Increasing shares of intermittent sources in Reunion Island: Impacts on the future reliability of power supply

Renewable and Sustainable Energy Reviews 46 (2015) 120–128

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Increasing shares of intermittent sources in Reunion Island: Impacts on the future reliability of power supply Mathilde Drouineau a,n, Edi Assoumou a, Vincent Mazauric b, Nadia Maïzi a a b

MINES ParisTech, Centre for Applied Mathematics, CS 10207, 06904 Sophia Antipolis Cedex, France Schneider Electric, Strategy & Innovation, 38TEC/T1, 37 quai Paul-Louis Merlin, 38050 Grenoble, France

art ic l e i nf o

a b s t r a c t

Article history: Received 13 September 2013 Received in revised form 17 January 2015 Accepted 8 February 2015 Available online 9 March 2015

This paper analyzes the capability of Reunion Island to achieve electricity autonomy by 2030. Currently, electricity production in Reunion Island is mainly based on imported fuels while it is blessed with high levels of renewable energy potentials. The issue addressed in this paper is the technical and economical feasibility of this ambitious target. The approach relies on a prospective study conducted by the TIMES-Reunion model which provides future production mixes according to different scenarios. It is combined with a quantitative assessment of reliability of power supply with two reliability indicators, regarding that intermittent sources may highly develop and consequently worsen reliability. This study enables us to draw three main conclusions: (i) electricity autonomy can be achieved thanks to high levels of biomass production and of intermittent sources; (ii) however, since fuel oil's power plants appear as back-up units, the reliability of power supply will be lowered. This is illustrated by the decrease of the reliability indicators over the time horizon; (iii) however, provided that appropriate rules on the instantaneous production are enforced, a generation mix that both complies with the electricity autonomy target and with a satisfying reliability of power supply is possible. & 2015 Elsevier Ltd. All rights reserved.

Keywords: Long-term energy planning Reunion Island Reliability of power supply

Contents 1. 2.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Context for power production in Reunion Island. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. A necessary change in power production: currently based on imported fuels while high levels of domestic renewable sources are available in Reunion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. A power demand driven by the possible development of electrical vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. General description of the model TIMES-Reunion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Specification of the long-term scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. The reliability indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Results and discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Impacts on the future production mix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Impacts on the level of installed capacities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3. Impacts on reliability of power supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

n Corresponding author. Present address: EDF R&D, 1 avenue du Général de Gaulle, BP 408, 92 141 Clamart Cedex, France. Tel.: þ 33 1 47 65 47 20; fax: þ33 1 47 65 42 06. E-mail addresses: [email protected] (M. Drouineau), [email protected] (E. Assoumou), [email protected] (V. Mazauric), [email protected] (N. Maïzi).

http://dx.doi.org/10.1016/j.rser.2015.02.024 1364-0321/& 2015 Elsevier Ltd. All rights reserved.

120 121 121 121 122 122 123 123 123 123 125 126 127 127 127

1. Introduction Pushed by the need for carbon emission abatement and the expected depletion of fossil fuels, significant changes will impact future generation shares in electricity production and architecture of power systems. Among possible options of development,

M. Drouineau et al. / Renewable and Sustainable Energy Reviews 46 (2015) 120–128

increasing shares of renewable energy sources are attractive alternatives for a cleaner and unlimited power generation. In particular, high shares of renewable energy sources may become a critical aspect of future energy systems, both for centralized scheme and for distributed architecture. The integration of renewable energy sources in electricity production has indeed been widely studied to determine their development's challenges and options [1–4]. Current studies analyze drivers and barriers to the target of decarbonizing the electricity mix [5–9]. These studies provide methods to estimate the impacts the decarbonization will have on the electrical sector and the changes required. In this context, the emergence of different paradigms for serving electricity than those for which the system was designed [10] challenges the future changes of the electricity production mix. These features have rapidly been encountered in remote territories as small islands. Small islands indeed mainly rely on imported fossil fuels for energy production [11,12] so that they are likely to be pioneers regarding the latter changes. In this paper, we focus on the case of the Reunion Island which is a salient example of the “decarbonization” of a production mix since its local authorities have set the ambitious objective by 2030 of reaching self-sufficiency. Considering that a little above one third of electricity production is currently based on renewable sources and that most of existing power plants will be removed within the next two decades, the power sector in Reunion is thereby expected to change substantially. Several analyses have already studied possible options that will draw Reunion towards a more sustainable energy system [13,14]. They exhibit the available potentials for renewable energy sources and show that Reunion is blessed with abundant resources such as sugarcane bagasse, solar, wind, geothermal and marine energies. Beyond these studies, a prospective analysis is conducted herein to determine the long-term development of the Reunion's power system and to evaluate its capability to reach a production mix with 100% renewable sources by 2030. The analysis, performed with the long-term energy-planning model TIMES-Reunion, enables an evaluation of power sector investment options and activity levels against a multiplicity of load growth and resource supply scenarios. However, since power supply is usually weakly reliable on small islands, a large integration of renewable energy sources, and especially of intermittent sources, raises technical issues and may lower the reliability of power supply. It is therefore recommended to consider reliability of supply when building options with large integration of intermittent sources, especially for the small, weakly meshed, and remote power system of the Reunion Island. In fact, the reliability of power supply, in Reunion Island is currently lower than in a wide and integrating power system (the average duration of electricity not supplied is estimated at 4 h/year/consumer, compared to 73 min in Metropolitan France as stated by ERDF, the main distributor system operator). In this paper, we propose to analyze both in terms of renewable energy potentials and of economical and technical feasibility the capability of the Reunion's power system to achieve electricity autonomy by 2030. This approach is, to the best of our knowledge, the first prospective study combined with a quantitative assessment of reliability of power supply. Section 2 briefly explains the context of power production in Reunion Island. In Section 3, we then describe the main principles of the TIMES-Reunion model, used to perform the prospective analysis, and reliability indicators that assess the reliability of power systems' management according to their dynamical properties. In the fourth section, we present the main characteristics of the electricity production in 2030 in Reunion Island for the different scenarios and discuss their relevance through analyses

