model, which can provide balancing power by itself;
Open system model that provides balancing power at the balancing market;
Hybrid system model with hybrid plants based on wind, hydro and solar energy, having the ability to store, convert and use this energy for balancing purposes;
Mix model that includes options from the previous three. The models are elaborated on an arbitrary conventional power system and simulated applying International Atomic Energy Agency's software tools. Considering chosen technical, economic, environmental and social parameters, conducted analyses resulted with the Mix model as the most suitable option for a sustainable development of the treated power system type. Due to similarities between generation portfolio structures in developing countries, the model can provide guidelines for sustainable planning and contribute to a low carbon future. © 2017 Elsevier Ltd. All rights reserved.

1. Introduction Due to increased concerns regarding rising demand for electricity, hardly predictable oil prices and greenhouse gas (GHG) emissions, the search for clean and efficient energy sources has been intensified. Governments are designing energy and environmental policies to minimize their exposure to volatile international fossil fuel prices and reduce carbon emissions in the energy sector, in particular the electricity power sector [1]. Appropriate directives, e.g. Ref. [2], strategies, e.g. Refs. [3e6] and guidelines have been

* Corresponding author. E-mail addresses: [email protected] (A. Merzic), elektroprivreda.ba (M. Music), [email protected] (Z. Haznadar). http://dx.doi.org/10.1016/j.energy.2017.03.016 0360-5442/© 2017 Elsevier Ltd. All rights reserved.

m.music@

issued, in order to promote the use of renewable energy sources (RES) and lead to their proper integration. In addition, conclusions of the UN Climate Change Conference held in Paris in December 2015 emphasize the transition towards a clean economy, suspending dangerous climate change. Additionally, a very important aspect linked to energy use is assigned to social issues of a country, as outlined in Refs. [7e9]. All this has been placed in the context of sustainable development in this paper, with a focus on the generation portfolio planning of an energy system. Generation portfolios represent a very important sub-system within energy systems and have a very important role within comprehensive sustainable development planning of a country. Thus, sustainable generation portfolio planning development here has been looked at as a process of change in which the exploitation of resources, the direction of

A. Merzic et al. / Energy 126 (2017) 112e123

Nomenclature BAT CCGT EPB&H EISD GHG HPP HPS HSSW LOLP O&M PHPP PVPP RoR TPP WPP

Best available technologies Combined cycle gas turbine Public Enterprise Elektroprivreda of Bosnia and Herzegovina Energy indicators for sustainable development Greenhouse gas Hydro power plant Hybrid power system Hybrid power system based on solar and wind energy Loss of load probability Operation and maintenance Pumped-storage hydro power plant Photovoltaic power plant Run-off river Thermal power plant Wind power plant

investments and the orientation of technological development enhance both current and future potential to meet human needs, evaluating sustainability in this paper through the consideration of several indicators, i.e. technical, economic, environmental and social parameters of the considered power system. 1.1. Research focus and objective Most power systems in developing countries and countries in transition are based on conventional energy sources, mainly on coal fired thermal power plants (TPP) used for base load generation and hydro power plants (HPP), also used to cover variations in consumption. Most often is the ratio of installed power and electricity production in such conventional systems in favor of TPP. Such systems are characterized by inflexibility and have been traditionally designed to meet own power needs. Given that energy represents one of the most important factors in the overall efforts for achieving sustainable development, countries tend to adopt such strategies and policies that will align their energy system's transition with the goals of sustainable development. In developed countries the debate on sustainability is mainly related to environmental protection, while in underdeveloped and developed countries the focus is more set to economic and social issues. This is also one of the reasons why developing countries resort to traditional power system planning by relying on national energy resources, fossil fuels (coal) in this sense, trying in this way to keep jobs as well, e.g. for those employed in TPP and coal mines. Thus, when projecting sustainable transition of power generation portfolios in underdeveloped and developing countries, social issues should be taken into account in particular. Inter alia, the social dimension reflects also the need for people to have access to electricity at an affordable price and in these countries there are still people which have no access to electricity [7e9]. Thus, the research focus of this paper are conventionally structured power generation portfolios, mainly in developing countries and their proper transition towards sustainable systems. Due to the generation portfolio energy mix and economic and social circumstances in these countries, it is much more difficult for those power systems to access sustainable development, compared to systems of developed and richer countries. Having also in mind the overtaken obligations from directives and development strategies [1e4], conventional power systems

113

need to make special efforts and find adequate ways to achieve sustainable development. Accordingly, measures taken to reduce emissions, with a focus on GHG, increased penetration of generation facilities based on intermittent RES, electricity market liberalization, approaching sources of electricity to consumers by means of distributed generation and increasing at the same time electricity access through micro systems, etc. represent “new” working conditions and considerable challenges for traditional power systems. The objective of this paper is to explore and propose a viable transition concept for conventional power systems into sustainable ones, by reaching specific RES share and decarbonization targets and bearing in mind the social aspect of the considered society, all discussed and elaborated through chosen sustainability indicators. Considering the so called “new” working conditions set before conventional power systems, a mid-term development and transition plan until year 2035 has been offered through four models, addressing also challenges in balancing output power variations from intermittent RES. The described research has been performed on an arbitrarily conceived generation portfolio of a conventional power system, which structure is based on a real power system in exploitation. With respect to similarities between generation portfolios of developing countries, and a special focus on South East European countries, proposed models can provide guidelines for an acceptable transition of conventionally structured generation portfolios into sustainable ones, within the framework of a low carbon future. 1.2. State of the art In available literature a variety of models used for sustainable development simulations are offered, e.g. reduction of GHG emissions (decarbonization) [10e12], integration of intermittent RES, finding the most appropriate way for balancing their output power variations [13e19], as well as determining the maximum acceptable level of RES penetration in a power system, as in Ref. [20]. Thus, in Ref. [11] an integrated optimization modeling approach has been developed for CO2 abatement planning through emission trading scheme and clean development mechanism. A number of studies and plans are available for China, an intensively developing country. Binding reductions in intensity of CO2 emissions per unit of gross domestic product have a significant reflection of the economy and the energy system of the country. In Ref. [12] 18 Chinese energy modeling tools have been reviewed and compared. A frequently used software tool in a variety of sustainable development simulations is EnergyPLAN [20e24]. In Ref. [21] the feasible wind power penetration in the existing Chinese energy system has been discussed using EnergyPLAN. EnergyPLAN has also been used in Ref. [24] where different future strategies for the Portuguese power system have been considered, including a 100% RES scenario. The concept of 100% RES has been considered in Ref. [23] for developing a model of the Hvar island power system, using the same software tool. EnergyPLAN has also been used in Ref. [20] to model the Irish energy system, identify future energy costs and the maximum wind penetration possible by 2020. In Ref. [25] EnergyPLAN has also been applied in combination with TIMES software for planning electricity systems with high penetration of renewables. One of the software tools used in sustainable development planning is PRIMES, applied in Ref. [10] where decarbonization of the EU economy by 2050 has been addressed. Another tool is the LEAP program used for the analysis of energy policies and programs to mitigate climate change, as e.g. in Ref. [26]. In future energy system plannings, hybrid power systems (HPS) are increasingly attracting attention and are seen as part of the solution that can contribute to sustainable development [27].

