Sustainable Energy Policy Research Articles

Comparison of Trends in Sustainable Energy Development in the Czech Republic and Poland

The contemporary process of economic development necessitates a heightened focus on matters of sustainability, with a particular emphasis on sustainable energy policy. This is of paramount importance for the protection of the natural environment and the achievement of long-term economic growth. In the context of countries such as the Czech Republic and Poland, which have historically relied on high-carbon energy sources, the transition to a more sustainable energy system represents a significant challenge. The objective of this paper is to undertake a comparative analysis of the trends in energy sustainability in the Czech Republic and Poland from 2017 to 2021, with a particular focus on key performance indicators. The analysis, based on data from the OECD database, revealed notable discrepancies in the rate of change between the two countries, with Poland exhibiting a more pronounced surge in the proportion of renewable energy sources (RES). A Student’s t-test confirmed the existence of statistically significant differences in key indicators between the Czech Republic and Poland, thereby underscoring the diverse challenges that both countries encounter in their pursuit of sustainable energy development. The Granger causality test was employed to ascertain whether variables exhibit temporal relationships that may suggest potential correlations. However, it is important to note that this test does not prove direct causality, but rather indicates that the variables are related at a specific point in time. Interpretation of the results must be undertaken with caution, as the test does not account for the full complexity of relationships between variables, including external factors and structural changes in the economy. Meanwhile, the LMDI decomposition analysis identified the principal drivers of alterations in CO2 emissions. The findings indicate that, despite advancements in sustainable energy development, Poland and the Czech Republic are confronted with distinctive challenges that necessitate the implementation of tailored policy responses. It is therefore recommended that further investment in renewable energy and the modernisation of energy infrastructure be made in order to achieve long-term sustainability goals.

Impact of urbanization, economic growth, FDI, and trade openness on energy demand in Ireland: An ARDL approach

Abstract This research study uses an autoregressive distributed lag (ARDL) paradigm to examine the effects of trade openness, urbanization, economic growth, and foreign direct investment (FDI) on energy demand in Ireland. This thorough theoretical framework anticipates a relationship between energy demand and trade, foreign direct investment, and urbanization. This study demonstrates both short- and long-run cointegration among the variables employing an ARDL (autoregressive distributed lag) bounds-testing method for the data set period from 1972 to 2021. Additionally, Fully Modified Ordinary Least Square (FMOLS), Dynamic Ordinary Least Square (DOLS), and Canonical Cointegrating Regression (CCR) were utilized in the study to verify the results' robustness. Nonetheless, this analysis discovers that trade openness and rising GDP (Gross Domestic Product) per capita increase energy consumption. The results show that for every 1% increase in GDP, energy consumption increases by 0.967%. On the flip side, energy consumption in Ireland is declining due to increased urbanization and foreign direct investment. The results show that for every 1% increase in urbanization, energy usage decreases by 1.738%. The investigation shows that Ireland's energy usage is strongly impacted by trade liberalization, FDI, urbanization, and economic expansion. Findings like these can help policymakers and stakeholders manage and optimize energy usage in the context of urbanization, economic expansion, foreign direct investment, and global trade. The report recommends sustainable energy planning and policy initiatives to strike a healthy balance between meeting the increasing demand for energy and protecting the environment.

Assessing dynamics of urban solar PV power generation using grid divisional method

The assessment of solar energy potential and urban density has become a crucial prerequisite for urban sustainable development. However, two significant challenges persist: the high computational cost associated with assessments across large urban areas and the lack of detailed rooftop information for each building. This study aims to integrate solar photovoltaic (PV) systems in urban environments of varying built density in an Indian city and assesses the solar energy potential (SEP) using grid divisional method and simulations. The methodology involved extracting, filtering and developing a 2.5 D model with GIS using the open buildings dataset, followed by simulations of grid-connected PV systems using PV-Sol. The results demonstrated the dynamics in correlation of SEP and grid morphology indicators, with built density and roof area showing a strong positive relation. The financial analysis resulted in average payback period of 8–10 years. The study also highlighted significant CO2 emission reductions, with thermal power plants generating 26,982 tons/kWh compared to just 1,513 tons/kWh for solar power. The findings demonstrate the financial viability and environmental benefits of PV adoption in urban areas, offering crucial insights for sustainable energy planning and policy development.

