Energy Policy Research Articles

Advanced Carbon Management: Innovations in Materials and Process Integration for Carbon Capture, Storage, and Utilization (CCSU)

Purpose: This article systematically explores the complex landscape of Carbon Capture, Storage, and Utilization (CCSU) technologies, emphasizing their critical role in global climate change mitigation. The article aims to provide a strategic framework for stakeholders to understand the integration of CCSU technologies into the broader energy and environmental policy landscape. Methodology: Through an integrated approach, this study examines the latest technological advancements in CCSU, studies the global regulatory frameworks influencing these technologies, and analyzes the economic factors that drive or obstruct their adoption. It also involves evaluating the role of international cooperation in standardizing and disseminating best practices for CCSU implementations worldwide. Findings: The study highlights the profound impact of legislative and financial mechanisms on the pace and scope of CCSU technology deployment. It discusses the potential of innovative materials and processes to reduce costs and increase the efficacy of carbon capture and storage. Furthermore, the review provides valuable insights into the current state and future prospects of CCSU technologies. Unique contribution to theory, policy and practice: The article emphasizes the necessity of robust research and development, supported by a conducive policy environment and strategic economic incentives, to enhance the efficiency, scalability, and commercial viability of CCSU technologies. It concludes with targeted recommendations for policymakers, suggesting ways to refine regulatory approaches and foster market conditions conducive to rapid CCSU adoption.

Comparative assessment and policy analysis of forecasting quarterly renewable energy demand: Fresh evidence from an innovative seasonal approach with superior matching algorithms

In the pursuit of sustainable development, accurate renewable energy demand forecasting holds great significance for climate change mitigation and promoting sustainability. However, renewable energy forecasting has been consistently challenged by seasonality and nonlinearity. Identifying the periodic and nonlinear characteristics concealed within renewable energy sources accurately is still an unexplored problem. Consequently, an innovative nonlinear discrete seasonal grey model is proposed for renewable energy forecasting, which incorporates seasonal dummy variables and a power exponent term for handling the seasonality and nonlinear patterns in time series. Furthermore, an intelligent algorithm matching framework is proposed to augment the flexibility of the newly developed model. For practical purposes, the new methodology is contrasted against a range of benchmarks encompassing statistical, machine-learning, and traditional grey models in forecasting the quarterly total renewable energy consumption in the United States. The proposed model exhibits over 27% improvement rates over its counterparts, achieving the most superior predictive accuracies of 1.45%, 39.27, and 0.79 in MAPEP, RMSEP, and MASEP metrics, respectively. Furthermore, the probability density and sample size analyses are conducted to validate the robustness of the new model, confirming its adaptability and stability towards algorithm randomness and historical information volume. Consequently, the novel model is employed to forecast the short-to-long-terms renewable energy consumption in the U.S., showcasing an upward trend and seasonal fluctuations of the consumption for the forthcoming 24 quarters from 2023Q4 to 2029Q3. These insights can offer valuable implications to the stakeholders such as energy suppliers, utility managers, and policy advocates, highlighting actionable strategies for optimizing renewable energy consumption forecasting and aiding sustainable development initiatives.

Blue Lead‐Free Perovskite Derivatives: Structural Diversity, Luminescence Properties and Light‐Emitting Diode Applications

AbstractHalide perovskite light‐emitting diodes (LEDs) have made remarkable advancements in both efficiency and stability. However, when compared to green and red LEDs, blue perovskite LEDs still lag behind in terms of efficiency and stability. Presently, efficient blue LEDs primarily rely on lead‐based perovskites, which goes against the environmentally friendly practices and restricts potential industrial applications. Consequently, there has been a surge of interest in academic research toward developing blue LEDs using lead‐free perovskites. This paper provides a comprehensive review of the structural diversity of lead‐free perovskite derivatives used for blue emission, encompassing Sn‐, Zr‐, Bi‐, Sb‐, Cu‐, Zn‐based halides as well as double perovskites. Various material synthesis techniques are discussed, such as nanocrystal preparation and film preparation. Additionally, the photoluminescence properties for different energy band structures are outlined, along with the luminescence mechanism involving energy transfer and strategies for enhancing luminous efficiency. The advancement in efficiency and stability of lead‐free perovskite LEDs is also examined in this review. Finally, the current challenges and future opportunities in advancing research on blue lead‐free perovskite derivatives and their potential application in LED technology is emphasized.

