Article
Economics
Katarzyna Maciejowska, Weronika Nitka, Tomasz Weron
Summary: Recent years have seen rapid development of renewable energy sources globally, with predictions of RES and demand levels recognized as key factors for future electricity prices. Bias in forecasts of fundamental variables published by TSOs can be improved with simple regression models, resulting in more accurate price predictions and increased revenues.
Article
Business, Finance
Shusheng Ding, Tianxiang Cui, Yongmin Zhang
Summary: Future markets play vital roles in supporting economic activities, and volatility forecasting in futures markets has gained increasing attention in financial research. This study utilizes big data analytics to improve the accuracy of volatility forecasting in futures markets and demonstrates the application of big data analytics in the financial spectrum. The empirical results indicate that the XGBoost method outperforms other models in terms of volatility forecasting accuracy.
INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS
(2022)
Article
Economics
Anselm Eicke, Oliver Ruhnau, Lion Hirth
Summary: This study views electricity balancing as a market where supply and demand determine the equilibrium price and quantity of imbalance energy. System operators provide imbalance energy while market participants' behavior affects the demand for imbalance energy. The research finds that in Germany, there is a significant decrease in demand for imbalance energy for each increase in the imbalance price by 1 euro per MWh.
Article
Green & Sustainable Science & Technology
John Atherton, Markus Hofmeister, Sebastian Mosbach, Jethro Akroyd, Feroz Farazi, Markus Kraft
Summary: The expansion of variable renewable energy (VRE) generation presents challenges for national energy systems, as coal energy generation maintains and grows its position in the imbalance market. A comparative study of the British and German markets reveals changing roles of VRE, fossil fuelled energy, and compensation technologies.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Energy & Fuels
Christoph Fraunholz, Emil Kraft, Dogan Keles, Wolf Fichtner
Summary: This article introduces an innovative methodology combining machine learning and agent-based modeling for electricity price forecasting. Through a case study, it was found that the neural network approach outperforms the linear regression method in terms of prediction accuracy, and the use of an outlier handling classifier significantly improves forecasting accuracy.
Review
Energy & Fuels
Hakan Acaroglu, Fausto Pedro Garcia Marquez
Summary: Forecasting electricity market prices and loads has been a critical area of research, with a focus on wind energy techniques. The complexity of forecasting is influenced by multiple variables and methodologies, impacting market operations and decision makers.
Article
Energy & Fuels
Salih Gunduz, Umut Ugurlu, Ilkay Oksuz
Summary: This paper proposes using transfer learning to utilize information from other electricity price markets for forecasting. The experiments show that transfer learning significantly improves the electricity price forecasting performance, and the method outperforms state-of-the-art algorithms.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2023)
Article
Economics
Anselm Eicke, Tim Schittekatte
Summary: Contrary to the uniform pricing within bidding zones in European power markets, nodal pricing in liberalized U.S. electricity markets has been increasingly considered as a potential solution due to its significant cost-saving benefits. However, the persistent opposition to nodal pricing in Europe is mainly based on perceived flaws of the concept, rather than practical justifications.
Article
Energy & Fuels
James Hyungkwan Kim, Andrew D. Mills, Ryan Wiser, Mark Bolinger, Will Gorman, Cristina Crespo Montanes, Eric O'Shaughnessy
Summary: This study analyzes the impact of various strategies on the net value of grid-connected PV electricity in the United States, finding that maximizing generation (such as solar tracking plus oversized PV arrays) in conjunction with storage can yield the largest net value gains at high penetrations.
Article
Computer Science, Information Systems
Kehe Wu, Yanyu Chai, Xiaoliang Zhang, Xun Zhao
Summary: With the reform of the power system, power price prediction has become a crucial problem that needs to be addressed. This study proposes a power price prediction method based on particle swarm optimization of the XGBoost model, which improves the accuracy of the prediction by optimizing the model's parameters. Experimental results show that the PSO-XGBoost model outperforms other methods in terms of accuracy and trend conformity.
Article
Energy & Fuels
Oliver Ruhnau
Summary: By adding flexible electricity demand, green hydrogen production can effectively and permanently halt the decline in market value of renewable energy.