114

A. Merzic et al. / Energy 126 (2017) 112e123

Different software tools are also used for modeling various HPS concepts, as presented in Ref. [28] and a lot of research has been done on simulation, optimum sizing and techno-economic analysis of different HPS configurations, e.g. Refs. [29e31]. Not to suppress also a large number of researches for analyzing electricity systems with high penetration of intermittent RES dealing with power system stability issues and the applied models within, e.g. Refs. [32,33]. Simulations performed applying all mentioned tools are aimed to analyze possibilities of sustainable development and facilitate its implementation. The vast majority of published researches are focused on only selected sectors, e.g. the residential sector with the focus on reducing energy consumption and the associated greenhouse gas emissions as in Ref. [34]. Different methods for analyzing various options contributing to sustainable development have been applied in available literature as well. In this regard, the most commonly used method is the multi-level perspective method, as in e.g. Refs. [35e38]. By reviewing available literature, it can be seen that there are various models and methods for analysis and simulation in sustainable development planning, proposing solutions in particular segments of sustainable planning. In Refs. [39,40] different models for energy planning issues have been described. Energy systems in developing countries differ significantly from those in developed, industrialized countries, as emphasized in Ref. [41]. It has been generally agreed that most of the existing simulation tools and models are adapted to systems of developed countries, neglecting some important characteristics of developing countries. Accordingly, for sustainable development planning of conventional power systems suitable are software tools which enable the user to define certain restrictions (e.g. limit emissions), target achievements (e.g. RES share increase), working performance of generating units (e.g. working performance of a designed hybrid power system concept) etc. Having further in mind that the research performed within this paper proposes a transition model for conventionally structured generation portfolios of developing countries into sustainable power systems, suitable are software tools with the possibility of mid and long-term generation portfolio development planning. Thus, for the purpose of research demonstrated in this paper, selected are two software tools, i.e. MESSAGE and WASP IV, adapted to the treated problem. Published papers lack on researches when it comes to conventional power systems. Also, to the authors' best knowledge, MESSAGE and WASP IV software tools have not been used combined for sustainable development planning, simulation and analysis. The MESSAGE software tool has recently been used in Ref. [42], where a methodology for defining electric-sector reliability and variability as essential feature of renewable sources has been introduced. In this paper models for the transition of conventionally structured power generation portfolios into sustainable ones are conceived, aiming, amongst others, to achieve certain CO2 emission reduction and intermittent RES penetration increase, considering different ways of output power variation balancing, mainly for wind power plants (WPP) and photovoltaic power plants (PVPP), as well as their combined operation in certain HPS. Different output power variation balancing means are described in available literature and countries that have acceded to their intensive exploitation are already successfully coping with it. Usually, these are developed countries, such as Germany, Denmark, Netherlands, Spain, etc. In addition to the use of predictive models, flexible generation portfolio is being highlighted as a solution in articles [43e45]. Strong interconnections among neighboring countries can also ensure balancing power, as described in Refs. [43] and [46]. Closely related to interconnections is the possibility of providing balancing power at the balancing market, as presented in Refs. [47e49]. Energy

storage also facilitates the management of power systems with high intermittent RES penetration [50] and mitigates their variability [51]. There are different storage options, as stated in Refs. [52e54], further noting that storage is currently the weakest link in the energy domain, but a key element for increasing intermittent RES integration. A partial solution might also be the installation of a properly managed, wind-powered, pumped hydro energy storage system, as proposed in Ref. [55]. Certain benefits on balancing output power variations can further be achieved through the existence of appropriate HPS [56]. In this sense, the complementary use of wind and solar energy in specific HPS configurations can be influential, as presented e.g. in Ref. [57]. When it comes to the evaluation of sustainable development and guidance on that path, different approaches can be find in disposable literature, addressing various indicators, e.g. Refs. [5e9,58e66]. Thus, in articles [7,8] an analytical tool for the assessment of sustainable development of the energy sector has been presented. This joint work of five international agencies [7] identifies and describes 41 energy indicator for sustainable development (EISD) and provides guidance to establish them. These have further been applied in many researches, some of which are presented in articles [9,58e60]. The EISD are classified into three main groups, i.e. social, economic and environmental, whereby some EISD may be classified into more than one group, due to numerous connections between them [7]. The described approach together with the established EISD represents a very useful tool for policymakers, analysts and statisticians for their assessment of the current situation in the energy sector, the effectiveness evaluation of adopted energy policies and the redefinition of energy strategies on the path to sustainability. Even though the EISD set is not exhaustive, it covers the most important issues related to the energy sector for countries around the world. To apply the EISD package for the energy sector development in developed countries of the EU, preferable are: energy use; energy intensities; end-use intensities of economic branches; energy security and environmental energy impacts [60]. However, the social group of indicators are especially important for many underdeveloped and developing countries. In reports [5,6] the drives and risks preventing the development of sustainable energy systems are examined, recommending also an Agenda for Change to accelerate the global transition to sustainable systems. In Ref. [5], the Energy Sustainability Index evaluates how well some countries balance three goals of energy sustainability, defined as energy trilemma, i.e. energy security, energy equity and environmental sustainability. Many available researches attempt to address the energy trilemma, e.g. Refs. [61e64]. Article [61] is pointing to challenges for the energy governance in managing the trilemma in Indonesia. Further, it has been argued that security of supply of power systems has received less attention than the other two aspect of the trilemma, so more attention is paid to these issues in Ref. [62], indicating to all stakeholders in the energy business to strike a careful balance between the three aspects. On the trail of the above stated, respecting performed researches and established EISD, but at the same time recognizing overtaken obligations from the directives [2e4], which to a certain extend direct the development strategy in the treated group of countries, sustainability assessment of the proposed transition models for conventionally structured generation portfolios has been done considering certain technical, economic, environmental and social parameters, chosen as the basis for sustainable development. 2. Methodological approach In order to meet challenges placed before conventional power systems and contribute to the sustainability of developing