Optimal Gasoline Price Predictions: Leveraging the ANFIS Regression Model

This study presents an in-depth analysis of gasoline price forecasting using the adaptive network-based fuzzy inference system (ANFIS), with an emphasis on its implications for policy-making and strategic decisions in the energy sector. The model leverages a comprehensive dataset from the U.S. Energy Information Administration, spanning over 30 years of historical price data from 1993 to 2023, along with relevant temporal features. By combining the strengths of fuzzy logic and neural networks, the ANFIS approach can effectively capture the complex, nonlinear relationships present in the data, enabling reliable price predictions. The dataset’s preprocessing involved decomposing the date into year, month, and day components to enhance the model’s input features. Our methodology entailed a systematic approach to ANFIS regression, including data preparation, model training with the inclusion of the previous week’s prices as an additional feature, and rigorous performance evaluation using MSE, RMSE, and correlation coefficients. The results indicate that incorporating previous prices significantly enhances the model’s accuracy, as reflected by improved scores and correlation metrics. The findings have significant implications for the energy sector, where stakeholders can leverage the ANFIS model’s insights for strategic decision-making. Accurate gasoline price forecasts are instrumental in devising pricing strategies, managing risks associated with price volatility, and guiding policy formulation. The model’s predictive capability enables energy companies to optimize resource allocation, plan for future investments, and maintain competitive advantage in a market influenced by fluctuating prices. Moreover, policymakers can utilize these predictions to assess the impact of energy policies on market prices and consumer behavior, ensuring that regulatory measures align with market dynamics and sustainability goals. In addition to the ANFIS model, we also employed Vector Autoregression (VAR) and Autoregressive Integrated Moving Average (ARIMA) models to validate our approach and provide a comprehensive understanding of time series forecasting within the energy sector. Notably, the ANFIS model achieves a score of 0.9970 and a robust correlation of 0.9985, demonstrating its ability to accurately forecast gasoline prices based on historical data and features. The integration of these traditional techniques with advanced ANFIS modeling offers a robust framework for accurate and reliable gasoline price prediction, which is vital for informed policy-making and strategic planning in the energy industry.

The implications of the ecological footprint and renewable energy usage on the financial stability of South Asian countries

This study explores the complex relationships involving ecological footprints, energy use, carbon emissions, governance efficiency, economic prosperity, and financial stability in South Asian nations spanning the period from 2000 to 2022. Employing various methodologies such as cross-sectional dependence tests, co-integration analysis, and first- and second-generation unit-root tests, we use a panel Autoregressive Distributed Lag model, feasible generalized least squares, and Panel Corrected Standard Errors to ensure the robustness of our findings. We find noteworthy positive correlations between several variables, including heightened ecological consciousness, effective governance structures, increased GDP per capita, and amplified CO2 emissions. These relationships suggest potential pathways to strengthen the financial stability of the entire region; they also highlight the latent potential of embracing ecologically sustainable practices to fortify economic resilience. Our results also underscore the pivotal role of appropriate governance structures and higher income levels in bolstering financial stability in South Asian countries. Interestingly, we also find negative coefficients associated with the use of renewable energy, suggesting that escalating the adoption of renewable energy could create financial instability. This finding stresses the importance of diversification in energy strategies, cautioning policymakers to carefully consider the financial ramifications of potentially costly imports of renewable energy sources while seeking to reduce carbon emissions, emphasizing the need to strike a balance between ambitious sustainability goals and the pursuit of sustained economic robustness in the region. In considering the implications of these findings, it is crucial to consider each country’s broader socioeconomic context. Our results offer valuable insights for policymakers in developing renewable energy strategies.

The time-varying dynamic impact of US renewable energy prices on agricultural prices in China: the case of fuel ethanol.

