Diesel Prices Research Articles

Self-organizing Maps and Bayesian Regularized Neural Network for Analyzing Gasoline and Diesel Price Drifts

Any nation’s growth depends on the trend of the price of fuel. The fuel price drifts have both direct and indirect impacts on a nation’s economy. Nation’s growth will be hampered due to the higher level of inflation prevailing in the oil industry. This paper proposed a method of analyzing Gasoline and Diesel Price Drifts based on Self-organizing Maps and Bayesian regularized neural networks. The US gasoline and diesel price timeline dataset is used to validate the proposed approach. In the dataset, all grades, regular, medium, and premium with conventional, reformulated, all formulation of gasoline combinations, and diesel pricing per gallon weekly from 1995 to January 2021, are considered. For the data visualization purpose, we have used self-organizing maps and analyzed them with a neural network algorithm. The nonlinear autoregressive neural network is adopted because of the time series dataset. Three training algorithms are adopted to train the neural networks: Levenberg-Marquard, scaled conjugate gradient, and Bayesian regularization. The results are hopeful and reveal the robustness of the proposed model. In the proposed approach, we have found Levenberg-Marquard error falls from − 0.1074 to 0.1424, scaled conjugate gradient error falls from − 0.1476 to 0.1618, and similarly, Bayesian regularization error falls in − 0.09854 to 0.09871, which showed that out of the three approaches considered, the Bayesian regularization gives better results.

A Case Study on Rising Petrol and Diesel Prices in Fourteen Cities of India

A Case Study on Rising Petrol and Diesel Prices in Fourteen Cities of India

Розвиток конкуренції на ринку світлих нафтопродуктів: теорія, проблеми і шляхи їх вирішення

It is substantiated that the development of competition in the market of light oil products is complex and controversial, due to a number of problems: reduction of domestic production and leadership of importers in the Ukrainian market of light oil products; non-transparency of economic relations, strengthening of shadow operations; unstable internal and external price environment; fluctuations in retail prices for gasoline and diesel fuel; aggravation of problems caused by Russian aggression in Ukraine. It is determined that the market of retail sales of light oil products is characterized as a «rigid» or «vague oligopoly» formed by several powerful market operators, occupying about 70%, whose collective position in the markets has structural features of a monopoly (dominant), which creates the possibility of conscious parallel behavior of market participants (tacit collusion). The economic and legal principles of limiting the abuse of dominant operators in the market and the development of competition in it are substantiated.

Impact of India's Diesel Subsidy Reforms and Pricing Policy on Growth and Inflation

Impact of India's Diesel Subsidy Reforms and Pricing Policy on Growth and Inflation

Fractional transportation problem under interval-valued Fermatean fuzzy sets

<abstract><p>The concept of an interval-valued Fermatean fuzzy set (IVFFS), an extension of Fermatean fuzzy sets, is a more resilient and reliable tool for dealing with uncertain and incomplete data in practical applications. The purpose of this paper is to define a triangular interval-valued Fermatean fuzzy number (TIVFFN) and its arithmetic operations. Fractional transportation problems (FTPs) have important implications for cost reduction and service improvement in logistics and supply management. However, in practical problems, the parameters in the model are not precise due to some unpredictable factors, including diesel prices, road conditions, weather conditions and traffic conditions. Therefore, decision makers encounter uncertainty when estimating transportation costs and profits. To address these challenges, we consider a FTP with TIVFFN as its parameter and call it an interval-valued Fermatean fuzzy fractional transportation problem (IVFFFTP). A new method for solving this IVFFFTP is proposed without re-transforming the original problem into an equivalent crisp problem. Illustrative examples are discussed to evaluate the precision and accuracy of the proposed method. Finally, the results of the proposed method are compared with those of existing methods.</p></abstract>

Investigating the Role of Energy Prices in Enhancing Inflation in Pakistan: Fresh Insight from Asymmetric ARDL Model

Inflation is a serious problem of poor countries in this modern world because the majority of people live below the poverty line. It becomes difficult for poor people to fulfill their basic needs with higher inflation rate. The main objective of this study to analyze the impact of energy prices on the inflation rate in Pakistan. For analysis purpose the study uses time series data for the period 1990-2020. Consumer Price Index (CPI) is used as the dependent variable while independent variables include pump diesel domestic prices, pump gasoline domestic prices, GDP per capita, real effective exchange rate, government expenditure and imports of goods and services. The study uses non-linear Autoregressive Distributed Lag model (NARDL) econometric technique for estimation purpose. The results show that pump diesel and gasoline prices have U-shaped Kuznets curve, while economic growth, real exchange rate and government expenditures have emerged as important contributors of inflation in Pakistan. This study suggests that government should take effective measures to decrease dependence on imported energy resources and should rely on renewable energy resources to tackle the rising deficit in balance of payments (BOP).

