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The focus of this study is to analyse and compare the predictive capabilities of univariate and multivariate methods of forecasting the global horizontal irradiance (GHI) for an hour ahead. The forecasting problem is addressed using supervised machine learning methods. In order to simplify the model, a feature selection algorithm is used to identify the highly correlated features. The forecasting is performed by utilizing popular machine learning algorithms viz., random forest (RF), K-nearest neighbors regression (KNN), support vector machine (SVM) and artificial neural networks (ANN). The paper evaluates and contrasts the effectiveness of these models for this application. Additionally, the study examines how the forecasting models' performance varies throughout the year and across seasons.

The focus of this study is to analyse and compare the predictive capabilities of univariate and multivariate methods of forecasting the global horizontal irradiance (GHI) for an hour ahead. The forecasting problem is addressed using supervised machine learning methods. In order to simplify the model, a feature selection algorithm is used to identify the highly correlated features. The forecasting is performed by utilizing popular machine learning algorithms viz., random forest (RF), K-nearest neighbors regression (KNN), support vector machine (SVM) and artificial neural networks (ANN). The paper evaluates and contrasts the effectiveness of these models for this application. Additionally, the study examines how the forecasting models' performance varies throughout the year and across seasons.

According to the second law of thermodynamics, all human activities cause exergy destructions, adding to additional root causes for carbon dioxide emissions responsibility. It means that current carbon dioxide concentrations are accurately observed, but the root causes and their potential solutions against global warming fall short of achieving the goals of the Paris agreement by almost 45% in terms of decarbonization efforts, as shown in this paper. This result applies to all activities, including the green facility concept. In this respect, the primary aim of this paper is to raise awareness about the essence of the Second Law of Thermodynamics in expanding the green facility concept to reach more effective and sustainable rating methodologies concerning the climate crisis. A new evaluating and rating model with a set of exergy-based green building metrics that relate additional carbon dioxide emissions to irreversible exergy destructions has been developed. Examples about apparently green buildings according to the First Law of Thermodynamics are given by showing that these buildings are not green due to additional carbon dioxide emissions responsibility due to exergy destructions. An airport terminal building case is elaborated. It has been shown that although part of the electricity comes from a third-party wind energy provider, it ends up with carbon dioxide emissions responsibility because it is not entirely used in exergy-rational demand points and compares less favorably with an on-site cogeneration system using natural gas by about 30% more emissions responsibility. The results and derivations of new metrics are discussed, which shed light on adding new criteria to existing green building certification programs.

According to the second law of thermodynamics, all human activities cause exergy destructions, adding to additional root causes for carbon dioxide emissions responsibility. It means that current carbon dioxide concentrations are accurately observed, but the root causes and their potential solutions against global warming fall short of achieving the goals of the Paris agreement by almost 45% in terms of decarbonization efforts, as shown in this paper. This result applies to all activities, including the green facility concept. In this respect, the primary aim of this paper is to raise awareness about the essence of the Second Law of Thermodynamics in expanding the green facility concept to reach more effective and sustainable rating methodologies concerning the climate crisis. A new evaluating and rating model with a set of exergy-based green building metrics that relate additional carbon dioxide emissions to irreversible exergy destructions has been developed. Examples about apparently green buildings according to the First Law of Thermodynamics are given by showing that these buildings are not green due to additional carbon dioxide emissions responsibility due to exergy destructions. An airport terminal building case is elaborated. It has been shown that although part of the electricity comes from a third-party wind energy provider, it ends up with carbon dioxide emissions responsibility because it is not entirely used in exergy-rational demand points and compares less favorably with an on-site cogeneration system using natural gas by about 30% more emissions responsibility. The results and derivations of new metrics are discussed, which shed light on adding new criteria to existing green building certification programs.

Abstract As main contributors to greenhouse gas emissions, power and transportation are crucial sectors for energy system decarbonization. Their interaction is expected to increase significantly: plug-in electric vehicles add a new electric load, increasing grid demand and potentially requiring substantial grid upgrade; hydrogen production for fuel cell electric vehicles or for clean fuels synthesis could exploit the projected massive power overgeneration by intermittent and seasonally-dependent renewable sources via Power-to-Hydrogen. This work investigates the infrastructural needs involved with a broad diffusion of clean mobility, adopting a sector integration perspective at the national scale. The analysis combines a multi-node energy system balance simulation and a techno-economic assessment of the infrastructure to deliver energy vectors for mobility. The article explores the long-term case of Italy, considering a massive increase of renewable power generation capacity and investigating different mobility scenarios, where low-emission vehicles account for 50% of the stock. First, the model solves the energy balances, integrating the consumption related to mobility energy vectors and taking into account power grid constraints. Then, an optimal infrastructure is identified, composed of both a hydrogen delivery network and a widespread installation of charging points. Results show that the infrastructural requirements bring about investment costs in the range of 43–63 G€. Lower specific costs are associated with the exclusive presence of FCEVs, whereas the full reliance on BEVs leads to the most significant costs. Scenarios that combine FCEVs and BEVs lie in between, suggesting that the overall power + mobility system benefits from the presence of both drivetrain options.

