Search results for: energy price dynamics

Authors: Bel Abed Ines Mariem

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Different stock markets keep changing their exchange structure for the only purpose of improving the functioning of their markets. This paper investigates the effects of the transfer from one trading category to another in the Tunisian Stock Exchange on market price and liquidity. The sample consists of 40 securities transferred from call auction to continuous auction and conversely during the period between 2004 and 2013. The methodology used is the event study. Empirical results show an interesting phenomenon observed; stocks transferred to the call system have experienced an improvement on their price and liquidity especially for less liquid ones. However, price and liquidity for stocks transferred from call system to continuous system have decreased.

Keywords: microstructure, call auction, continuous auction, price, liquidity and event study

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Authors: Nikolaos Georgantzis, Efi Vasileiou

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We present results from experimental price-setting oligopolies in which green firms undertake different levels of energy-saving investments motivated by public subsidies and demand-side advantages. We find that consumers reveal higher willingness to pay for greener sellers’ products. This observation in conjunction to the fact that greener sellers set higher prices is compatible with the use and interpretation of energy-saving behaviour as a differentiation strategy. However, sellers do not exploit the resulting advantage through sufficiently high price-cost margins, because they seem trapped into “run to stay still” competition. Regarding the use of public subsidies to energy-saving sellers we uncover an undesirable crowding-out effect of consumers’ intrinsic tendency to support green manufacturers. Namely, consumers may be less willing to support a green seller whose energy-saving strategy entails a direct financial benefit. Finally, we disentangle two alternative motivations for consumer’s attractions to pro-social firms; first, the self-interested recognition of the firm’s contribution to the public and private welfare and, second, the need to compensate a firm for the cost entailed in each pro-social action. Our results show the prevalence of the former over the latter.

Keywords: corporate social responsibility, energy savings, public good, experiments, vertical differentiation, altruism

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Authors: Li Li, Kai-Hsuan Chu

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It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.

Keywords: real estate price, least-square, grey correlation, macroeconomics

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Authors: S. K. Ashiquer Rahman

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Recently, oil has become more influential in almost every economic sector as a key material. As can be seen from the news, when there are some changes in an oil price or OPEC announces a new strategy, its effect spreads to every part of the economy directly and indirectly. That’s a reason why people always observe the oil price and try to forecast the changes of it. The most important factor affecting the price is its supply which is determined by the number of wildcats drilled. Therefore, a study about the number of wellheads and other economic variables may give us some understanding of the mechanism indicated by the amount of oil supplies. In this paper, we will consider a relationship between the number of wellheads and three key factors: the price of the wellhead, domestic output, and GNP constant dollars. We also add trend variables in the models because the consumption of oil varies from time to time. Moreover, this paper will use an econometrics method to estimate parameters in the model, apply some tests to verify the result we acquire, and then conclude the model.

Keywords: price, domestic output, GNP, trend variable, wildcat activity

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Authors: Boulis M. Ibrahim, Iordanis A. Kalaitzoglou

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A micro structural pricing model is proposed in which price components account for learning by incorporating changing expectations of the trading intensity and the risk level of incoming trades. An analysis of European carbon futures transactions finds expected trading intensity to increase the information component and decrease the liquidity component of price changes, but at different rates. Among the results, the expected persistence in trading intensity explains the majority of the auto correlations in the level and the conditional volatility of price changes, helps predict hourly patterns in the bid–ask spread and differentiates between the impact of buy versus sell and continuing versus reversing trades.

Keywords: CO2 emission allowances, market microstructure, duration, price discovery

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Authors: Md. Shafiullah, Ali T. Al-Awami

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This project proposes optimal scheduling of imported power of a load aggregator with the utilization of EVs to maximize its profit. As with the increase of renewable energy resources, electricity price in competitive market becomes more uncertain and, on the other hand, with the penetration of renewable distributed generators in the distribution network the predicted load of a load aggregator also becomes uncertain in real time. Though there is uncertainties in both load and price, the use of EVs storage capacity can make the operation of load aggregator flexible. LA submits its offer to day-ahead market based on predicted loads and optimized use of its EVs to maximize its profit, as well as in real time operation it uses its energy storage capacity in such a way that it can maximize its profit. In this project, load aggregators profit maximization algorithm is formulated and the optimization problem is solved with the help of CVX. As in real time operation the forecasted loads differ from actual load, the mismatches are settled in real time balancing market. Simulation results compare the profit of a load aggregator with a hypothetical group of 1000 EVs and without EVs.