This paper intends to look into the time-varying dynamic impact of US fuel ethanol, one of the renewable energy sources, on the prices of agricultural products (specifically corn, soybeans, rice, and wheat) in China based on monthly price data from January 2000 to January 2023. To achieve this, a time-varying parameter vector autoregressive (TVP-VAR) model is employed, which takes into account structural changes in emergencies through time-varying parameters. The empirical results show that the equal-interval impulse responses of price fluctuations in agricultural commodities are primarily positive to variations in fuel ethanol prices and production. And the intensity and direction of the effects vary at distinct time lags. Additionally, the magnitude of these responses is most pronounced in the short term for all agricultural commodities except for corn, and the duration of the impulse responses at different time points is generally longer for corn prices compared to other commodities. The study also reveals that the influence of US fuel ethanol on Chinese agricultural commodity prices is not substantial on the whole. Therefore, there is a necessity to advance the growth of biofuels and provide policy support and financial subsidies for agricultural products earmarked for food production. These actions could shed insights into the progression of Chinese renewable energy and food policies, ensuring the stability of the market in the long run.

Solar potential for social benefit: Maps to sustainably address energy poverty utilizing open spatial data in data poor settings

Access to affordable sustainable energy is a significant challenge for many lowincome countries experiencing energy poverty. The United Nations (UN) Sustainable Development Goal (SDG) 7 aims to “ensure access to affordable, reliable, sustainable and modern energy for all.” Simultaneously, the European Union (EU) seeks to reduce emissions by 55 % by 2030. Decarbonization policies must be carefully considered to avoid adverse effects on vulnerable groups experiencing energy poverty. Solar technology offers a viable solution to decarbonize the building sector, reduce energy dependence on fossil fuels, and provide financial benefits to the public. Mapping solar potential is crucial to determine where investment in solar photovoltaic (PV) technology is most advantageous to the populations who stand to benefit the most. We combine a solar potential mapping approach incorporating socio-economic indicators indicative of energy poverty, using off-the-shelf Geographic Information Systems (GIS) tools that are easily replicated across cities facing energy poverty. Utilizing lowest common denominator data and analysis approaches, we offer creative and innovative mapping solutions. The socio-economic factors help to contextualise the benefits of distributed PV systems and highlight the need for mapping solar potential, in combination with energy poverty indicators for sustainable planning and policymaking. Our results for a case study in the city of Plovdiv, Bulgaria, demonstrate high solar energy potential that could meet 29 % of the city's electricity needs, save citizens about M€ 43.84 annually, and pinpoint where to invest first for the highest gains. Finally, we offer suggestions on how to use these results to inform decarbonization policies to benefit low-income populations that are often missed in existing energy policies.

Exploring policy coherence to understand limited progress of gender and social inclusion in the energy sector: The case of Nepal

Goal 7 of the Sustainable Development Goals (SDGs) aims to ensure access to affordable, reliable, sustainable, and modern energy for all by 2030 but securing universal access to energy supplies remains a challenge worldwide. There is increased recognition that gender and social inclusion (GESI) is critical for the transition towards low-carbon energy.Nepal's inclusive 2015 Constitution, and its 2021 federal-level Gender Equality Policy translate this commitment. Likewise, Nepal is committed to SDG 7. Yet energy policy includes only limited provisions for ensuring energy access by marginalized groups and women. This paper focuses on energy policy coherence to identify cohesion between policies and policy instruments at different levels of governance to identify bottlenecks to GESI. Using a policy coherence and feminist policy approach within an energy justice context, it traces the coherence of GESI policy through time and in relation to overall GESI policy objectives. Horizontal and internal coherence are assessed through the parallels/disjoints between energy-related periodic plans, policies, budgets, and GESI aims. The evolution of GESI in energy investments has been slow in part because of a narrow conceptualization of the policy problem and a lack of coherence and synchronization across documents, which undermines implementation of the GESI agenda.