121

that study both economical aspects and the long-term evolution of supply reliability.

2. Context for power production in Reunion Island 2.1. A necessary change in power production: currently based on imported fuels while high levels of domestic renewable sources are available in Reunion First, electricity production in Reunion strongly relies on coal and fuel oils as illustrated in Table 1. For the year 2010, two thirds of the 2699 GWh produced were based on fossil fuels. The electricity sector is therefore almost responsible for half of CO2 emissions in Reunion, i.e. 49% in 2010 [15]. The production facilities are mainly composed of thermal units: 221 MW work either with coal or sugarcane bagasse, used for base loads, and 265 MW work with heavy or distillate fuel oils, used for semi-base and peak loads. Besides, nine diesel engines of 18.3 MW have in the recent years replaced old fuel oils units (125 MW). Their future activity is driven by the future prices of fossil fuel imports provided by the World Energy Outlook [16]. Secondly, Reunion Island is blessed with high potentials of renewable energy sources, whose development has known a noticeable increase in the last decade thanks to local and national energy policies. Two plans, one launched by the Regional Council of Reunion (called PRERURE) in 2000 and one national (called GERRI) launched in 2008, have indeed promoted investments to achieve an energy mix with 100% renewable energy sources by 2025 through incentive mechanisms such as tax exemptions, direct subsidies or feed-in tariffs. Since, photovoltaics systems have strongly developed and amounted to 130 MW at the end of 2011. This growth has lead the authorities to set a limit of 30% of intermittent sources in the instantaneous electricity production following the recommendations of EDF, the electricity provider, on the impacts of intermittent generation in a remote island power system [18]. The increase of renewable energy sources in the electricity production mix can continue considering the renewable energy potentials of Reunion Island which are presented in Table 2. The given figures rely on data provided by [13,14] and on discussions with experts. More details are given in [19]. 2.2. A power demand driven by the possible development of electrical vehicles Focusing on the electricity demand, the average growth rate of electricity consumption was approximatively 5.3% per year

Table 1 Shares of electricity production in Reunion Island in 2010 and installed capacities at the 1/1/2012 [17]. Sources

Shares (%)

Installed capacities (MW)

Imported fossil fuels Coala Fuel oil (heavy and distillate)

49 18

52.5 265

Domestic and renewable sources Sugarcane bagasse Hydroelectricity Wind energy Photovoltaics Municipal waste

10 20 0.6 2.8 0.3

159 146 16.5 130 4

a Most capacities functioning with coal also work with sugarcane bagasse and are therefore included in sugarcane bagasse capacities.

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Table 2 Current use of renewable energy sources and their potentials in 2030. Resources Biomass Sugarcane bagasse Non-sugar cane Wood and green waste Hydropower Geothermal energy Ocean energy OTECa Wave energy Wind onshore Solar Biogas

Table 3 Growth of electricity consumption in the Reunion Island proposed by EDF.

2008 levels

2030 potentials

Characteristics of electricity growth in the scenarios

25,000 ha – – 121 MW –

25,000 ha 7500 ha 67,500 t 268 MW 20 MW

– – 16.8 MW 130 MWb 4 MW

100 MW 50 MW 50 MW 750 MW –

Medium demand Consumption (GWh) Growth rate (%) Peak power (MW) Enhanced DSMa Consumption (GWh) Growth rate (%) Peak power (MW) Electrical vehicles Consumption (GWh) a

a b

2010 2015 2020 2025 2030

2710 3110 3.2 2.6 445 520

3500 3805 4100 2.4 1.5 1.5 595 670 720

2705 3020 3130 3200 3248 3.1 2.2 0.7 0.4 0.3 435 480 521 560 596 1400

Demand-Side Management.

Ocean Thermal Energy Conversion. In 2012. Table 4 Installed capacities (MW) in Reunion Island in 2030 for the different scenarios.

between 2000 and 2005 and decreased to 3.5% between 2005 and 2010. Such inflexion is the result of a demand-side management program defined since 2000 in Reunion which has compensated for the economic growth. For the coming decades, the rate of growth of electricity consumption should continue to decline due to the demographic slowdown and to the short-term retrofitting equipment rate. Four different electricity demand projections in Reunion until 2030 are considered plausible by the electricity provider in the future [17], i.e.: low, medium, high and enhanced demand-side management. In this paper, we rely on the enhanced demand-side management scenario for being consistent with the energy autonomy target, and on the medium scenario for establishing the baseline scenario (see Table 3). Besides ARER, the Reunion Regional Energy Agency, has anticipated the development of electrical vehicles which may induce an increase of 1400 GWh in electricity production by 2030 [13] since the transportation sector must also decrease its use of fossil fuels (Table 4). Lastly, electrical losses currently represent 10% of the electricity production [17].