A. Merzic et al. / Energy 126 (2017) 112e123

countries, four different transition scenarios have been proposed and examined in this paper. A development plan until year 2035 has been offered, considering „new” working conditions set ahead, bearing in mind social aspects of the considered society. These conditions primarily include:
reducing the negative impact of the electricity sector on the environment, primarily by CO2 emission reduction for at least 20% compared to the initial state;
increased penetration of intermittent RES by at least 30% in installed power compared to the initial state;
liberalization of the electricity market. Regarding the, in this paper applied CO2 emission estimation approach, only running emissions without raw materials and construction phase have been considered. For a country having acceded „new” working conditions and thus decarbonization targets related to annual running emissions, the used approach can be considered as justified. Otherwise, life cycle CO2 emission assessment approach is recommended for application. For comparative purposes, the current principle of development planning of conventional power generation portfolios, without taking into account the defined „new” working conditions has also been simulated as the Baseline model. All these scenarios have been applied to an arbitrarily conceived conventional power generation portfolio of a developing country and examined through simulations in two software tools. International Atomic Energy Agency's software tools WASP IV and MESSAGE have been applied. Each model has been evaluated by the following values obtained through simulations: installed capacity per different generating facility type; energy deficient; RES share in total electricity generation; cumulative costs; total CO2 emissions and the highest LOLP value throughout the considered time period. These values expressed in relative terms, have further been used for the establishment of appropriate sustainability indicators, by which the evaluation of the proposed transition models has been performed. Thus, an analytical approach resting on multiple criteria analysis has been applied for the assessment and selection of the most suitable transition scenario, by optimizing technical, economic, environmental and social parameters of the considered power system. 2.1. Case study and initial assumptions formulation The generation portfolio structure of the conceived power

115

system consists of two coal-fired TPP and three cascade related HPP. The conceived structure is based on a real power system in exploitation, the power system of Public Enterprise Elektroprivreda of Bosnia and Herzegovina (EPB&H), in order not to undermine its functioning and stability. Thus, annual fixed operation and maintenance (O&M) costs, variable costs and the CO2 emission factor used for simulation purposes have been defined according to actual values of the existing generating units in EPB&H, in line with [67,68]. Further development is solely based on the idea and the sustainable development concept conceived within this research. Basic information on existing TPP and HPP are provided in Table 1 and Table 2, respectively. It is assumed that, as in most developing countries expected, TPP are with obsolete technologies, low efficiency and rather high emissions of pollutants and CO2 as well. Therefore, a gradual shut-down dynamics has been taken into account, resulting with a complete decommission of the thermal units by 2028 in accordance with presumed ages of these generating units. Existing HPP are in a good condition and do not require any repair other than regular annual overhauls during the planned period. 2013 has been selected as the base year. A period of 22 years has been treated for the transition process, i.e. until 2035. In the base year, peak load has been determined at 1.247 MW and accordingly the consumption at 7.210 GWh. Annual consumption growth rate of 3,3% has been taken into account, which corresponds to forecasts for power systems in developing countries, according to [69]. The discount rate of 8% per annum has been considered in each of the scenarios. During simulations, apart from the „new” working conditions, following has also been given attention to:
the initial conventional power system meets consumer needs;
reliability of the power system and security of supply shall not be compromised, which is considered through the allowed value of the Loss of load probability index (LOLP);
the existing distribution and transmission network can accept electricity and power from the generating facilities considered in the transition scenarios;
expected outages caused by regular annual overhauls for each of the considered generating units have been foreseen and respected in the simulations. Assuming that coal is a domestic resource and that local labor is engaged in its exploitation (i.e. in mines and in TPP), it has been foreseen that a part of consumer needs shall still be met by this type

Table 1 Basic information on existing TPP. TPP

Capacity [MW]

Efficiency [%]

Decommissioning dynamics [year: MW]

CO2 emission factor [kg/MWh]

Fixed O&M costs [USD/kW/yr]

Variable costs [USD/kW/yr]

TPP_1

651

28,8

1.062

299

28,46

TPP_2

410

30,4

2018: 91 2023:182 2026:180 2028:198 2021:100 2022:210 2023:100

187

57,93

Table 2 Basic information on existing HPP. HPP

Capacity [MW]

Usable volume [hm3]

Fixed O&M costs [USD/kW/yr]

Variable costs [USD/kW/yr]

HPP_S1 HPP_S2 HPP_S3

180 120 210

288 5 16

20 20 20

2 2 2

116

A. Merzic et al. / Energy 126 (2017) 112e123

of generating units in the future. This incorporates a certain part of the social aspect in the development strategy of the considered country and also ensures safe and reliable supply of electricity for covering a part of the base load. Thus, for replacing the TPP units, best available technologies (BAT) will be applied, increasing efficiency and significantly reducing emissions of pollutants and CO2. Desulfurization has been planned for the TPP units and has been simulated through increased costs of this generating facility. Due to specific requirements of the used software tools, this has been modelled as an increase in fixed O&M costs and costs of the resource for the use of limestone, for 25% and 20%, respectively, in relation to applied average cost values.

2.2. Transition models conceived In order to meet the targeted CO2 emission reduction and intermittent RES share increase and with regard to challenges in intermittent RES output power variation balancing, in this research the following four models have been established:





Flexible generation portfolio model; Open system model; Hybrid system model; Mix model.

These development models could possibly result in new TPP based on BAT (TPP_BAT), HPP represented as run-off river type (RoR), WPP, PVPP, CCGT, hybrid power systems based on solar and wind energy (HSSW) and pumped-storage HPP (PHPP). Basic information on possible new generating facilities, which are expected to be put into operation according to different transition scenarios, are given in Table 3. In majority of developing countries where consumer needs are primarily met by TPP, there are still large reserves of coal. Also, in the case of EPB&H, coal reserves are sufficient for the planned TPP_BAT, their life span and even more, [67,68]. But given that the focus of the transition is sustainable development with defined decarbonization targets in the electricity sector, installed capacities in TPP_BAT are limited to values given in Table 3. These data, among others, have further been used for modeling the proposed transition scenarios in two different software tools, i.e. WASP IV and MESSAGE. The upper installed capacity limit for the considered generating unit types is shown in the table, but depending on the scenario simulated, resulting capacities differ. Additionally, in each of the scenarios with high penetration of intermittent RES, their geographical dispersion is being planned, having a positive effect on reducing expected output power variations [70]. In each simulated transition model, the software tool was given the choice of integrating generating facilities in accordance with set assumptions and its operation algorithm for obtaining satisfactory