Modelling the Relationship between Air Pollution and Economic Growth in Somalia

Throughout human history, there has been a clear connection between pollution and the economy. However, the relationship between environmental harm and economic progress is complex, and disagreements between various academic disciplines have made it difficult to understand this phenomenon fully. A unit root test was conducted to gain more insight, which proposed the possibility of further empirical analysis. The Johansen cointegration method was also used to show a long-term connection between air pollution and economic growth. At the same time, the vector autoregressive model (VAR) indicated a short-term connection between the two. A Vector Error Correction Model (VECM) was then employed to estimate the relationship, and the findings confirmed the existence of the Environmental Kuznets Curve (EKC). The EKC demonstrates that economic growth has positive and negative effects on air pollution. The Granger causality test conducted in Somalia showed a causal link between economic growth and air pollution. The EKC model further supported this finding by demonstrating that economic growth has a statistically significant positive impact on greenhouse gas (GHG) emissions. This implies that Somalia has seen increased GHG emissions, leading to environmental degradation. Therefore, the Somali government must prioritise the implementation of a sustainable energy policy to improve air quality and prevent further environmental deterioration.

Energy consumption and environmental economy: The development and impact of fossil energy and new energy in China

With the rapid development of China's economy and the continuous increase in energy consumption, the usage of fossil energy and new energy resources and their impact on the environment and economy have attracted increasing attention. Through literature review and data analysis, combined with relevant research, this paper systematically collates and analyzes the latest statistics on China's energy consumption. It also explores the effects of this consumption on both the environment and the economy. This study will cover the production, consumption and environmental influence of various energy sources, with the aim of providing a scientific foundation for sustainable energy policy. Through extensive studies on the advancement of various energy resources, they can serve as a scientific foundation for the formation of future energy policy and the promotion of sustainable development. The study reveals that while fossil fuels continue to be the primary source of energy, the consumption of alternative energy sources is experiencing a significant and quick increase.

Exergy and Energy Analysis of Bifacial PV Module Performance on a Cloudy Day in Saudi Arabia

Bifacial solar modules, capable of harvesting sunlight from both sides, present a promising pathway for sustainable energy generation. This study examines the performance of bifacial modules on a cloudy day through comparative exergy and energy analyses. The analysis considers both the quality and quantity of energy produced by bifacial and monofacial modules. Conducted at Qassim University in Buraydah City, Saudi Arabia, the study recorded measurements during two intervals on a cloudy day using a real-time photovoltaic measurement system. Module performance was evaluated concerning energy yield, exergy yield, and solar irradiance, factoring in ambient and module temperatures. The results demonstrate that bifacial modules outperformed monofacial modules in electrical energy and output exergy. In the first period, the bifacial modules showed a 9.5% higher exergy efficiency and a 7% greater energy efficiency compared to the monofacial modules. During the second period, the bifacial modules achieved a 4.5% higher exergy efficiency and a 3.5% increased energy efficiency over the monofacial modules. These findings contribute to global sustainability efforts by reducing fossil fuel dependence and optimizing bifacial PV module design and operation for enhanced energy and exergy efficiency, even in cloudy conditions. The study’s implications for sustainable development and energy policies underscore the essential role of advanced PV technologies in achieving sustainable energy goals.

