Estimation of solar and wind energy resources over Lesotho and their complementarity by means of WRF yearly simulation at high resolution

D’Isidoro, Massimo; Briganti, Gino; Vitali, Lina; Righini, Gaia; Adani, Mario; Guarnieri, Guido; Moretti, Lorenzo; Raliselo, Muso; Mahahabisa, Mabafokeng; Ciancarella, Luisella; Zanini, Gabriele; Fino, Ernesto

doi:10.1016/j.renene.2020.05.106

Cited by 36 publications

(17 citation statements)

References 54 publications

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“…Thereafter, Pereira et al (2019) proposed an offline procedure to improve further solar irradiance magnitude and variability that takes into account shadowing and slope effects from orographic features. CPRCMs were used in different studies to evaluate the solar energy resources and identify regions that have a greater photovoltaic potential over the contiguous U.S. (James et al, 2017), Kuwait (Gueymard & Jiménez, 2018), the Arabian Peninsula (Dasari et al, 2019), southeastern Australia (Prasad & Kay, 2020), and Lesotho (D'Isidoro et al, 2020). Moreover, CPRCM projections were performed to assess the impacts of climate change on the solar resources (Carreño et al, 2020) that would consequently affect power system operations (Craig et al, 2019) and high energy stress periods in a region (Texas) with high wind and solar penetrations (Craig et al, 2020).…”

Section: Cprcm Benefits For Impact Studiesmentioning

confidence: 99%

Convection‐permitting modeling with regional climate models: Latest developments and next steps

Lucas‐Picher

Argüeso

Brisson

et al. 2021

WIREs Climate Change

134

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Approximately 10 years ago, convection-permitting regional climate models (CPRCMs) emerged as a promising computationally affordable tool to produce fine resolution (1-4 km) decadal-long climate simulations with explicitly resolved deep convection. This explicit representation is expected to reduce climate projection uncertainty related to deep convection parameterizations found in most climate models. A recent surge in CPRCM decadal simulations over larger domains, sometimes covering continents, has led to important insights into CPRCM advantages and limitations. Furthermore, new observational gridded datasets with fine spatial and temporal ($1 km; $1 h) resolutions have leveraged additional knowledge through evaluations of the added value of CPRCMs. With an improved coordination in the frame of ongoing international initiatives, the production of ensembles of CPRCM simulations is expected to provide more robust climate projections and a better identification of their associated uncertainties. This review paper presents an overview of the methodology to produce CPRCM simulations and the latest research on the related added value in current and future climates. Impact studies that are already taking advantage of these new CPRCM simulations are highlighted. This review paper ends by proposing next steps that could be accomplished to continue exploiting the full potential of CPRCMs.

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Section: Cprcm Benefits For Impact Studiesmentioning

confidence: 99%

Convection‐permitting modeling with regional climate models: Latest developments and next steps

Lucas‐Picher

Argüeso

Brisson

et al. 2021

WIREs Climate Change

134

View full text Add to dashboard Cite

show abstract

“…This configuration was then adopted to perform the multiannual assessment of wind and solar photovoltaic energy resources. Details on the comparison between modelled and observed hourly and aggregated data is given in [61], where a preliminary estimation of wind and photovoltaic potential over Lesotho was presented based on the 2015 simulation.…”

Section: Modelling Setup and Datamentioning

confidence: 99%

“…In order to estimate the final energy production, technical details on the wind generator have to be assumed. These include its power curve i.e., how large the electrical power output would be at different wind speeds (e.g., [61,66]). Technical data describing real-world wind turbines features were used, being the choice of the turbines taken into account based on both worldwide market penetration and data availability.…”

Section: Wind Power Production Estimationmentioning

confidence: 99%

“…Assessment was carried out assuming diffuse radiation being uniformly and isotropically distributed over the sky dome according to Liu and Jordan [69] and photovoltaic modules being set in the optimal configuration, i.e., facing the equator. More details on the formulations used for the assessment can be found in [61]. Concerning the module inclination with respect to the horizontal plane, its best value, maximizing the annual energy production, was computed by means of an optimization procedure and made available as an additional product in the framework of the project.…”