and optimal solutions. 2.2.1. Flexible generation portfolio model The Flexible generation portfolio model is designed to establish the desired flexibility of the product portfolio, able to accept the planned penetration of intermittent RES. Within this model, appropriate combined cycle gas turbines (CCGT) are scheduled. These units are characterized by a quick response, and can increase or decrease their output power in a short period of time, depending on the power fluctuations from e.g. WPP. CO2 emissions for the CCGT units are modelled according to [http://www.etsap.org/ (April, 2014.)], which correspond to approximately 2,3 times lower emissions of CO2 compared to emissions in the modelled TPP_BAT. 2.2.2. Open system model The Open system model takes into account the electricity market liberalization factor and thus provides balancing power at the balancing market. Since the WASP IV software tool does not provide the user with the opportunity to model the market, it has been modelled as a virtual power plant which MWh purchase price is taken over from [http://www.epexspot.com/ (March, 2014.)]. 2.2.3. Hybrid system model Hybrid power systems are considered an important contribution to sustainable development and various configurations are in operation today [56,71,72]. In this research, the Hybrid system model is conceived as a model with hybrid plants based on wind, solar and hydro energy, included in the generation portfolio, with the ability to store, convert and use this energy for balancing purposes. Introduction of a significant number of autonomous hybrid systems with smaller installed capacities, as the ones in e.g. Refs. [27,73,74] is foreseen in this model, too. That effect is assumed to be manifested in the reduction of the overall electricity consumption, i.e. decrease in peak load by 10%, by the end of the proposed transition period. Further in this transition scenario, the possibility of integrating hybrid systems based on WPP and PVPP at the same site, with equal participation in power has been conceived (HSSW). In that way, the complementarity of these two generating facilities is more respected, when it comes to output power variation and the need for its balancing [70,75]. HSSW is simulated as one generating facility, having characteristics of combined work of the WPP and PVPP, thus increasing the total capacity factor of the HSSW compared to the WPP and PVPP alone, decreasing expected output power variations in short time intervals and hence decreasing the needed balancing reserves in the power system. In addition, the combined work of WPP and PHPP is being considered in this transition model. It is conceived as a hybrid system with the ability to store, convert and use this energy for

Table 3 Basic information on possible new installed capacities. Generation facility type

Upper limit of installed capacity [MW]

Fixed O&M costs (with fuel price included) [USD/kW/yr]

Variable costs [USD/kW/yr]

CO2 emission factor [kg/MWh]

Investment costs [USD/kW]

TPP_BAT HPP WPP PVPP CCGT HSSW PHPP

1.700 341 1.000 500 550 300 350

136,9 5 3,8 1,7 617,7 5,5 5

11 2 8,5 4,2 8,5 12,7 2

730 0 0 0 340 0 0

2.555 2.654 1.649 2.900 1.000 4.594 2.464

A. Merzic et al. / Energy 126 (2017) 112e123

balancing purposes. The nighttime energy consumption is considered to be met by TPP_BAT in the system, whose shutdown during this period has no technical nor economic justification. Hence, the surplus WPP energy during the night is used to pump the water from the lower to the upper reservoir in the PHPP and thus store it for balancing purposes during the day. In that sense, the PHPP will be provided with more generators (pumps) having lower installed capacity values. 2.2.4. Mix model In the conceived Mix transition model, all proposed generating facilities, together with the options from the three previous models are considered during simulations.

LOLPðKt Þ < Ct

117

(3)

whereby At stands for the maximal reserves limit; Bt for the minimal reserve limit; Ct for the critical value of LOLP; Dt for the peak load; P(Kt) for the installed capacity in year t and Kt for the power generation portfolio configuration in year t. Due to specific requirements of the used WASP IV software tool, where only TPP, HPP and nuclear power plants have input requirements defined, WPP, PVPP and HSSW have been modelled as TPP with certain characteristics that simulate their operation in reality. Thus, output power variability of generating facilities based on intermittent RES has been simulated by increased forced outage rates in combination with appropriate values of their capacity factor.

2.3. Software tools applied Software tools applied for simulations in this paper are International Atomic Energy Agency's software tools WASP IV [76] and MESSAGE [77]. Both software tools are used for mid and long-term generation portfolio development planning, whereby WASP IV is based on a static planning principle and MESSAGE on a dynamic planning principle. 2.3.1. WASP IV software tool WASP IV (Wien Automatic System Planning) is used for optimal economical planning of the power generation portfolio expansion, taking into account certain restrictions set by the user. Restrictions may relate to the reliability degree of the power system, number of new generating units per year, emission amounts, fuel availability and annual electricity generation per unit. Its operating principle is based on:
probabilistic methods of engaging power facilities in order to satisfy consumption in the considered system;
linear programming techniques for determining the optimal dispatch of power facilities respecting set restrictions;
dynamic optimization methods for cost comparison of alternative development plans. The optimal development plan is determined based on discounted total costs. Possible development plans which meet set restrictions are estimated on the basis of the cost objective function B [76]. Chosen is the solution which provides the lowest value of B for the development plan j, according to (1):

Bj ¼

T   X I j;t  Sj;t þ Lj;t þ F j;t þ Mj;t þ Oj;t

(1)

j¼1

where I stands for capital investment costs; S for the residual value of the investment; L for the unamortized costs of capital investments (e.g. fuel inventory, initial stock of spare parts, etc.); F for fuel costs; M for maintenance costs; O for undelivered electrical energy costs; t for the time in years; T for the total number of years in the considered planning period. All costs are discounted to a certain discount rate i, which in (1) is represented with a line above each symbol. The optimal development plan is defined with minimal Bj among all j. For a development plan to be allowed, it is essential that restrictions regarding electricity supply are met. In this case, the following applies:

ð1 þ At Þ  Dt > PðKt Þ > ð1 þ Bt Þ  Dt

(2)

2.3.2. MESSAGE software tool The operation principle of the MESSAGE (Model for Energy Supply Strategy Alternatives and their General Environmental Impacts) software tool is based on the optimization of the objective function under a set of defined restrictions. It is a very complex software tool, which enables modeling of whole energy chains, from the very reserves, over each level of processing and transformation of the primary into the final energy form, including all losses that occur in the system. In it, an energy model is designed to formulate and evaluate alternative strategies of energy supply in accordance with restrictions defined by the user, e.g. restrictions on new investment, fuel availability, environmental standards, penetration rate of new technologies in the system, etc. 2.4. Sustainability assessment Upon performed simulations, obtained results have further been used for the establishment of appropriate sustainability indicators and the assessment of the conceived transition models. Since the challenge of moving from a conventional into a sustainable energy system requires the recognition of the energy systems' complexity in relation to social, technological, economic and environmental aspects, an analytical model as described in Ref. [27] has been applied for the choice of the preferred model amongst the four conceptualized ones. The assessment has been done focusing on multiple indicators divided into three major dimensions of sustainable development, i.e.:
techno-economic (systemic) indicators: reliability of supply, security of supply, power system independence, diversification of the product portfolio, cumulative costs;
environmental indicators: CO2 emission reduction, RES share in electricity generation;
social indicators: technology transfer (employment opportunities), electricity availability. In order to evaluate the functioning of the treated power system, reliability of supply and security of supply have been chosen as systemic indicators, considered through the LOLP index and energy deficient, respectively. To this group of indicators power system independence and diversification of the product portfolio have been added as important means in the concept of sustainable development. Economic feasibility of the model has been rated through the cumulative costs parameter, which includes construction costs, salvage values, O&M costs and energy not served costs throughout the considered time period. In the last decades, there has been a significant increase in GHG emissions, indicated as a key factor in climate change, whereas the energy sector is identified as the main to blame. The impact of the

