Energy Investment Research Articles

The Asian Infrastructure Investment Bank's Role in Promoting Sustainable Hydropower Projects: A Comparative Analysis of the Mangdechhu and Punatsangchhu-I Projects

This study compares the Asian Infrastructure Investment Bank (AIIB)-led Mangdechhu Hydroelectric Project with the World Bank-supported Punatsangchhu-I Hydroelectric Project. By comparing the approval and implementation process, multilateral and regional cooperation, sustainable development factors, and challenges and coping strategies of these two hydropower projects, it is concluded that AIIB has a clear advantage in promoting sustainable energy projects. AIIB has demonstrated an efficient project approval and implementation process, as well as close multilateral and regional partnerships. In addition, AIIB has systematically focused on the environmental, social and economic impacts of the project, so that sustainable development can be balanced in the progress of energy projects. However, the agency's pressing issues include technical difficulties, environmental protection, and population resettlement. In order to meet these challenges, AIIB needs to strengthen the learning of experience, optimize the project strategy, and expand the scope of cooperation. The findings of this study have guiding value for policymakers and academia. In future energy cooperation and investment, governments, multilateral development banks and relevant institutions should learn from the practical experience of AIIB and formulate more effective and targeted policies and plans. By tackling challenges together, we will contribute to solving global energy problems and promoting sustainable development.

Assessing Decarbonization Approaches across Major Economies

The global energy transition is an uneven process, fundamentally related to the level of economic development of countries and their access to energy resources (renewable and non-renewable) to a large extent. The global climate is interconnected, and all nations impact it through their products and services. The six countries discussed—China, Brazil, Germany, Japan, Russia, and India—account for 44.8% of global primary energy consumption and 49% of global CO2 emissions. Each of them has its own strategy for achieving carbon neutrality, based on different decarbonization scenarios, which, according to the authors, depend on geopolitical factors, national economy characteristics, and the established pragmatic goals and objectives. However, the “green agenda” itself may not always be among the top priorities when formulating energy strategies. The study objective is to analyze the feasibility of the stated goals in these countries using a combined logistic curve-based forecasting tool for predicting solar and wind production as well as investment volumes. It aims to justify the relation between solar and wind energy production and investment policies using a calculated technological coefficient. Results show similar, but time-shifted fluctuating investment dynamics in solar and wind energy trends in Japan, Germany and China, with Germany and Japan outperforming investment forecasts when considering the technology efficiency coefficient. Furthermore, the findings highlight the overwhelming appreciation of the unevenness of the green transition process, which will consequently make it impossible to meet the goals of the Paris Agreement until 2050. Taking these factors into consideration, exploratory decarbonization scenarios for these six major world economies alongside two dimensions, namely, the pace of green transition versus green technology and versus resources, are presented.

An integrated expert recommender system approach to environmental service priorities in renewable energy

The purpose of this study is to analyze the investment success of renewable energy generation projects design. A novel model has been constructed for this purpose. At the first stage, collaborative filtering methodology is taken into consideration to complete missing evaluations. After that, M-SWARA based on QUSFSs with golden cut is used to compute the weights of these factors. Finally, the components of the service design are ranked by TOPSIS approach. The main contribution of the paper is that a new methodology (M-SWARA) has been created in this study by making improvements to SWARA. With the help of this new model, causal directions between the indicators can also be examined. Similarly, collaborative filtering methodology is taken into consideration to complete missing evaluations. In this process, the decision makers are allowed to leave the questions they wanted blank. This situation is considered as the superiority of the proposed model compared to many previous models in the literature. The findings indicate that cost is the most significant factor for the success of renewable energy investments because it gets the highest weight (.261). The ranking results also demonstrate that product is the most essential component of the service design of renewable energy investments. Therefore, solving the high-cost problem is of vital importance to increase these investments. First, renewable energy companies can reduce costs with more effective financial management. To carry out this process effectively, a finance department consisting of qualified personnel is needed. Thanks to this team, current situations in the financial markets will be better followed and this will play an important role in reducing costs.