The Role of Renewable Energy Policy and R&D in Renewables Diffusion

This paper explores how investments in research and development (R&D) and government policies impact the growth of renewable energy in Brazil, Chile, and Colombia up to 2040. The study presents four scenarios to understand how different levels of R&D investment and the presence or absence of supportive policies affect the spread of renewable technologies such as solar and wind energy. The scenarios range from an optimistic one with high R&D funding and strong policy support to a worst-case scenario with low R&D efforts and weak policies. The findings emphasize the importance of solid government backing and strategic R&D investments in promoting renewable energy and increasing the number of green patents. On the other hand, scenarios with limited policy support and R&D funding show much slower growth, highlighting the challenges posed by economic constraints and tough market conditions. The study shows that strong renewable energy policies could boost renewable energy adoption by 100% to 200%. Overall, this research adds to the discussion on sustainable energy policies and provides useful insights for policymakers and stakeholders to develop strategies that maximize the potential of renewable energy in the region.

Monthly electricity consumption data at 1 km × 1 km grid for 280 cities in China from 2012 to 2019

High spatio-temporal resolution estimates of electricity consumption are essential for formulating effective energy transition strategies. However, the data availability is limited by complex spatio-temporal heterogeneity and insufficient multi-source feature fusion. To address these issues, this study introduces an innovative downscaling method that combines multi-source data with machine learning and spatial interpolation techniques. The method’s accuracy showed significant improvements, with determination coefficients (R2) increasing by 30.1% and 33.4% over the baseline model in two evaluation datasets. With this advanced model, we estimated monthly electricity consumption across 1 km x 1 km grid for 280 Chinese cities from 2012 to 2019. Our dataset is highly consistent with officially released electricity consumption of different industries (Pearson correlation coefficients within 0.83 - 0.91). Moreover, our data can reflect the electricity consumption patterns of different urban land uses compared to other datasets. This study bridges a significant gap in fine-grained electricity consumption data, providing a robust foundation for the development of sustainable energy policies.

Effects of solar energy absorbed by south wall on carbon emission from space heating in hot summer-cold winter region

Carbon emission caused by space heating (CEH) in hot summer and cold winter climate zone has increased dramatically. Taking advantage of the solar energy absorbed by south wall (SEASW) can effectively reduce CEH, however, the accurate quantification of its impact remains a challenge. The study investigates the potential of SEASW in mitigating CEH. Key parameters affecting CEH, such as sunny day ratio, insulation form, and outer surface heat transfer coefficient of south wall (h), were analyzed. Results show the reduction in carbon emissions caused by the solar energy absorbed by each unit area of the south-facing wall (ΔCreduction) can be as high as 18.61 kgCO2⋅m−2 for the wall employing internal insulation and smaller h. A prediction model of ΔCreduction was further developed by using multivariate nonlinear regression, which can estimate the reduction in CEH for different fuels as heating source by a south wall in different sizes. Besides, the potential of SEASW on the reduction of carbon emission per unit floor area can reach 12.2 %. This study underscores the importance of SEASW as a carbon-neutral heating strategy, particularly for regions characterized by short winter heating periods and lower heating loads compared to colder climates. It provides valuable insights for sustainable energy practices and policy formulation.

From Tweets to Energy Trends (TwEn): An exploratory framework for machine learning-based forecasting of urban-scale energy behavior leveraging social media data

Understanding energy behavior is crucial in addressing climate change, yet the accuracy of energy predictions is often limited by reliance on oversimplified occupancy data. This study develops an exploratory framework, from Tweets to Energy Trends (TwEn), leveraging machine learning and geo-tagged social media data to investigate the social dynamics of urban energy behavior. TwEn explores the relationship between social media interactions, specifically the frequency of tweets using data from the X Platform, and energy use patterns on an hourly basis. Employing various machine learning models, including artificial neural networks (ANN), decision tree (DTREE), random forest (RDF), and gradient boosting machine (GBM), the study evaluates their efficiency in both static and time-series forecasting of energy use trends and investigates the capability of social media data in predicting urban energy patterns. In addition, the study carries out a series of sensitivity analyses to provide an examination of the data and models. Furthermore, comprehensive data acquisition methods are developed and implemented. Tested on New York City using actual hourly electricity consumption data, the framework demonstrates significant predictive power of tweet frequency on urban electricity use. The framework also exhibits significant seasonality in X data, identifying patterns and trends that can inform time series urban building energy models (UBEM). The results offer new insights into the determinants of urban energy behavior and provide crucial perspectives for augmenting UBEMs, ensuring they are closely aligned with the complex social dynamics of contemporary urban environments. By integrating both digital and physical data, this study sheds light on urban energy behavior, supporting the formulation of effective and sustainable energy policies for urban futures.

