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A gas flowmeter for measuring low flow rate has been widely used in the field of medical, health, environmental protection, energy industry, aerospace, etc. To against Covid-2019, the requirement on the low flow rate has been increasing dramatically. At present, the typical standard devices for calibrating low gas flowmeter mainly include standard bell provers of gas flow, standard piston provers of low gas flow and standard laminar of low gas flow. Different measuring principles are adopted among these typical standard devices. To ensure the consistency of these typical standard devices, a comparison test is performed. The standard devices used in the comparison are of the same accuracy grade, with an extended uncertainty of 0.2%(k=2). The piston-type gas flow calibrator of grade 1.0 is selected as the transfer standard, and three flow points with high flow rate, medium flow rate and low flow rate are selected for test. The consistency of measurement results is evaluated by normalized deviation En. The comparison results are acceptable which show that three typical standard devices are accurate and reliable. © FLOMEKO 2022.All rights reserved
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The article describes the world's experience in developing the solar industry. It discusses the mechanisms of state support for developing renewable energy sources in the cases of five countries that are the most successful in this area—China, the United States, Japan, India, and Germany. Furthermore, it contains a brief review of state policy in producing electricity by renewable energy facilities in Kazakhstan. This paper uses statistical information from the International Renewable Energy Agency (IRENA), the International Energy Agency (IEA), British Petroleum (BP), and the Renewable Energy Network (REN21), and peer-reviewed sources. The research methodology includes analytical research and evaluation methods to examine the current state of solar energy policy, its motivators and incentives, as well as the prospects for its development in Kazakhstan and in the world. Research shows that solar energy has a huge development potential worldwide and is sure to take its place in gross electricity production. This paper focuses on the selected economic policies of the top five countries and Kazakhstan, in what may be considered a specific research limitation. Future research suggestions for the expansion of Renewable Energy (RE) in Kazakhstan could include analysing the impact of introducing dedicated policies and incentives for solar systems and exploring the benefits and challenges of implementing large RE zones with government–business collaboration.
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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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Crude Palm Oil (CPO) is the mainstay of Indonesian agricultural products which is the largest CPO producing country in the world. The high market share of Indonesian CPO exports reflects the high competitiveness of Indonesian CPO in the global market. The purpose of this study is to determine the competitiveness of Indonesian CPO, the concentration of the Indonesian CPO industry, and analyze the factors that are suspected to affect the competitiveness of the CPO industry in Indonesia. The data used in this study are secondary data with a five-digit ISIC (10432) using time series data for 2001-2020 and the analytical techniques used in this study include Revealed Competitive Advantage (RCA), Gini Coefficient, and Error Correction Model (ECM). The results showed that Indonesian CPO has high competitiveness in the international market, the Indonesian CPO industry is not concentrated, in the short term the variables that affect competitiveness are CPO prices, subsidized solar prices policy, and industrial concentrations, while in the long term the influential variables are biodiesel policy, subsidized diesel oil policy and industrial concentration
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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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This review focuses on analysing the strategy and aspirations of the European Union within the hydrogen sector. This aim is achieved through the examination of the European Parliament's hydrogen strategy, allowing for a study of actions and projects in hydrogen technologies. The Parliament's hydrogen strategy is the document that provides the guideline of how the EU intends to function in the hydrogen sector and manages to cover a wide range of topics, all of them significant to represent the entirety of the hydrogen sector. It touches on subjects such as hydrogen demand, infrastructure, research, and standards, among others. The review discusses also the aspect that the EU intends to be a leader in the hydrogen sector, including the large-scale industrialization of key elements such as electrolysers, and this purpose is corroborated by the large number of associations, strategies, plans, and projects that are being established and developed by the European Union. The most important conclusions to learn from this analysis are that hydrogen has many of the right characteristics to make it the key to decarbonisation, especially in hard-to-abate sectors, and that it is bound to be one of the main actors in the imminent green transition. Moreover, hydrogen seems to be having its breakthrough, and this field's development can have benefits not only from an environmental perspective but also from an economical one, enabling the way into the green transition and the fight against climate change.
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The ocean holds abundant resources, but the utilization of those resources for the marine economy presents a complex and dynamic industrial situation. Exploring sustainable development in this industry is of practical value, as it involves the rational use of marine resources while protecting the environment. This study provides an innovative review of the current application status of Digital Twins Technology (DTT) in various sectors of the marine industry, including the ship-building industry (SBI), Offshore Oil and Gas Industry, marine fishery, and marine energy industry. The findings reveal that DTT offers robust support for full life cycle management (LCM) in SBI, including digital design, intelligent processing, operation, and error management. Furthermore, this work delves into the challenges and prospects of DTT application in the marine industry, aiming to provide reference and direction for intelligent systems in the industry and guide the rational development and utilization of marine resources in the future.