Green investments and inclusive growth: The case of the BRICS economies

Investments in green energy projects are highly critical to promoting climate transition and sustainable development. This objective motivates the investigation of the effect of green investments on inclusive growth. We develop an endogenous inclusive growth model that illustrates the channel through which private and public investments in green investments contribute to inclusive growth. By employing a dataset of the BRICS economies from 1990 to 2019, we fit both linear fixed-effects and fixed-effects threshold regression, the latter of which exhibits better prediction of green investment effects. Accordingly, the threshold regression estimates reveal that higher thresholds of green investments substantially accelerate inclusive growth in the BRICS economies. Furthermore, by controlling for the threshold role of financial sector development, we document the heterogeneous effects of green investments on inclusive growth. Unlike financial institutions’ development thresholds, a higher level of overall financial development and financial market development strengthens the positive role of green investments. Our findings offer impeccable policy actions to the governments and policymakers of the BRICS economies on pathways to promote green energy investments for sustainable development.

The role of investment in energy and industry value added in the presence of financial resources in fostering sustainable economic growth of China

The role of investment in energy and industry value added in the presence of financial resources in fostering sustainable economic growth of China

Urban transport emission prediction analysis through machine learning and deep learning techniques

About 6.6 million people die every year from air pollution diseases globally. Transportation industry is considered one of the leading contributors in air pollution. This research utilizes deep learning and machine learning techniques to predict China’s transport-related CO2 emissions and energy needs by utilizing variables like population, car kilometers, year and GDP per capita. The outcomes have been analyzed using six analytical measures: determination coefficient, RMSE, relative RMSE, mean absolute percentage error, mean bias error and mean absolute bias error. Findings indicate that yearly increase in transport-related CO2 emissions in China will be 3.66%, and transport energy consumption will increase by 3.8%. Energy consumption and transport CO2 emissions are projected to rise by roughly 3.5 times by 2050 as compared to current levels. Therefore, government should re-evaluate its energy investment plans for the future and institute new rules, and standards regarding transport-related energy consumption and pollution reduction.

Renewable Energy Investments Impact on Economic Diversification And Strategic Growth: A Review Of Literature In The Context Of Oman Vision 2040

Renewable Energy Investments Impact on Economic Diversification And Strategic Growth: A Review Of Literature In The Context Of Oman Vision 2040

Workflow to support cost-benefits comparison and sensitivity analysis of BIPV case studies: Three examples of BIPV facades in the south of Switzerland

The building skin surfaces represent a vast potential for decentralising renewable energy investments and offering unique opportunities for prosumers thanks to the built environment. Despite the recognised potential of building-integrated photovoltaics (BIPV), cost-effectiveness is still a market barrier to accelerate deployment. The literature reports investigations on costs at product level and cost-effectiveness scenarios and prospects. However, the literature assessing the economic viability of real building processes is scarce. BIPV costs are strongly project-related and affected by construction work factors that cannot be generalised or observed at a macro-scale. Thus, the lack of concrete and documented applications in existing buildings is a missing gap for the sector and doesn’t support the market in clarifying the real economic costs and benefits of BIPV systems or the main parameters influencing the economic variability in real constructions. This study contributes to the field by developing a cost-benefit analysis of established BIPV case studies situated in the southern region of Switzerland. The approach employs a comprehensive economic evaluation, utilizing the net present value method. A sensitivity analysis is developed to assess costs by varying key economic input parameters that significantly impact the financial aspects of BIPV installations. This research aims to conduct a comprehensive analysis of specific case studies, presenting original findings that elucidate the interplay between energy and construction factors. By discerning these relationships, the study seeks to unveil the determinants of cost competitiveness, ultimately contributing to the increase of attractiveness within the realm of BIPV facade benefits throughout the entire value chain.

Strategic Recommendations for Enhancing Renewable Energy Investments and Economic Diversification: The Case of Oman

Strategic Recommendations for Enhancing Renewable Energy Investments and Economic Diversification: The Case of Oman

Quantitative and Qualitative Insights on Renewable Energy Investments Impact on Economic Diversification and Strategic Growth: The Case of Oman

Quantitative and Qualitative Insights on Renewable Energy Investments Impact on Economic Diversification and Strategic Growth: The Case of Oman

Investigating the main factors responsible for changes in income inequality in China between 2000 and 2018

