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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "B: Energy and Environment".

Deadline for manuscript submissions: 10 June 2025 | Viewed by 9720

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Special Issue Editors

Dr. Alberto Troccoli

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Guest Editor

World Energy & Meteorology Council (WEMC), Norwich, Norfolk, UK
Interests: weather and climate; applications to energy and other sectors

Dr. Laurent Dubus

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Guest Editor

RTE France, Paris-La Defense, Paris, France
Interests: power system evolution; climate change; short-term supply-demand balance

Prof. Dr. Sue Ellen Haupt

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Guest Editor

Research Applications Laboratory (RAL), National Center for Atmospheric Research, Boulder, CO, USA
Interests: meteorology; wind energy; artificial intelligence; renewable energy; boundary layer meteorology
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Special Issue Information

Dear Colleagues,

The energy sector is undergoing an enormous transformation. On one hand, a transition to renewables is essential to meet future energy demand and to achieve a carbon emission reduction of 45 per cent by 2030 and net-zero carbon emissions by 2050 aligned with the 1.5 °C target, as stipulated by the Paris Agreement (2015), as well as to fulfil the aim of Sustainable Development Goal 7 (Ensure access to affordable, reliable, sustainable and modern energy for all). On the other hand, there is a need to ensure climate resilience across the energy sector against more frequent and intense extreme weather, water and climate events, as climate change is putting energy security at risk, globally.

For the energy sector, achieving net zero emissions requires a rapid decarbonisation of the energy system (e.g., generation, infrastructure, transport) with much of the replacement capacity being variable renewable energy. Such decarbonisation also includes a drastic increase in energy efficiency and system resilience, a thorough digitalisation for smart decisions and a boosted investment in low-carbon innovation. As a result, the energy sector has recently begun an epochal infrastructure, technological and societal transformation. In this context, Weather and Climate information is an indispensable enabler for an effective and timely energy transformation.

In this context, many lines of research are active and expanding that support this energy transition. This Special Issue, therefore, invites papers that contribute toward the following areas:

Energy Planning and Financing;
Energy Operations and Maintenance;
Energy Resource Management;
Energy Systems Risk Assessment and Investment;
Climate and Energy Modelling;
Environmental impacts of energy systems;
Weather and Climate Services for Energy;
Energy policy, programmes and cross-sectoral issues;
Education/training programmes in energy and meteorology.

We look forward to receiving your contributions

Dr. Alberto Troccoli
Dr. Laurent Dubus
Prof. Dr. Sue Ellen Haupt
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

weather and climate
forecasting and projections
climate and energy modelling
energy operations and maintenance
energy planning and financing
energy systems risk assessment & resilience

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Published Papers (6 papers)

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Research

23 pages, 8674 KiB

Open AccessArticle

Analysis of the Characteristics of Heat Island Intensity Based on Local Climate Zones in the Transitional Season of Shenyang

by Tianyu Xi, Jin Li, Nuannuan Yang, Xinyu Liu and Fei Guo

Energies 2025, 18(5), 1053; https://doi.org/10.3390/en18051053 - 21 Feb 2025

Viewed by 252

Abstract

The data derived from Local Climate Zone (LCZ) field measurements can contribute to the construction of regional climate datasets with urban heat island (UHI) effects and accurately present urban heat island intensity (UHII) characteristics in different areas, thereby improving the accuracy of building energy consumption simulations. This study focuses on Shenyang, a severe cold-region city, as the research area. By mapping the LCZs in the central city of Shenyang and selecting eight different types of LCZ plots for field temperature measurement, the UHI effect of various LCZs in Shenyang was analyzed. Air temperature and UHII were used to evaluate the UHII characteristics of LCZs under typical meteorological conditions. Additionally, this study investigated the temperature dynamics and heating/cooling rates of each LCZ under typical meteorological days. The results reveal significant differences in UHII characteristics among LCZ types, closely related to their surface structure and land cover characteristics. These findings further validate the effectiveness of the LCZ classification method in severe cold regions. The data obtained in this study can be used as high-precision climate model parameters for urban energy consumption models and building energy efficiency models, thus making simulation results more consistent with local characteristics and enabling more accurate energy consumption predictions. Full article

(This article belongs to the Special Issue The Application of Weather and Climate Research in the Energy Sector)

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26 pages, 9118 KiB

Open AccessArticle

Optimization of Residential Indoor Thermal Environment by Passive Design and Mechanical Ventilation in Tropical Savanna Climate Zone in Nigeria, Africa