Effects of different batteries and dispatch strategies on performance of standalonePV/WT/DG/battery system: A case study

AbstractThe idea of integrated hybrid renewable energy systems (IHRES) is gaining attention for electrification of rural areas where on‐grid electricity supply is uneconomical. From this point of view, the technical and economic feasibility analysis is carried out for a standalone IHRES in a remote area of Malnad region in Karnataka, India. Solar and wind energy are the prominent renewable resources available in the selected area for study. In the present study, lithium‐ion, lead‐acid and zinc‐bromide batteries effect on “PV‐WT‐DG‐Battery” system is examined and compared. The control strategies used in the study are “load following (LF)” and “predictive dispatch (PD).” The simulation results reveal that the “cost of energy (COE)” and “net present cost (NPC)” are found to be low in zinc‐bromide batterybased system with “PD control strategy.” The NPC and COE are found to be $55 262 and $0.35 per kWh for optimal system. Zinc‐bromide batteries are best suited for remote electrification with less load demand. The sensitivity analysis shows that there is a minimal effect on the performance of the planned IHRES upon variation in the “inflation rate,” “discount rate,” and “diesel price.”

Techno-economic Analysis and Life-Cycle Analysis of Renewable Diesel Fuels Produced with Waste Feedstocks

Wet waste feedstocks represent an important category of resources that could be utilized to produce biofuels. Diversion of the wet waste resources from going through conventional waste management practices to utilization as feedstocks for energy production also benefits from avoided cost and pollutant emissions of waste management and disposal. This study investigates the economic and environmental implications of producing bioblendstocks for mixing controlled compression ignition engines from two waste-to-fuel pathways: hydroprocessed esters and fatty acids (HEFA) from yellow grease and swine manure hydrothermal liquefaction (HTL) followed by biocrude upgrading. Detailed process models were developed for both pathways, which informed the techno-economic analysis and life-cycle analysis. Conventional swine manure management practice was also modeled in detail as the business-as-usual scenario for the swine manure HTL pathway. The estimated minimum fuel selling prices were $1.22/gasoline liter equivalent (GLE) and $0.94/GLE for the yellow grease to HEFA and swine manure HTL pathways, respectively. The life-cycle greenhouse gas (GHG) emissions of the two pathways were 11.2 and −33.3 g of CO2e/MJ, respectively, for the yellow grease to HEFA and swine manure HTL pathways. The credits of avoided emissions from conventional swine manure management were the main reason for the negative GHG emissions of the swine manure HTL pathway. The marginal GHG emissions abatement costs were estimated to be $116–$270/tonne CO2e and $5–$103/tonne CO2e for the yellow grease HEFA and swine manure HTL pathways, respectively, for a diesel price ranging between $0.5/GLE and $0.9/GLE. Since the yellow grease HEFA pathway is already commercialized, it can benefit from the $200/tonne carbon credit in the California Low Carbon Fuel Standard market, which could help the yellow grease HEFA pathway to achieve near-zero marginal GHG emissions abatement cost.

Economic evaluation of fuel cell-powered OFF-ROAD machinery using stochastic analysis

This study proposes a business model to obtain a successful off-road machinery retrofit using fuel cell technology by the means of evaluating scenarios using the net present value NPV of the project as a figure of merit. Given the uncertainty of some parameters, such as the price of diesel, cost of hydrogen, and cost of technology. It is proposed to carry out a Monte Carlo simulation to sensitize the business model. The results of the simulation declare that the possibility of achieving a positive NPV is increased from 54% considering present conditions to 99% considering projections for the year 2030. The prices of diesel and hydrogen condition the results in a more relevant manner and a price relationship is obtained between these two variables. Taxes could play a key role in the future, according to the results obtained in this study.