Poverty, and especially the widening disparity between the rich and the poor, leads to social unrest that can interrupt the harmonious development of human society. Understanding the reasons for income inequality, and supporting the development of an effective strategy to reduce this inequality, have been major goals in socioeconomic research around the world. To identify the determinants of the income gap, we calculated the Gini coefficients for Chinese provinces and performed regression analysis and contribution analysis for heterogeneity, using data from 30 Chinese provinces from 2002 to 2018. We found that urbanization, higher education, and foreign direct investment in eastern China and energy in central and western China were important factors that increased the Gini coefficient (i.e., decreased equality). Therefore, paying more attention to the fair distribution of the factors that can increase the Gini coefficient and investing more in the factors that can reduce the Gini coefficient will be the keys to narrowing the income gap. Our approach revealed factors that should be targeted for solutions both in China and in other developing countries that are facing similar difficulties, although the details will vary among countries and contexts.

Domestication of halotolerant methanogens for energy-efficient microbial electrosynthesis of methane from CO2

Microbial electrosynthesis (MES) has great potential for CO2 reduction and renewable energy storage. However, high energy consumption and investment costs constrained the practical application of MES. Here, the domestication of halotolerant methanogens was proposed to improve the energy efficiency of MES, and methane metabolism under low and high Na+ concentrations was explored by metagenomic analysis. The Na+ concentration of the catholyte was increased from 4.07 g·L-1 to 23.01 g·L-1, and the reactor maintained great performance after initial inhibition. High-salinity catholyte improved the energy efficiency to 47% and reduced the cathode voltage consumption. Increasing Na+ concentration, microorganisms resisted damage by secreting more extracellular polymers, and maintained methane production through community evolution. The relative abundance of Euryarchaeota increased from 50% to 80%. Methanobrevibacter and Methanobacterium were dominant genera at Na+ of 23.01 g·L-1. Incorporating metagenomic analysis, the methane metabolism at the initial period (Na+:4.07 g·L-1) included a CO2-reduction pathway and acetoclastic pathway. However, when Na+ concentration increased to 23.01 g·L-1, the CO2-reduction pathway with 4Fe–4S ferredoxin and common pathways was significantly enhanced, in addition, the acetyl metabolism pathway using CO2 as substrate was also enhanced. Overall, methane metabolism was enhanced, and the metabolic pathways changed with increasing Na⁺ concentration.

Life cycle climate performance of photovoltaic power plant for Turkey’s solar power conditions

ABSTRACT In this study, a solar power plant with an output power of 10 kW AC was designed according to the Turkish Electricity Legislation. Silicon-based photovoltaic modules were used in the design. The solar power plant’s annual and lifetime electricity generation was calculated for 81 provinces of Turkey. The study contributes significantly to the literature by evaluating the environmental impacts of energy sources in a more realistic way. According to the electricity generation calculations, the power plant in Trabzon generates a minimum of 13,037 kWh of electricity per year. In comparison, the power plant in Antalya generates a maximum of 18,562 kWh. Over the plant’s life, Antalya will generate 464,040 kWh of electricity and Trabzon will generate 325,929 kWh. The life cycle climate performance technique was used to understand the environmental impacts during the installation phase, and these values were determined to be 5759 kgCO2. Emission values from electricity generation vary between 0.01241 and 0.01767 kgCO2 per kWh. These data provide a comprehensive assessment of the environmental impacts of solar power plants. This study contributes to the literature by investigating the potential and environmental effects of solar energy in different regions of Turkey in detail. In particular, presenting the emission values of electricity generation from photovoltaic systems for each province provides valuable data that can be used in shaping energy policies and developing environmental strategies. This unique study will provide a scientific basis for planning and implementing solar energy investments in Turkey and contribute significantly to developing energy policies and environmental strategies.