Abstract As main contributors to greenhouse gas emissions, power and transportation are crucial sectors for energy system decarbonization. Their interaction is expected to increase significantly: plug-in electric vehicles add a new electric load, increasing grid demand and potentially requiring substantial grid upgrade; hydrogen production for fuel cell electric vehicles or for clean fuels synthesis could exploit the projected massive power overgeneration by intermittent and seasonally-dependent renewable sources via Power-to-Hydrogen. This work investigates the infrastructural needs involved with a broad diffusion of clean mobility, adopting a sector integration perspective at the national scale. The analysis combines a multi-node energy system balance simulation and a techno-economic assessment of the infrastructure to deliver energy vectors for mobility. The article explores the long-term case of Italy, considering a massive increase of renewable power generation capacity and investigating different mobility scenarios, where low-emission vehicles account for 50% of the stock. First, the model solves the energy balances, integrating the consumption related to mobility energy vectors and taking into account power grid constraints. Then, an optimal infrastructure is identified, composed of both a hydrogen delivery network and a widespread installation of charging points. Results show that the infrastructural requirements bring about investment costs in the range of 43–63 G€. Lower specific costs are associated with the exclusive presence of FCEVs, whereas the full reliance on BEVs leads to the most significant costs. Scenarios that combine FCEVs and BEVs lie in between, suggesting that the overall power + mobility system benefits from the presence of both drivetrain options.

AbstractThis study compared the economic and environmental impacts of torrefaction on bioenergy supply chains against conventional pellets for scenarios where biomass is produced in Mozambique, and undergoes pre‐processing before shipment to Rotterdam for conversion to power and Fischer‐Tropsch (FT) fuels. We also compared the impacts of using different land quality (productive and marginal) for feedstock production, feedstocks (eucalyptus and switchgrass), final conversion technologies (XtY and CXtY) and markets (the Netherlands and Mozambique). At current conditions, the torrefied pellets (TOPs) are delivered in Rotterdam at higher cost (7.3–7.5 $/GJ) than pellets (5.1–5.3 $/GJ). In the long term, TOPs costs could decline (4.7–5.8 $/GJ) and converge with pellets. TOPs supply chains also incur 20% lower greenhouse gas (GHG) emissions than pellets. Due to improved logistics and lower conversion investment, fuel production costs from TOPs are lower (12.8–16.9 $/GJFT) than from pellets (12.9–18.7 $/GJFT). Co‐firing scenarios (CXtY) result in lower cost fuel (but a higher environmental penalty) than 100% biomass fired scenarios (XtY). In most cases, switchgrass and the productive region of Nampula provide the lowest fuel production cost compared to eucalyptus and the marginally productive Gaza region. Both FT and ion in Mozambique are more costly than in Rotterdam. For the Netherlands, both FT and power production are competitive against average energy costs in Western Europe. The analysis shows that large‐scale bioenergy production can become competitive against fossil fuels. While the benefits of TOPs are apparent in logistics and conversion, the current higher torrefaction costs contribute to higher biofuel costs. Improvements in torrefaction technology can result in significant performance improvements over the future chain. © 2013 Society of Chemical Industry and John Wiley & Sons, Ltd

AbstractThis study compared the economic and environmental impacts of torrefaction on bioenergy supply chains against conventional pellets for scenarios where biomass is produced in Mozambique, and undergoes pre‐processing before shipment to Rotterdam for conversion to power and Fischer‐Tropsch (FT) fuels. We also compared the impacts of using different land quality (productive and marginal) for feedstock production, feedstocks (eucalyptus and switchgrass), final conversion technologies (XtY and CXtY) and markets (the Netherlands and Mozambique). At current conditions, the torrefied pellets (TOPs) are delivered in Rotterdam at higher cost (7.3–7.5 $/GJ) than pellets (5.1–5.3 $/GJ). In the long term, TOPs costs could decline (4.7–5.8 $/GJ) and converge with pellets. TOPs supply chains also incur 20% lower greenhouse gas (GHG) emissions than pellets. Due to improved logistics and lower conversion investment, fuel production costs from TOPs are lower (12.8–16.9 $/GJFT) than from pellets (12.9–18.7 $/GJFT). Co‐firing scenarios (CXtY) result in lower cost fuel (but a higher environmental penalty) than 100% biomass fired scenarios (XtY). In most cases, switchgrass and the productive region of Nampula provide the lowest fuel production cost compared to eucalyptus and the marginally productive Gaza region. Both FT and ion in Mozambique are more costly than in Rotterdam. For the Netherlands, both FT and power production are competitive against average energy costs in Western Europe. The analysis shows that large‐scale bioenergy production can become competitive against fossil fuels. While the benefits of TOPs are apparent in logistics and conversion, the current higher torrefaction costs contribute to higher biofuel costs. Improvements in torrefaction technology can result in significant performance improvements over the future chain. © 2013 Society of Chemical Industry and John Wiley & Sons, Ltd