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The COVID-19 pandemic appeared in the midst of developing the European Green Deal, the most ambitious project to decarbonise the EU's economy to date. Among other issues, the project highlighted the challenges connected to the long-term role of natural gas as a fossil fuel in the European economy. Moreover, the changes to the gas architecture caused by the development of new import infrastructure (especially Nord Stream and its extension, which is currently under construction) put additional pressure on the transit countries, mainly of which are linked to the Brotherhood pipeline. These have been strong supporters of natural gas utilisation and harsh critics of new pipelines that circumvent their territories, as they consider energy transit to be an important part of their energy sectors. This research examines the political discourse on gas transit in Slovakia and Ukraine in order to identify the main arguments connected to these positions. The paper examines a total of 233 textual units from both countries for the period 2014–2018. It concludes that, while Ukraine sees transit predominantly through the lens of cooperation with the EU and other actors, the Slovak political discourse considers gas transit in terms of energy security and the availability of gas for the national economy. [ABSTRACT FROM AUTHOR]

This research article provides a comprehensive scenario analysis of key structural changes in Kazakhstan's fuel and energy complex subsectors until 2060, focusing on decarbonization efforts. The background places the issue of decarbonization in a broader context, considering the country's vast size and sparse population. The study's purpose involves analyzing the development of the climate agenda by comparing two scenarios: a "reference" scenario without decarbonization measures and a carbon neutrality scenario until 2060 (CN2060). A mathematical technical-economic model based on the TIMES paradigm (The Integrated MARKAL-EFOM System) serves as the method to optimize and simulate Kazakhstan's energy system. The main findings reveal sets of policies, standards, and legislative, economic, and political decisions that are required to achieve CN2060. Additionally, the integration of a low-carbon policy, sectoral and cross-cutting approaches, the impact of the coronavirus crisis, the Russia-Ukraine conflict, and energy security issues receive a discussion. The article concludes with projected shares of generation and investment in renewable energy sources (RES) necessary for attaining CN2060. This work offers novel insights into challenges and opportunities for Kazakhstan's transition to a low-carbon economy. [ABSTRACT FROM AUTHOR]

The ongoing Russia–Ukraine conflict has exacerbated the global crisis of natural gas supply, particularly in Europe. During the winter season, major importers of liquefied natural gas (LNG), such as South Korea and Japan, were directly affected by fluctuating spot LNG prices. This study aimed to use machine learning (ML) to predict the Japan Korea Marker (JKM), a spot LNG price index, to reduce price fluctuation risks for LNG importers such as the Korean Gas Corporation (KOGAS). Hence, price prediction models were developed based on long short-term memory (LSTM), artificial neural network (ANN), and support vector machine (SVM) algorithms, which were used for time series data prediction. Eighty-seven variables were collected for JKM prediction, of which eight were selected for modeling. Four scenarios (scenarios A, B, C, and D) were devised and tested to analyze the effect of each variable on the performance of the models. Among the eight variables, JKM, national balancing point (NBP), and Brent price indexes demonstrated the largest effects on the performance of the ML models. In contrast, the variable of LNG import volume in China had the least effect. The LSTM model showed a mean absolute error (MAE) of 0.195, making it the best-performing algorithm. However, the LSTM model demonstrated a decreased in performance of at least 57% during the COVID-19 period, which raises concerns regarding the reliability of the test results obtained during that time. The study compared the ML models' prediction performances with those of the traditional statistical model, autoregressive integrated moving averages (ARIMA), to verify their effectiveness. The comparison results showed that the LSTM model's performance deviated by an MAE of 15–22%, which can be attributed to the constraints of the small dataset size and conceptual structural differences between the ML and ARIMA models. However, if a sufficiently large dataset can be secured for training, the ML model is expected to perform better than the ARIMA. Additionally, separate tests were conducted to predict the trends of JKM fluctuations and comprehensively validate the practicality of the ML models. Based on the test results, LSTM model, identified as the optimal ML algorithm, achieved a performance of 53% during the regular period and 57% d during the abnormal period (i.e., COVID-19). Subject matter experts agreed that the performance of the ML models could be improved through additional studies, ultimately reducing the risk of price fluctuations when purchasing spot LNG. [ABSTRACT FROM AUTHOR]

Energy is one of the most important aspects of urban development and technological advancements. As its production and consumption are connected to several environmental, social, and economic issues covering all three sustainability pillars, strategic and targeted energy planning is vital to the smooth transition towards a more efficient and greener society. In accordance with the specific priorities of every state, sustainable energy planning should also satisfy the international trends, requirements, and targets, including the global commitments for sustainable development. As of this time, energy transition with further deployment of renewable energy and energy efficiency improvement are the priorities for a sustainable future. However, due to recent global events, a new situation has been established. The COVID-19 pandemic and the ongoing war in Ukraine have caused new circumstances challenging the recognized approaches for an effective sustainable energy strategy. While the global pandemic led to a temporary reduction of energy use and created habits for further savings, the war caused energy security issues, especially for Europe, and an increase in energy prices. Moreover, both questioned the implementation of green energy strategies and policies and initiated energy poverty. In this framework, the perspectives of the criteria, on which the energy planning and the relevant research could lean, are investigated and discussed. [ABSTRACT FROM AUTHOR]

The effects of the global COVID-19 pandemic on the energy sector and the economy as a whole are being followed by the global energy crisis, which has been exacerbated by the war in Ukraine. The situation is particularly difficult for European countries, which are heavily dependent on imported energy from Russia. In the face of such economic uncertainty, it is necessary to analyze and assess the energy poverty situation in the region. The article overviews the extent of energy poverty among European Union (EU) countries and determines regional differences by comparing the situation, trends and policy measures applied, followed by the challenges and opportunities to combat energy poverty among households during the global COVID-19 crisis and economic uncertainty. A scientific literature review was performed and the effect of the COVID-19 pandemic on the energy poverty of households was identified. Moreover, a set of indicators reflecting the extent of energy poverty in different EU countries has been developed and an analysis of indicators was performed by comparing the situation, trends and policy measures applied. [ABSTRACT FROM AUTHOR]