THE IMPACT OF DIGITALIZATION ON THE IMPLEMENTATION OF CARBON-FREE ECONOMY PRINCIPLES IN UKRAINE

This study explores the role of digitalization in implementing carbon-free economy principles in Ukraine, with a particular focus on how digital technologies contribute to enhancing energy efficiency and reducing CO2 emissions. Digitalization serves as a critical enabler of sustainable development by providing tools for optimizing energy consumption, improving resource management, and minimizing the environmental footprint of economic activities. Through correlation and regression analyses, the research investigates the relationship between investments in digital technologies, environmental protection measures, and CO2 emissions for the period from 2007 to 2020. The results reveal that while digitalization has the potential to improve energy efficiency, its current impact on reducing CO2 emissions remains limited. The findings indicate that increased investments in renewable energy sources and more comprehensive integration of digital technologies into the energy sector are essential to achieve significant reductions in emissions. Additionally, the study highlights the positive effect of innovation-driven activities on energy efficiency but points to the need for further development and deployment of environmentally friendly digital solutions. The research also underscores the importance of continued financial support for green technologies and emphasizes the necessity of improving greenhouse gas monitoring systems. Practical recommendations include increasing investment in renewable energy, expanding the use of smart technologies across industries, and promoting long-term innovation strategies aimed at achieving carbon neutrality. Overall, the research concludes that digital innovation plays a supporting role in achieving energy efficiency but requires stronger policy frameworks, investment, and coordination to realize its full potential in contributing to environmental sustainability.

A Review of the Effect of Cleaner Energy Transition on Food Prices and Climate Change Mitigation in Sub-Saharan Africa

Background: Access to clean energy is crucial for achieving sustainable development goals, but investment in renewable energy has been unevenly distributed between developed and developing countries. Developed nations have seen significant growth in renewable energy investment since the Paris Agreement, while developing countries struggle to secure the necessary funds. This study focuses on Sub-Saharan Africa and explores the relationship between the transition to cleaner energy and its impact on food prices. Methods: By conducting a systematic literature review, the study highlights the challenges posed by investment disparities, particularly in Sub-Saharan Africa, where financial constraints and infrastructural deficits hinder progress in clean energy infrastructure. Results: The findings suggest that, without appropriate policy reforms and consistent implementation, the transition to cleaner energy in the region may contribute to rising food prices and exacerbate food insecurity. Effective integration of agricultural and energy policies is essential to ensure that the energy transition supports food security objectives. Conclusion: Governments in Sub-Saharan Africa should prioritize policy reforms that promote renewable energy adoption while considering food security. Additionally, reintroducing transparent subsidy programs can help mitigate the impact of high energy costs during the transition to cleaner energy. This review emphasizes the importance of equitable investment and comprehensive policy strategies to balance renewable energy adoption with food security and economic equity in Sub-Saharan Africa.

Analyzing banking sector development and renewable energy consumption impact on load capacity factor in Sudan

This study delves into the impact of banking sector development (BSD), renewable energy consumption (REC) and economic growth (EG) on environmental quality (EQ), using the load capacity factor (LCF) in Sudan. Utilizing time series data from 1990 to 2018 and the Autoregressive Distributed Lag (ARDL) method, this research aims to explore both short-term and long-term dynamics, and cointegration, to provide a detailed understanding of these relationships. The study's primary objective is to elucidate the effects of BSD, REC, and EG on Sudan's EQ through the LCF metric and to test the Load Capacity Curve (LCC) hypothesis. The results indicate that the squared values of per capita GDP (long-term) and REC (short- and long-term) contribute to an increase in Sudan's LCF, thereby enhancing EQ,while BSD and per capita GDP negatively affect EQ, thus confirming the LCC hypothesis. Sudan authorities are urged to prioritize environmentally friendly economic policies, sustainable urban development, and the transition to renewable energy sources. However, the revelation that BSD diminishes environmental sustainability suggests a reevaluation of the financial sector's role. Encouraging green technologies could amplify the LCF and mitigate environmental degradation, enabling Sudan to create a sustainable environment by promoting renewable energy investments and long-term GDP per capita growth while curbing financial expansion. This research provides a critical framework for policymakers to create strategies that balance economic development with ecological preservation, ensuring Sudan's long-term sustainability.Graphical

Optimal allocation of wind-based distributed generators and STATCOMs using a hierarchical stochastic programming approach

Allocating static synchronous compensators (STATCOMs) to regulate given allotted wind-based distributed generators (W-DGs) during planning stages can provide high investment returns by maximizing the installed W-DGs. Amidst rising global warming concerns, commitments to adopt renewable energy gain international momentum to curb greenhouse emissions and meet environmental targets, reducing reliance on fossil-based resources. Renewable energy's intermittency complicates distribution planning, stressing voltage devices and increasing network losses. This paper presents a new hierarchical stochastic planning model that addresses uncertainties related to W-DGs and generic loads. The model optimizes allocation with voltage constraints and reactive power while incorporating a two-stage mixed-integer nonlinear program (MINLP), maximizing net profit, and adding an economic dimension to promote renewable energy investments. Improved wind power modeling with historical data and collective evaluation metrics for selecting the best-fitted probability distribution function (PDF) enhances the accuracy of wind power integration assessment. The hierarchical approach considers relaxed voltage constraints in Stage I to allow maximum allotment of W-DGs while introducing STATCOMs and DGs' reactive power in Stage II to address voltage violations. Verification on the Canadian 41-bus network demonstrates the advantage of the hierarchical approach in allocating more W-DGs and achieving higher profits than the simultaneous planning approach. These advances significantly enhance renewable energy integration in power systems.