118

A. Merzic et al. / Energy 126 (2017) 112e123

energy sector on the environment depends on how energy is being generated, i.e. the generation portfolio structure and its energy mix. In this regard, CO2 emission reduction and RES share in electricity generation have been chosen as major environmental indicators. As already pointed out, the social aspect of sustainability within the treated group of countries is of particular importance. Given that majority of electricity in conventionally structured generation portfolios is produced in TPP and that a large number of people are employed in these facilities, including mines, the shut-down of old thermal blocks, which is in line with the proposed strategy, will lead to job cuts. It should also be noted that in the context of the proposed transition process, significant integration of technologies that so far have not been present in these conventional power systems (WPP, PVPP, HPS, HSSW) is foreseen. Thus, and in line with [78], where technology promotion is recommended as an important policymaking tool, technology transfer has been chosen as a parameter to assess some of the social aspects. Technology transfer in this paper has been valorized through the possibility of acquiring new knowledge, development and, the most important, employment opportunities. In the evaluation of the social aspects of sustainability, electricity availability has also been included in this paper. This involves also the electrification of remote sites, especially enabled through microsystems and remote HSSW. After the establishment of the selected group of indicators, and in accordance with the approach described in Ref. [27], the mutual order of the considered models per sustainability indicator has to be determined in the first run. The assessment (ranking) of individual options based on defined sustainability indicators is performed in the range of 0 to n - 1, where n indicates the number of the models analyzed. In doing so, the largest value (n - 1) is then awarded to the model, which is the most favorable according to the criterion (sustainability indicator) observed. The preferred model is obtained by summing up the awarded values per sustainability criteria. In the second iteration, weighted values have been assigned to each of the indicators, in order to analyze the sensitivity of the proposed transition models. 3. Results Simulation results for the business as usual development scenario and the conceptualized transition models obtained through the applied software tools are summarized in Table 4. Given are

obtained characteristics for all conceived models, represented in relative terms for better comparative purposes, which have been used for the sustainability assessment and establishment of appropriate sustainability indicators further in the analysis. Relative values are established in the way that, by simulation obtained results are divided with the highest amount per individual characteristic. Thus, the highest installed capacity in CCGT by the end of the planning period has been obtained for the Flexible generation portfolio model, resulting in 550 MW, which in relative terms is expressed by 1. The Mix model resulted in 100 MW installed in CCGT. This vale (100 MW) further divided by the highest obtained amount (550 MW) between all considered transition models, resulted in 0,18 in relative terms. 3.1. Baseline model - the business as usual scenario results The Baseline model builds on the current practice of power system functioning in developing countries, without restrictions on GHG emissions and without integration of new generating facilities on alternative RES. The model is considered to show the power supply reliability and cost characteristics of the current development planning approach also in the future. Results obtained from the applied software tools are shown in Table 4 and are further used for comparative purposes with other proposed transition models. Secondary electricity generation output result from the MESSAGE software tool for the considered Baseline model is given in Fig. 1. Resulting CO2 emissions are displayed in Fig. 2. Reduction in emissions are evident during periods when outdated thermal units are gradually being put out of operation and the consumption has not yet increased significantly. However, the commissioning of new TPP_BAT units substantially increases the emissions, especially when they are dominantly meeting consumer needs, as reaching the last years of the planning period. 3.2. Flexible generation portfolio model results Obtained results according to this model are provided in Table 4, in relative terms. CO2 emissions do not exceed permissible limits. Emitted CO2 tones are below the upper limit when outdated TPP units are being put out of operation, and consumer needs are being met by new generating facilities.

Table 4 Simulation results expressed in relative terms. Characteristic

Baseline model

Flexible portfolio model

Open system model

Hybrid system model

Mix model

HPP e installed capacity by the end of the planning period TPP_BAT e installed capacity by the end of the planning period WPP - installed capacity by the end of the planning period PVPP e installed capacity by the end of the planning period PHPP e installed capacity by the end of the planning period HSSW e installed capacity by the end of the planning period CCGT e installed capacity by the end of the planning period Total installed capacity by the end of the planning period RES share in total electricity generation during the entire planning period Total CO2 emissions by the end of the planning period Total energy deficient Total energy taken over at the market Cumulative (total) costs The highest LOLP index value recorded during the considered planning period

1 1 e e e e e 0,7 0,57

1 0,43 1 1 e e 1 1 0,92

1 0,66 1 0,32 e e e 0,86 0,95

1 0,59 0,8 0,4 1 1 e 0,96 1

1 0,56 0,8 0 0,81 0,84 0,18 0,89 0,97

1 1 e 1 0,08

0,77 0,42 e 0,87 1

0,8 0 1 0,91 0,95

0,78 0,42 e 0,85 0,53

0,77 0,42 0 0,84 0,33

A. Merzic et al. / Energy 126 (2017) 112e123

119

16000 14000 12000

GWh

10000 8000 6000 4000 2000 0 201420152016201720182019202020212022202320242025202620272028202920302031203220332034

years unserved_en

TPP_1

TPP_2

TPP_BAT

HPP_1

HPP_2

HPP_3

RoR_1

RoR_2

Fig. 1. Annual secondary electricity generation [GWh] for the Baseline model.

10000

kton CO2

8000 6000 4000 2000 0 201420152016201720182019202020212022202320242025202620272028202920302031203220332034

years Fig. 2. Projection of CO2 [kt] emissions during the observed time period for the Baseline model.

3.3. Open system model results Simulation results for the Open system model are represented in Table 4. The advantages of this model is certainly the no energy deficiency during the entire planning period, whereas the CO2 emissions also remain below the allowable limit. 3.4. Hybrid system model results Obtained results for the Hybrid system transition model expressed in relative terms are shown in Table 4. CO2 emissions during the observed time period remain under the allowed upper limits. Furthermore, the largest RES share in electricity generation has been achieved, compared to other models considered. 3.5. Mix model Results are provided in Table 4 in form of relative values, and the annual secondary electricity generation by each generating facility during the considered time period is given in Fig. 3. CO2 emissions during the observed time period remain under the allowed upper limits and are shown in Fig. 4. 4. Discussion Considering the financial aspect, which in Table 4 is represented

by cumulative costs, the conventional principle of development planning requires the highest investment. Environmental requirements are not met. The implementation of this model takes a fairly long period, mainly due to the time required for the construction of new TPP. Such an approach can disrupt the security and reliability of power supply, if one takes into account the shut-down dynamics of the old TPP units, in the first years of the planning period. Further, it relies on coal. Although it has been assumed that the treated developing country exploits domestic deposits and that there are enough of them, reserves are limited. At a certain period in the future, such a system could be forced to import this fuel, which would further increase the overall financial structure and make the power system dependent on imports and the coal prices on the market. All four conceived transition models have resulted in a sustainable transition development plan, meeting the defined „new” working conditions. The LOLP index is within tolerable limits for all considered scenarios, where the best feature on that basis is evident for the Baseline model with the dominant production in TPP. Energy deficient is present in all considered models, expect for the Open system transition model, where all deficiencies can be compensated at the electricity market. The largest amount is noted for the Baseline model, due to decommissioning of old TPP, the lack of time for the construction of new generating facilities, and yet anticipated increase in electricity consumption. The highest RES share is achieved in the Hybrid and Mix models. Even a greater RES