The Long-Run Linkage among the Macroeconomic Factors and CO2 Emissions in terms of Sea Transport Induced EKC Hypothesis in USA

The main aim of this article is to comprehend the long-run relationship among sea transportation, energy use, GDP, and CO2 for USA from 1980 to 2023. In this sense, FMOLS, DOLS, CCR, and ARDL analyses are employed in order to investigate the entity of long-run linkage between the relevant variables. According to results of this manuscript, except energy use there is no both long-run relationship among variables and effects of independent variables (GDP, sea transportation) on dependent variable (CO2 emissions) from 1980 to 2023 in USA. Therefore, the sea transport-induced EKC hypothesis has not been confirmed empirically. Although the hypothesis has not been confirmed, there are some issues to consider in terms of energy consumption. Transportation energy consumption and greenhouse gas emissions are seen as an alarming threat to leaving a livable and sustainable green environment and economy to future generations. Fossil fuels used in transportation have an important place in carbon dioxide emissions. This is seen as a crucial environmental factor that all stakeholders should consider when planning energy and environmental policy decisions. In order to prevent environmental quality from being negatively affected by greenhouse gas and exhaust emissions, policy makers need to encourage more energy efficient and healthier transportation ways. Thus, the harmful effects of transportation energy consumption can be reduced as well.

Assessing the EU Climate and Energy Policy Priorities for Transport and Mobility through the Analysis of User-Generated Social Media Content Based on Text-Mining Techniques

For over three decades, the European Union’s (EU) transport policy has aimed at fostering environmental sustainability and energy efficiency. Since 2015, European policymakers have focused more on three key sustainable development goals: decarbonizing the transport system, promoting low-emission mobility solutions, and transitioning to renewable and alternative fuels. To effectively communicate priorities and engage stakeholders, EU policymakers regularly use social media platforms like Twitter (now known as X). This active discourse involves policymakers, industrial stakeholders, the media, and the public, offering insights into the role of transport policy in addressing climate change and energy transition challenges. The current research endeavors to track and analyze the evolution of user-generated content related to climate change, energy transition, and smart mobility on Twitter from 2011 to 2021. This research uses text-mining and social network analysis techniques to quantitatively and qualitatively assess the dynamics of relevant EU policies and their effects. The study’s findings can be used to establish a robust monitoring and evaluation framework at the EU and national levels. This framework will assess the effectiveness of communicating strategic priorities for sustainable transport development. It also holds potential for application in other sectors, broadening its impact.

The Relationship between the Renewable Energy and CO2 Emissions to the Indonesian Economy

The Indonesian government through the National Energy Council (DEN) has a target for new renewable energy to be increased, starting from 2025 with a target of 23 percent to 2060 with a target of 66 percent, but in fact new renewable energy in Indonesia only increases 0.55 percent per year. Indonesia has great potential, but can the potential be maximized by the government in the direction of a better and environmentally friendly energy policy. This study analyzes the movement of renewable energy and C02 emissions to the Indonesian economy from 1990-2021, using the Vector Error Correction Model (VECM) statistical method by considering short-term and long-term results in the model. The results show that in the long and short term economy the role of GDP per unit of energy use for the economy is needed and has a positive effect, the role of carbon emissions in the short and long term C02 has a positive and significant direction, non-renewable energy in the long term and short term is still moving negative and significant, this indicates that renewable energy in Indonesia tends to be low, energy replacement must be carried out slowly and gradually, shock response conditions conclude when GDP energy use and CO2 are affected by a negative shock will disrupt economic development, meanwhile, if there is a negative shock on consumption Renewable energy still tends to be stable and positive for the development of the Indonesian economy.

