Energy Investment Research Articles

Development of wind power plants to increase the fulfilment ratio of renewable energy in Taiwan using system dynamics modelling

ABSTRACT This research aims to improve wind energy development by addressing environmental challenges and market dynamics. To achieve this, a system dynamics model was used to analyze the complex relationships between various factors, including wind energy production, electricity demand, costs, and government policies. The study focuses on increasing the fulfilment ratio and reducing the price of wind energy. By simulating different scenarios, researchers explored the potential impact of expanding wind farm capacity through the addition of onshore and offshore turbines. The research also investigates the role of government incentives, particularly the feed-in tariff (FIT), in stimulating investment in wind energy. The findings suggest that a higher FIT can significantly boost profitability, attract more investment, and accelerate the expansion of wind farm capacity. The optimal FIT level of 5.5 NTD/KWh is projected to lead to a 6.7% annual growth rate and substantial profits by 2040.

Qatar's energy policy in the field of renewable energy

Qatar has abundant oil and gas reserves and has made extensive investments in renewable energy according to the zero-carbon policy in recent years. Renewable energy is vital for Qatar, and many investments and plans have been made in this country. Therefore, this article examines Qatar's energy policy in renewable energy using a mixed quantitative-qualitative methodology. In this article, an attempt has been made to answer the question, what is Qatar's energy policy in the field of renewable energy? As a hypothesis, Qatar's energy policy has changed from dependence on non-renewable energies to using and developing renewable energies to stabilize its energy security in the coming decades. Also, the theoretical framework of energy security has been used to test the hypothesis. The research findings indicate that Qatar has also adopted this policy due to the significant changes in the orientation of developed and developing countries towards new energies. Like many Persian Gulf countries, Qatar's policies have been aimed at reducing carbon. With extensive investments and long-term planning until 2030, Qatar can become a model country in the Middle East region in terms of renewable energy. This issue and fossil fuels give Qatar a special place that can turn Qatar into a fossil and renewable energy hub.

Predicting Natural Gas Production in Various Nations Using a Fractional Grey Bernoulli Approach

Accurate forecasting of natural gas production is crucial for economic stability, environmental sustainability, and market investment. This study presents an advanced forecasting method using the fractional grey Bernoulli model, which combines fractional accumulation and Bernoulli processes to enhance the predictive accuracy for nonlinear datasets. The model’s versatility and flexibility allow it to adapt to various data characteristics and complexities, thereby outperforming traditional grey models in forecasting performance. To optimize the model parameters, this study employs the Particle Swarm Optimization (PSO) algorithm, further improving the model’s effectiveness. Empirical analysis of natural gas production data from Brazil, Italy, and Qatar demonstrates that the model exhibits significant advantages in both fitting and forecasting capabilities. The findings indicate that the fractional grey Bernoulli model achieves high accuracy and reliability in predicting natural gas production in these countries, providing a robust framework for strategic energy planning and investment decision-making. With average forecast errors of 1.9113%, 4.0353%, and 1.8902% for natural gas production in Brazil, Italy, and Qatar respectively, this study underscores the model’s effectiveness in enhancing forecast reliability and minimizing risk, providing valuable insights for sustainable energy development.

Transition of China’s global energy investment: Decarbonization, dispersion and denationalization

China’s global energy investment (CGEI) plays a role in global energy transition. This paper uses a “3D” (decarbonization, denationalization, and dispersion) framework to analyze CGEI from 2005 to 2020 based on the China Global Investment Tracker (CGIT) database. Results indicate that significant decarbonization of CGEI has occurred, particularly after 2013, with the most pronounced effects observed in middle- and low-income countries. Dispersion is also significant as Chinas investment reached some 97 countries expanding across the globe to Africa and Latin America, led by solar and wind energy. On the other hand, a denationalization trend was less obvious. After a short period of expansion by private enterprises, denationalization stalled as central state-owned enterprises surged ahead in leading CGEI.