120

A. Merzic et al. / Energy 126 (2017) 112e123

16000 14000 12000

GWh

10000 8000 6000 4000 2000 0 201420152016201720182019202020212022202320242025202620272028202920302031203220332034

years unserved_en

TPP_1

TPP_2

TPP_BAT

HPP_1

HPP_2

HPP_3

RoR_1

RoR_2

WPP

PVPP

HSSW

CCGT

PHPP

Fig. 3. Annual secondary electricity generation [GWh] for the Mix model.

kton CO2

8000 6000 4000 2000 0 201420152016201720182019202020212022202320242025202620272028202920302031203220332034

years CO2 value

CO2 upper limit

Fig. 4. Projection of CO2 [kt] emissions during the observed time period for the Mix model.

share can be expected due to significant integration of autonomous hybrid systems in remote areas with exploitable RES. According to economic indicators, the Mix model shows to be the most preferable option. The largest reduction in CO2 emissions is achieved in the Mix and Flexible portfolio model. As it can be seen, the selection of the most appropriate model depends on the criteria observed, e.g. lowest costs, largest emission reduction achieved, etc, which essentially represents a rating based on single criteria analysis. In this research, however, the choice of

the preferred model from the four conceptualized transition models is done in accordance to the approach described before, including multiple indicators influencing sustainable development. Establishing the mutual order of the considered models per chosen sustainability indicators as shown in Table 5, the Mix model shows to be the preferred amongst all considered development planning options. Even in the second iteration, when weighting values are awarded for each sustainability indicator and multiplied by values assigned during the mutual order determination, as

Table 5 Mutual order of the considered models per sustainability indicator. Sustainability indicator

Weighting value

Baseline model

Flexible portfolio model

Open system model

Hybrid system model

Mix model

Reliability of supply Security of supply Power system independence Diversification of the product portfolio Cumulative costs CO2 emission reduction RES share in electricity generation Technology transfer (employment) Access to electricity

0,13 0,13 0,13 0,045 0,13 0,13 0,045 0,13 0,13

4 0 3 0 0 0 0 0 0

0 1 1 2 2 3 1 2 2

1 2 0 1 1 1 2 1 1

2 1 4 3 3 2 4 3 3

3 1 2 4 4 3 3 3 3

A. Merzic et al. / Energy 126 (2017) 112e123

indicated in Table 5, the Mix model remains as the most suitable solution. In accordance with preferred characteristics of a sustainable system, as described in e.g. Refs. [3,4,10] and providing an objective and reliable model rating, equal and highest weighting values have been assigned to the following sustainability indicators: reliability of supply; security of supply; power system independence; cumulative costs; CO2 emission reduction; technology transfer and access to electricity. This has been done in order to provide normal functioning of the treated system considered through the chosen systemic parameters, addressing proposed social aspects of the considered society and at the same time focusing on its decarbonization, its independence and the lowest costs development model. Lower weighting values have been assigned to the diversification and RES share indicators, since both contribute to decarbonization. In order to conduct a sensitivity analysis, indicators have also been observed within groups in which they are classified (technoeconomic, environmental and social). Regardless of which indicator group advantage is assigned to, the Mix model is shown as the preferable transition scenario. It is followed by the Hybrid system model, Flexible portfolio model, then the Open system model and finally the Baseline model. The only change in the mutual order of other scenarios occurs when an advantage of 90% or higher is assigned to the techno-economic group of indicators (i.e. weighting values of 0,18 or higher) and the remaining two groups of 5% share, each (i.e. weighting values of 0,025). The ranking is altered in such a way that the Open system model becomes the last ranked. Slight changes occur also in the case when the environmental or the social group of indicators an advantage of 95% or more is assigned. In this case, the Hybrid system model closely follows the Mix model, sharing the first place in ranking. 5. Conclusions Promoting sustainable development and climate change mitigation have become integral aspects of energy planning, analysis and creation of development policies in many countries. Emission reduction and RES integration should be an integral part of strategic decisions. However, conventionally structured power systems of developing countries are placed in front of special challenge in this regard. Conducted simulations and analyzes indicate that the current way of power system generation portfolio development planning needs changes. It is no longer a question of whether to continue to rely on technologies that consume limited reserves of available energy sources and thereby emit pollutants, but how fast and to what extent will different power systems accept and integrate RES, thus contributing to sustainable development. Performed researches, obtained results, as well as the applied sustainability assessment through the chosen set of indicators emphasize the Mix model, among four conceived, as the most favorable transition scenario for development planning of conventionally structured power systems in „new” working conditions. Although two different software tools which work on different planning principles have been applied for simulation purposes, i.e. WASP IV on a static and MESSAGE on a dynamic planning principle, obtained results point to the same conclusions. The generation portfolio structure in the Mix model is mainly based on domestic energy sources and the mutually arranged work and functioning of the generating units in the system. For a more effective way of balancing output power variations caused by high penetration of intermittent RES in the system, it is very important to take advantage of the mutual complementarity of individual sources. The idea is to get best performances of the system as a whole, reduce variability of output power variations, e.g. by

121

implementing HPS based on WPP and PHPP and HSSW, thereby increasing the efficiency of their use and operation, thus contributing to the power system adequacy. Further, the integration of autonomous HPS based on RES can reduce the total system load, losses during transmission and distribution and the negative impact on the environment. Additionally, an increase in electricity availability in remote places can be achieved by implementing these facilities in micro-grids, as proposed in this paper. Another very important social, but at the same time economic aspect addressed in this transition scenario is the employment. This can be achieved through the transfer of technologies and knowledge from developed to developing countries with the aim of creating new job opportunities and compensating the loss of jobs due to the withdrawal of obsolete technologies in old TPP. The conceived Mix model is characterized by the diversification of mostly locally available resources. The resulting mixture is sufficiently stable to meet the expected increase in consumption, flexible enough to respond to power variations and balance differences, „clean” enough to meet expected emission restrictions, affordable enough to be acceptable to consumers, and takes care about employment opportunities at the same time. The effectiveness of this combination will further be supported by the implementation and development of smart grids. Thus, having in mind the unenviable position of conventionally structured power systems, obligations taken over through the implementation of directives, the quite complex decision-making processes needed to realise a sustainable energy system, the proposed development scenario with the chosen set of indicators and their evaluation as described in this paper, offer a useful mean for decisionmakers when it comes to tracing sustainable transition of conventionally structured generation portfolios in developing countries. With respect to similarities between generation portfolio structures in South East European countries and other developing countries, characterized by a conventional power generation portfolio and exposed to challenges of the “new” working conditions, the proposed transition model can provide guidelines and principles for timely identifications, preparations and actions on the way towards sustainable planning and development, and contribute to a low carbon future, as the ultimate goal.