Indian Commodity Market Price Comparative Study of Forecasting Methods - A Case Study on Onion, Potato and Tomato

In this study several characteristics are taken into account so that the crop price forecast is accurate. Forecasting the price of agriculture commodities based on Volume, diesel price helps the agriculturist and also the agriculture mandi’s in India. We look at onion, tomato, and potato trading in India and present the evaluation of a price forecasting model, and anomaly detection and compared differently Supervised, Unsupervised and Forecasting prediction models. We prefer to use wholesale prices, retail prices, arrival volumes of the agricultural commodities and Diesel prices in India. We also provide an in-depth forecasting analysis of the effect on these retail prices. Our results are encouraging and point towards the likelihood of building pricing models for agricultural commodities and to detect anomalies. These data can then be stored and analyzed. The empirical comparison of the chosen methods on the various data showed that some methods are more suitable than others for this type of problem. In this research, we did a comparative study of Auto ARIMA (Autoregressive Integrated Moving Average), RNN (Recurrent Neural Network), LSTM, VAR (vector autoregressive model), and Random Forest Regression, XGBoost in their ability to predict Retail prices of potatoes, onions and tomatoes.

Techno-Economic Assessment of a Standalone Hybrid System Using Various Solar Tracking Systems for Kalpeni Island, India

Achieving electrification in an island considering less emission and levelized energy cost is a challenging goal on developing islands such as Kalpeni Island. This work exhibits the techno-economic assessment of a standalone hybrid system to generate power to Kalpeni Island, India through sensitivity and optimization analysis using HOMER software. Various system configurations like solar/DG, wind/DG, solar/wind/DG, and solar/wind are analyzed based on cost and electrical parameters. Based on the optimization results, the best hybrid system is chosen for Kalpeni Island considering different solar tracking methods. Then, multi-year and sensitivity analysis are performed to analyze the effect of load growth, rising diesel price, rising battery minimum SOC, rising PVS derating, rising photovoltaic cell temperature, and changing inverter and rectifier efficiency. The system operated with a solar photovoltaic system (PVS) and diesel generator (DG) with a tracking system on a vertical axis (TSVA) shows the best optimization result compared to other hybrid configurations with a low levelized energy cost (LEC) of 0.222 $/kWh and net present cost (CNP) of $448,269 for the chosen location. The TSVA plays a vital role on power production in the system operated with solar and DG sources, which produces 9.77% more power compared to fixed system without tracking (FSWT). The total emission produced in the system operated with solar and diesel generator with TSVA is 88.2% less compared to an WT/DG configuration operated with FSWT.

Petroleum Price Volatility on Macroeconomic Indicators in India

The selling price of petrol and diesel in the domestic market is determined by the volatility of crude oil pricein the international market and taxes and excise duty imposed on it. India is heavily dependent on foreigncountries to meet its growing petrol-diesel demand. Consequently, net trade balance reflected in the BOP isalways adverse, which in turn adversely affects all the macroeconomic indicators and thereby, the poorperformance of the entire economy. So attempts should be made and petroleum price fluctuations in Indiamust be controlled to reduce the current inflation and to maintain a balanced growth rate in the economy.

Agriculture and inflation: Expected and unexpected shocks

This study assesses the inflationary role of agriculture in Brazil using procedures that measure these effects as unanticipated shocks. We focus on the effects of unexpected price shocks to three groups of commodities of the sector, understood as supply shocks, on the unanticipated changes in the IPCA, Brazil's official inflation index. Supply-side shocks related to the energy sector, the exchange rate and the international agricultural commodity prices are also considered. The theoretical basis is the hybrid New Keynesian Phillips Curve and the econometric procedures applied to the quarterly data from 2001 to 2019 are related to the analysis of autoregressive vectors – Impulse Response Functions (IRF), Forecast Error Variance Decomposition (FEVD), and Historical Decomposition of Forecast Errors (HDFE). We use two specifications: one that assumes that changes in domestic prices implicitly reflect the effects of both international dollar prices and exchange rate shocks and other which explicitly includes these two variables together with an aggregate agricultural price. The benefit of using of the two specifications is twofold: test the robustness of analytical context and examine the external components of the Brazilian inflation. The main results are: i) expected inflation, grains and diesel prices and the exchange rate stand out in explaining the variability of IPCA forecasting errors, and shocks in the IPCA itself are also relevant; ii) although of relevant magnitude, shocks to IPCA itself dissipate quickly, while supply shocks, because they are relatively large, even with small coefficients in IRF, have important impacts on inflation; iii) shocks to international prices and exchange rate affect domestic aggregate agricultural price; and iv) unanticipated supply shocks (from agriculture, energy, and exchange rate) plus inflation expectation jointly played a disinflationary role in 2018 and 2019.