The Impact of Implementing a Carbon Tax on Welfare: Case Study of Indonesia and The Other ASEAN Member Countries

Green House Gases emitted into the atmosphere over decades cause global warming now. The aim of this research is the impact of implementing the carbon tax on welfare in Indonesia. The research method used is the CGE method using GTAP-E to evaluate energy policy in the economy. GTAP-E consists of 140 countries and 57 sectors combined into forty-two regions and eight sectors. Using carbon tax scenario (simulation 1 is 1.93 USD/ton CO 2, simulation 2 is 3.72 USD/ton CO 2, and simulation 3 is 4.83 USD/ton CO 2). The results of the Indonesian equivalent variation show a negative value. The higher the carbon tax is applied, the greater the decline in welfare. This is also felt by all research countries except the Philippines, Singapore, Thailand, Oceania, OtherSEAsia, East Asia, Argentina, Japan, Poland, Portugal, and Ukraine. The variable of the regional demand, it can be seen that the carbon tax causes Indonesia's regional income to increase, and Singapore's income to decrease, while other countries experience no change in income. The primary factor return ratio also shows that the increase in the carbon tax caused a decline in the Land, Unsklab, Sklab, Capital, and Natural Resources sectors. Indonesia's GDP also shows a decrease if a higher carbon tax is implemented, but other countries have no impact on GDP. The Carbon emissions show that it decreases to Indonesia. So, the implementation of the carbon tax causes a decrease in welfare as seen from the equivalent variation, Primary Return Ratio, and GDP in Indonesia. The government must have an alternative policy if a carbon tax is implemented in Indonesia.

Acceptance of offshore wind farm in Southwest Sardinia in Italy. Do regional energy policies matter?

Purpose The social acceptance of wind energy is increasingly conditioning the Italian Government and regions to authorize the construction of these plants. The proposal of offshore wind farm in the south-west of Sardinia has raised many perplexities both from the marine environmental point of view and from concern about increasing the electricity production in a region that already exports electricity to the peninsula. The purpose of this study is to evaluate what are the factors that most affect the coastal residents’ acceptability of an offshore wind farm. Design/methodology/approach The data is based on a Sardinia-wide in-person survey with about 512 participants in the period between May and June 2023. Respondents were selected randomly from five different locations in Carloforte region. Multiple regression analysis investigates the factors that influenced acceptability to construction and development of offshore wind power plant. Four independent variables were selected in the regression models such as (i) interest towards wind energy, (ii) attitude towards renewable energy production, (iii) perceived regional energy policy and (iv) attitude towards offshore wind farm. The dependent variables are the rates of coastal local residents’ acceptance of offshore wind farm for respondents in five coastal towns. Findings Fishermen and summer tourism operators’ respondents expressed significant reluctance to accept the new project because they perceive a strong risk of environmental impact on both tuna fishing and marine recreational activities in the vicinity. The distance between the turbines at sea and local residents along the coast and surrounding small islands does not have an influence to accept wind energy. The energy policy of the Region of Sardinia, which is perceived by respondents as an expansive energy policy in the production of electricity that exceeds their needs, not being accompanied by a scenario of reducing that from fossil fuels, is the variable that led about 70% of respondents to express a negative opinion towards this project. Research limitations/implications A potential problem associated with the survey is that local response produced sample selection bias. The proportion of respondents with secondary education and no school certificate is quite high. It is possible that respondents who provided valid questionnaires were more low-educated and therefore, the sample may be biased towards lower-educated people. While this does not invalidate the results of this study, it is important to note that the sample was on average less educated than the overall population in Italy. In addition, people with lower incomes were more likely to complete the questionnaires; the results are more representative of a portion of the population with incomes below the national average. Practical implications Results showed how coastal communities are in favour of wind energy within their island, but not within a marine protected area that is considered unique for its beauty and marine ecosystem. Wind energy developers should, before submitting a proposal for an offshore wind farm project, consider among other things the long approval time and understand the activities carried out by local communities and their attachment to those places. Politicians and developers should develop a coherent energy transition policy based on a long-term vision of zero emissions, because according to the findings of this study, it was the regional energy policy that is the most controversial reason for residents to reject the project. Originality/value The contribution of this study is to fill a part of the research gap linking to ongoing energy transitions. In particular, this study analysed for the first time in Italy the acceptability level of an offshore renewable energy project considering the environmental implications and risks in the fragile marine ecosystem of Carloforte waters. This study also made it possible to analyse the impact of the regional energy policy on the acceptability of residents towards the development of offshore wind farms, which is scarcely discussed in the literature.