Temperature variation and urban electricity consumption in China: Implications for demand management and planning

With the pressing challenges of climate change and rapid urbanization, understanding the impact of temperature variation on electricity consumption in urban areas is crucial for effective demand management and planning. This study investigates the relationship between temperature and electricity usage in Chinese urban centers, shedding light on critical patterns that can inform sustainable energy policies. Using panel data analysis reveals a significant impact of temperature change on household electricity consumption. The findings indicate an optimal temperature range of 18–24 °C and a non-linear association between temperature and power usage. Notably, the rise in summer temperatures has a greater impact on electricity consumption than the decrease in colder winters. The study also highlights variations in the influence of temperature on electricity consumption based on regional economic development and north-south disparities. The study suggests implications for optimizing power supply planning.

Post-Modern Planning Theory: the New era of Indonesia Energy Planning

Objective: The objective of this study is to explore how decision-making procedures based on postmodern planning theories can facilitate the integration of social and environmental aspects into energy planning. This is critical in the context of global agendas such as the Sustainable Development Goals (SDGs) and the New Urban Agenda (NUA), which emphasize the provision of clean energy and equitable access to energy. Theoretical Framework: This study is grounded in postmodern planning theories, which prioritize inclusivity, communication, and the negotiation of values among various stakeholders. These theories contrast with traditional, market-oriented energy planning approaches that often marginalize social and environmental considerations. Method: The research employs a qualitative approach, analyzing case studies where postmodern planning principles have been applied to energy planning. This includes a review of policy documents, interviews with key stakeholders, and an examination of the interactions between government sectors and between the government and society. Result and Discussion: The findings indicate that postmodern planning approaches can effectively bridge the gap between social/environmental goals and economic interests in energy planning. Through enhanced communication and negotiation among stakeholders, it is possible to achieve more inclusive and sustainable energy policies. The study highlights specific instances where these approaches have led to more balanced energy planning outcomes, especially in regions focused on rapid economic growth. Research Implication: The implications of this research suggest that adopting postmodern planning principles can significantly improve the inclusivity and sustainability of energy planning processes. Policymakers are encouraged to foster greater communication and value exchange among stakeholders to balance economic, social, and environmental objectives. Originality/Value: This study contributes to the literature by demonstrating the practical application of postmodern planning theories to energy planning. It provides a novel perspective on how to reconcile the often competing interests of economic growth and sustainable development, particularly in the energy sector.

