ABSTRACT
The objective of the study was to identify the impact of renewable energy on Saudi economy during 2000-2021. Analytical techniques were used to conduct this study. An analysis of the study used a set of variables, in which Renewable energy perceives as independent variable and the dependent variables are GDP per capita, net foreign direct investment, unemployment, fixed capital formation, and net foreign trade. The data of the study were analyzed using the E-views program. According to the study, renewable energy has an impact on certain economic variables and does not have an impact on others. A partial validity is found for the study's central hypothesis. According to our findings, renewable energy contributes significantly to net foreign direct investment, unemployment, and fixed capital formation, but not to GDP per capita, net foreign trade, or fixed capital formation.
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Energy poverty is a multifaceted phenomenon that affects many Europeans. Alleviating energy poverty is high in the EU, national, and local policy agendas. Despite the attention the phenomenon has been gaining from a policy perspective, especially after the current energy crisis, there are still some gaps due to the complexity of the issue and its vastly different manifestations across Europe. This manuscript presents the policy implications stemming from the implementation of the POWEPROOR approach in alleviating energy poverty in eight European countries, as co-created with relevant stakeholders in each country. The knowledge gained from empowering energy-poor citizens by promoting behavioural changes and small-scale energy efficiency interventions, as well as by encouraging the uptake of renewable energy sources in the form of collective energy initiatives while leveraging innovative financing schemes, resulted in policy recommendations for national and sub-national governments and lessons for civil society and the private sector.
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Developing a sustainable and reliable photovoltaic (PV) energy system requires a comprehensive analysis of solar profiles and an accurate prediction of solar energy performance at the study site. Installing the PV modules with optimal tilt and azimuth angles has a significant impact on the total irradiance delivered to the PV modules. This paper proposes a comprehensive optimization model to integrate total irradiance models with the PV temperature model to find the optimal year-round installation parameters of PV modules. A novel integration between installation parameters and the annual average solar energy is presented, to produce the maximum energy output. The results suggest an increase in energy yields of 4% compared to the conventional scheme, where tilt angle is equal to the latitude and the PV modules are facing south. This paper uses a real-time dataset for the NEOM region in Saudi Arabia to validate the superiority of the proposed model compared to the conventional scheme, but it can be implemented as a scheme wherever real-time data are available.
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The shift to renewable sources of energy has become a critical economic priority in African countries due to energy challenges. However, investors in the development of renewable energy face problems with decision making due to the existence of multiple criteria, such as oil prices and the associated macroeconomic performance. This study aims to analyze the differential effects of international oil prices and other macroeconomic factors on the development of renewable energy in both oil-importing and oil-exporting countries in Africa. The study uses a panel vector error correction model (P-VECM) to analyze data from five net oil exporters (Algeria, Angola, Egypt, Libya and Nigeria) and five net oil importers (Kenya, Ethiopia, Congo, Mozambique and South Africa). The study finds that higher oil prices positively affect the development of renewable energy in oil-importing countries by making renewable energy more economically competitive. Economic growth is also identified as a major driver of the development of renewable energy. While high-interest rates negatively affect the development of renewable energy in oil-importing countries, it has positive effects in oil-exporting countries. Exchange rates play a crucial role in the development of renewable energy in both types of countries with a negative effect in oil-exporting countries and a positive effect in oil-importing countries. The findings of this study suggest that policymakers should take a holistic approach to the development of renewable energy that considers the complex interplay of factors, such as oil prices, economic growth, interest rates, and exchange rates.
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The global greenhouse effect and air pollution problems have been deteriorating in recent years. The power generation in the future is expected to shift from fossil fuels to renewables, and many countries have also announced the ban on the sale of vehicles powered by fossil fuels in the next few decades, to effectively alleviate the global greenhouse effect and air pollution problems. In addition to electric vehicles (EVs) that will replace traditional fuel vehicles as the main ground transportation vehicles in the future, unmanned aerial vehicles (UAVs) have also gradually and more recently been widely used for military and civilian purposes. The recent literature estimated that UAVs will become the major means of transport for goods delivery services before 2040, and the development of passenger UAVs will also extend the traditional human ground transportation to low-altitude airspace transportation. In recent years, the literature has proposed the use of renewable power supply, battery swapping, and charging stations to refill the battery of UAVs. However, the uncertainty of renewable power generation cannot guarantee the stable power supply of UAVs. It may even be very possible that a large number of UAVs need to be charged during the same period, causing congestion in charging stations or battery swapping facilities and delaying the arranged schedules of UAVs. Although studies have proposed the method of that employing moving EVs along with wireless charging technology in order to provide electricity to UAVs with urgent needs, the charging schemes are still oversimplified and have many restrictions. In addition, different charging options should be provided to fit the individual need of each UAV. In view of this, this work attempts to meet the mission characteristics and needs of various UAVs by providing an adaptive flight path and charging plan attached to individual UAVs, as well as reducing the power load of the renewable power generation during the peak period. We ran a series of simulations for the proposed flight path and charging mechanism to evaluate its performance. The simulation results revealed that the solutions proposed in this work can be used by UAV operators to fit the needs of each individual UAV.