Public perceptions of fossil and alternative energy in Serbia: Between NIMBYism and nationalism

Understanding public perceptions of energy sources is essential for successful policy formulation. Our study explores the Serbian public's attitudes toward different types of energy, taking into account NIMBY (“Not In My Back Yard") sentiments, nationalist orientation, and pro-Russian attitudes. A correlational cross-sectional design utilized an online survey disseminated via social media platforms. The study examined public preferences for various energy types and their correlations with nationalist and pro-Russian tendencies. Poststratification weighting was applied to address sample representativeness. Our research revealed the public's preference for renewable energy, particularly solar and wind. Surprisingly, nationalist views did not significantly align with fossil fuel preferences, differentiating Serbia from Western European trends. Geopolitical considerations, such as Serbia's relationship with Russia, did not strongly influence public opinion. These findings underscore the importance of considering public preferences in shaping Serbia's energy policy, emphasizing the need for investment in renewables. Based on the results we offer concrete policy recommendations. This study offers a methodological approach adaptable to other countries undergoing similar energy transition.

A systematic framework for compilation of critical raw material lists and their importance for South Africa

Mineral resources are important contributors to the global economy and societal wellbeing. Directly, they provide employment, revenue and taxes through the extraction, processing and sale of minerals. Indirectly, they are essential to all modern industries, including: energy, manufacturing, construction, biotic and abiotic resource extraction and agriculture. The principle that ‘one cannot understand the value of what they have until they measure it’ is particularly relevant with critical raw materials (CRMs). CRM is a concept that categorises select resources (mainly minerals and metals) as critical in the sense that, at a national level, they are essential and difficult to replace, and their supply is prone to disruption. It is becoming increasingly recognised that the continuity of civilisation and living standards as some have envisioned them in the future is constrained by the quality and quantity of various minerals. National-level strategic planning, including energy policy, foreign relations policy, geopolitical operations, national defence, education and infrastructure planning, among others, all require knowledge of the requirement and supply of raw materials towards a practical strategic implementation. Hence, a national CRM framework is essential for a prosperous, productive and stable future. To effectively manage the supply and use of CRMs, it is important to comprehend both their formal (e.g., economic) and informal (e.g., social and environmental) values, and to measure and monitor these values effectively over time. This study examines international practices and methodologies as components of a comprehensive CRM framework. We then propose a prototype CRM framework for South Africa as such a framework is currently missing.All CRM frameworks feature one or more rating schemes to identify the degree of criticality of raw materials. The actual rating metrics are divided into dimensions (or factors), such as: socio-economic importance, technological importance, environmental, social and governance risks. Such dimensions are important due to the following reasons.•Delineating criticality from non-criticality: by rank-ordering CRMs based on various factors, a country can identify which ones are the most important for its economy, industry and national security. This information can help policymakers prioritise the development of domestic production and secure a stable supply of CRMs.•Assessing resource sustainability and supply stability: by rating CRMs based on environmental, social and ethical factors, a country can assess the sustainability of its resource use and identify areas for improvement. This information can help policymakers develop strategies to mitigate resource depletion, and supply chain disruption, minimise negative environmental and social impacts, and promote responsible resource management.•Supporting informed decision-making: an ordered ranking of CRMs provides quantitative and qualitative information to governmental bodies, industry and other stakeholders to support informed decision-making, including strategic planning. This information can help stakeholders make informed choices about the sources and types of CRMs they use and the sustainability of their resource use.•Promoting transparency and accountability: adopting suitable business ethical dimensions, such as through a corporate social responsibility framework, enables a country to promote transparency and accountability in its resource use and supply chains. This approach can help reduce illicit financial flows, corruption, and abuse of power, while increasing trust and confidence in the resource sector.•Innovation and investment opportunities: a CRM framework enables a nation to establish policy conditions that foster innovation and investment in key activities such as measuring, monitoring, sustainability, extracting, responsible processing, and efficient use of CRMs.Findings from this study underscores the necessity of a structured CRM framework in South Africa to effectively manage the complexities of resource management, economic ground, and sustainability. Integrating these frameworks into national policies can enable South Africa to secure a sustainable, economically viable, and environmentally responsible future. Such strategic initiatives are impor tant for national security, industrial policy, structural transformation, and economic stability, as well as aligning with global initiatives for responsible sourcing and climate change.