The Interplay Between China’s Regulated and Voluntary Carbon Markets and Its Influence on Renewable Energy Development—A Literature Review

This is the first review study that focuses on the interplay between China’s regulated and voluntary carbon markets, the Emissions Trading System (ETS), the China Certified Emission Reduction (CCER) scheme, and their combined influence on the development of renewable energy in the country. Through a comparative literature review of 52 peer-reviewed academic papers published between 2009 and 2024, this study aims to elucidate how these market mechanisms interact to drive renewable energy deployment. The findings indicate that both the ETS and the CCER system positively affect China’s renewable energy landscape. The ETS, with its Cap-and-Trade (CaT) mechanism, sets a cap on total emissions and allows for the trading of emission quotas, thereby creating financial incentives for companies to reduce emissions and invest in renewable energy. The CCER scheme complements the ETS by allowing companies to use the CCER scheme for a capped share of their ETS certificates, whereby the lower CCER price diverts investments to where the saved ton of CO2 in China is cheapest, further incentivizing investments in renewable energy. This dual mechanism allows for a more flexible and cost-effective approach to achieving emission reduction targets, thereby fostering an environment conducive to investment in renewable energy. It will stimulate additional investment in renewable energy projects in the long run, particularly in economically underdeveloped regions, contributing to both local economic development and national emission reduction targets.

Mechanisms of international economic cooperation to support the global energy transition: ways to improve

The global energy transition is a complex process and requires deep international economic cooperation and joint efforts to achieve sustainable development. Effective interaction between countries, financial institutions and the private sector is essential to ensure sufficient investment in renewable energy and technological innovation. International financial mechanisms, such as green bonds, can significantly contribute to accelerating this process, but they must ensure access to resources for all participants, especially developing countries. Reforming the international financial system and developing new instruments for attracting private capital is an important step towards reducing risks and increasing the investment attractiveness of renewable energy projects. Removing barriers to investment in countries with unstable economies through the development of technical assistance programs and financial guarantees is also an important condition for success. The energy transition can only be successfully realized through a concerted international effort involving both developed and developing countries. A sustainable energy future and ambitious climate change targets can only be achieved through global cooperation, innovative financial solutions and technology sharing.

Analysis of Factors Affecting CO2 Emissions in Türkiye Using Quantile Regression

This study aims to show how the impact of factors on carbon dioxide (CO2) emissions differs at the quantile level and to demonstrate the superiority of the quantile regression method over the OLS method by using quantile regression and ordinary least squares (OLS) methods in order to examine the factors affecting CO2 emissions in Türkiye in depth. Covering the period 1990–2021, this study evaluates the relationship between CO2 emissions and GDP per capita growth, population growth, and renewable energy consumption. One of the important findings of the study is that the increase in the population ratio, which is insignificant according to the OLS method, positively affects CO2 emissions at the 0.25 quantile point. According to both OLS and quantile regression methods, GDP growth does not affect CO2 emissions, while renewable energy consumption has a significant and negative effect according to both models. These results demonstrate that economic growth has no discernible impact on CO2 emissions in Türkiye, while investments in renewable energy can significantly lower emissions and open the door for quantile regression to be used more widely in related research. Unlike traditional methods that focus only on the conditional mean, the quantile regression method provides a comprehensive framework for Türkiye’s sustainable development policies by exploring factor effects at different emission levels.

Trends and opportunities in renewable energy investment in Saudi Arabia: Insights for achieving vision 2030 and enhancing environmental sustainability

Renewable energy has emerged as a critical alternative to traditional energy sources due to growing environmental concerns and the need for sustainable energy development. Saudi Arabia, driven by its Vision 2030, has strongly committed to shifting from fossil fuels to renewable energy sources such as solar, wind, and hydrogen. Despite significant progress, existing investment methods often focus narrowly on financial returns and do not adequately address the risks and uncertainties associated with renewable energy projects, such as policy changes, technological challenges, and fluctuating energy prices. This paper aims to highlight and compare the trends in renewable energy investments and incorporate a risk analysis matrix to address the economic, environmental, and social aspects of Saudi Arabia’s environment. The details used in the study are obtained from Kaggle, while the adopted analysis technique involves multi-criteria decision-making (MCDM). It provides a fresh qualitative approach that allows an all-sided assessment of the investment prospects by focusing on appropriate weight for different factors. The analysis results show that using the proposed framework can help effectively prioritize investment opportunities identifying major trends and risks in developing renewable energy sources in Saudi Arabia. Current investment trends have been reviewed systematically; experts have been interviewed; MCDM techniques have been employed, as the methodology effectiveness improves the comprehension of investment tendencies and contributes to strategic management in the renewable energy market stakeholder’s activity. The MCDM analysis results show that the solar energy system has the highest investment index in the Saudi Arabian cities; the first place belongs to Abha with an investment index of 0.93, the second place belongs to Jeddah with an investment index of 0.85, and the third place belongs to Dammam with an investment index of 0.75. From these outcomes, we can easily conclude that Abha is the best place to place a solar energy project, probably because of environmental and legal factors. The analysis underscores geographic factors in deploying renewable energy, directing investors and policymakers to cities with favourable solar power generation about sustainability and economic objectives. The results are expected to enhance investment awareness among local and international stakeholders, support the strategic goals of Vision 2030, and contribute to a more sustainable and diversified energy future for Saudi Arabia. This study provides a strategic framework for optimizing renewable energy investments, promoting sustainable development, and achieving long-term economic growth. Data AvailabilityData sharing is not applicable to this article as no data sets were generated during the current study.