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Advanced metering infrastructure (AMI) is becoming increasingly popular as an efficient means of energy demand management. By collecting energy data through AMI, it is possible to provide users with information that can induce them to change their behavior. To ensure that AMI continues to expand and to encourage the use of energy data, it is important to increase consumer participation and analyze their preferred service attributes. This study utilized a choice experiment to analyze consumer preferences for and acceptance of smart energy services based on AMI data. The results of a mixed logit model estimation show that consumers prefer the electricity information service for individual households and the social safety-net service among convergence services. A scenario analysis confirms that monetary compensation to offset any additional charges is important to maintain the level of consumer acceptance. These empirical findings offer insights for policymakers and companies seeking to develop policies and similar services.
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In recent years, time series forecasting has become an essential tool for stock market analysts to make informed decisions regarding stock prices. The present research makes use of various exponential smoothing forecasting methods. These include exponential smoothing with multiplicative errors and additive trend (MAN), exponential smoothing with multiplicative errors (MNN), and simple exponential smoothing with additive errors (ANN) for the forecasting of the stock prices of six different companies in the petroleum, electricity, and gas industries that are listed in the IBEX35 index. The database employed for this research contained the IBEX35 index values and stock closing prices from 3 January 2000 to 30 December 2022. The models trained with this data were employed in order to forecast the index value and the closing prices of the stocks under study from 2 January 2023 to 24 March 2023. The results obtained confirmed that although none of the proposed models outperformed the rest for all the companies, it is possible to calculate forecasting models able to predict a 95% confidence interval about real stock closing values and where the index will be in the following three months.
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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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Despite this focus on pandemic-related supply chain disruptions, fewer empirical studies have sought to isolate short-term price impacts in food and nonfood agricultural commodity markets.1 Understanding the drivers of short-term commodity price impacts is critical to understanding future susceptibility to major market shocks and to informing policies related to shock mitigation. Declines in ethanol production reached an estimated 2 billion gallons lost from March to November 2020, leading to a corresponding decline of 700 million bushels of corn usage and a loss of billions of dollars of ethanol producer surplus (Renewable Fuels Association, 2020b;Schmitz, Moss, and Schmitz, 2020). Increases in corn-based ethanol production that started in 2005 have linked agricultural commodity prices and energy markets as US ethanol production increased rapidly from 3.9 billion gallons in 2005 to 13.3 billion by 2010 and 15.8 billion by 2019 (Chakravorty, Hubert, and Nøstbakken, 2009;Wright, 2011;Roberts and Schlenker, 2013;Asgari, Saghaian, and Reed, 2020;US Department of Agriculture, 2021). Given that over 90% of US ethanol is used in mixtures of E10 gasoline and the US market reached a 10% "blend wall" in 2016, any reduction in gasoline use will cause proportional decreases in ethanol use (US Energy Information Administrationa, 2020;US Department of Agriculture, 2021).
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Climate change, the scarcity of fossil fuels, advances in clean energy, and volatility of crude oil prices have led to the recognition of clean energy as a viable alternative to dirty energy. This paper investigates the multifractal scaling behavior and efficiency of green finance markets, as well as traditional markets such as gold, crude oil, and natural gas between 1 January 2018, and 9 March 2023. To test the serial dependency (autocorrelation) and the efficient market hypothesis, in its weak form, we employed the Lo and Mackinlay test and the DFA method. The empirical findings showed that returns data series exhibit signs of (in)efficiency. Additionally, there is a negative autocorrelation among the crude oil market, the Clean Energy Fuels Index, the Global Clean Energy Index, the gold market, and the natural gas market. Arbitration strategies can be used to obtain abnormal returns, but caution should be exercised as prices may increase above their actual market value and reduce the profitability of trading. This work contributes to the body of knowledge on sustainable finance by teaching investors how to use predictive strategies on the future values of their investments.
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PurposeThis paper investigates the influence of the ongoing crisis of Russia's incursion on Ukraine on the risk dynamics of energy futures contracts with high-frequency data on four different futures contracts using risk metrics of value at risk (VaR) and conditional value at risk (CVaR) for the USA market.Design/methodology/approachThe author used different generalised autoregressive conditional heteroscedasticity - Extreme Value Theory (GARCH)-EVT models and compared the performance of each of the competing models. Backtesting evidence shows that VaR and CVaR combined with GARCH-EVT better estimate risk.FindingsThe study results show that combined risk metrics are efficient and adaptive to estimating the risk dynamics and backtesting of the models, revealing that the autoregressive moving average (ARMA) (1,1)-asymmetric power autoregressive conditional heteroscedasticity (APARCH) model performs relatively better than other models.Practical implicationsThe paper has practical implications for different market participants. From the risk manager's and day traders' angles, the market participants can estimate the risk exposure in the energy futures contract and take positions accordingly. The results are important for oil-importing countries due to the developing supply crisis and price escalation, which can brew inflation in the economy.Originality/valueTo the best of the author's knowledge, the paper is the first to throw light on the risk angle of energy futures contracts during the ongoing crisis of the Russia–Ukraine war.