Post-Fracture Production Prediction with Production Segmentation and Well Logging: Harnessing Pipelines and Hyperparameter Tuning with GridSearchCV

As the petroleum industry increasingly exploits unconventional reservoirs with low permeability and porosity, accurate predictions of post-fracture production are becoming critical for investment decisions, energy policy development, and environmental impact assessments. However, despite extensive research, accurately forecasting post-fracture production using well-log data continues to be a complex challenge. This study introduces a new method of data volume expansion, which is to subdivide the gas production of each well on the first day according to the depth of logging data, and to rely on the correlation model between petrophysical parameters and gas production to accurately combine the gas production data while matching the accuracy of the well-log data. Twelve pipelines were constructed utilizing a range of techniques to fit the regression relationship between logging parameters and post-fracture gas production These included data preprocessing methods (StandardScaler and RobustScaler), feature extraction approaches (PCA and PolynomialFeatures), and advanced machine learning models (XGBoost, Random Forest, and neural networks). Hyperparameter optimization was executed via GridSearchCV. To assess the efficacy of diverse models, metrics including the coefficient of determination (R2), standard deviation (SD), Pearson correlation coefficient (PCC), mean absolute error (MAE), mean squared error (MSE), and root-mean-square error (RMSE) were invoked. Among the several pipelines explored, the PFS-NN exhibited excellent predictive capability in specific reservoir contexts. In essence, integrating machine learning with logging parameters can be used to effectively assess reservoir productivity at multi-meter formation scales. This strategy not only mitigates uncertainties endemic to reservoir exploration but also equips petroleum engineers with the ability to monitor reservoir dynamics, thereby facilitating reservoir development. Additionally, this approach provides reservoir engineers with an efficient means of reservoir performance oversight.

Mapping the European Union’s Renewable Energy Transition Amidst the Russo-Ukrainian War

This research paper delves into the complex interplay between the European Union's (EU) ambitious renewable energy transition and the geopolitical backdrop of the Russo-Ukrainian War. Against the backdrop of evolving global energy dynamics and the EU's commitment to sustainability, the study aims to elucidate how the conflict has shaped and influenced the EU's pursuit of renewable energy sources. The Russo-Ukrainian War, marked by geopolitical tensions and energy security concerns, has prompted the EU to reassess its energy landscape. The paper employs a multi-faceted approach, combining geopolitical analysis, policy evaluation, and energy infrastructure mapping to understand how the conflict has impacted the EU's renewable energy strategies. It scrutinises the policy shifts, regulatory frameworks, and investment patterns in the renewable energy sector within the EU member states. Furthermore, the research investigates the role of energy diplomacy and the EU's efforts to diversify its energy sources in response to the geopolitical instability stemming from the conflict. It explores the challenges and opportunities presented by the war, such as the urgency for energy independence and the need for cohesive cross-border collaboration. By employing data-driven analyses and case studies, this paper contributes to the broader discourse on the intersection of geopolitics and renewable energy transitions. It offers insights into the dynamic relationship between regional conflicts and the imperative for sustainable energy practices, providing policymakers, scholars, and industry stakeholders with valuable perspectives on navigating the intricate landscape of renewable energy transitions in the midst of geopolitical uncertainties.

Power improvement of triboelectric nanogenerator by morphological transformation strategy for harvesting irregular wave energy