Controversy or Consensus: Launching Small Modular Nuclear Reactors in Romania

Abstract The transition towards net zero by 2050 is underway in the European Union, but its country members are divided over their energy strategies. France, Poland, Hungary, Bulgaria, Slovakia, and Romania support nuclear plants as contributing to carbon neutrality, while Germany, Spain, Denmark, Portugal, and Luxembourg oppose (Reuters, 2023). The study “Between Stability and Sustainability: Nuclear Energy in Romania's Energy Mix” concludes that Romania can benefit from its nuclear facilities and domestic uranium resources, to consolidate its sustainable energy policy. However, new nuclear capacities may pose considerable challenges, especially in terms of costs (Dumitrescu, 2023). Unfortunately, rising costs per megawatt hour are the very reason why NuScale, the operator chosen by Romania to deploy six small nuclear reactors by 2027, canceled their US-based flagship Carbon Free Power Project (Fortune, 2023). Nevertheless, the setback in the home country did not prevent Romanian authorities from licensing the NuScale small modular reactor power plant in Doicești (World Nuclear News, 2023). The watchdog Greenpeace warned about the project’s high costs and the long construction timeframe. It was also emphasized that Romania adopted a technology that had never been tested before. In addition, the location of the new plant had been decided without prior consultation from the local community, claimed the NGO (Greenpeace, 2022). According to the journalists, the local community has been divided between those who want new jobs and people afraid of radiations. Reporters made a parallel between the current situation and a formerly failed Chevron shale gas production investment, due to the strong opposition to fracking (Hotnews, 2024). This paper attempts to determine how a newcomer to the nuclear energy market, with a significant approval setback in its home country, using untested technology, can complete the construction of six small modular reactors in Romania, integrate those into the national grid and win over the public acceptance by 2030.

Impact of Sustainable Energy Policies on European Stock Markets

Impact of Sustainable Energy Policies on European Stock Markets

Toward a sustainable environment within the framework of carbon neutrality scenarios: Evidence from the novel Fourier‐NARDL approach

AbstractSustainable energy policies are directly proportional to countries' achievement of the Sustainable Development Goals (SDGs). Economies that want to achieve their 2030 and 2050 targets are looking for alternative energy sources until renewable energy sources mature. In this context, this study models the environmental quality of France, which is the leader in the use of nuclear energy in Europe, from a different perspective through nuclear energy technologies. This study empirically uses the novel Fourier asymmetric autoregressive distributed lag approach. It confirms that increases and decreases in nuclear technology have different effects on the load capacity factor within the framework of the load capacity curve (LCC) hypothesis. It also provides evidence for the existence of the LCC hypothesis and offers sustainable energy policies for France. The French government should allocate funds to cleaner energies instead of investing in nuclear energy technologies. Thus, the long‐term transition to a low‐carbon economy can be accelerated instead of short‐term targets. By eliminating nuclear energy, a severe burden on the French economy, infrastructure can be created for alternative energy sources. Finally, the French government can gain momentum in achieving SDGs 7 and 13 by withdrawing support from nuclear energy technologies.

Consumption-Based Energy Footprints in Iceland: High and Equally Distributed

With the urgent global need to limit warming to 2 °C as well as a localized need in our case study to address rising energy demand amid electrical and thermal network limitations, a critical examination of demand-side energy reductions and the concept of energy sufficiency is needed. This paper contributes to the sparse literature on bottom-up analysis by utilizing Iceland—a leader in renewable energy generation—as a case study to explore the socio-economic factors influencing energy footprints. Our findings reveal significant energy footprints across various consumption domains, particularly housing and mobility, influenced by income levels, urbanization, and lifestyle choices. The study highlights the paradox of a high renewable energy supply leading to potential misconceptions regarding abundant and low-cost energy, resulting in substantial energy consumption-related environmental impacts. Using detailed household consumption survey data, this research provides insights crucial for developing sustainable energy policies that not only target technological advancements but also address the need for a reduction in energy demand and a shift towards energy sufficiency. This work marks a contribution to the literature through the provision of a case study of low income inequality and high energy footprints in a highly renewable energy system context. Further, this work is useful for Icelandic and international policymakers to understand in such high-demand contexts which consumption domains would be most relevant for sufficiency policies. This comprehensive analysis opens pathways for future research to further explore the intersections of energy consumption, socio-economic factors, and well-being, offering a nuanced understanding necessary for crafting sufficiency and demand-side policies aimed at a sustainable energy future.