Keywords: CVX, electricity market, load aggregator, load and price uncertainties, profit maximization, real time balancing operation

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Authors: Yosra Mefteh Rekik, Younes Boujelbene

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We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

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Authors: Ernawati Mustafa Kamal, Hasnanywati Hassan, Atasya Osmadi

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The housing industry is crucial for sustainable development of every country. Housing is a basic need that can enhance the quality of life. Owning a house is therefore the main aim of individuals. However, affordability has become a critical issue towards homeownership. In recent years, housing price in the main cities has increased tremendously to unaffordable level. This paper investigates factors influencing the housing price from developer’s perspective and provides recommendation on strategies to tackle this issue. Online and face-to-face survey was conducted on housing developers operating in Penang, Malaysia. The results indicate that (1) location; (2) macroeconomics factor; (3) demographic factors; (4) land/zoning and; (5) industry factors are the main factors influencing the housing price. This paper contributes towards better understanding on developers’ view on how the housing price is determined and form a basis for government to help tackle the housing affordability issue.

Keywords: factors influence, house price, housing developers, Malaysia

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Authors: Pratheeba Subramanian, Anjula Gurtoo, Mary Mathew

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Transaction of patents in emerging patent markets is gaining momentum. Pricing patents for a transaction say patent sale remains a challenge. Patents vary in their pricing with some patents fetching higher prices than others. Sale of patents in portfolios further complicates pricing with multiple patents playing a role in pricing a bundle. In this paper, a set of 138 US patents sold individually as single invention lots and 462 US patents sold in bundles of 120 portfolios are investigated to understand the dynamics of selling prices of singletons and portfolios and their determinants. Firstly, price variations when patents are sold individually as singletons and portfolios are studied. Multivariate statistical techniques are used for analysis both at the lot level as well as at the individual patent level. The results show portfolios fetching higher prices than singletons at the lot level. However, at the individual patent level singletons show higher prices than per patent price of individual patent members within the portfolio. Secondly, to understand the price determinants, the effect of patent, seller, and bundling related characteristics on selling prices is studied separately for singletons and portfolios. The results show differences in the set of characteristics determining prices of singletons and portfolios. Selling prices of singletons are found to be dependent on the patent related characteristics, unlike portfolios whose prices are found to be dependent on all three aspects – patent, seller, and bundling. The specific patent, seller and bundling characteristics influencing selling price are discussed along with the implications.

Keywords: auction, patents, portfolio bundling, seller type, selling price, singleton

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Authors: Baoubadi Atozou, Koffi Akakpo

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Since the decade 2000, the use of foodstuffs such as corn, wheat, and soybeans in biofuel production has been growing sharply in the United States, Canada, and Europe. Thus, prices for these agricultural products are rising in the world market. These cereals are the most important source of calorific energy for West African Economic and Monetary Union (WAEMU) countries members’ population. These countries are highly dependent on imports of most of these products. Thereby, rising prices can have an important impact on import levels and consequently on food security in these countries. This study aims to analyze the interrelationship between the prices of these commodities and their volatilities, and their effects on imports of these agricultural products by each WAEMU ’country member. The Autoregressive Distributed Lag (ARDL) model, the GARCH Multivariate model, and the Granger Causality Test are used in this investigation. The results show that import levels are highly and significantly sensitive to price changes as well as their volatility. In the short term as well as in the long term, there is a significant relationship between the prices of these products. There is a positive relationship in general between price volatility. And these volatilities have negative effects on the level of imports. The market characteristics affect food security in these countries, especially access to food for vulnerable and low-income populations. The policies makers must adopt viable strategies to increase agricultural production and limit their dependence on imports.

Keywords: price volatility, import of agricultural products, food safety, WAEMU

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Authors: Maedeh Rahimnejad, Bahman Vahidi, Bahman Ebrahimi Hoseinzadeh, Fatemeh Yazdian, Puria Motamed Fath, Roghieh Jamjah

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Introduction: The intensive labor and high cost of developing new vehicles for controlled drug delivery highlights the need for a change in their discovery process. Computational models can be used to accelerate experimental steps and control the high cost of experiments. Methods: In this work, to better understand the interaction of anti-cancer drug and the nanocarrier with the cell membrane, we have done molecular dynamics simulation using NAMD. We have chosen paclitaxel for the drug molecule and dipalmitoylphosphatidylcholine (DPPC) as a natural phospholipid nanocarrier. Results: Next, center of mass (COM) between molecules and the van der Waals interaction energy close to the cell membrane has been analyzed. Furthermore, the simulation results of the paclitaxel interaction with the cell membrane and the interaction of DPPC as a nanocarrier loaded by the drug with the cell membrane have been compared. Discussion: Analysis by molecular dynamics (MD) showed that not only the energy between the nanocarrier and the cell membrane is low, but also the center of mass amount decreases in the nanocarrier and the cell membrane system during the interaction; therefore they show significantly better interaction in comparison to the individual drug with the cell membrane.