by Tianyu Xi, Salanke Umar Sa’ad, Xinyu Liu, Haibo Sun, Ming Wang and Fei Guo

Energies 2025, 18(3), 450; https://doi.org/10.3390/en18030450 - 21 Jan 2025

Viewed by 768

Abstract

Thermal comfort is a fundamental goal of architecture aiming at protecting individuals from harsh weather conditions. In Nigeria’s savanna climate zone, such as Kaduna, poor indoor thermal comfort leads to over-reliance on air-conditioning systems. There is limited research on the application of passive design strategies in the Nigerian savanna climate, which creates a barrier to their widespread implementation in residential buildings. In response to the increased awareness of climate change and the need for sustainable design, this study explores the potential of passive design strategies, focusing on the combination of rooftop insulation and reflective materials with mechanical ventilation as a means of improving indoor thermal comfort solutions. This study conducted a 3-day field experiment of typical dwellings in Kaduna, a major city in the Nigerian savanna climate zone. The data collected from this experiment served as the basis for a simulation study using EnergyPlus software, which tested and evaluated 3 different strategies: passive design (roof insulation + reflective materials), mechanical ventilation, and a combination of passive design and mechanical ventilation. This study highlights the potential for passive design strategies to provide a more sustainable, cost-effective solution, reducing dependence on air conditioning while supporting indoor comfort. Additionally, the research methodology and insights gained offer a basis for developing future building codes in Nigeria that emphasize sustainable practices. Such codes would guide architects, builders, and policymakers in designing homes that respond to local climate needs and align with broader sustainability goals. Further research could explore additional passive measures, including advanced window technologies, shading, and natural ventilation, to maximize sustainable residential design potential in tropical savanna climates. Full article

(This article belongs to the Special Issue The Application of Weather and Climate Research in the Energy Sector)

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22 pages, 2628 KiB

Open AccessArticle

Remote-Sensing-Based Estimation of Rooftop Photovoltaic Power Production Using Physical Conversion Models and Weather Data

by Gabriel Kasmi, Augustin Touron, Philippe Blanc, Yves-Marie Saint-Drenan, Maxime Fortin and Laurent Dubus

Energies 2024, 17(17), 4353; https://doi.org/10.3390/en17174353 - 30 Aug 2024

Viewed by 915

Abstract

The global photovoltaic (PV) installed capacity, vital for the electric sector’s decarbonation, reached 1552.3

{GW}_{p}

in 2023. In France, the capacity stood at 19.9

{GW}_{p}

in April 2024. The growth of the PV installed capacity over a year was nearly 32% [...] Read more.

The global photovoltaic (PV) installed capacity, vital for the electric sector’s decarbonation, reached 1552.3

{GW}_{p}

in 2023. In France, the capacity stood at 19.9

{GW}_{p}

in April 2024. The growth of the PV installed capacity over a year was nearly 32% worldwide and 15.7% in France. However, integrating PV electricity into grids is hindered by poor knowledge of rooftop PV systems, constituting 20% of France’s installed capacity, and the lack of measurements of the production stemming from these systems. This problem of lack of measurements of the rooftop PV power production is referred to as the lack of observability. Using ground-truth measurements of individual PV systems, available at an unprecedented temporal and spatial scale, we show that by estimating the PV power production of an individual rooftop system by combining solar irradiance and temperature data, the characteristics of the PV system inferred from remote sensing methods and an irradiation-to-electric power conversion model provides accurate estimations of the PV power production. We report an average estimation error (measured with the pRMSE) of 10% relative to the system size. Our study shows that we can improve rooftop PV observability, and thus its integration into the electric grid, using little information on these systems, a simple model of the PV system, and weather data. More broadly, this study shows that limited information is sufficient to derive a reasonably good estimation of the PV power production of small-scale systems. Full article

(This article belongs to the Special Issue The Application of Weather and Climate Research in the Energy Sector)

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23 pages, 16236 KiB

Open AccessArticle

On Predicting Offshore Hub Height Wind Speed and Wind Power Density in the Northeast US Coast Using High-Resolution WRF Model Configurations during Anticyclones Coinciding with Wind Drought

by Tasnim Zaman, Timothy W. Juliano, Patrick Hawbecker and Marina Astitha

Energies 2024, 17(11), 2618; https://doi.org/10.3390/en17112618 - 29 May 2024

Cited by 1 | Viewed by 1350

Abstract

We investigated the predictive capability of various configurations of the Weather Research and Forecasting (WRF) model version 4.4, to predict hub height offshore wind speed and wind power density in the Northeast US wind farm lease areas. The selected atmospheric conditions were high-pressure systems (anticyclones) coinciding with wind speed below the cut-in wind turbine threshold. There are many factors affecting the potential of offshore wind power generation, one of them being low winds, namely wind droughts, that have been present in future climate change scenarios. The efficiency of high-resolution hub height wind prediction for such events has not been extensively investigated, even though the anticipation of such events will be important in our increased reliance on wind and solar power resources in the near future. We used offshore wind observations from the Woods Hole Oceanographic Institution’s (WHOI) Air–Sea Interaction Tower (ASIT) located south of Martha’s Vineyard to assess the impact of the initial and boundary conditions, number of model vertical levels, and inclusion of high-resolution sea surface temperature (SST) fields. Our focus has been on the influence of the initial and boundary conditions (ICBCs), SST, and model vertical layers. Our findings showed that the ICBCs exhibited the strongest influence on hub height wind predictions above all other factors. The NAM/WRF and HRRR/WRF were able to capture the decreased wind speed, and there was no single configuration that systematically produced better results. However, when using the predicted wind speed to estimate the wind power density, the HRRR/WRF had statistically improved results, with lower errors than the NAM/WRF. Our work underscored that for predicting offshore wind resources, it is important to evaluate not only the WRF predictive wind speed, but also the connection of wind speed to wind power. Full article