Wave is inherently characterized by disorder and randomness, which is a great challenge for the conventional wave-based triboelectric nanogenerator (W-TENG) and necessitates conducting adaptability research on the device. Therefore, we proposed a morphological transformation strategy, that is, W-TENG can actively transform the motion patterns of self-structure to accommodate the variations in waves and achieve power improvement. And a morphological transformation TENG (MT-TENG) with multi-mode operation is developed for harvesting irregular wave energy. Furthermore, the disorder wave motion is transformed into a bidirectional continuous rotation of power generation units, which realizes the continuous waveform output. Experimental results demonstrate that the wave power grows by 9.22 times with frequency increase, and the device's performance increases by 114.136 times utilizing this strategy. MT-TENG can output 39.67 mA through the energy management circuit (EMC) and a peak power density of 30.62 W/m3 under the wave excitation of 1.1 Hz. Finally, the self-powered environmental monitoring system is constructed, which can illuminate ten 30 W LEDs in series and provide a continuous energy supply to the wireless sensor module. This work presents a research paradigm for the design of wave-environment adaptability, holding significant implications for improving performance and constructing self-powered sensing systems.

Перешкоди впровадженню теплових насосів у централізованому теплопостачанні

Today, heat pumps are recognized as one of the technologies that most contribute to the decarbonization of almost all spheres of modern society life, especially industry and energy. The integration of heat pumps into district heating is considered as an implementation of renewable energy technology that will enable the European Union (EU) to achieve its ambitious energy and climate policy goals for developing sustainable society. The purpose of this article is to analyze and systematize the EU experience in overcoming obstacles to the introduction of heat pump technologies in district heating and to determine the possibilities of its application in Ukraine. It was found that it is impossible to ensure the universal integration of heat pumps into district heating for all EU members, and an individual analysis is required for each EU country, taking all technical and environmental aspects into account. Obstacles to the large-scale implementation of heat pump technologies into district heating are of a complex nature. Complex obstacles require an integrated approach that simultaneously removes these obstacles and includes direct incentives, indirect taxes, technical standards, building codes, education, etc. An analysis of the experience of the EU countries (financial support, education and training, preferential tariffs for electricity for heat pump operation, EU regulations on energy efficiency of buildings, the EU directive on renewable energy sources, etc.) made it possible to identify obstacles to the widespread implementation of heat pumps in district heating. The main such obstacles are the high initial cost of heat pump equipment, the high cost of electricity, the high cost of connecting to electricity and heat networks, insufficient government incentives, the lack of domestic production of heat pumps and highly qualified personnel for their implementation. The proposed main preventive measures to overcome these obstacles are the creation of a State Program to stimulate the introduction of heat pumps; legislative support aimed at accelerating the introduction of heat pumps; creation of financial incentives for their implementation; state stimulation of production of heat pump equipment and professional training of operating personnel. This article is aimed at discussing directions for the formation of effective legislative and regulatory measures for comprehensive stimulation of the large-scale introduction of heat pumps in the district heating in Ukraine. Keywords: heat pumps, renewable energy sources, district heating, implementation, obstacles, overcoming.

Marine Renewable-Driven Green Hydrogen Production toward a Sustainable Solution and a Low-Carbon Future in Morocco

Oceanic energy sources, notably offshore wind and wave power, present a significant opportunity to generate green hydrogen through water electrolysis. This approach allows for offshore hydrogen production, which can be efficiently transported through existing pipelines and stored in various forms, offering a versatile solution to tackle the intermittency of renewable energy sources and potentially revolutionize the entire electrical grid infrastructure. This research focusses on assessing the technical and economic feasibility of this method in six strategic coastal regions in Morocco: Laayoune, Agadir, Essaouira, Eljadida, Casablanca and Larache. Our proposed system integrates offshore wind turbines, oscillating water column wave energy converters, and PEM electrolyzers, to meet energy demands while aligning with global sustainability objectives. Significant electricity production estimates are observed across these regions, ranging from 14 MW to 20 MW. Additionally, encouraging annual estimates of hydrogen production, varying between 20 and 40 tonnes for specific locations, showcase the potential of this approach. The system’s performance demonstrates promising efficiency rates, ranging from 13% to 18%, while maintaining competitive production costs. These findings underscore the ability of oceanic energy-driven green hydrogen to diversify Morocco’s energy portfolio, bolster water resilience, and foster sustainable development. Ultimately, this research lays the groundwork for comprehensive energy policies and substantial infrastructure investments, positioning Morocco on a trajectory towards a decarbonized future powered by innovative and clean technologies.