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Remote community initiatives for renewable energy are rapidly emerging across Canada but with varying numbers, success rates, and strategies. To meet low-carbon transition goals, the need to coordinate technology deployment and long-term policy to guide the adoption is critical. Renewable resources such as wind, solar, hydro, and biomass can provide energy at a subsidized cost, create sustainable infrastructure, and provide new economic viability in social value integration. The renewable energy transition is crucial to Canada in sustaining remote and indigenous communities by providing local, clean, and low-carbon-emission energy for heat, power, and possibly transportation. This paper identified 635 renewable resources projects deployed to improve and increase electricity supply. To an extent, balancing demand within the remote and indigenous communities of Canada and highlighting sustainable renewable energy development through ownership participation within the communities is achievable before 2050 and beyond through energy efficiency and the social value of energy. The article identifies clean energy targets as mandated by the different provinces in Canada to reach net-zero GHG emissions.
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[...]in an End-To-End approach (De Boeck et al., 2019;Lemmens et al., 2016), multiple aspects of the supply network need to be considered and coordinated, in a way that many upstream decisions and aspects in R&D have a considerable impact on the downstream supply network up to the very last mile and point of vaccination. The next paper "Enhancing the Environmental Sustainability of Emergency Humanitarian Medical Cold Chains with Renewable Energy Sources” by Saari extends toward sustainability by focusing on the cold chain aspects of vaccine supply chains. [...]the seventh and closing paper "Modeling a closed-loop vaccine supply chain with transshipments to minimize wastage and threats to the public: a system dynamics approach”, by Andiç-Mortan and Gonul Kochan, shows by means of a causal loop diagram causal relationships with respect to vaccine waste management and the consequential public health threats.
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As a riveting example of social housing in Brazil, the Minha Casa Minha Vida program was set in 2009 to diminish the 6-million-home housing deficit by offering affordable dwellings for low-income families. However, recurrent thermal discomfort complaints occur among dwellers, especially in the Baltimore Residential sample in Uberlândia City. To avoid negative effects of energy poverty, such as family budget constraints from the purchase of electric appliances and extra costs from power consumption, a simulation based on system dynamics modeling shows a natural ventilation strategy with a mixed combination of sustainable and energy-efficient materials (tilting window with up to 100% opening, green tempered glass, and expanded polystyrene wall) to observe the internal room temperature variation over time. With a 50% window opening ratio combined with a 3 mm regular glass window and a 12.5 cm rectangular 8-hole brick wall, this scenario presents the highest internal room temperature value held during the entire period. From the worst to the best-case scenario, a substantial reduction in the peak temperature was observed from window size variation, demonstrating that natural ventilation and constructive elements of low complexity and wide availability in the market contribute to the thermal comfort of residential rooms.
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The six Gulf monarchies—Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and United Arab Emirates (UAE)—are more politically stable than their peers in the Middle East and North Africa. Explanations for governance resilience range from repression to neopatrimonial and instrumental legitimacy, hydrocarbon-based rentierism, and permissive regional and international environments. This paper considers, in view of the proliferation and uptake of renewable energy in the Gulf, how governance resilience may be affected as a result of changes in state-society relations during the energy transition away from a fossil-fuel-based energy system. It offers a qualitative analysis of the impact of renewable energy deployment in the Gulf, supported by a rich array of secondary literature and data. It also offers a deep, if brief, dive to highlight intra-regional nuances. The authors conclude that in the short term, renewable energy deployment has a very modest impact given its limited share of power generation. In the longer term, even assuming that stated ambitions for renewable energy are fulfilled, no negative impact on monarchial resilience is expected thanks to gains in legitimacy and revenue streams, as well as purposeful alignment with an external environment supportive of renewable power in developing countries.