Keywords: anti-cancer drug, center of mass, interaction energy, molecular dynamics simulation, nanocarrier

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Authors: Jingxian An, Wei Yu

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The commercial value (retail price) of wine is mostly determined by the wine quality, ageing potential, and oak influence. This paper reveals that wine quality, ageing potential, and oak influence are favourably correlated, hence positively influencing the commercial value of Pinot noir wines. Oak influence is the most influential of these three sensory attributes on the price set by wine traders and estimated by experienced customers. In the meanwhile, this study gives winemakers with chemical instructions for raising total phenolics, which can improve wine quality, ageing potential, and oak influence, all of which can increase a wine’s economic worth.

Keywords: retail price, ageing potential, wine quality, oak influence

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Authors: Adel Almasarwah

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This study investigates the nature of association between profit warnings and stock price informativeness in the context of Jordan as an emerging country. The analysis is based on the response of stock price synchronicity to profit warnings percentages that have been published in Jordanian firms throughout the period spanning 2005–2016 in the Amman Stock Exchange. The standard of profit warnings indicators have related negatively to stock price synchronicity in Jordanian firms, meaning that firms with a high portion of profit warnings integrate with more firm-specific information into stock price. Robust regression was used rather than OLS as a parametric test to overcome the variances inflation factor (VIF) and heteroscedasticity issues recognised as having occurred during running the OLS regression; this enabled us to obtained stronger results that fall in line with our prediction that higher profit warning encourages firm investors to collect and process more firm-specific information than common market information.

Keywords: Profit Warnings, Jordanian Firms, Stock Price Informativeness, Synchronicity

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Authors: D. He, Y. Pang, G. Lodewijks

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Belt conveyors play an important role in continuous dry bulk material transport, especially at the mining industry. Speed control is expected to reduce the energy consumption of belt conveyors. Transient operation is the operation of increasing or decreasing conveyor speed for speed control. According to literature review, current research rarely takes the conveyor dynamics in transient operation into account. However, in belt conveyor speed control, the conveyor dynamic behaviors are significantly important since the poor dynamics might result in risks. In this paper, the potential risks in transient operation will be analyzed. An existing finite element model will be applied to build a conveyor model, and simulations will be carried out to analyze the conveyor dynamics. In order to realize the soft speed regulation, Harrison’s sinusoid acceleration profile will be applied, and Lodewijks estimator will be built to approximate the required acceleration time. A long inclined belt conveyor will be studied with two major simulations. The conveyor dynamics will be given.

Keywords: belt conveyor , speed control, transient operation, dynamics

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Authors: Olukunle C. Olawole, Dilip K. De, Moses Emetere, Omoje Maxwell

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Graphene can stand very high temperature up to 4500 K in vacuum and has potential for application in thermionic energy converter. In this paper, we discuss the application of energy dynamics principles and the modified Richardson-Dushman Equation, to estimate the efficiency of solar power conversion to electrical power by a solar thermionic energy converter (STEC) containing emitter made of graphene. We present detailed simulation of power output for different solar insolation, diameter of parabolic concentrator, area of the graphene emitter (same as that of the collector), temperature of the collector, physical dimensions of the emitter-collector etc. After discussing possible methods of reduction or elimination of space charge problem using magnetic field and gate, we finally discuss relative advantages of using emitters made of graphene, carbon nanotube and metals respectively in a STEC.

Keywords: graphene, high temperature, modified Richardson-Dushman equation, solar thermionic energy converter

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Authors: Sisi Xia, Dezhuan Tao, Junyan Yang, Weiting Xiong

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Under the background of Chinese urbanization changing from incremental development to stock development, the completion of urban public service facilities is essential to urban spatial quality. As public services facilities is a huge and complicated system, clarifying the various types of internal rules associated with the land market price is key to optimizing spatial layout. This paper takes Wuxi City as a representative sample location and establishes the digital analysis platform using urban price and several high-precision big data acquisition methods. On this basis, it analyzes the coupling relationship between different public service categories and land price, summarizing the coupling patterns of urban public facilities distribution and urban land price fluctuations. Finally, the internal mechanism within each of the two elements is explored, providing the reference of the optimum layout of urban planning and public service facilities.