Section: Photovoltaic Power Potential Estimationmentioning

confidence: 99%

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A Cooperation Project in Lesotho: Renewable Energy Potential Maps Embedded in a WebGIS Tool

et al. 2021

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In this paper the background, activities undertaken, and main outcomes of the cooperation project “Renewable Energy Potential Maps for Lesotho” are presented. The project was launched in 2018 in fulfilment of the Paris Agreement by the Italian Ministry for the Environment and the Lesotho Ministry of Energy and Meteorology, with the aim to facilitate the local Government in the future planning and development of renewable energy in the country. A user-oriented WebGIS platform was utilised to share and analyse the outcomes of the project: a hydrological map to recognize potential areas for power generation; a wind atlas to identify specific sites with the most potential for wind energy generation; a solar radiation map, defining the different levels of radiation intensity, useful to localise sites for photovoltaic production. Human capacity building and technology transfer were carried out to strengthen the local expertise and ability to manage and plan renewable energy sources exploitation. The implementation of the project was based on a fruitful collaboration between scientists and stakeholders at the same time giving the local authorities a useful dataset and tool for renewable energy growth in Lesotho.

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“…Correlation coefficients are by far the most widely used metric for assessing complementarity between energy sources time series. This approach has been used, for example, in Poland (Jurasz, 2017), Portugal (Moura and de Almeida, 2010;Castro and Crispim, 2018), Spain (Ren et al, 2019), Italy (Monforti et al, 2014;François et al, 2014), USA (Slusarewicz and Cohan, 2018), Colombia 20 (Parra et al, 2020;Peña Gallardo et al, 2020b;Henao et al, 2020;Cantor et al, 2019), Germany (Schindler et al, 2020), Australia (Kay, 2015), Brazil (Silva et al, 2016;de Oliveira Costa Souza Rosa et al, 2017;dos Anjos et al, 2015;Cantão 25 et al, 2017), China (Xu et al, 2017;Li et al, 2019;Cao et al, 2019), Sweden (Widen, 2011), Mexico (Peña Gallardo et al, 2020a), Canada (Denault et al, 2009), Lesotho (D'Isidoro et al, 2020), Finland (Solomon et al, 2020), Argentina 30 (Genchi et al, 2018), Britain (Bett and Thornton, 2016), Saudi Arabia (Sahin, 2000) and Chile (Odeh and Watts, 2019). It has also been used at the international level (e.g.…”

Section: Introductionmentioning

confidence: 99%

Total variation as a metric for complementarity in energy resources time series

Cantor¹,

Ochoa²,

Sánchez³

2021

Preprint

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Complementarity has become an essential concept in energy supply systems. Although there are some other metrics, most studies use correlation coefficients to quantify complementarity. The standard interpretation is that a high negative correlation indicates a high degree of complementarity. However, we show that the correlation is not an entirely satisfactory measure of complementarity. As an alternative, we propose a new index based on the mathematical concept of the total variation. For two time series, the new index φ is one minus the ratio of the total variation of the sum to the sum of the two series' total variation. We apply the index first to an auto-regressive (AR) process and then to various Colombian electric system series. The AR case clearly illustrates the limitations of the correlation coefficient as a measure of complementarity. We then evaluate complementarity across various space-time scales in the Colombian power sectors, considering hydro and wind projects. The complementarity assessment on a broad temporal and geographical scale helps analyze large power systems with different energy sources. The case study of the Colombian hydropower systems suggests that φ is better than ρ because (i) it considers scale, whereas ρ, being non-dimensional, is insensitive to the scale and even to the physical dimensions of the variables; (ii) one can apply φ to more than two resources; and (iii) ρ tends to overestimate complementarity.

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Estimation of solar and wind energy resources over Lesotho and their complementarity by means of WRF yearly simulation at high resolution

Cited by 36 publications

References 54 publications

Convection‐permitting modeling with regional climate models: Latest developments and next steps

Convection‐permitting modeling with regional climate models: Latest developments and next steps

A Cooperation Project in Lesotho: Renewable Energy Potential Maps Embedded in a WebGIS Tool

Total variation as a metric for complementarity in energy resources time series

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