Climate-Driven Sustainable Energy Investments: Key Decision Factors for a Low-Carbon Transition Using a Multi-Criteria Approach

Currently, the need for a clean transition has made the upscaling of sustainable energy investment projects imperative. This paper addresses the increasing importance of sustainable energy investment projects in the context of climate change and the urgent need for a global energy transition. Given the complexity of decision-making in this field, a multi-criteria decision-making (MCDM) approach is employed to assess the main criteria considered by project developers and financial institutions. Using the Analytic Hierarchy Process (AHP) method, eight criteria are identified and evaluated. Results highlight differing priorities between project developers and investors, emphasizing the need for adaptable approaches to accelerate sustainable energy investments. The study underscores the importance of understanding diverse stakeholder preferences and priorities in formulating effective strategies and managing associated risks to effectively promote sustainable energy projects. Future research should focus on real-life case studies and policy assessments to further enhance the understanding of sustainable energy investment dynamics.

Public Energy R&D Spending and Green Energy for Sustainable Development: COP28 Perspective of G7 Economies

Achieving sustainable development goals (SDGs) is one of the top priorities for countries worldwide, and the recent COP28 has focused mainly on achieving sustainable development via clean energy investment financing. However, countries and regions still struggle to find various policy-level indicators to achieve sustainability engagement. In this context, finding the right combination of policy indicators becomes crucial. Therefore, the current study seeks to identify the key drivers of sustainability for the G7 economies by utilizing data from 1990–2019. This study employed the cross-sectional autoregressive distributed lag (CS-ARDL) panel time series method of estimating primary results and a novel sustainable development index as the dependent variable. The study revealed that public energy R&D budgets, increasing income levels, improving the political risk index, and promoting clean energy are important for achieving sustainable development in the G7 countries and that the depletion of natural resources has an adverse influence on sustainability. These empirical results are supported by various economic and environmental theories, i.e., the environmental Kuznets curve, the innovation theory of sustainability, the Dutch disease hypothesis, and the political economy of development and energy transition theory. Based on these findings, energy investment is recommended, especially for clean energy projects, and increasing income levels via sustainable economic activities to achieve sustainability in the G7 economies.

Energy Policy Uncertainty, Financial Development and Public-Private Investment in BRIC Nations

The transition to sustainable energy systems requires substantial investment, yet the impact of policy uncertainty on investment decisions remains poorly understood, particularly in emerging economies. While previous studies have examined various determinants of energy investment, the interplay between energy policy uncertainty (EPU) and financial sector development (FSD) in shaping public-private energy investments has received limited attention. This study investigates how EPU influences public-private energy investments in BRIC nations and examines FSD's moderating role. Using an ARDL model on data from 1998-2022, we find that EPU significantly deters investment, while FSD exhibits a positive influence. Notably, FSD moderates the negative impact of EPU, suggesting that robust financial sectors can buffer against policy uncertainty's adverse effects. These findings provide crucial insights for policymakers in emerging economies, highlighting the importance of stable policy frameworks and developed financial markets in facilitating energy transition investments.

The role of financial inclusion and technological innovation in stimulating environmental sustainability in the European countries: A new perspective based on load capacity factor

Given the alarming level of climate change, policymakers across the globe are seeking strategies to mitigate environmental pollution to achieve sustainable development. In this context, renewable energy and technological advancements have emerged as an effective way to lower pollution and attain sustainable development. This study evaluates the effect of financial inclusion, technological innovation, and renewable energy on the load capacity factor (LCF) in European countries from 2004 to 2018. LCF is considered the most comprehensive indicator of ecological sustainability, combining both the biocapacity factor and ecological footprint. Hence, the present work fills the literature gap by exploring, for the first time, the effect of financial inclusion on the LCF. Applying the advanced Method of Moment Quantile Regression (MMQR), the study demonstrates that technological innovation and economic growth have adverse effects on LCF while renewable energy and financial inclusion promote LCF. The study indicates that technological innovation and economic growth undermine ecological excellence in European nations while green energy and financial inclusion enhance it. Moreover, the findings of the causality analysis reveal a causal association between financial inclusion, renewable energy, and LCF. Our study recommends prioritizing financial inclusion alongside investments in renewable energy to enhance ecological sustainability.