Keywords: public service facilities, land price, urban spatial morphology, big data

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Authors: Fauzia Dianawati, Riska W. Purnomo

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Food and agricultural sector become the biggest sector contributing to inflation in Indonesia. Especially in Wonogiri district, red cayenne pepper was the biggest sector contributing to inflation on 2016. A national statistic proved that in recent five years red cayenne pepper has the highest average level of fluctuation among all commodities. Some factors, like supply chain, price disparity, production quantity, crop failure, and oil price become the possible factor causes high volatility level in red cayenne pepper price. Therefore, this research tries to find the key factor causing fluctuation on red cayenne pepper by using ARCH/GARCH method. The method could accommodate the presence of heteroscedasticity in time series data. At the end of the research, it is statistically found that the second level of supply chain becomes the biggest part contributing to inflation with 3,35 of coefficient in fluctuation forecasting model of red cayenne pepper price. This model could become a reference to the government to determine the appropriate policy in maintaining the price stability of red cayenne pepper.

Keywords: ARCH/GARCH, forecasting, red cayenne pepper, volatility, supply chain

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Authors: Simone Tedeschi, Francesco Crespi, Paolo Liberati, Massimo Paradiso, Antonio Sciala

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This paper aims at contributing to the understanding of smokers’ responses to cigarette prices increases with a focus on heterogeneity, both across individuals and price levels. To do this, a stated preference quasi-experimental design grounded in a random utility framework is proposed to evaluate the effect on smokers’ utility of the price level and variation, along with social conditioning and health impact perception. The analysis is based on individual-level data drawn from a unique survey gathering very detailed information on Italian smokers’ habits. In particular, qualitative information on the individual reactions triggered by changes in prices of different magnitude and composition are exploited. The main findings stemming from the analysis are the following; the average price elasticity of cigarette consumption is comparable with previous estimates for advanced economies (-.32). However, the decomposition of this result across five latent-classes of smokers, reveals extreme heterogeneity in terms of price responsiveness, implying a potential price elasticity that ranges between 0.05 to almost 1. Such heterogeneity is in part explained by observable characteristics such as age, income, gender, education as well as (current and lagged) smoking intensity. Moreover, price responsiveness is far from being independent from the size of the prospected price increase. Finally, by comparing even and uneven price variations, it is shown that uniform across-brand price increases are able to limit the scope of product substitutions and downgrade. Estimated price-response heterogeneity has significant implications for tax policy. Among them, first, it provides evidence and a rationale for why the aggregate price elasticity is likely to follow a strictly increasing pattern as a function of the experienced price variation. This information is crucial for forecasting the effect of a given tax-driven price change on tax revenue. Second, it provides some guidance on how to design excise tax reforms to balance public health and revenue goals.

Keywords: smoking behaviour, preference heterogeneity, price responsiveness, cigarette taxation, random utility models

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Authors: Mas Aji Rizki Widjayanto, Rizka Yunita

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The building which has an efficient and low-energy today followed by the developers. It’s not because trends on the building nowaday, but rather because of its positive effects in the long term, where the cost of energy per month to be much cheaper, along with the high price of electricity. The use of solar power (Photovoltaic System) becomes one source of electrical energy for the apartment so that will efficiently use energy, water, and other resources in the operations of the apartment. However, more than 80% of the solar radiation is not converted into electrical energy, but reflected and converted into heat energy. This causes an increase on the working temperature of solar panels and consequently decrease the efficiency of conversion to electrical energy. The high temperature solar panels work caused by solar radiation can be used as medium heat exchanger or heating water for the apartments, so that the working temperature of the solar panel can be lowered to reduce the reduction on the efficiency of conversion to electrical energy.

