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The CLIMIX Model a Tool to Create and Evaluate Spatially-Resolved

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The CLIMIX Model a Tool to Create and Evaluate Spatially-Resolved Renewable and Sustainable Energy Reviews 42 (2015) 1–15 Contents lists available at ScienceDirect Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser The CLIMIX model: A tool to create and evaluate spatially-resolved scenarios of photovoltaic and wind power development S. Jerez a,b,n, F. Thais c, I. Tobin a, M. Wild d, A. Colette e, P. Yiou a, R. Vautard a a Laboratoire des Sciences du Climat et de l’Environnement (LSCE), IPSL, CEA-CNRS-UVSQ, 91191 Gif sur Yvette, France b Department of Physics, University of Murcia, 30100 Murcia, Spain c Institut de Technico-Economie des Systèmes Energétiques (I-Tésé), CEA/DEN/DANS, 91191 Gif sur Yvette, France d Institute for Atmospheric and Climate Science, ETH Zurich, 8092 Zurich, Switzerland e Institut National de l’Environnement Industriel et des Risques (INERIS), Parc Technologique Alata, 60550 Verneuil en Halatte, France article info abstract Article history: Renewable energies arise as part of both economic development plans and mitigation strategies aimed Received 16 April 2014 at abating climate change. Contrariwise, most renewable energies are potentially vulnerable to climate Received in revised form change, which could affect in particular solar and wind power. Proper evaluations of this two-way 5 August 2014 climate–renewable energy relationship require detailed information of the geographical location of the Accepted 26 September 2014 renewable energy fleets. However, this information is usually provided as total amounts installed per administrative region, especially with respect to future planned installations. To help overcome this Keywords: limiting issue, the objective of this contribution was to develop the so-called CLIMIX model: a tool that Wind power performs a realistic spatial allocation of given amounts of both photovoltaic (PV) and wind power Solar photovoltaic power installed capacities and evaluates the energy generated under varying climate conditions. This is done Spatial distribution of renewable energy over a regular grid so that the created scenarios can be directly used in conjunction with outputs of plants ° fi Europe climate models. First, we used the 0.44 resolution grid de ned for the EURO-CORDEX project and Euro-Cordex applied the CLIMIX model to spatially allocate total amounts of both unreported 2012 and future 2020 PV and wind power installations in Europe at the country level. Second, we performed a validation exercise using the various options for estimating PV and wind power production under the created scenarios that are included in the model. The results revealed an acceptable agreement between the estimated and the recorded power production values in every European country. Lastly, we estimated increases in power production derived from the future deployment of new renewable units, often obtaining non-direct relationships. This latter further emphasizes the need of accurate spatially-resolved PV and wind power scenarios in order to perform reliable estimations of power production. & 2014 Elsevier Ltd. All rights reserved. Contents 1. Introduction..........................................................................................................2 2. Data................................................................................................................2 2.1. PV and wind power installed capacity . 2 2.2. Climate simulation. 3 2.3. Population . 3 2.4. PV and wind power production . 3 3. Methodology: the CLIMIX model . 5 3.1. Creation of installed power spatial scenarios. 5 3.1.1. Criteria for differentiating small and large PV plants. 5 3.1.2. Determining factor, forbidden locations and efficiency filter.......................................................5 3.1.3. Basic algorithm . 5 3.2. Estimation of power production under the created scenarios. 7 n Corresponding author at: Edificio CIOYN (Oficina 1.3), Departamento de Física, Campus de Espinardo, Universidad de Murcia, 30100 Murcia, Spain. Tel.: þ34 868 88 85 52. E-mail address: [email protected] (S. Jerez). http://dx.doi.org/10.1016/j.rser.2014.09.041 1364-0321/& 2014 Elsevier Ltd. All rights reserved. 2 S. Jerez et al. / Renewable and Sustainable Energy Reviews 42 (2015) 1–15 3.2.1. Options for the estimation of PV power production . 7 3.2.2. Approaches for the estimation of wind power production . 7 4. Results..............................................................................................................8 4.1. Spatial scenarios of PV and wind power installations . 8 4.2. Estimates of PV and wind power production under the created scenarios . 8 4.2.1. Validation. 8 4.2.2. Application: future expectations . 8 5. Conclusions and discussion. 9 Acknowledgments. 13 Appendix A. The hindcast climate simulation . 13 References.............................................................................................................. 