3. Methodology To assess future power mixes in Reunion Island, we develop a TIMES-Reunion model that enables us to perform a prospective analysis. We also rely on two reliability indicators to quantify the reliability of power systems' management according to their dynamical properties. The main principles of these methods are described in this section. 3.1. General description of the model TIMES-Reunion The TIMES-Reunion model is used to compute the power system's responses to the target of an electricity production mix with 100% renewable energy sources by 2030 under different conditions specified in scenarios. The optimization framework has been developed since the mid-1980s under the auspices of the International Energy Agency and has been proven useful to provide plausible options of the long-term development of energy systems [20,21]. In TIMES models, the energy sector is described as a chain of transformations between the primary energy resources and the final energy demand. The transformations are explicit input/output relationships between individual technologies, which are associated to a precise transformation step. The explicit description of technologies, and of commodity flows they produced or consumed, can be formalized in the so-called reference energy system. Two main sets of technical constraints ensure that the description of the energy system remains consistent over the

Power units:

BASE

RENEW

RENEW-HighInt

RENEW-Cane

Coal Coal and sugarcane Fuel oilsa Biomassb Hydropowerc PV panels Wind onshore Geothermal energy OTEC Wave energy

332 140 315 – 147 106 50 – 29 12

118 45 245 430 194 300 47 20 66 30

92 45 245 315 192 750 9 – 101 51

122 45 245 475 194 300 50 – 17 12

Total (MW)

1131

1495

1799

1433

a b c

Heavy and distillate. Sugarcane, cane, wood. Dams and run-of-the-river.

time horizon: flow equilibrium conditions, imposing that the production of each commodity flow equals or exceeds its consumption, and capacity transfer constraints, which are set over the time horizon according to the lifetime of technologies. The principle of TIMES models is to maximize the total surplus of the energy system over a large time horizon (typically several decades) in an intertemporal optimization framework. As a result, the solution provides the levels of energy resources and technologies that are effectively used from the total available set of possibilities modeled, and is therefore well suited for a detailed investigation of future technology choices. In the TIMES-Reunion model, one year is divided into two seasons (summer and sugar season), and one day into eight timeslices, each representing a few hours of a day. To describe power systems, flow equilibrium conditions are published separately for several timeslices to follow the load curve and distinguish between the different hours of a day. A peak reserve constraint also guarantees the setting-up of an additional capacity reserve and stipulates that the total production capacity must be oversized by a given percentage to satisfy the peak demand and insure against grid contingencies. Besides, for such a small system, investments in power stations are limited to those of implementable size by introducing discrete variables and setting an upper bound of 80 MW for new power plants. The TIMES-Reunion model was specifically developed to describe Reunion Island's electricity sector and study its responses to contrasted scenarios for the period 2008–2030. The model has been calibrated with data from the years 2008 and 2010 [22,17,23,15]. Costs and technical properties for new power plants are derived from the European program RES2020, which assessed the directives on Renewable Energy Sources and policy recommendations in the European Union using a TIMES model.

M. Drouineau et al. / Renewable and Sustainable Energy Reviews 46 (2015) 120–128

3.2. Specification of the long-term scenarios The power sector's response to energy autonomy policies under different conditions is studied with three scenarios introducing renewable energy sources compared to a baseline (or business-asusual) scenario:

 The baseline, BASE, considers the medium growth of electricity







consumption. The current production mix is extended over the time horizon: no limit is set on fossil fuels' importations and no specific incentives promote the use of renewable energy sources. The RENEW scenario reaches a production mix with 100% renewable energy sources by 2030, since a constraint is set to progressively ban importations of fossil fuels. This is partly enforced with the development of 300 MW of PV systems by 2020, a plausible level of development suggested by [13]. Besides, electricity consumption decreases due to the enhanced DSM program. The development of electrical vehicles by 2030 mitigates the impact on the overall need of electricity production. The RENEW-HighInt scenario studies the system's response to a larger increase of photovoltaics and ocean energies, in line with ambitious policy recommendations [24,13]: 750 MW of solar panels and 150 MW of ocean energy units are projected by 2030. In the RENEW-Cane scenario, the decline of the sugar industry, though rather unlikely for now, is considered to fully dedicate sugarcane fields to energy purposes from 2020 (in this scenario, there is no sugar production by 2030).