Keywords: photovoltaic system, efficient, heat energy, heat exchanger, efficiency of conversion

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Authors: Gianvito Colucci, Valeria Di Cosmo, Matteo Nicoli, Orsola Maria Robasto, Laura Savoldi

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The hydrogen value chain deployment is likely to be boosted in the near term by the energy security measures planned by European countries to face the recent energy crisis. In this context, some countries are recognized to have a crucial role in the geopolitics of hydrogen as importers, consumers and exporters. According to the European Hydrogen Backbone Initiative, Italy would be part of one of the 5 corridors that will shape the European hydrogen market. However, the set targets are very ambitious and require large investments to rapidly develop effective hydrogen policies: in this regard, scenario analysis is becoming increasingly important to support energy planning, and energy system optimization models appear to be suitable tools to quantitively carry on that kind of analysis. The work aims to assess the competitiveness of hydrogen in contributing to the Italian energy security in the coming years, under different price and import conditions, using the energy system model TEMOA-Italy. A wide spectrum of hydrogen technologies is included in the analysis, covering the production, storage, delivery, and end-uses stages. National production from fossil fuels with and without CCS, as well as electrolysis and import of low-carbon hydrogen from North Africa, are the supply solutions that would compete with other ones, such as natural gas, biomethane and electricity value chains, to satisfy sectoral energy needs (transport, industry, buildings, agriculture). Scenario analysis is then used to study the competition under different price and import conditions. The use of TEMOA-Italy allows the work to catch the interaction between the economy and technological detail, which is much needed in the energy policies assessment, while the transparency of the analysis and of the results is ensured by the full accessibility of the TEMOA open-source modeling framework.

Keywords: energy security, energy system optimization models, hydrogen, natural gas, open-source modeling, scenario analysis, TEMOA

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Authors: Ira Joseph

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The LNG paradox addresses the issue of how the most expensive form of gas supply, which is LNG, will grow in an end user market where demand is most competitive, which is power generation. In this case, LNG demand growth is under siege from two entirely different directions. At one end is price; it will be extremely difficult for gas to replace coal in Asia due to the low price of coal and the age of the generation plants. Asia's coal fleet, on average, is less than two decades old and will need significant financial incentives to retire before its state lifespan. While gas would cut emissions in half relative to coal, it would also more than double the price of the fuel source for power generation, which puts it in a precarious position. In most countries in Asia other than China, this cost increase, particularly from imports, is simply not realistic when it is also necessary to focus on economic growth and social welfare. On the other end, renewables are growing at an exponential rate for three reasons. One is that prices are dropping. Two is that policy incentives are driving deployment, and three is that China is forcing renewables infrastructure into the market to take a political seat at the global energy table with Saudi Arabia, the US, and Russia. Plus, more renewables will lower import growth of oil and gas in China, if not end it altogether. Renewables are the predator at the gate of gas demand in power generation and in every year that passes, renewables cut into demand growth projections for gas; in particular, the type of gas that is most expensive, which is LNG. Gas does have a role in the future, particularly within a domestic market. Once it crosses borders in the form of LNG or even pipeline gas, it quickly becomes a premium fuel and must be marketed and used this way. Our research shows that gas will be able to compete with batteries as an intermittency and storage tool and does offer a method to harmonize with renewables as part of the energy transition. As a baseload fuel, however, the role of gas, particularly, will be limited by cost once it needs to cross a border. Gas converted into blue or green hydrogen or ammonia is also an option for storage depending on the location. While this role is much reduced from the primary baseload role that gas once aspired to land, it still offers a credible option for decades to come.

Keywords: natural gas, LNG, demand, price, intermittency, storage, renewables

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Authors: M. Zake, I. Barmina, R. Valdmanis, A. Kolmickovs

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Experimental investigations of the DC electric field effect on thermal decomposition of biomass, formation of the axial flow of volatiles (CO, H2, CxHy), mixing of volatiles with swirling airflow at low swirl intensity (S ≈ 0.2-0.35), their ignition and on formation of combustion dynamics are carried out with the aim to understand the mechanism of electric field influence on biomass gasification, combustion of volatiles and heat energy production. The DC electric field effect on combustion dynamics was studied by varying the positive bias voltage of the central electrode from 0.6 kV to 3 kV, whereas the ion current was limited to 2 mA. The results of experimental investigations confirm the field-enhanced biomass gasification with enhanced release of volatiles and the development of endothermic processes at the primary stage of thermochemical conversion of biomass determining the field-enhanced heat energy consumption with the correlating decrease of the flame temperature and heat energy production at this stage of flame formation. Further, the field-enhanced radial expansion of the flame reaction zone correlates with a more complete combustion of volatiles increasing the combustion efficiency by 3 % and decreasing the mass fraction of CO, H2 and CxHy in the products, whereas by 10 % increases the average volume fraction of CO2 and the heat energy production downstream the combustor increases by 5-10 %

Keywords: biomass, combustion, electrodynamic control, gasification

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Authors: Elvira S. Castillo, Surupa Shaw

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This paper delves into the uncharted territories of innovative applications of applied fluid mechanics in sustainable energy. By exploring the intersection of fluid mechanics principles with renewable energy technologies, the study uncovers untapped potential and novel solutions. Through theoretical analyses, the research investigates how fluid dynamics can be strategically leveraged to enhance the efficiency and sustainability of renewable energy systems. The findings contribute to expanding the discourse on sustainable energy by presenting innovative perspectives and practical insights. This paper serves as a guide for future research endeavors and offers valuable insights for implementing advanced methodologies and technologies to address global energy challenges.