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Human activities have been limited by coronavirus disease 2019 (COVID-19), and the normal conditions of our lifestyles have changed, particularly in terms of electricity usage. The aim of this study was to investigate the impact of COVID-19 on the power sector in the Lao PDR in 2020, as well as the challenge of using solar energy to supply power to the network using an optimal approach. The returns on investment of network extension and the purchase of solar energy were also evaluated. Furthermore, load conditions caused by the country's lockdown policy were analyzed. We analyzed the optimal sizing and location of solar energy using a particle swarm optimization method based on the main objective functions, with the system's power loss decreasing and its reliability improved. The results demonstrated that the suddenly reduced load from industry and commercial business did not have a large impact on its operations;however, revenue was reduced. The optimal method for connecting solar energy to a network can reduce power loss and improve system reliability. In addition, we discovered that the location and capacity of solar generation can reduce the investment costs of extensions for new lines, with the surplus power being exported.
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Maintaining our standard of living and keeping the economy running smoothly is heavily reliant on a consistent supply of energy. Renewable energy systems create abundant energy by utilizing resources such as the sun, wind, earth, and plants. The demand for renewable energy is increasing, despite power scarcity, pollution, and climate change posing challenges to long-term development in the Association of Southeast Asian Nations (ASEAN), which has seen significant social and economic growth in recent years. To achieve its 23% renewable energy (RE) target, ASEAN can develop solar photovoltaic (PV) electricity. Members of the ASEAN have established regulations and incentives to encourage individuals and businesses to use renewable energy in the future. This paper explores Southeast Asian countries' comprehensive fossil-free energy options, the region's renewable energy potential, current capacity, goals, and energy needs. Through the ASEAN Plan of Action for Energy Cooperation (APAEC) 2016–2025 and the ASEAN Declaration on Renewable Energy, ASEAN is committed to reducing its greenhouse gas emissions and promoting sustainable development aligning with the Paris Agreement's aim to limit global warming to well below 2 degrees Celsius above pre-industrial levels. Results show that decarbonizing the region's energy system is possible, but current policies and actions must be altered to reach that target level. Further research is necessary to optimize the ASEAN region's renewable resource technical potential and commercial viability with available technology.
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Amidst the ongoing COVID-19 pandemic, the contentious U.S. 2020 presidential election featured candidates with quite different stances on regulating the oil and gas industry, leaving many to question the longevity of fossil fuel use. However, little research explores the relationship between presidential policies and the oil market. In this paper, extensive research into presidential energy policies and their effects on domestic oil prices and production dating back to 1977 helps us identify whether we can predict the industry's future under Joe Biden's administration. The paper's results suggest the domestic oil industry is more dependent on external foreign events - with presidential policies offering almost negligible effects on prices and production.
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PurposeThe mining process is essential in cryptocurrency networks. However, it consumes considerable electrical energy, which is undoubtedly harmful to the environment. In response, energy-conserving cryptocurrency projects with reduced energy requirements or based on renewable energies have been developed. Recently, the COVID-19 pandemic and the Russian invasion of Ukraine ignited an unprecedented upheaval in financial products, especially in cryptocurrency and energy markets. Therefore, the paper aims to explore the response of these energy-conserving cryptocurrencies to the COVID-19 pandemic and the Russia–Ukraine conflict.Design/methodology/approachThis paper investigates the response of these energy-conserving cryptocurrencies to the COVID-19 pandemic and the Russia–Ukraine conflict. Their competitiveness is compared with conventional ones by analyzing their efficiency through multifractal detrended fluctuation analysis and automatic variance ratio during the COVID-19 and Russian invasion periods.FindingsThe empirical results show that all investigated energy-conserving cryptocurrencies negatively responded to the pandemic and positively reacted to the Russian invasion. On the other hand, all conventional cryptocurrencies reacted negatively to the COVID-19 pandemic and the amid-Russian attack. Besides, Bitcoin and SolarCoin were the least inefficient before the outbreak of COVID-19. Nevertheless, the Ethereum market became the most efficient after the pandemic spread. Similarly, the efficiency of Ripple was the most significant during the conflict between Russia and Ukraine. The energy crisis caused by Russia benefited the efficiency of the studied energy-conserving cryptocurrencies.Practical implicationsThis research is of interest to investors seeking opportunities in these energy-conserving cryptocurrencies and policymakers working to implement reforms to improve their market efficiency and promote long-term financial market growth.Originality/valueTo the best of the authors' knowledge, the behavior of cryptocurrencies based on renewable and reduced energy during the recent conflict between Russia and Ukraine has not been explored.