3.3. The reliability indicators

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and voltage can lead to brownouts or power outages. Stability studies are used to check the real-time reliability of power supply. They involve time scales ranging from a few milliseconds to a few hours, while prospective analyses deal with several years, making them unsuitable for prospective studies. Conversely, we rely in this work on an aggregated approach based on thermodynamics to theoretically derive the suitable energies, whatever the topology, the conversion machines and the operating system implemented in a power grid. Such a description of course matches the basics of current power transmission systems and also offers a rigorous way to reconcile the time-scales involved by power management and planning, without explicitly performing a timestepping resolution. Variational principles deduced from thermodynamics are applied to achieve a global description of power systems that comes down to a oneloop equivalent circuit lumping the dynamic properties of a wide power system [29–31]. It is found that reliability relies on the dynamics properties of production and transmission capacities, assessed through the magnetic reserve F and the kinetic reserve Ekin of the whole system. The two reserves give inertia to the system when experiencing transient states and enable us to recover steady-state conditions. To quantify the levels of magnetic and kinetic reserves available in the system, two reliability indicators H mag and H kin are introduced: they represent the stored energies evaluated in terms of per-unit parameters and have the dimensions of time [19,32]: F H mag ¼ P

ð1Þ

E H kin ¼ Pkin k Sk

ð2Þ

k Sk

where High shares of intermittent energy sources in electricity production will make more complex the operation of a power system and may damage the associated reliability of power supply. Thus, the production mix proposed for the three renewable scenarios may show weaknesses for addressing reliability of supply and are rather likely to correspond to unrealistic options. We therefore recommend to evaluate the reliability of supply to focus on solutions that propose the technical features ensuring an appropriate reliability of power supply. To do so, we propose an assessment of reliability through reliability indicators that evaluate the dynamic properties of production and transmission. The method is derived from previous works that describe “reliability indicators” quantifying the magnetic and kinetic reserves. These reserves are necessary to ensure an adequate level of inertia in a power system to enable its stability under operations. The reliability indicators are described in [19,25]. We summarize the main results and present how the reliability indicators are combined with the long-term analysis of the production mix in Reunion Island. According to the ENTSO-E, the European Network of Transmission System Operators for Electricity, reliability of power supply can be addressed by considering both the adequacy of the system, i.e. its ability to supply the aggregate electrical demand and energy requirements of the customers at all times, and the security of supply, i.e. its ability to withstand sudden disturbances such as unanticipated loss of system elements (e.g. load or production fluctuations, network contingencies) [26]. Reliability refers to the ability of the power system to lock back into steady-state conditions after sudden disturbances and is usually enforced with an appropriate management of voltage and frequency [27,28]. Ancillary services are necessary to ensure suitable ranges of deviations for frequency and voltage and depend on the reactive power and on the kinetic and spinning reserves of the power system, since high deviations for frequency

 we sum over all the machines connected to the system;  Sk is the apparent power rating of the kth machine. Typical values of H mag vary around few milliseconds and those of H kin around few seconds, pointing out that the magnetic reserve is about three orders of magnitude less than the kinetic reserve. Both H mag and H kin are critical factors in the determination of the dynamic performances and stability of power systems: the greater the indicators, the smaller the frequency and voltage deviations, the more reliable the system. The two reliability indicators are used in this paper to compute the reliability of the future power systems on Reunion Island over the time horizon in the four scenarios.

4. Results and discussions Consistent results concerning electricity generation choices in Reunion Island can be discussed thanks to the computation of the responses of the system to the different scenarios. Results and discussions addressed both the economical and technical feasibility of the scenarios. 4.1. Impacts on the future production mix Fig. 1 presents the evolution of electricity production over the time horizon, a classical output of TIMES models. As expected, electricity consumption in the three renewable scenarios differ from the baseline according to the taken assumptions: the enhanced DSM program enables us to decrease electricity production of 10.5% by 2020, and by 21.5% in 2030. In 2030, the decrease is however compensated due to

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5000

GWh

4500 4000 3500

Wave energy

Wind (onshore) 3000

Photovoltaics OTEC

2500

Geothermy 2000

Land fill Run-of-the-river

1500

Dams

Biomass

1000

Fuel oils 500

Coal

0 2008 Initial mix

2020

2030

BASE

2020

2030

RENEW

2020

2030

RENEW-HighInt

2020

2030

RENEW-Cane

Fig. 1. Electricity production over the modeling horizon.

the 1400 GWh increase related to the spread of electrical vehicles in the three “renewable” scenarios. In the baseline scenario (entitled BASE), the production mix remains dominated by fossil fuels with a market share that remains at two thirds of electricity production over the time horizon. The use of fossil fuels decreases over the time horizon but is compensated by electricity production based on coal since investments in new coal power plants are more efficient from an economic point of view because of higher prices of oils compared to those of coal. In the meanwhile, renewable energy sources increase of 71% over the time horizon in absolute terms, driven by greater available potential of sugarcane bagasse. It only represents a slight increase of the renewable sources in the whole production mix. In all renewable scenarios (entitled RENEW or RENEW-xxx), renewable energy sources ensure energy autonomy in Reunion Island, since fossil fuels' imports decrease to zero by 2030 as set. In the three scenarios, energy autonomy can be achieved thanks to a strong development of biomass production, which represent at leats half of the total production by 2030. Other renewable energy sources develop in the scenarios according to the various assumptions taken in their specification:

 In the scenario RENEW, almost two thirds of electricity produc

tion are based on biomass and hydropower. Photovoltaics also increase their contribution compared to the baseline. In RENEW-HighInt and RENEW-Cane, the production mixes only slightly differ according to the resources promoted in each scenario: the share of photovoltaics rises up to 18% in RENEWHighInt, which is twice as high as in RENEW since the level of installed solar panels is set to 750 MW. In the scenario RENEWCane, the share of biomass reaches 72% of electricity production because landfills are available for non-sugar cane production which have higher yields that sugarcane bagasse and which can be harvested twice a year (instead of once for sugarcane bagasse).