Analysis of green energy-oriented sustainable development goals for emerging economies

Countries should focus on the improvements to achieve sustainable development goals. However, taking these actions create some operational costs. Thus, it is appropriate for rising nations to prioritize sustainable development objectives. Due to this condition, more critical sustainable development goals should be identified. Accordingly, this study evaluates green energy-oriented sustainable development goals for emerging economies. Within this context, a model is generated by considering the golden cut and bipolar q-rung orthopair fuzzy sets (q-ROFSs). The novelty of this study is to identify key green energy-oriented sustainable development goals for the improvement of emerging economies by an original model based on the golden cut and bipolar q-ROF decision making approach. All results are similar, indicating the proposed model's validity and coherency. It is concluded that increasing renewable energy is the most significant target with a weight of 0.235 regarding green energy-oriented sustainable development. Cooperation and efficiency are other significant issues for this condition, with weights of 0.198 and 0.196. It is also identified that Turkey and Mexico are the most successful countries in reaching green energy-oriented sustainable development goals. Increasing the share of renewable energy in total energy production and consumption is important for emerging countries. For this situation, governments should provide subsidies for renewable energy investors to provide a cost advantage. In this context, issues such as tax cuts and loans with low-interest rates can increase the motivation of clean energy investors.

Economic Growth, Industrialization, and CO2 Emissions in Pakistan: Insights from ARDL Modeling

This study explores how industrialization, economic growth (measured by GDP per capita), and CO? emissions have interacted in Pakistan over nearly five decades, from 1974 to 2022. It also considers the influence of population growth and foreign direct investment (FDI) on this relationship. To analyze the data, the ARDL model was used, ensuring the reliability of the results by confirming stationarity with the Augmented Dickey-Fuller (ADF) test. The results showed that in the long run, a 1% increase in GDP per capita and FDI inflows results in respective increases in CO? emissions of 0.33% and 0.061%. Still, a 1% rise in industrial activity lowers CO? emissions by 0.34%. In the short run, a 1% rise in GDP per capita and FDI reduces CO? emissions by 0.21% and 0.020%, respectively. Conversely, a 1% increase in industrial activity causes emissions of 0.29%. These findings are in line with the Environmental Kuznets Curve (EKC) theory, which holds that CO? emissions initially rises when a nation industrializes but as the technology advances and more rigorous rules are followed, the level of CO? emissions decreases. Based on these results, policies emphasizing investments in renewable energy, strict environmental rules enforced, and support of clean technologies and sustainable industrial practices are suggested.

Public investment on renewable energy R&D Projects: The role of geopolitical risk, and economic and political uncertainties

Recently, there has been growing concern about the impacts of geopolitical tension as well as economic and political uncertainties on the decision-making process of governments when it comes to allocating resources for renewable energy R&D. This paper employs the panel autoregressive distributed lag (ARDL), cross-sectional panel autoregressive distributed lag (CS-ARDL) and Fully Modified Ordinary Least Squares (FMOLS) technique to examine the impacts of geopolitical risk, economic and political uncertainties, renewable energy technologies innovations, government financial affordability and CO2 emissions on government spending on renewable energy research and development projects. The novel aspects of the panel ARDL and CS-ARDL methodologies lie in their ability to capture both short-run and long-run dynamics within a panel data framework, as well as their ability to provide a more comprehensive understanding of the relationships under investigation. The empirical results presented in this paper indicate that in the face of ongoing geopolitical tension, as well as economic and political uncertainties, financially capable governments continue to increase their investments in renewable energy R&D in the long run. This strategic move aims to safeguard the supply of renewable energy, uphold economic and political policy credibility, maintain a first-mover advantage, and establish control over the intellectual property rights associated with renewable energy technology.