English

This study analyses the asymmetric effects of the swings in diesel prices and exchange rates on Turkey’s food prices with the Non-Linear Autoregressive Distributed Lag (NARDL) model. For this purpose, Turkey’s diesel prices, exchange rate, and general food price index data for the same period between January 2000 and December 2019 were adopted. Considering that diesel prices are an essential cost item in agricultural production, it becomes crucial to determine the effect on food prices. Besides, the exchange rate fluctuations are expressed as another important macro variable that impacts food prices. As a result of the NARDL model, asymmetric co-integration between the general food price index, diesel prices, and the exchange rate was determined. Still, it has been observed that the negative and positive changes in diesel prices on food prices, in the long run, do not have a significant effect. On the other hand, the negative effect of the exchange rate was significant. It is concluded that a 1% decrease in the negative changes in the exchange rate will cause 0.94% decrease in food prices. Consequently, the general food price is affected by adverse shocks on the exchange rate in the long run. One may be concluded that the exchange rate should be considered while formulating policies about the swings in food prices. Especially, the local production of agricultural inputs affected by exchange rate fluctuations could be encouraged.

Microgrid distributed energy resources planning based on a long-term dynamic microsimulation

In this paper, we study a DERs simulation platform that can adapt to dynamic infrastructure changes. We present a long-term dynamic-planning simulation platform focused on DERs based on MATLAB and TCP/IP network communication via GridLAB-D. This platform can capture critical features of DERs by combining MATLAB’s ability to optimize control with GridLAB-D’s capacity for accurate and discrete event-based microsimulations. The proposed platform architecture is divided into inner and outer layers. The outer layer simulates changes in the external environment (i.e., changes in load level as well as the price of diesel fuel and planned equipment components) and equipment characteristics (i.e., the running lives of batteries and diesel generators). These features provide dynamic scenarios and re-planning boundary conditions that can be used to inform the inner layer simulation. The inner layer presents an operational simulation of the planned microgrid that leverages day-ahead scheduling and the real-time adjustments associated with uncertainties in DER output. Simulation results have shown our proposed planning scheme will result in increased profits and improved resource utilization efficiency during the entire 10-year cycle. Compared to traditional planning scheme, our proposed planning scheme can perform dynamic adjustments to the configuration of various DERs according to changing external factors and network conditions.

Reactive separation processes applied to biodiesel production from residual oils and fats: Design, optimization and techno-economic assessment of routes using solid catalysts

Three solid acid-catalyzed (SAC) processes for biodiesel production from residual oil and fats (ROFs) with HWSi/Al2O3 as catalyst were designed and optimized using Aspen Plus: simultaneous esterification, transesterification, and methanol separation based on catalytic distillation (CD) (process A) and catalytic absorption (CA) (process B), where CA has not yet been investigated in these conditions; and hydro-esterification industrial process using CD (process C1). For the first time, processes A, B and C based on SAC route were optimized and compared regarding to techno-economic and environmental aspects. Processes A and B were the most economically and eco-friendly options. Compared to process B, process A was the best option due to simpler flowsheet. Process A2 presented 25.6, 60.1, 4.6, 8.6, 52.6 and 62.8% lower capital, utilities (Cutil), operation, total annualized (TAC), waste treatment (Cwaste) and CO2 emission costs than process C1. A global optimization developed for process A saved 430 k$/year on TAC. After a heat integration, process B presented 4.9 and 10.8% lower Cutil and Cwaste than process A. Process A was also designed for FFA levels of 5–25 wt%, where the biodiesel break-even price remained competitive (0.48–0.75 $/kg) with diesel price.