Results show that high levels of biomass production are needed to enable energy autonomy in Reunion Island by 2030. Such levels rely on the development of non-sugar-cane fully dedicated to energy production, which provides higher electricity production by ha of fields than sugarcane bagasse. With non-sugar-cane,

electricity production is the purpose of the cane production, not a co-product of the sugar industry, which enables to harvest cane fields twice a year instead of once. In RENEW-Cane, non-sugarcane represents all of the electricity production from biomass. In RENEW and RENEW-HighInt, it represents half of the electricity production from biomass and the conventional sugarcane bagasse still contributes to almost the other half, with improvements made in sugarcane yields that increase the production of bagasse by tons of sugarcane. Wood and green waste also contribute to electricity production. In fact, all new biomass power plants are gasification units, even though they are expensive, that have higher efficiency rates than conventional thermal units. These results indicate that non-sugar cane production, eventually combined with IGCC power plants, is an essential element for achieving energy autonomy in Reunion Island. Fig. 1 also exhibits a large development of intermittent sources with high shares in the production mixes. To analyze the impacts of intermittent sources on the power system, the TIMES-Reunion model also provides results on the daily production for average days (summer and winter) using the different timeslices. The division in timeslices indeed enables us to represent future load curves for the average days. Daily production in summer 2030 is presented in Fig. 2 for the scenarios BASE and RENEW-HighInt, which presents the highest levels of intermittent sources, mostly photovoltaics, by 2030. The RENEW-HighInt scenario exhibits several hours in a day where photovoltaics represent two thirds of electricity production. High levels of photovoltaics installed and a lower biomass production in summer, considering that sugar production occurs only in winter, explain this result. Compared to the baseline scenario for which at least half of the electricity production relies on coal production plants, it is expected that operating the power system in RENEW-HighInt in such conditions will be more complex and is expected to threaten reliability of power supply. This aspect is presented in the following part where the evolution reliability of power supply is presented with the aforementioned indicators. Currently, the legal limit of 30% of intermittent sources in the instantaneous production prohibits such situations in Reunion Island. However, this limit was not set in the model in the first place in order to analyze the impacts of its enforcement on reliability of power supply, and eventually to explore

M. Drouineau et al. / Renewable and Sustainable Energy Reviews 46 (2015) 120–128

125

700 600

P

mean

(MW)

500 400 300 200 100 0

0

5

10

15

20

15

20

t (h) 700 600

400 300

P

mean

(MW)

500

200 100 0

0

5

10 t (h)

Coal

Coal / sugarcane

Heavy fuel oil

Distillate fuel oil

Sugarcane / wood

Hydropower (dams)

Hydropower (run of river)

Biogaz

Photovoltaïcs

Wind energy (onshore)

OTEC

Wave energy

Fig. 2. Daily production in the summer 2030. Units functioning whether with coal or with sugarcane bagasse only use coal during summer, because sugar factories are shut down. Reliability of power supply is assessed in Section 4.3 for the timeslice from 12 a.m. to 5 p.m.

other options. In RENEW and RENEW-Cane scenarios, intermittent production amounts up to 40% by 2030 in the instantaneous production of summer timeslices, for which the associated reliability of supply is also an issue (but to a lesser extent).



4.2. Impacts on the level of installed capacities This section focuses on the impacts on the levels of installed capacities in Reunion Island. All renewable scenarios exhibit higher levels of installed capacities in 2030 than in the baseline scenario, which is explained by the higher objectives taken for the spread of renewable sources of electricity. The installed capacities are even much higher for the scenario REN-HighInt, in line with the expected development of PV systems and ocean energies. However, the four scenarios exhibit similar characteristics:

 They rely on a large contribution of thermal or IGCC units functioning either with coal in the baseline scenario or with

 

biomass in the renewable scenarios. Thermal or IGCC units indeed represent around 800 MW in all scenarios, except for RENEW-HighInt because of tremendous investments in PV systems. The fuel oil's power plants in 2030 result from investments over the whole studied time horizon: 305 MW in the baseline scenario, and 245 MW in the three RENEW scenarios, even though fossil fuels' imports are not allowed in 2030. Fuel oil's power plants appear in the renewable scenarios as back-up units and enable us to comply with the reserve constraint, considering that intermittent energy sources do not contribute to the reserve and that no other options are considered in the first place, e.g. storage capacity. The latter is discussed in Section 4.3. The level of hydraulic capacities varies between 147 MW (in the BASE scenario) and 194 MW (in the RENEW-Cane scenario). The other renewable sources experience significant development according to the assumptions taken in the different scenarios. Interestingly, in the RENEW scenario a large number

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6

6

Hkin (s)

5

5

4

4

3

3

2

BASE

2

RENEW 1

RENEW-Cane RENEW-HighInt

0

2010

16

2015

2020

2025

Hkin (s)

2030

Hmag (ms)

BASE RENEW-HighInt

1 0

RENEW-HighInt-30p 0

16

14

10

15

20

Hmag (ms)

14

12

10

12

8

10

6

8

BASE RENEW

4

6

RENEW-Cane

2 0

5

RENEW-HighInt 2010

2015

2020

2025

2030

Fig. 3. H kin and Hmag in summer 2030 between 12 a.m. and 5 p.m.