References [1] CIGRE working group C1/C2/C6.18, coping with limits for very high penetrations of renewable energy. February 2013. [2] European parliament and the council of the European union, directive 2009/ 28/EC on the promotion of the use of energy from renewable sources. 2009. [3] European Commission. Energy 2020. Brussels, Belgium: European Union; 2011. [4] European Climate Foundation. Energy roadmap 2050. Brussels, Belgium: European Union; 2010. [5] World Energy Council (WEC). World Energy Trilemma. Time to get real e the case for sustainable energy investment. United Kingdom. September. 2013. [6] World Energy Council (WEC). World Energy Trilemma 2016: defining measures to accelerate the energy transition. United Kingdom. May. 2016. [7] Vera IA, Langlois LM, Rogner HH, Jalal AI, Toth FL. Indicators for sustainable energy development: an initiative by the international atomic energy agency. Nat Resour Forum November, 2005;29(4):274e83. [8] Vera I, Langlois L. Energy indicators for sustainable development. Energy June, 2007;32(6):875e82. [9] Kemmler A, Spreng D. Energy indicators for tracking sustainability in developing countries. Energy Policy April, 2007;35(4):2466e80. [10] Capros P, Tasios N, De Vita A, Mantzos L, Paroussos L. Model-based analysis of decarbonising the EU economy in the time horizon to 2050. Energy Strategy Rev September, 2012;1(2):76e84. [11] Li YP, Huang GH, Li MW. An integrated optimization modeling approach for planning emission trading and clean-energy development under uncertainty. Renew Energy February, 2014;62:31e46. [12] Mischke P, Karlsson KB. Modelling tools to evaluate China's future energy system e a review of the Chinese perspective. Energy May, 2014;69:132e43. [13] Borggrefe F, Neuhoff K. Balancing and intraday market design: options for

122

A. Merzic et al. / Energy 126 (2017) 112e123

wind integration. Climate Policy Intiative, BIW Berlin. 2011. [14] Ackermann T, Abbad JR, Dudurych IM, Erlich I, Holttinen H, Kristoffersen JR, et al. European balancing act. IEEE Power Energy Mag. November/December, 2007:90e130. [15] Ummels B. Power system operation with large-scale wind power in liberalised environments. Dissertation. Netherlands: Technical University Delft; 2009. [16] Diaz-Gonzalez F, Sumper A, Gomis-Bellmunt O, Villafafila-Robles R. A review of energy storage technologies for wind power applications. Renew Sustain Energy Rev May, 2012;16(4):2154e71. [17] Halamay DA, Brekken TKA, Simmons A, McArthur S. Reserve requirement impacts of large-scale integration of wind, solar and ocean wave power generation. IEEE Trans Sustain Energy July, 2011;2(3):321e8. [18] Khodayar ME, Wu Lei, Shahidehpour M. Hourly coordination of electric vehicle operation and volatile wind power generation in SCUC. IEEE Trans Smart Grid September, 2012;3(3):1271e9. [19] Pillai JR. Electric vehicle based battery storages for large scale wind power integration in Denmark. Dissertation. Denmark: Aalborg University; 2010. [20] Connolly D, Lund H, Mathiesen BV, Leahy M. Modelling the existing Irish energy-system to identify future energy costs and the maximum wind penetration feasible. Energy May, 2010;35(5):2164e73. [21] Liu W, Lund H, Mathiesen BV. Large-scale integration of wind power into the existing Chinese energy system. Energy August, 2011;36(8):4753e60. [22] Ma T, Ostergaard PA, Lund H, Yang H, Lu L. An energy system model for Hong Kong in 2020. Energy April, 2014;68:301e10. [23] Medic ZB, Cosic B, Duic N. Sustainability of remote communities: 100% renewable island of Hvar. J Renew Sustain Energy 2013;5(4). [24] Fernandes L, Ferreira P. Renewable energy scenarios in the Portuguese electricity system. Energy May, 2014;69:51e7. [25] Pina A, Silva CA, Ferrao P. High-resolution modeling framework for planning electricity systems with high penetration of renewables. Appl Energy December, 2013;112:215e23. [26] Park NB, Yun SJ, Jeon EC. An analysis of long-term scenarios for the transition to renewable energy in the Korean electricity sector. Energy Policy January, 2013;52:288e96. [27] Merzic A, Music M, Rascic M, Hadzimejlic N. An integrated analysis for sustainable supply of remote winter tourist centers - a future concept case study. Turkish J Electr Eng Comput Sci 2016;24:3821e37. http://dx.doi.org/10.3906/ elk-1412-48. [28] Sinha S, Chandel SS. Review of software tools for hybrid renewable energy systems. Renew Sustain Energy Rev April, 2014;32:192e205. [29] Bernal-Agustín JL, Dufo-Lopez R. Simulation and optimization of stand-alone hybrid renewable energy systems. Renew Sustain Energy Rev October, 2009;13(8):2111e8. [30] Zhou W, Lou C, Li Z, Lu L, Yang H. Current status of research on optimum sizing of stand-alone hybrid solarewind power generation systems. Appl Energy February, 2010;87(2):380e9. [31] Karakoulidis K, Mavridis K, Bandekas DV, Adoniadis P, Potolias C, Vordos N. Techno-economic analysis of a stand-alone hybrid photovoltaic-dieselebattery-fuel cell power system. Renew Energy August, 2011;36(8):2238e44. [32] Sanchez JA, Veganzones C, Martínez S, Blazquez F, Herrero N, Wilhelmi JR. Dynamic model of wind energy conversion systems with variable speed synchronous generator and full-size power converter for large-scale power system stability studies”. Renew Energy June, 2008;33(6):1186e98. [33] Foley AM, Gallachoir BPO, Hur J, Baldick R, McKeogh EJ. A strategic review of electricity systems models. Energy December, 2010;35(12):4522e30. [34] Swan LG, Ugursal VI. Modeling of end-use energy consumption in the residential sector: a review of modeling techniques. Renew Sustain Energy Rev October, 2009;13(8):1819e35. [35] Foxon TJ. A coevolutionary framework for analysing a transition to a sustainable low carbon economy. Ecol Econ October, 2011;70(12):2258e67. [36] Rosenbloom D, Meadowcroft J. The journey towards decarbonization: exploring socio-technical transitions in the electricity sector in the province of Ontario (1885e2013) and potential low-carbon pathways. Energy Policy February, 2014;65:670e9. [37] Foxon TJ. Transition pathways for a UK low carbon electricity future. Energy Policy January, 2013;52:10e24. [38] Ahmad S, Tahar RM. Selection of renewable energy sources for sustainable development of electricity generation system using analytic hierarchy process: a case of Malaysia. Renew Energy March, 2014;63:458e66. [39] Pfenninger S, Hawkes A, Keirstead J. Energy systems modeling for twenty-first century energy challenges. Renew Sustain Energy Rev May, 2014;33:74e86. [40] Connolly D, Lund H, Mathiesen BV, Leahy M. A review of computer tools for analysing the integration of renewable energy into various energy systems. Appl Energy April, 2010;87(4):1059e82. [41] Urban F, Benders RMJ, Moll HC. Modelling energy systems for developing countries. Energy Policy June, 2007;35(6):3473e82. [42] Sullivan P, Krey V, Riahi K. Impacts of considering electric sector variability and reliability in the MESSAGE model. Energy Strategy Rev March, 2013;1(3): 157e63. [43] Gruop of Authors. Design and operation of power systems with large amounts of wind power, final report IEA WIND Task 25. Helsinki: VTT Tiedotteita; 2009. [44] Lukac A, Music M, Avdakovic S, Rascic M. Flexible generating portfolio as basis for high wind power plants penetration - Bosnia and Herzegovina case study. In: Proceedings of IEEE/PES - 10th international conference on environment