(This article belongs to the Special Issue The Application of Weather and Climate Research in the Energy Sector)

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36 pages, 17997 KiB

Open AccessFeature PaperArticle

Evaluation and Bias Correction of the ERA5 Reanalysis over the United States for Wind and Solar Energy Applications

by James M. Wilczak, Elena Akish, Antonietta Capotondi and Gilbert P. Compo

Energies 2024, 17(7), 1667; https://doi.org/10.3390/en17071667 - 31 Mar 2024

Cited by 9 | Viewed by 2917

Abstract

The applicability of the ERA5 reanalysis for estimating wind and solar energy generation over the contiguous United States is evaluated using wind speed and irradiance variables from multiple observational data sets. After converting ERA5 and observed meteorological variables into wind power and solar power, comparisons demonstrate that significant errors in the ERA5 reanalysis exist that limit its direct applicability for a wind and solar energy analysis. Overall, ERA5-derived solar power is biased high, while ERA5-derived wind power is biased low. During winter, the ERA5-derived solar power is biased high by 23% on average, while on an annual basis, the ERA5-derived wind power is biased low by 20%. ERA5-derived solar power errors are found to have consistent characteristics across the contiguous United States. Errors for the shortest duration and most extreme solar negative anomaly events are relatively small in the ERA5 when completely overcast conditions occur in both the ERA5 and observations. However, longer-duration anomaly events on weekly to monthly timescales, which include partially cloudy days or a mix of cloudy and sunny days, have significant ERA5 errors. At 10 days duration, the ERA5-derived average solar power produced during the largest negative anomaly events is 62% greater than observed. The ERA5 wind speed and derived wind power negative biases are largely consistent across the central and northwestern U.S., and offshore, while the northeastern U.S. has an overall small net bias. For the ERA5-derived most extreme negative anomaly wind power events, at some sites at 10 days duration, the ERA5-derived wind power produced can be less than half of that observed. Corrections to ERA5 are derived using a quantile–quantile method for solar power and linear regression of wind speed for wind power. These methods are shown to avoid potential over-inflation of the reanalysis variability resulting from differences between point measurements and the temporally and spatially smoother reanalysis values. The corrections greatly reduce the ERA5 errors, including those for extreme events associated with wind and solar energy droughts, which will be most challenging for electric grid operation. Full article

(This article belongs to the Special Issue The Application of Weather and Climate Research in the Energy Sector)

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30 pages, 8038 KiB

Open AccessFeature PaperArticle

Power Production, Inter- and Intra-Array Wake Losses from the U.S. East Coast Offshore Wind Energy Lease Areas

by Sara C. Pryor and Rebecca J. Barthelmie

Energies 2024, 17(5), 1063; https://doi.org/10.3390/en17051063 - 23 Feb 2024

Cited by 1 | Viewed by 2432

Abstract

There is an urgent need to develop accurate predictions of power production, wake losses and array–array interactions from multi-GW offshore wind farms in order to enable developments that maximize power benefits, minimize levelized cost of energy and reduce investment uncertainty. New, climatologically representative simulations with the Weather Research and Forecasting (WRF) model are presented and analyzed to address these research needs with a specific focus on offshore wind energy lease areas along the U.S. east coast. These, uniquely detailed, simulations are designed to quantify important sources of wake-loss projection uncertainty. They sample across different wind turbine deployment scenarios and thus span the range of plausible installed capacity densities (ICDs) and also include two wind farm parameterizations (WFPs; Fitch and explicit wake parameterization (EWP)) and consider the precise WRF model release used. System-wide mean capacity factors for ICDs of 3.5 to 6.0 MWkm⁻² range from 39 to 45% based on output from Fitch and 50 to 55% from EWP. Wake losses are 27–37% (Fitch) and 11–19% (EWP). The discrepancy in CF and wake losses from the two WFPs derives from two linked effects. First, EWP generates a weaker ‘deep array effect’ within the largest wind farm cluster (area of 3675 km²), though both parameterizations indicate substantial within-array wake losses. If 15 MW wind turbines are deployed at an ICD of 6 MWkm⁻² the most heavily waked wind turbines generate an average of only 32–35% of the power of those that experience the freestream (undisturbed) flow. Nevertheless, there is no evidence for saturation of the resource. The wind power density (electrical power generation per unit of surface area) increases with ICD and lies between 2 and 3 Wm⁻². Second, EWP also systematically generates smaller whole wind farm wakes. Sampling across all offshore wind energy lease areas and the range of ICD considered, the whole wind farm wake extent for a velocity deficit of 5% is 1.18 to 1.38 times larger in simulations with Fitch. Over three-quarters of the variability in normalized wake extents is attributable to variations in freestream wind speeds, turbulent kinetic energy and boundary layer depth. These dependencies on meteorological parameters allow for the development of computationally efficient emulators of wake extents from Fitch and EWP. Full article

(This article belongs to the Special Issue The Application of Weather and Climate Research in the Energy Sector)

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