of technologies appears by 2030, e.g. wind onshore spreads to its maximum potential and geothermal energy develops. In the 100% electricity from renewable sources scenarios, the fuel oil's power plants do not appear in the production mix by 2030 (see Fig. 1) since their imports are banned. However, the TIMES-Reunion model only exhibits results for average day and the use of fuel oil's power plants as back-up units is very likely to occur when operating this power system. Consequently, since Reunion Island aims at a production mix based on 100% of renewable sources, using these units will not be possible and the reliability of the power supply will be worsen in the three scenarios. 4.3. Impacts on reliability of power supply The two reliability indicators are used to compute power systems' reliability over the time horizon, relying on daily load curves similar to the ones in Fig. 2. Fig. 3 presents quantitative evaluations of H kin and H mag over the summer 2010 to 2030 for the timeslice between 12 a.m. and 5 p.m. for all scenarios. Highest shares of intermittent sources in the instantaneous electricity production occur during the chosen timeslice (12 a.m. to 5 p.m.). It is when the values of the reliability indicators will be the most critical. Calculations rely on data given by [33] and estimate accurate orders of magnitude of the indicators. H kin and H mag provide a precise evaluation of the available reserves on the system. Comparing the indicators between the different scenarios is fully trustworthy as calculations rely on the very same assumptions. However absolute values must be considered with caution.

4

BASE

2

RENEW-HighInt-30p

0

RENEW-HighInt

0

5

10

15

20

Fig. 4. Reliability indicators in a 2030 summer day for the scenarios BASE, RENEWHighInt and RENEW-HighInt-30%.

The similar variations of both indicators in Fig. 3(a) and (b) can be explained because all production capacities almost participate at the same level to the magnetic and the kinetic reserves. Thereby, any change in the production mix leads to similar effects on H mag and H kin . However, both indicators are significant to ensure a reliable power supply and may evolve differently under other conditions. For instance, in case specific technologies develop in Reunion, such as flying wheels, H kin will increase whereas H mag will stay unchanged. For the three renewable scenarios, both indicators decrease over the time horizon, thus revealing that reliability of power supply will be damaged with a production mix with a 100% renewable energy sources compared to the baseline evolution. Results confirm that reliability of supply decreases when achieving energy autonomy while it remains stable otherwise. In RENEWHighInt, lower levels of magnetic and kinetic reserves suggest that large shares of intermittent sources may not provide enough inertia for the system to remain stable. Inversely, in RENEW and RENEW-Cane, the indicators decrease until 2020 but then levels off. We investigate in an alternative scenario, named RENEWHighInt-30% and derived from the scenario RENEW-HighInt, the efficiency of the legal limit of 30% of intermittent sources in the instantaneous electricity production set by the French government for the Reunion Island and other overseas territories. In this scenario, we set an additional constraint on the share of intermittent sources in future production mixes to reproduce the current legislation. The limitation on intermittent sources is

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enforced for all the timeslices. In the scenario RENEW-HighInt-30%, the production of intermittent sources is reduced during sunny hours. Fig. 4 presents the reliability indicators for an average day of the summer 2030 in the scenarios BASE, RENEW-HighInt and RENEW-HighInt-30%. In the baseline scenario, denoted by the solid lines in Fig. 4(a) and (b), the indicators remain stable during the day: H kin levels off around 5 s and H mag stabilizes around 14 ms. The two constants correspond approximatively to the time during which the kinetic and magnetic reserves are emptied when disturbances occur on the power system. In the RENEW-HighInt scenario, denoted by the dashed lines, H kin and H mag strongly fluctuate within a day. During dark hours (from 5 p.m. to 7 a.m.), H kin levels off around 4.5 s and H mag stabilizes around 14 ms because electricity is mostly produced by non-intermittent units which efficiently participate to increase the reserves. Inversely, during daytime, when high levels of photovoltaics' production represent two thirds of the electricity demand, indicators are divided by two, thereby pointing out a weaker reliability of supply. With smaller indicators, the kinetic and magnetic reserves are lower and provide less inertia to the system, which correspond to a decrease in reliability of supply. Such results indicate that higher shares of intermittent sources tend to weaken reliability of supply. Inversely, in the 30% scenario, denoted by the mixed lines, H mag levels off at around 12 ms and H kin around 4 s, showing that the reserves are twice as high during daytime, i.e. the most critical hours, with the management rule. Enforcing a real-time limit on the share of intermittent sources can consequently restores reliability of power supply, almost to the same levels as in the baseline scenario. This result validates the 30% rule fixed by the regulator and also illustrates the key role the indicators can play in improving the real-time management of reliability of supply. Furthermore, it would be interesting to follow the evolution of the indicators in the case where storage units are used to mitigate the impact of photovoltaics on the reliability of power supply, considering the increasing development of energy storage devices, such as pumped storage hydro plants, hydrogen storage, flywheels, electrochemical batteries, supercapacitors (and others) in power systems [34,35]. Besides, recent works demonstrate that energy storage devices can improve the performance of power systems facing high shares of intermittent sources by mitigating their intermittency [36–38]. In particular, storage devices can be useful to secure reliability of supply and to reduce instability phenomena (among other services) [39]. Their impacts on reliability of supply and subsequent overcosts should also be investigated in a longterm perspective. In this prospect, research on this specific topic has recently been carried out to pursue this work and impacts of intermittent sources on the reliability of future power production mixes have been endogenized in the TIMES-Reunion model to fully address the technical feasibility of different scenarios. These improvements are useful to determine the level of intermittency compatible with reliability requirements or to consider appropriate investments in storage or changes in consumption patterns induced with demand response to prevent from decreasing reliability of power supply [40,41].

