Statistical methodology for on-site wind resource and power potential assessment under current and future climate conditions: a case study of Suriname

Research Article Statistical methodology for on‑site wind resource and power potential assessment under current and future climate conditions: a case study of Suriname Peter Donk1 · Els Van Uytven2 · Patrick Willems2 © Springer Nature Switzerland AG 2019 Abstract The feasibility and long term sustainability of proposed projects for wind energy production strongly depend on the availability of wind resources. This availability is assessed by means of local wind speed statistics. Under climate change, the future (long term) wind resource availability is, however, highly uncertain. This research proposes a methodology for on-site wind resource assessment in future (climate change) perspective based on stochastic modeling, observed data and the latest generation of climate model results for future projections. Statistical downscaling and bias correction methods, i.e., the Quantile Perturbation Method and Quantile Matching, are applied to enable local scale assessments. It requires observed data for extended periods to facilitate climate change signal assessments and associated future projections. Two types of data sets are considered for observed data, i.e., on-site (local) measurements and reanalysis data. Two stochastic modeling approaches were adopted for the local observations data extension, i.e., a Markov and Weibull model, allowing for a sensitivity assessment. The methodology has been applied to a potential wind site in Suriname. Results reveal significant changes in wind power potential for the end of the century (2070–2100), ranging from − 27 to 89%. Analysis of the extreme conditions reveals an extended range, from − 65 to 282%. Keywords Wind energy · Climate change · Climate modeling · Statistical downscaling · CMIP5 · Suriname 1 Introduction The COP21 agreement, at the 21th session of the UNFCCC Conference of the Parties, commits parties to a common effort on nationally determined commitments to develop strategies for low emission development to face climate change [41]. The rapid deployment of renewable energy technologies would aid in attaining a low emission status. Most renewable energy sources, namely solar, wind, and hydropower, are, however, dependent on weather and climate. Although the renewable aspect of these energies is attractive, it is possible that under climate change its potential may also change. The energy sector in Suriname relies on thermal and hydropower generation, with hydropower contributing to approximately 40% of the power demand [13]. The power demand increases with an average of 6% annually, resulting in a further increasing contribution of thermal power generation. At the other hand, extreme climate events, i.e., droughts in the recent decade, have had significant impact on the water resources in Suriname, hence hydropower capacity. Although there is no strong evidence that the recent events are related to Electronic supplementary material The online version of this article (https://doi.org/10.1007/s42452-019-0885-6) contains supplementary material, which is available to authorized users. * Peter Donk, ; ; Els Van Uytven, ; Patrick Willems, | 1N.V. Energiebedrijven Suriname, Noorderkerk Straat 2‑14, Paramaribo, Suriname. 2Department of Civil Engineering, Hydraulics Section, KU Leuven, Leuven, Belgium. SN Applied Sciences (2019) 1:846 | https://doi.org/10.1007/s42452-019-0885-6 Received: 2 April 2019 / Accepted: 4 July 2019 / Published online: 10 July 2019 Vol.:(0123456789) Research Article SN Applied Sciences (2019) 1:846 | https://doi.org/10.1007/s42452-019-0885-6 climate change, there is a concern that hydropower may be subject to potential negative impacts of climate change in the future, i.e., extreme droughts occurring with higher frequency and greater intensity [13]. It is therefore important to develop a long term energy strategy to address both, (I) the commitments towards the COP21 agreement, and (II) to develop an energy matrix of complementary renewable energy resources, to guarantee a sustainable energy supply on the long term, with minimal thermal contribution. Although there are no existing wind farms and plans for the near future (short term) to develop wind power projects, preliminary assessments show that under the current climatic conditions in Suriname, wind resources may complement hydropower during the dry seasons, as these seasons have favorable wind conditions (substantially greater wind speeds occurring with higher frequency). Hence, to some extent, wind could mitigate the impact of the potential loss of hydropower capacity as a consequence of droughts. However, climate change could potentially have a negative impact on wind as well, which would be a setback for the development of wind power projects in Suriname. Climate modeling for renewable energy applications is an emerging research topic for both climate scientists and renewable energy engineers [21]. The advancements in climate models have increased the confidence in their outputs, such that they can be applied for climate change impact assessments. Research on this subject, including wind energy, has been done recently for different regions in the world [7, 9, 10, 15, 34, 35, 37, 40, 49], but mostly limited to large scale projections rather than local (on-site) assessments. One of the main reasons is that, at present, there are limitations on the use of climate models for local impact analysis due to the coarse spatial and temporal resolutions. Also, the systematic bias in the output of the models has to be dealt with [4, 31, 47]. Different attempts have been made to develop downscaling or bias correction methodologies [10, 12, 20, 36, 40], but in general the limiting factor is the additional need of long term observational data when applying a specific downscaling or bias correction methodology. The methods indeed need to be calibrated/trained (or at least validated) before use. The aim of this paper is to present a methodology for downscaling of climate model outputs that enables local impact assessments and also deals with the problem of model bias and limited observational data. A case study has been considered for a potential wind site in Suriname. 2 Materials and methods 2.1 Suriname and its climatology Suriname is located in the northern part of South America (1.5–6°NL, 54–58°WL) and has a tropical wet climate. Vol:.(1234567890) The average annual temperature is about 26.8 °C, the annual precipitation about 2100 mm and the average annual evaporation about 1750 mm. The relative humidity is around 80% and the annual average solar irradiance about 5 kWh/m2/day. The monthly rainfall distribution throughout the year is mainly governed by the Inter Tropical Convergence Zone (ITCZ), alternately causing wet and dry seasons in Suriname. The short (Dec–Jan) and the long (May–Aug) wet seasons account for about 75% of the annual rainfall. Precipitation is also influenced by various dynamic processes on inter-decadal and interannual scale (...truncated)