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Senegal has been investing in the development of its energy sector for decades. By using a novel multi-criteria decision analysis (MCDA) based on the principal component analysis (PCA) method, this paper develops an approach to determine the effectiveness of Senegal's policies in supporting low-carbon development. This was determined using six criteria (C1 to C6) and 17 policies selected from the review of Senegal's energy system. In order to determine the optimal weighting of the six criteria, a PCA is performed. In our approach, the best weighted factor is the normalized version of the best linear combination of the initial criteria with the maximum summarized information. Proper weighted factors are determined through the percentage of the information provided by the six criteria kept by the principal components. The percentage of information is statistically a fit of goodness of a principal component. The higher it is, the more statistically important the corresponding principal component is. Among the six principal components obtained, the first principal component (comp1) best summarizes the values of criteria C1 to C6 for each policy. It contains 81.15% of the information on energy policies presented by the six criteria and was used to rank the policies. Future research should take into account that when the number of criteria is high, the share of information explained by the first principal component could be lower (less than 50% of the total variance). In this case, the use of a single principal component would be detrimental to the analysis. For such cases, we recommend a higher dimensional visualization (using two or three components), or a new PCA should be performed on the principal components. This approach presented in our study can serve as an important benchmark for energy projects and policy evaluation.
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The world is facing several challenges, and the problem of sustainable development is one of the most important. It is worth considering that European countries are playing a significant role as pioneers in building a sustainable world, such as those promises made by signing the Paris Agreement and European Taxonomy. To achieve ambitious targets within sustainable development, a huge amount of capital is necessary, while financial and capital market participants are expected to demonstrate a high level of engagement in the domain of sustainability. Facing growing interest and demand, a relatively new product—the ESG (environmental, social, and governance) investment fund—was introduced. Scientific literature is providing some controversial views regarding the overall evaluation of this product. Therefore, additional research providing different angles would contribute to a better understanding. This study examines European ESG funds in the energy sector, from the perspective of news flows and investors. It is worth noting that the authors use the word "European” to refer to members of the European Union (EU). The paper consists of the following parts. In the introduction, the current state of this issue is discussed. The following section offers a literature review and a news flow analysis that contributes to a deeper understanding of these issues. A description of the methodology applied for the data analysis follows this, and the final section presents the research results and conclusions. The authors apply statistical analysis and the Carhart model to determine the differences in the performance of the ESG and conventional funds and use their own tool for text analysis to examine the relevance of the topic of ESG to attract client interest. The authors claim that the performance of the European ESG equity funds do not show a statistically significant difference from the non-ESG equity funds in the majority of the periods examined. The application of the adjusted Carhart model demonstrates that the factor of sustainability has a non-significant and negative effect on the fund performance. Finally, the authors highlight the urgent necessity for the unified usage of keywords and terminology, such as "ESG”, "sustainability”, etc., to ensure comparison and attribution possibilities.
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The current study aims to investigate and compare the effects of waste plastic oil blended with n-butanol on the characteristics of diesel engines and exhaust gas emissions. Waste plastic oil produced by the pyrolysis process was blended with n-butanol at 5%, 10%, and 15% by volume. Experiments were conducted on a four-stroke, four-cylinder, water-cooled, direct injection diesel engine with a variation of five engine loads, while the engine's speed was fixed at 2500 rpm. The experimental results showed that the main hydrocarbons present in WPO were within the range of diesel fuel (C13–C18, approximately 74.39%), while its specific gravity and flash point were out of the limit prescribed by the diesel fuel specification. The addition of n-butanol to WPO was found to reduce the engine's thermal efficiency and increase HC and CO emissions, especially when the engine operated at low-load conditions. In order to find the suitable ratio of n-butanol blends when the engine operated at the tested engine load, the optimization process was carried out by considering the engine's load and ratio of the n-butanol blend as input factors and the engine's performance and emissions as output factors. It was found that the multi-objective function produced by the general regression neural network (GRNN) can be modeled as the multi-objective function with high predictive performances. The coefficient of determination (R2), mean absolute percentage error (MAPE), and root mean square error (RSME) of the optimization model proposed in the study were 0.999, 2.606%, and 0.663, respectively, when brake thermal efficiency was considered, while nitrogen oxide values were 0.998, 6.915%, and 0.600, respectively. As for the results of the optimization using NSGA-II, a single optimum value may not be attained as with the other methods, but the optimization's boundary was obtained, which was established by making a trade-off between brake thermal efficiency and nitrogen oxide emissions. According to the Pareto frontier, the engine load and ratio of the n-butanol blend that caused the trade-off between maximum brake thermal efficiency and minimum nitrogen oxides are within the approximate range of 37 N.m to 104 N.m and 9% to 14%, respectively.