5. Conclusion This paper analyzes the capability of Reunion Island to achieve electricity autonomy by 2030. Currently, almost two thirds of the electricity in Reunion Island are produced from imported fossil fuels while the island is blessed with high levels of renewable energy potentials. In this context, power production in Reunion Island is expected to change substantially. The question addressed in this work is the technical and economical feasibility of the

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electricity autonomy target by 2030. The approach relies on a prospective study of electricity resources and demand based on the TIMES-Reunion model which provides future production mixes according to different scenarios. The outputs enable us to discuss the conditions leading to the energy autonomy target. The prospective analysis is combined with a quantitative assessment of reliability of power supply regarding that intermittent sources may highly develop and consequently worsen the reliability of power supply. The question of reliability of power supply is indeed critical with large integration of intermittent sources, especially for small, weakly meshed, and remote power systems. This study enables us to draw three main conclusions:

 Electricity autonomy is achievable by 2030 with the available





renewable energy sources potentials in the island. The three renewable scenarios, which prohibit fossil fuels, can indeed fulfill the electricity consumption, even considering a large development of electrical vehicles. The results show that the electricity autonomy can only be achieved thanks to high levels of biomass production, which represent at least half of the total production by 2030. It also leads to high shares in the production mixes: in 2030, these scenarios exhibit several hours by day where photovoltaics represent from 40% to two thirds of the instantaneous electricity production. However, we observe that the reliability indicators decrease over the time horizon, thus revealing that reliability of power supply will be damaged with high levels of intermittent sources. This also explains why fuel oil's power plants appear as back-up units when facing high shares of intermittency even though they do not produce electricity in the results. Since the use of fossil fuels is prohibited in 2030, the reliability of power supply will actually be worsen in scenarios that aim at electricity autonomy, as long as reliability is not addressed properly. Finally, results also show that it is possible to restore the reliability of supply when enforcing the legal limit of 30% of intermittent sources in the instantaneous production. This result consequently provides a generation mix that both complies with the electricity autonomy target and with a satisfying reliability of power supply, provided that appropriate rules on the instantaneous production are defined. Furthermore, impacts on reliability of supply and subsequent overcosts of storage devices or changes in consumption patterns induced with demand response should also be investigated. This can be achieved by endogenizing the reliability of future power production mixes in TIMES models to consider appropriate investments preventing from decreasing reliability of power supply.

Acknowledgements This work was supported by the Chair Modeling for sustainable development, driven by MINES ParisTech, École des Ponts ParisTech, AgroParisTech, and ParisTech; and supported by ADEME, EDF, RENAULT, SCHNEIDER ELECTRIC and TOTAL. References [1] Golusin M, Ivanovic OM, Redzepagic S. Transition from traditional to sustainable energy development in the region of western balkans current level and requirements. Appl Energy 2013;101(0):182–91. [2] 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: Proceedings of 8th international workshop on large-scale integration of wind power into power systems as well as on transmission networks of offshore wind farms, Bremen, Germany; 2009.

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[3] Esteban M, Leary D. Current developments and future prospects of offshore wind and ocean energy. Appl Energy 2012;90(1):128–36 [Energy solutions for a sustainable world, Special issue of international conference of applied energy, ICA2010, April 21–23, 2010, Singapore]. [4] Haller M, Ludig S, Bauer N. Bridging the scales: a conceptual model for coordinated expansion of renewable power generation, transmission and storage. Renew Sustain Energy Rev 2012;16(5):2687–95. [5] Budzianowski WM. Target for national carbon intensity of energy by 2050: a case study of Poland's energy system. Energy 2012;46(1):575–81 [Energy and exergy modelling of advance energy systems]. [6] Lund H. The implementation of renewable energy systems. Lessons learned from the Danish case. Energy 2010;35(10):4003–9. [7] Rosenbloom D, Meadowcroft J. The journey towards decarbonization: exploring socio-technical transitions in the electricity sector in the province of ontario (18852013) and potential low-carbon pathways. Energy Policy 2014;65 (0):670–9. [8] Tigas K, Giannakidis G, Mantzaris J, Lalas D, Sakellaridis N, Nakos C, et al. Wide scale penetration of renewable electricity in the greek energy system in view of the european decarbonization targets for 2050. Renew Sustain Energy Rev 2015;42(0):158–69. [9] Hernández-Moro J, Martínez-Duart J. Economic analysis of the contribution of photovoltaics to the decarbonization of the power sector. Renew Sustain Energy Rev 2015;41(0):1288–97. [10] Ilic MD. From hierarchical to open access electric power systems. In: Proceedings of the IEEE 2007, vol. 95(5); 2007. p. 1060–84. http://dx.doi.org/ 10.1109/JPROC.2007.894711. [11] Weisser D. On the economics of electricity consumption in small island developing states: a role for renewable energy technologies?. Energy Policy 2004;32(1):127–40. http://dx.doi.org/10.1016/S0301-4215(03)00047-8. [12] Guerassimoff G, Maïzi N, Mastère OSE. Îles et Énergie: un paysage de contrastes. Les Presses-MINES ParisTech; 2008 [in French]. [13] ARER. PETREL - île de la Réunion Plan économique de Transition et de Relance via des énergies 100% Locales île de la Réunion. Technical Report, ARER; 2009 [in french]. [14] Praene JP, David M, Sinama F, Morau D, Marc O. Renewable energy: progressing towards a net zero energy island, the case of Reunion Island. Renew Sustain Energy Rev 2012;16(1):426–42. http://dx.doi.org/10.1016/j.rser.2011.08.007. [15] Observatoire Énergie Réunion, ARER. Bilan énergétique 2010 de l'i\widehatle de la Réunion. Technical Report, Observatoire Énergie Réunion, ARER; 2011. [16] International Energy Agency (Organisation for Economic Cooperation and Development). World Energy Outlook 2009. International Energy Agency (Organisation for Economic Cooperation and Development); 2009. [17] EDF. Bilan Prévisionnel Pluriannuel: investissements en production. Technical Report, EDF (Électricité de France); 2011 [La Réunion, in french]. [18] Fesquet F, Juston P, Garzulino I. Impact and limitation of wind power generation in an island power system. In: IEEE Bologna power technical conference; 2003. [19] Drouineau M. Modélisation prospective et analyse spatio-temporelle: intégration de la dynamique du réseau électrique [Ph.D. thesis]. MINES ParisTech; 2011. [20] Loulou R, Goldstein G, Noble K. Documentation of the MARKAL Family of models. Energy Technology Systems Analysis Program; 2004.