Article
Engineering, Electrical & Electronic
Alex Coronati, Jose R. Andrade, Ricardo J. Bessa
Summary: This paper introduces the application of long short-term memory (LSTM) network for forecasting residual demand curves (RDCs), enabling market agents to evaluate bidding strategies by combining past RDCs and exogenous variables. The method of transforming RDCs' temporal sequence into a sequence of images improves prediction performance and outperforms other machine learning models with over 35% improvement in both root mean square error and Frechet distance in empirical tests.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Energy & Fuels
Gaurav Kapoor, Nuttanan Wichitaksorn
Summary: In this study, different statistical models and machine learning models were compared for daily electricity price forecasting in the New Zealand electricity market. GARCH and SV models, along with their t-distribution variants and feature selection techniques, were found to perform exceptionally well, particularly when combined with a diverse set of explanatory variables. When compared to popular machine learning models like LSTM, GRU, XGBoost, LEAR, and a four-layer DNN, the GARCH and SV models consistently outperformed them, especially when combined with LASSO feature selection. The comprehensive evaluation provided in this study highlights the practical relevance of the best-performing model, which improved the symmetric mean absolute percentage error (sMAPE) and mean absolute scaled error (MASE) by 2% to 3% over the LEAR benchmark model.
Article
Engineering, Electrical & Electronic
Alvaro Manso-Burgos, David Ribo-Perez, Sergio Mateo-Barcos, Pablo Carnero, Tomas Gomez-Navarro
Summary: This study assesses the market value of improving PV solar power generation forecasting and analyzes the correlation between different agents in the electricity system. Accurate renewable energy forecasting has significant potential but requires proper regulation to prevent exploitation by malicious agents.
Article
Engineering, Electrical & Electronic
Dhaou Said
Summary: Smart micro-grid is a growing segment of the modern power grid, bringing benefits in terms of improving power reliability, quality, security, sustainability, and competitiveness in a deregulated electricity market. However, it is still in the early commercial stage, and success depends on addressing open issues such as standardization and regulations.
IEEE COMMUNICATIONS MAGAZINE
(2021)
Article
Energy & Fuels
Dazhi Yang, Stefano Alessandrini, Javier Antonanzas, Fernando Antonanzas-Torres, Viorel Badescu, Hans Georg Beyer, Robert Blaga, John Boland, Jamie M. Bright, Carlos F. M. Coimbra, Mathieu David, Azeddine Frimane, Christian A. Gueymard, Tao Hong, Merlinde J. Kay, Sven Killinger, Jan Kleissl, Philippe Lauret, Elke Lorenz, Dennis van der Meer, Marius Paulescu, Richard Perez, Oscar Perpinan-Lamigueiro, Ian Marius Peters, Gordon Reikard, David Renne, Yves-Marie Saint-Drenan, Yong Shuai, Ruben Urraca, Hadrien Verbois, Frank Vignola, Cyril Voyant, Jie Zhang
Review
Energy & Fuels
Fernando Antonanzas-Torres, Javier Antonanzas, Julio Blanco-Fernandez
Summary: The current electrification status in West African countries requires improvement, and off-grid mini grids have shown great potential in addressing energy challenges, attracting international funding. Despite rapid growth in the market, research and data on the social impact of mini grids in this region remains scarce.
Article
Environmental Sciences
Silvia Rivas, Yeray Hernandez, Ruben Urraca, Paulo Barbosa
Summary: Current trends in climate change show that urban areas are at high risk due to their population concentration. The Covenant of Mayors for Climate and Energy initiative aims to tackle local adaptation to climate change in a global and harmonized way. Stakeholder and citizen engagement, especially at the local level, can significantly facilitate the acceptance of adaptation plans within the initiative, with smaller municipalities benefiting more from such engagement opportunities.
ENVIRONMENTAL SCIENCE & POLICY
(2021)
Article
Green & Sustainable Science & Technology
J. Antonanzas, J. C. Quinn
Summary: While the PV industry has achieved greenhouse gas emissions payback between 2012 and 2016, its effectiveness in preventing other environmental damages is limited. More technology improvements are needed to lower the impact in other environmental categories beyond climate change and make solar PV more sustainable.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Green & Sustainable Science & Technology
Fernando Antonanzas-Torres, Javier Antonanzas, Julio Blanco-Fernandez
Summary: This study examined the environmental impact of SHS in Sub-Saharan Africa, highlighting lead-acid batteries as the main contributor to environmental harm. User training was identified as crucial for improving energy payback time and reducing GHG emissions associated with SHS operations.
Article
Green & Sustainable Science & Technology
Silvia Rivas, Ruben Urraca, Valentina Palermo, Paolo Bertoldi
Summary: To ensure success for climate change mitigation policies, it is essential to address the issue of inadequate monitoring. This can be achieved through increased participation and collaboration, accurate budget allocation, and timely development and implementation of action plans.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Green & Sustainable Science & Technology
Silvia Rivas, Ruben Urraca, Paolo Bertoldi, Christian Thiel
Summary: This study examines the factors driving European cities to set ambitious GHG reduction targets by 2030 and finds that developing local mitigation actions based on baseline emission inventory results is key. It also shows that specific cities have the ability to set highly ambitious mitigation targets by municipalizing energy facilities and addressing highly emitting sectors such as transportation. Additionally, the study highlights easy-to-reach solutions for increasing climate ambition, such as developing in-house action plans and engaging stakeholders early in the planning process.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Green & Sustainable Science & Technology
Fernando Antonanzas-Torres, Ruben Urraca, Camilo Andres Cortes Guerrero, Julio Blanco-Fernandez
Summary: The feasibility and economic cost of e-cooking were evaluated in rural Sub-Saharan Africa, showing that using solar home systems and low-power cooking devices can provide clean and environmentally-friendly cooking options for households. Compared to traditional cooking technologies using wood and charcoal fuel, e-cooking has lower carbon emissions and is more cost-effective.