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Climate change, pollution, drought, and rising seas impede the achievement of the seventh sustainable development goal SDG#7 (i.e. affordable and clean energies).To counter these threats, the use of Renewable Energy (RE) as an alternative to conventional energy has an important role to play in sustainable development. In this context, the purpose of our paper is to investigate the effect of RE deployment on environmental protection in China, The United States of America (USA), and Germany: the top three ranked countries in terms of RE production, according to RENEWABLE 2021 GLOBAL STATUSREPORT. To achieve this objective, the paper adopts a Panel fully modified OLS (FMOLS) method. Results declare that renewable energy significantly reduce pollution indicators;furthermore, we find that Research and development fully moderate this relationship. The findings of this study emphasize the importance of increasing spending on Research and development activities in the RE sector. In addition, the countries studied and countries around the world should pay greater attention to investment in research and development to support the long-term plan for advancing sustainable energy sources for feasible energy and economic development.
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In Greece biomass is often being disposed of uncontrollably, resulting in significant environmental impacts. The aim of this study is the single-stage anaerobic co-digestion assessment, valorizing Northern and Southern Greece mixtures, resulting from previous literature reviews, experimental designs, and biochemical methane potential (BMP) assays. Regarding the methane yield maximization, in Northern Greece, the most suitable mixture was 10% corn silage, 80% cattle manure, and 10% malt;while in Southern Greece it was 10% corn silage, 57% cattle manure, 23% orange peels, and 10% olive pomace for fall/winter season. The hydraulic retention time (HRT) was set at 20 d and an initial organic loading rate (OLR) of 2 g COD/(L·d) was applied, with a view to gradually increase it. However, volatile fatty acids accumulation was observed, which led to OLR reduction to 1.5 g COD/(L·d) for both experiments. The Northern Greece reactor operated successfully for OLR 1.5–5 g COD/(L·d), while further increase led to system failure. On the other hand, the reactor of the Southern Greece mixture operated successfully at OLR 1.5–2 g COD/(L·d), but further operation indicated inadequacy, probably due to inhibitor (such as limonene) accumulation. Mixtures consisting of corn silage, cattle manure, and malt can be successfully valorized at high OLR. However, further investigation for mixtures with orange peels is suggested due to the presence of inhibitors.
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The cost of electricity and gas has a direct influence on the everyday routines of people who rely on these resources to keep their businesses running. However, the value of electricity is strongly related to spot market prices, and the arrival of winter and increased energy use owing to the demand for heating can lead to an increase in energy prices. Approaches to forecasting energy costs have been used in recent years;however, existing models are not yet robust enough due to competition, seasonal changes, and other variables. More effective modeling and forecasting approaches are required to assist investors in planning their bidding strategies and regulators in ensuring the security and stability of energy markets. In the literature, there is considerable interest in building better pricing modeling and forecasting frameworks to meet these difficulties. In this context, this work proposes combining seasonal and trend decomposition utilizing LOESS (locally estimated scatterplot smoothing) and Facebook Prophet methodologies to perform a more accurate and resilient time series analysis of Italian electricity spot prices. This can assist in enhancing projections and better understanding the variables driving the data, while also including additional information such as holidays and special events. The combination of approaches improves forecast accuracy while lowering the mean absolute percentage error (MAPE) performance metric by 18% compared to the baseline model.
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Interpretive structural modeling (ISM) is widely used to understand the complex connections between different components. This study presents a bibliometric overview of ISM research, with a focus on its linkages to the Sustainable Development Goals (SDGs) and the impact of COVID-19. The study analyzed 1988 publications on ISM published between 2012 and 2021, of which 1202 were directly mapped to the SDGs and 59 were related to COVID-19. The study identified key authors, institutions, countries, and journals involved in the research and their linkages to the SDGs. The results showed that ISM research is strongly linked to SDG 12 (on responsible consumption and production) and SDG 9 (on industry, innovation, and infrastructure). We also identified influential SDGs on the basis of centrality measures such as betweenness and eigenvector. The top four countries contributing to ISM publications were India, China, the United Kingdom, and the United States. The most frequently cited journals were Benchmarking: An International Journal, Sustainability, the Journal of Modelling in Management, and the Journal of Cleaner Production. Four main clusters were identified in the ISM research, including (1) integration with AHP and fuzzy logic for promoting sustainability alignment, (2) ISM-based strategy development for various stakeholders, (3) ISM-based decision-making in various fields, and (4) ISM-based risk evaluation. For the first time, studies that used the ISM approach to understand the epidemiological characteristics of COVID-19 were identified, and their key findings were discussed. The study also identified several emerging topics for future ISM research, such as blockchain and IoT, environmental management systems, climate change adaptation, smart cities, and humanitarian logistics and their potential linkages to the SDGs.