An economic study of the use of solar energy in the irrigation of reclaimed agricultural lands in Assiut Governorate

The cost of energy sources used for irrigation on reclaimed land in the Assiut Governorate is a growing problem due to the high prices of electricity and diesel used for irrigation. Therefore, this research aims to study the daily needs of water crops, on the basis of which the solar power plant operating under various irrigation systems is proposed as an alternative source of electricity, and also to compare irrigation methods for the three categories of possession (less than 10 acres, larger than 10 acres, and less than 20 acres), and the differences in irrigation costs due to the use of various energy methods and both direct solar energy and hybrid energy in the reclaimed agricultural lands in the most important provinces of the Assiut Governorate. Finally; study and compare the advantages and disadvantages of solar, electricity, and diesel water pumps. The solar pumping program was used according to the water need for crops, and a serious study was conducted to compare the uses of various energy sources to irrigate reclaimed agricultural land. From the study of the feasibility study of the project during the 25 years of its establishment, the most important results were that the use of direct solar energy and hybrids on the one hand and electricity on the other hand to obtain energy for spray irrigation for the selected zones for the different categories of possession, where Albadari zone has the largest decrease, with an estimated 99.17%, 74.42% for the third category of possession of electricity, respectively, and Alfathzone was the lowest, with an estimated 19.92%, 10.68% for the first possession class of direct solar electricity and hybrids, respectively. In the case of drip irrigation, Albadarizone also recorded the largest reduction of the difference between direct solar energy, hybrid, and electricity, estimated at 99.9%, 72.09% of electricity for the third category. Manflotzone recorded a lower rate of 16.81 %, 5.7 % of electricity, either direct or hybrid, respectively, during the study period. Therefore, the study recommends the work of a solar power plant, due to the existence of a variance between the systems of energy use in irrigating the reclaimed agricultural lands, as the irrigation costs per acre were reduced in all centers instead of the use of electricity.

THE ANALYSIS OF ELECTRICAL SYSTEM REQUIREMENT OF JAVA COASTAL FISHING VESSELS

Traditional ships are dependent on diesel which functions not only as a propulsion, but also to supply power to the tools they use. This causes a decrease in the profits obtained by fishermen considering that the price of diesel fuel is increasingly expensive. This problem is also supported by the availability of diesel which is one of the non-renewable fossil fuels on earth which is getting thinner. The design and calculation of electrical power to supply tools that can make fishermen more effective in catching fish where the electrical energy obtained come from solar energy and is assisted by a portable generator as an emergency supply. The innovation of using solar energy as an effort to reduce the use of solar which will indirectly save fishermen's expenses. The 3GT fishing boat uses 4 solar panels with 450Wp specifications. This fishing boat design is equipped with radar, AIS, and navigation lights.

Techno‐Economic Assessment of Renewable Energy‐based Microgrids in the Amazon Remote Communities in Ecuador

Several remote communities have limited electricity access and are mainly dependent on environmentally damaging fossil fuels. The installation of microgrid networks and green energy initiatives are currently addressing this issue. Thus, the techno‐economic assessment of a microgrid that comprises photovoltaic arrays, a micro‐hydro turbine, and diesel generation is proposed herein. Two scenarios are evaluated considering the inclusion or not of diesel generation. This model is performed in HOMER. The results demonstrate that the best option in economics is to invest in a PV/hydro/diesel microgrid, resulting in an net present cost of 2.33 M$, and a cost of energy of 0.194 $ kWh−1. Furthermore, to address diesel price uncertainties, a sensitivity analysis is carried out based on three different projected diesel prices.

Deeper investigation of oxygen-containing compounds in oleaginous feedstock (animal fat) by preparative column chromatography and comprehensive two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry

The production of renewable fuels as biodiesel and bio-jet fuel is usually originated by the transformation and processing of oleaginous feedstocks, mainly composed of triacylglycerols. Currently, a significant part of the triacylglycerol production relies on grassy oil crops or other woody oil plants, representing more than 120 million metric tons every year. Considering that the worldwide triacylglycerol demand is expected to rise in the future, alternative routes are necessary to ensure a sustainable biodiesel industry and limit diesel price volatility. In this context, the use of animal fats could be an interesting alternative for biodiesel production as the production of animal byproducts represents nearly 17 million tons per year in the European Union only (2020). Animal fats, however, contain large amounts of no-esterified fatty acids and other oxygen compounds, reducing the yield of biodiesel. Therefore, a specific pretreatment is needed before the trans-esterification process. The setup of such appropriate pretreatments requires detailed upstream characterization of the minor components present in the feedstock. For this purpose, the minor component profile of animal fat was investigated by comprehensive two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry. This was preceded by an innovative sample fractionation and focalization of these minor components by a preparative liquid chromatographic column method. The overall method permitted to extract different levels of information from the two-dimensional chromatograms, leading to a tentative identification of more than 150 compounds, mainly oxygenated, belonging to different chemical classes.