14 1. Introduction The various data used in this work are listed in Section 2. Section 3 provides a detailed description of the CLIMIX model, as A spectacular deployment of new renewable energy installations, well as of the assumptions made for the creation of the 2012 and in particular solar plants and wind farms, is taking place in both 2020 PV and wind power scenarios. Section 4 presents the created developing and developed countries [1]. The commitment on low scenarios along with the results of the validation and application carbon energies as a substitute of traditional fossil energy resources exercises. Finally, Section 5 summarizes and discuss the main has a double motivation and objective. On the one hand, the conclusions. investments devoted to exploit the free, local and renewable resources, such as solar radiation and wind, are expected to rebound positively on economy by both promoting the local employment and favoring 2. Data the energetic independence of the countries that nowadays need to import expensive amounts of energy from abroad [2–4]. On the other 2.1. PV and wind power installed capacity hand, renewable energies constitute a major part of the mitigation strategies aimed at abating climate change by reducing greenhouse The total amounts of PV or wind power capacity installed or to gas (GHG) emissions [5,6].Inthisscenario,the20–20–20 target set by be installed in each European country are listed in Tables 1 and 2. the European Union commits countries to reduce GHG emissions, These correspond to 2012 reported quantities [17,18] or to 2020 increase the efficiency of the energy generation systems, and raise the planned fleets according to the European Climate and Energy share of energy production from renewable resources by 20% in 2020 compared to 1990s levels [7]. However, wind and solar renewable energies, among those that depend on the atmospheric conditions, Table 1 are, contrariwise, part of the sectors potentially vulnerable to changes Amounts of on-shore and off-shore wind power installed at known locations, at the in climate [8–11]. Besides, a massive development of renewable end of 2012 and planned for the year 2020 in each European country. Gray energy plants could have an additional effect on local weather and numbers in the 2012 columns indicate that we already know the locations of all the wind power installed at the end of 2012. Gray background colors in the 2020 climate by modifying atmospheric circulations [12–16]. columns indicate that the 2020 planned amounts have already been exceeded by In order to evaluate the effectiveness and environmental impacts of the year 2012. Units: MW. regional or global scenarios of renewable energy deployment along with climate change impacts on it, spatially-resolved scenarios with On-shore WP installations Off-shore WP installations the location of current and planned production units as accurate as Known 2012 2020 Known 2012 2020 possible are required. However, the lack of public information and detail in this respect is notable. The actual location of all current Austria 1314.4 1314.4 2578.0 0 0 0 renewable energy plants is often difficult to survey with accuracy, Belgium 920.8 920.8 2320.0 1791.2 1791.2 2000.0 especially regarding the diffuse network of solar photovoltaic (PV) Bulgary 636.0 668.0 1115.0 0 0 0 Cyprus 0 0 300.0 0 0 0 production. Moreover, future national or regional plans for the Czeh Rep. 261.3 261.3 743.0 0 0 0 development of new installations are generally provided at a very Denmark 2999.6 3373.0 2621.0 1466.2 1466.2 1339.0 low resolution, usually as totals over large administrative areas. Estonia 434.6 434.6 400.0 700.0 700.0 250.0 In this context, the objective of this work is to design and test a Finland 198.7 198.7 1600.0 800.3 800.3 900.0 model that provides gridded spatial scenarios of PV and wind power France 7759.6 7894.0 19,000.0 2311.5 2311.5 6000.0 Germany 31,334.1 32,118.0 35,750.0 10,307.9 10,307.9 10,000.0 installed at each location (i.e. grid cell) accounting for either present Greece 1237.9 1611.0 7200.0 536.0 536.0 300.0 deployment or future targets of power installed or to be installed Hungary 516.5 542.0 750.0 0 0 0 respectively over a region. As one of the major benefits of having these Ireland 1725.2 1823.0 4094.0 25.2 25.2 555.0 scenarios is that it allows assessments on climate and energy mix, we Italy 7858.5 8006.0 12,000.0 284.0 284.0 680.0 Latvia 31.8 32.0 236.0 0 0 180.0 called the model CLIMIX. The goal is to provide realistic scenarios Lithuania 142.9 198.0 500.0 0 0 0 rather than ideal or optimal ones. Hence, beyond the spatial distribu- Luxembourg 43.7 44.0 131.0 0 0 0 tion of the resources, the known location of current installations and Malta 0 0 14.45 0 0 0 factors such as the population density and the existence of protected Netherlands 2471.9 2535.0 6000.0 3128.0 3128.0 5178.0 areas where the installation of renewable units may be forbidden are Poland 1842.0 1867.0 5600.0 0 0 500.0 Portugal 4249.8 4488.0 6800.0 4.0 4.0 75.0 also taken into account.
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