Path to clean and sustainable energy from nuclear and renewable sources: Evidence from France

France is one of the countries that have made commendable progress towards accomplishing sustainable development goals but still struggles with combating environmental challenges. Decarbonizing the energy sector by deploying clean energy and reducing fossil fuels in the energy mix are essential steps. The study uses annual time series data from 1980 to 2021 and employs the ridge regression estimation technique to estimate a twice-differentiable transcendental production function, which approximates the second-order Taylor series to explore the potential for such decarbonization for France. The study finds that substitution possibilities exist between clean energy and fossil fuels, with substantial substitution possibilities coming from nuclear energy. Nuclear energy and renewables are found to be complements that can be deployed concurrently, but since nuclear energy already constitutes a significant proportion of clean energy for France, the study recommends increasing the proportion of renewable energy in the overall energy mix as the most plausible path to decarbonization. Other complementary sustainable energy policies are recommended in the body of the paper.

RESEARCH ON THE PERFORMANCE OF WASTE HEAT RECOVERY FOR THE THERMOELECTRIC POWER GENERATION

Non-renewable energy resources, which account for about 85% of worlds’ energy (68% fossil fuels are used for electric power generation), are getting exhausted rapidly. As predicted by the Institute of Sustainable Energy Policies, by the year 2050, only 33% of non-renewable energy resources will be available for electric power generation. Hence, to meet the required demand, the remaining 67% has to be replaced by renewable energy sources. This demand in electric power generation has to be met by a pollution free, low-cost, clean energy resource, which is the need of the hour. The present research targets towards two main applications for generating power using the biomass energy based resources. They are domestic based application – burning biomass wood and utilizing the heat for generating power, industrial based application – combustion of gasified de-oiled Pongamia cake and utilizing the heat energy for generating power. Key Words: TEG, SEEBECK EFFECT, ENERGY CONVERSION

ANALYSIS THE EFFECTIVENESS OF THERMOELECTRIC POWER GENERATION USING WASTE HEAT RECOVERY

Non-renewable energy resources, which account for about 85% of worlds’ energy (68% fossil fuels are used for electric power generation), are getting exhausted rapidly. As predicted by the Institute of Sustainable Energy Policies, by the year 2050, only 33% of non-renewable energy resources will be available for electric power generation. Hence, to meet the required demand, the remaining 67% has to be replaced by renewable energy sources. This demand in electric power generation has to be met by a pollution free, low-cost, clean energy resource, which is the need of the hour. The present research targets towards two main applications for generating power using the biomass energy based resources. They are domestic based application – burning biomass wood and utilizing the heat for generating power, industrial based application – combustion of gasified de-oiled Pongamia cake and utilizing the heat energy for generating power In order to achieve the proposed target, initially, the theoretical modeling on the performance of (Bi2Te3-PbTe) hybrid thermoelectric generator (TEG) composed of n-type Bismuth Telluride - p-type Lead Telluride semiconductor materials has been done. The effect of different performance parameters on the maximum conversion and power efficiencies have been theoretically analyzed by varying the hot side temperature. Key Words: Hybrid Thermoelectric Generator, Electric Power Generation, Graphene Nanoparticles.

Persistence of disaggregate energy RD&D expenditures in top-five economies: Evidence from artificial neural network approach

The motivation of this paper is to investigate the resistance of countries' energy research and development (RD&D) expenditures to random shocks. The analysis includes the five countries (France, Germany, Japan, the United States, and the United Kingdom) that are the biggest investors in RD&D in fossil fuels, renewables, energy efficiency, and nuclear energy. Thus, economies will be able to take precautions against global shocks in producing sustainable energy policies. To achieve this aim, this paper uses the artificial neural network approach, which uses a distributed computing model that can store and generalize data after a learning period. Empirical results widely depend on countries and distinct energy technology policy fields. The key findings provide evidence that RD&D expenditures, except for renewables, do not tend to mean revert. The economies of Japan, Germany, and the United States should make more renewable investments to reduce the resistance of renewable energy sources to shocks and thus produce policies for both environmental sustainability and energy security. The economies of France and the United Kingdom can ensure energy security by continuing their sustainable energy policies.