[21] Loulou R, Remme U, Kanudia A, Lehtila A, Goldstein G. Documentation for the TIMESModel (Parts I to III). Energy Technology Systems Analysis Program; 2005. [22] EDF. Bilan Prévisionnel Pluriannuel: investissements en production. Technical Report, EDF (Électricité de France); 2009 [La Réunion, in french]. [23] Observatoire Énergie Réunion, ARER. Bilan énergétique 2008 de l'île de la Réunion. Technical Report, Observatoire Énergie Réunion, ARER; 2009 [in french]. [24] Direction de l'Agriculture et de la Forêt de La Réunion. Protocole pour une gestion dynamique et responsable du foncier agricole. Technical Report, Direction de l'Agriculture et de la Forêt de La Réunion; 2008 [in french]. [25] Drouineau M, Maïzi N, Mazauric V. Impacts of intermittent sources on the quality of power supply: the key role of reliability indicators. Appl Energy 2014;116(0):333–43. [26] European Network of Transmission System Operators for Electricity. Operation Handbook. Technical Report, European Network of Transmission System Operators for Electricity; 2004. [27] Bergen AR, Vittal V. Power system analysis, 2nd ed., Englewood Cliffs, NJ: Prentice-Hall Series; 2000. [28] Bornard P, Pavard M, Testud G. Réseaux d'interconnexion et de transport: fonctionnement (in French). Techniques de l'ingénieur 2005;(D4091):1–12. [29] Mazauric VG. From thermostatistics to Maxwell's equations: a variational approach of electromagnetism. IEEE Trans Magn 2004;40:945–8. [30] Drouineau M, Maïzi N, Assoumou E, Mazauric V. A TIMES model of the Reunion Island for analysing the reliability of electricity supply. In: International energy workshop; 2011. [31] Mazauric V, Maïzi N. Optimality principles for the sustainability of electrical systems: a thermodynamic approach. In: International conference and applied energy; 2012. [32] Maïzi N, Drouineau M, Mazauric V, Bouckaert S. PCT/EP2012/074161: Procédé d'estimation de la fiabilité d'un système électrique; 2012 [in french]. [33] Anderson PM, Fouad AAA. Power system control and stability. Ames: The Iowa State University Press; 1977. [34] Divya K, Ostergaard J. Battery energy storage technology for power systems an overview. Electr Power Syst Res 2009;79(4):511–20. [35] Zucker A, Hinchliffe T, Spisto A. Assessing storage value in electricity markets, a literature review. Technical Report, European Commission (JRC) and EDF; 2013. [36] Yuan Y, Zhang X, Ju P, Qian K, Fu Z. Applications of battery energy storage system for wind power dispatchability purpose. Electr Power Syst Res 2012;93(0):54–60. [37] Hasan NS, Hassan MY, Majid MS, Rahman HA. Review of storage schemes for wind energy systems. Renew Sustain Energy Rev 2013;21(0):237–47. [38] Suberu MY, Mustafa MW, Bashir N. Energy storage systems for renewable energy power sector integration and mitigation of intermittency. Renew Sustain Energy Rev 2014;35(0):499–514. [39] Koh L, Yong GZ, Peng W, Tseng K. Impact of energy storage and variability of {PV} on power system reliability. Energy Proc 2013;33(0):302–10 [PV Asia pacific conference 2012]. [40] Bouckaert S, Mazauric V, Maïzi N. Expanding renewable energy by implementing demand response. Energy Proc 2014;61(0):1844–7 [International conference on applied energy {ICAE2014}]. [41] Bouckaert S, Wang P, Mazauric V, Maïzi N. Expanding renewable energy by implementing dynamic support through storage technologies. Energy Proc 2014;61(0):2000–3 [International conference on applied energy {ICAE2014}].