and electrical engineering, Rome, Italy; 2011. [45] Puga JN. The importance of combined cycle generating plants in integrating large levels of wind power generation. Electr J September 2010;23(7):33e44. [46] Holttinen H, Meibom P, Orths A, Lange B, O'Malley M, Tande JO, et al. Impacts of large amounts of wind power on design and operation of power systems, results of IEA collaboration. In: 8th international workshop on large scale integration of wind power into power systems as well as on transmission networks of offshore wind farms, Bremen; 2009. [47] Borggrefe F, Neuhoff K. Balancing and intraday market design: options for wind integration. BIW Berlin. 2011. [48] Frunt J, Kling WL, Hermans RM, Nobel FA, de Boer WW. Impact of design variables on balancing markets. In: 7th international conference on the european energy market; 2010. [49] Ackermann T, Abbad JR, Dudurych I, Erlich I, Holttinen H, Kristoffersen JR, et al. European balancing act. IEEE Power Energy Magazine. November/ December, 2007. [50] Beaudin M, Zareipour H, Schellenberglabe A, Rosehart W. Energy storage for mitigating the variability of renewable electricity sources: an updated review. Energy Sustain Dev December, 2010;14(4):302e14. [51] Beaudin M, Zareipour H, Schellenberglabe A, Rosehart W. Energy storage for mitigating the variability of renewable electricity sources: an updated review. Energy Sustain Dev December, 2010;14(4):302e14. [52] Ibrahim H, Ilinca A, Perron J. Energy storage systems - characteristics and comparisons. Renew Sustain Energy Rev June, 2008;12(5):1221e50. [53] Diaz-Gonzalez F, Sumper A, Gomis-Bellmunt O, Villafafila-Robles R. A review of energy storage technologies for wind power applications. Renew Sustain Energy Rev May, 2012;16(4):2154e71. [54] Zhao H, Wu Q, Hu S, Xu H, Rasmussen CN. Review of energy storage system for wind power integration support. Appl Energy January, 2015;137:545e53. [55] Padron S, Medina JF, Rodríguez A. Analysis of a pumped storage system to increase the penetration level of renewable energy in isolated power systems. Gran Canaria: a case study. Energy December, 2011;36(12):6753e62. [56] Nema P, Nema RK, Rangnekar S. A current and future state of art development of hybrid energy system using wind and PV-solar: a review. Renew Sustain Energy Rev October, 2009;13(No. 8):2096e103. [57] Merzic A, Music M, Redzic E, Aganovic D. World Scientific and Engineering Academy and Society - WSEAS Transactions on Power Systems. Comparative advantages using solar and wind energy in hybrid systems at the same site, vol. 9; 2014. p. 273e80. [58] Ledoux L, Mertens R, Wolff P. EU sustainable development indicators: an overview. Nat Resour Forum November, 2005;29(4):392e403. [59] Unander F. Energy indicators and sustainable development: the International Energy Agency approach. Nat Resour Forum November, 2005;(4):377e91. [60] Streimikiene D, Ciegis R, Grundey D. Energy indicators for sustainable development in Baltic States. Renew Sustain Energy Rev June, 2007;11(5): 877e93. [61] Gunningham N. Managing the energy trilemma: the case of Indonesia. Energy Policy March, 2013;54:184e93. [62] Boston A. Delivering a secure electricity supply on a low carbon pathway. Energy Policy January, 2013;52:55e9. [63] Bale CSE, Varga L, Foxon TJ. Energy and complexity: new ways forward. Appl Energy January, 2015;138:150e9. [64] Heffron RJ, McCauley D, Sovacool BK. Resolving society's energy trilemma through the Energy Justice Metric. Energy Policy December, 2015;87:168e76. [65] Mainali B, Pachauri S, Rao ND, Silveira S. Assessing rural energy sustainability in developing countries. Energy Sustain Dev April, 2014;19:15e28. [66] Narula K, Reddy BS. Three blind men and an elephant: the case of energy indices to measure energy security and energy sustainability. Energy February, 2015;80:148e58. [67] Sarajevo Public Enterprise Elektroprivreda of Bosnia and Herzegovina: master plan for the development of generating units in the power system of EPB&H until year 2030. 2014. [68] Sarajevo Public Enterprise Elektroprivreda of Bosnia and Herzegovina: annual reports on business for 2014. 2015. [69] U. S. Energy Information Administration. International energy outlook 2011. 2011. [70] Merzic A, Music M, Dzananovic I, Redzic E, Aganovic D. The quantitative effect of geographical dispersion of intermittent renewable energy sources on output power variation balancing. In: Proceedings of IEEE/PES ENERGYCON 2014; 2014. p. 366e71. [71] Nehrir MH, Wang C, Strunz K, Aki H, Ramakumar R, Bing J, et al. A review of hybrid renewable/alternative energy systems for electric power generation: configurations, control and applications. IEEE Trans Sustain Energy May, 2011;2(4):392e403. [72] Hazelton J, Bruce A, MacGill I. A review of the potential benefits and risks of photovoltaic hybrid mini-grid systems”. Renew Energy July, 2014;67:222e9. [73] Bernal-Agustin JL, Dufo-Lopez R. Simulation and optimization of stand-alone hybrid renewable energy systems. Renew Sustain Energy Rev October, 2009;13(8):2111e8. [74] Rehman S, Alam MM, Meyer JP, Al-Hadhrami LM. Feasibility study of a windepvediesel hybrid power system for a village. Renew Energy February, 2012;38(1):258e68. [75] Music M, Merzic A, Redzic E, Aganovic D. Complementary use of solar energy in hybrid systems consisting of a photovoltaic power plant and a wind power plant. Proc IEEE EED 2013 2013:106e11.

A. Merzic et al. / Energy 126 (2017) 112e123 [76] International Atomic Energy Agency. Wien automatic system planning (WASP) package, version WASP-IV, user manual. Austria. 2006. [77] International Atomic Energy Agency. MESSAGE - model for energy supply strategy alternatives and their general environmental impacts, user manual.

123

June, 2007. [78] Littlefield SR. Security, independence, and sustainability: imprecise language and the manipulation of energy policy in the United States. Energy Policy January, 2013;52:779e88.