Towards a Standardized LCOE Calculation for Informed Decision-Making in Energy Policy and Investment: Application to the Colombian Context

The Levelized cost of electricity - LCOE represents a constant cost per unit of generated electrical energy, resulting from the analysis of the total costs throughout the life cycle of a generation plant. Its widespread use, thanks to its simplicity of calculation and potential of standardization, has made it one of the primary criteria for comparing electricity generation technologies. However, in the pursuit of simplification and generalization, certain aspects associated with the socioeconomic context of the region, as well as accounting and financial concepts, are excluded due to externalities or incentives related to regulatory and fiscal policies. These exclusions affect the accuracy of LCOE and introduce uncertainty when using it as a criterion for investment decision-making or allocation of public resources for the development of renewable sources. This article proposes a clear and standardized methodology for calculating LCOE, which allows for a fair and precise comparison of renewable energy generation options in rural areas. It contributes to informed and transparent decision-making in the fields of energy policy and public investment for expanding electricity service coverage. The proposed methodology is based on the financial cash flow matrix to address variability sources in the calculation, considering the local context of the generation project.

Toward Environmental Sustainability: The Nexus between Agriculture, Renewable Energy, and Economic Growth in Mitigating CO2 Emissions in Somalia

This research investigates the intricate relationships between agriculture, renewable energy, economic growth, and carbon dioxide (CO2) emissions in Somalia from 1991 to 2022. This study uses the Autoregressive Distributed Lag (ARDL) model and Granger causality tests to understand their impact on environmental sustainability. ARDL results reveal a negative role of agriculture and renewable energy on CO2 in the short and long term. The country's reliance on fossil fuels and biomass further intensifies CO2 emissions. While economic growth is essential for improving living standards, it positively correlates with CO2 emissions in the short and long term, emphasizing the challenge of decoupling economic development from environmental degradation. Domestic investment has a short-run relation only to CO2 emissions. In Granger causality tests, the results indicated that Agriculture and domestic investment have bidirectional causality to carbon dioxide emissions. On the other hand, renewable energy, economic growth, and domestic investment have unidirectional causality to Agriculture in Somalia, while domestic investment has bidirectional causality to renewable energy and economic growth. The study recommends implementing comprehensive and integrated approaches to prioritize sustainable development strategies, clean energy alternatives, and efficient agricultural practices. Promoting economic growth while also focusing on capacity-building and awareness campaigns is essential. Collaborating with the international community on climate change mitigation and sustainable development initiatives can further support Somalia's journey toward environmental sustainability.

Corporate Tax Planning: Making Sense of Canada's Clean Energy Investment Tax Credits

Corporate Tax Planning: Making Sense of Canada's Clean Energy Investment Tax Credits

Optimal dimensioning of renewable energy generation and storage systems

With high energy demand and large available area, agricultural farms offer significant potential for renewable energy investments, like photovoltaic systems and electrical energy storages. However, the profitability of such investments depends strongly on self-consumption, so accurate planning requires computation-intensive simulation and optimization considering local consumption. This study presents a novel methodology for the optimal dimensioning and configuration of photovoltaic systems and electrical energy storages using efficient techniques from continuous non-linear optimization. Combining physical and economic models with measured consumption data, an investment’s net present value over 20 years is maximized. Using gradient-based solver WORHP, the simulation, optimal control, and optimal dimensioning of the local energy system are calculated simultaneously, allowing for efficient computation over an entire year of hourly data to capture both daily and seasonal variations.The approach is demonstrated with simple use cases, including an exemplary day of a dairy farm’s consumption, for which optimal systems with and without storage achieve 77% and 43% of autarky, respectively. Saturation effects of optimal plant size can be observed when sizes are large enough for optimal self-consumption but not expanded further for grid export. With energy storage, this saturation is reached at higher values. Optimizing photovoltaic plants with different orientations to match the specific consumption patterns characteristic of the dairy farm achieves similar autarky as a single plant while reducing investment costs by more than 20%. While thorough validation and comparison against heuristic methods predominantly used in the field is part of ongoing research, the presented use cases demonstrate the flexibility and efficiency of the proposed method and highlight its promise as a planning tool in the agricultural domain and beyond.