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PurposeThe Russian invasion of Ukraine generated unprecedented panic in the European financial system. As expected, the European Union (EU) felt most of the negative effects of the war due to geographical proximity to Ukraine and energy dependence on Russia. This study aims to investigate the influence of Brent crude oil (BCO), Dutch Title Transfer Facility Natural Gas, and CBOE Volatility Index (VIX) on Deutscher Aktien Index (DAX), Austrian Traded Index (ATX) and Milano Indice di Borsa (FTSEMIB). The German, Austrian and Italian equity indexes were chosen due to the heavy dependence of these countries on Russian gas and oil.Design/methodology/approachThe data cover the period from November 24, 2021, to June 24, 2022, including five months of the Russia–Ukraine war. To generate the intended results, vector autoregressive, structural vector autoregressive, vector error correction model, Johansen test and Granger causality test were used.FindingsThe results highlight that natural gas and the VIX carried negative effects on DAX, ATX and FTSEMIB. The BCO was expected to have influenced three selected equity indexes, while the results suggest that it was priced only in ATX.Originality/valueThis research provides modest evidence for the policymakers on the systemic risk that Russian gas has for the EU equity markets. From a managerial perspective, changes in oil and gas prices are a permanently integral part of portfolio risk analysis.
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According to the World Economic Forum, the building sector is responsible for 40% of global energy consumption and 33% of greenhouse gas (GHG) emissions, and this is expected to increase due to population growth and the subsequent impact on the environment, economy and health. To tackle the problem, countries have set new construction codes, policies and regulations for the construction of new buildings in an effort to make them greener. However, there is a need to enhance the status of the existing buildings, especially mosques, as they are the main contributors to energy usage and water consumption in the United Arab Emirates (UAE). Therefore, this research seeks to fill this gap, aiming to evaluate the energy usage and water consumption practices employed in the existing mosque buildings within the UAE and to provide recommendations for improving the sustainability of mosques, with a focus on the environmental and economic pillars. The methodology relies mainly on data collected from 146 existing mosque buildings that have undergone energy saving audits across the UAE. Descriptive statistical analysis is performed to analyze the data from the period of 2018–2019 in order to determine the most significant factors related to energy inefficiency in existing mosque buildings in the UAE and to determine the most cost-effective and energy-saving corrective measures for energy and water conservation. The findings further enhance the standard of experience for mosque visitors (social aspect);reduce energy bill expenses, providing an acceptable return on investment from the proposed energy conservation measures for stakeholders (economic);and reduce the overall energy consumption, which can reduce the total CO2 emissions from mosque buildings (environmental).
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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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China's energy structure is dominated by fossil fuels, especially coal consumption, which accounts for a relatively high share. In January 2020, the COVID-19 outbreak affected the global coal market, and many countries experienced negative economic growth. Economic development requires energy consumption. In 2021, China set a target of peaking carbon emissions by 2030 in order to phase out the dependence of carbon emissions on economic development. Therefore, the aim of this article is to develop directions for the sustainable development of China's coal industry. Based on the macroenvironment and situation analysis, the article concludes that, under the influence of geopolitics, China's shortage of imported coal resources and China's continuous rise in coal demand, the share of coal in China's energy structure will not decrease significantly in the long-term. The main directions for the sustainable development of China's coal industry are to ensure the safety of coal energy storage and improve the level of safety supervision;coordinate the development of regional energy;increase the clean, efficient, and low-carbon utilization of coal;and strengthen international coal strategic cooperation.
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In a time-frequency biwavelet framework, we analysed the short-, medium-, and long-term impacts of COVID-19-related shocks on ten energy commodities (i.e., Brent, crude oil, coal, heating oil, natural gas, gasoline, ethanol, naphtha, propane, and uranium) from January 2020 to April 2022. We document intervals of high and low coherence between COVID-19 cases and the returns on energy commodities across the short-, medium-, and long-term horizons. Low coherence at high frequencies indicated weak correlation and signified diversification, hedging, and safe-haven potentials in the short term of the pandemic. Our findings suggest that energy markets' dynamics were highly driven by the pandemic, causing significant changes in market returns, particularly across the medium- and low-frequency bands. Furthermore, the empirical results indicate dynamic lead-lag relationships between COVID-19 cases and energy returns between the medium- and long-term horizons, signifying that diversification could be sought through crossinvestment in different energy commodities. The results have significant implications for market participants, regulators, and practitioners.
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In this study, we analyze the upside and downside risk connectedness among international stock markets. We characterize the connectedness among international stock returns using the Diebold and Yilmaz spillover index approach and compute the upside and downside value-at-risk. We document that the connectedness level of the downside risk is higher than that of the upside risk and stock markets are more sensitive when the stock market declines. We also find that specific periods (e.g., the global financial crisis, the European debt crisis, and the COVID-19 turmoil) intensified the spillover effects across international stock markets. Our results demonstrate that DE, UK, EU, and US acted as net transmitters of dynamic connectedness;however, Japan, China, India, and Hong Kong acted as net receivers of dynamic connectedness during the sample period. These findings provide significant new information to policymakers and market participants.