Article
Green & Sustainable Science & Technology
F. Antonanzas-Torres, J. Antonanzas, J. Blanco-Fernandez
Summary: In West Africa, the study found that 100% PV mini grids outperform other mini grid solutions and national grid electricity in terms of most environmental indicators, with significantly lower greenhouse gas emissions and energy payback period.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2021)
Article
Environmental Sciences
Ruben Urraca, Christian Lanconelli, Fabrizio Cappucci, Nadine Gobron
Summary: This study analyzes the performance of multiple satellite products in monitoring surface albedo over snow. The results show that MCD43C3 has the smallest bias and more stable performance, while GLASS-AVHRR and C3S-v1/v2 show a decrease in albedo quality over snow.
Article
Green & Sustainable Science & Technology
Silvia Rivas, Ruben Urraca, Paolo Bertoldi
Summary: This paper evaluates the actual achievements of local climate action plans in Europe and analyzes the different reduction patterns and factors influencing local authorities. Large local authorities rely on climate experience and stakeholder engagement, while small local authorities depend more on political authorization and support from regional governments. The partnership between government levels is a key factor in climate action planning.
Article
Geography, Physical
Ruben Urraca, Nadine Gobron
Summary: Using Earth observation data and reanalysis products, it is now possible to monitor snow cover changes and infer climate change impacts. The stability of these products becomes crucial when tracking changes over time. The study evaluates the stability of satellite-based and reanalysis products using ground stations as reference data and highlights the challenges posed by assimilating new observations.
Article
Energy & Fuels
Siddharth Sradhasagar, Omkar Subhasish Khuntia, Srikanta Biswal, Sougat Purohit, Amritendu Roy
Summary: In this study, machine learning models were developed to predict the bandgap and its character of double perovskite materials, with LGBMRegressor and XGBClassifier models identified as the best predictors. These models were further employed to predict the bandgap of novel bismuth-based transition metal oxide double perovskites, showing high accuracy, especially in the range of 1.2-1.8 eV.
Article
Energy & Fuels
Wei Shuai, Haoran Xu, Baoyang Luo, Yihui Huang, Dong Chen, Peiwang Zhu, Gang Xiao
Summary: In this study, a hybrid model based on numerical simulation and deep learning is proposed for the optimization and operation of solar receivers. By applying the model to different application scenarios and considering multiple performance objectives, small errors are achieved and optimal structure parameters and heliostat scales are identified. This approach is not only applicable to gas turbines but also heating systems.
Article
Energy & Fuels
Mubashar Ali, Zunaira Bibi, M. W. Younis, Muhammad Mubashir, Muqaddas Iqbal, Muhammad Usman Ali, Muhammad Asif Iqbal
Summary: This study investigates the structural, mechanical, and optoelectronic properties of the BaCuF3 fluoroperovskite using the first-principles modelling approach. The stability and characteristics of different cubic structures of BaCuF3 are evaluated, and the alpha-BaCuF3 and beta-BaCuF3 compounds are found to be mechanically stable with favorable optical properties for solar cells and high-frequency UV applications.
Article
Energy & Fuels
Dong Le Khac, Shahariar Chowdhury, Asmaa Soheil Najm, Montri Luengchavanon, Araa mebdir Holi, Mohammad Shah Jamal, Chin Hua Chia, Kuaanan Techato, Vidhya Selvanathan
Summary: A novel recycling system is proposed in this study to decompose and reclaim the constituent materials of organic-inorganic perovskite solar cells (PSCs). By utilizing a one-step solution process extraction approach, the chemical composition of each layer is successfully preserved, enabling their potential reuse. The proposed recycling technique helps mitigate pollution risks, minimize waste generation, and reduce recycling costs.
Article
Energy & Fuels
Peijie Lin, Feng Guo, Xiaoyang Lu, Qianying Zheng, Shuying Cheng, Yaohai Lin, Zhicong Chen, Lijun Wu, Zhuang Qian
Summary: This paper proposes an open-set fault diagnosis model for PV arrays based on 1D VoVNet-SVDD. The model accurately diagnoses various types of faults and is capable of identifying unknown fault types.