Investigating the Impact of Renewable Energy Investment Announcements on Stock Returns of Borsa Istanbul Energy Companies

Investigating the Impact of Renewable Energy Investment Announcements on Stock Returns of Borsa Istanbul Energy Companies

Does climate risk as barometers for specific clean energy indices? Insights from quartiles and time-frequency perspective

This study presents the first analysis of the nexus between the Southern Oscillation Index (SOI), a measure of climate risk, and segmented clean energy indices (such as solar, renewable, and bioenergy). Our research findings indicate that (i) the Granger quantile causality significance of SOI on segmented clean energy indices is asymmetric across different conditional quantiles. Significant predictability of SOI is observed only at the 0.25 and 0.75 quantile levels for all segmented clean energy indices, except for the WilderHill Clean Energy Index and NASDAQ OMX Fuel Cell Index. (ii) The clean energy market is significantly influenced by SOI under bullish market conditions. Impacts of SOI on all clean energy markets are nearly negligible when clean energy indices are at the median and lower quantile levels. (iii) The influence of strong La Niña episodes on segmented clean energy indices is more pronounced than during periods of intense El Niño phenomena. (iv) SOI exhibited a positive correlation at mid-term and long-term frequencies with segmented Clean Energy sectors, excluding bioenergy, for the majority of the sample period. Our conclusions provide deeper insights for investors managing clean energy investments in extreme climate conditions. Additionally, they offer useful information for policymakers to formulate viable economic policies addressing climate change, ensuring energy security, and facilitating a safer transition to clean energy.

Data analytics driving net zero tracker for renewable energy

This research aims to assess the impact of renewable energy policies, investments, and emissions reductions toward achieving net-zero targets by 2050. We analysed key metrics using the Net Zero Tracker (NZT), including renewable energy capacity, policy strength, financial investment, and carbon emissions across multiple regions and industries. Our methodology involved data collection from 2020 to 2050, utilising predictive modeling to project trends in renewable energy adoption and emissions reduction. Key findings show that renewable energy capacity is expected to surpass 1000 GW by 2050, with an exponential increase around 2045. Policy Strength Index (PSI) will grow by 20 %, from 50 in 2020 to 60 in 2050, while investments in renewable energy will rise from $10 billion to $25 billion over the same period. Emissions are projected to steadily decrease to zero by 2050, which aligns with net-zero goals. The margin of error in the projections is ±5 %, considering potential policy implementation and technology development variations. These results underscore the critical role of enhanced policies, sustained investments, and international cooperation in accelerating the global transition to renewable energy. The research offers valuable insights for policymakers and stakeholders to guide future strategies for achieving a sustainable energy future.

Risk and Benefit Analysis of China’s Foreign Direct Investment in the Energy Sector: Case Study of the Belt and Road Initiative

Since 2011, China has been the world's largest energy consumer. The industrial sector uses two-thirds of the energy consumed in China. The main reason for investment in energy is that China is a net importer of energy, especially oil. The impact of Chinese foreign investments and the energy sector, which is the largest of the individual sectors, are the main subjects of the analysis of the presented paper. In the paper, we used the WoS viewer program to perform a bibliometric analysis of authors, countries, and keywords that deal with FDI. Subsequently, we used various scientific methods, such as the method of observation, method analysis, synthesis, comparison, exploration and explanation, to analyse Chinese investments that flow into multiple sectors worldwide, but especially into the countries participating in the Belt and Road Initiative and into the energy sector from 2013 to the present. As part of the Belt and Road Initiative, China invests in various projects in the form of "loans" and, in many cases, creates debt traps that allow China to seize the assets of participating countries. In this paper, we focused on the energy sector and its development so far within the given initiative, and we also defined what the initiative should focus on within renewable resources. China's energy investments include oil, hydropower, alternative energy, natural gas, and coal. The sharp drop in Chinese investment after 2019 was caused by the COVID-19 pandemic. To conclude, although energy has remained China's primary sector for investment within the BRI regions, Chinese capital has gradually diversified into sectors such as transportation, real estate, technology and innovation, and tourism.