Keywords: fluid mechanics, sustainable energy, sustainble practices, renewable energy

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Authors: Faisal Algosair

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We examine the role of monetary policy in the presence of commodity price shocks using a Dynamic stochastic general equilibrium (DSGE) model with price and wage rigidities. The model characterizes a commodity exporter by its degree of export diversification, and explores the following monetary regimes: flexible domestic inflation targeting; flexible Consumer Price Index inflation targeting; exchange rate peg; and optimal rule. An increase in the degree of diversification is found to mitigate responses to commodity shocks. The welfare comparison suggests that a flexible exchange rate regime under the optimal rule is preferred to an exchange rate peg. However, monetary policy provides limited stabilization effects in an economy with low degree of export diversification.

Keywords: business cycle, commodity price, exchange rate, global financial cycle

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Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

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In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: equivalent martingale measure, European put option, girsanov theorem, martingales, monte carlo method, option price valuation formula

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Authors: Saeidreza Radpour, Md. Ahiduzzaman, Amit Kumar

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Alberta’s mining sector consumed 871.3 PJ in 2012, which is 67.1% of the energy consumed in the industry sector and about 40% of all the energy consumed in the province of Alberta. Natural gas, petroleum products, and electricity supplied 55.9%, 20.8%, and 7.7%, respectively, of the total energy use in this sector. Oil sands mining and upgrading to crude oil make up most of the mining energy sector activities in Alberta. Crude oil is produced from the oil sands either by in situ methods or by the mining and extraction of bitumen from oil sands ore. In this research, the factors affecting oil sands production have been assessed and a framework has been developed for market penetration of new efficient technologies in this sector. Oil sands production amount is a complex function of many different factors, broadly categorized into technical, economic, political, and global clusters. The results of developed and implemented statistical analysis in this research show that the importance of key factors affecting on oil sands production in Alberta is ranked as: Global energy consumption (94% consistency), Global crude oil price (86% consistency), and Crude oil export (80% consistency). A framework for modeling oil sands energy technologies’ market penetration (OSETMP) has been developed to cover related technical, economic and environmental factors in this sector. It has been assumed that the impact of political and social constraints is reflected in the model by changes of global oil price or crude oil price in Canada. The market share of novel in situ mining technologies with low energy and water use are assessed and calculated in the market penetration framework include: 1) Partial upgrading, 2) Liquid addition to steam to enhance recovery (LASER), 3) Solvent-assisted process (SAP), also called solvent-cyclic steam-assisted gravity drainage (SC-SAGD), 4) Cyclic solvent, 5) Heated solvent, 6) Wedge well, 7) Enhanced modified steam and Gas push (emsagp), 8) Electro-thermal dynamic stripping process (ET-DSP), 9) Harris electro-magnetic heating applications (EMHA), 10) Paraffin froth separation. The results of the study will show the penetration profile of these technologies over a long term planning horizon.

Keywords: appliances efficiency improvement, diffusion models, market penetration, residential sector

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Authors: Hy Dang, Bo Mei

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The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: classification, machine learning, time representation, stock prediction

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Authors: Mahmood Khalghollah, Mohammad Tavallaeinejad, Mohammad Eghtesad

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The method of Controlled Lagrangian is an energy shaping control technique for under actuated Lagrangian systems. Energy shaping control design methods are appealing as they retain the underlying nonlinear dynamics and can provide stability results that hold over larger domain than can be obtained using linear design and analysis. In the present study, controlled lagrangian is employed for designing a controller in an under actuated rotating flexible plate system. In the system of rotating flexible plate, due to its nonlinear characteristics and coupled dynamics of rigid and flexible components, controller design is a known challenge. In this paper, controller objectives are considered to be vibration reduction of flexible component and position control of the tip of the plate. To achieve the goals, a method based on both kinetic and potential energy shaping is introduced. The stability of the closed-loop system is investigated and proved around its equilibrium points. Moreover, the proposed controller is shown to be robust against disturbance and plant uncertainties.

Keywords: controlled lagrangian, underactuated system, flexible rotating plate, disturbance

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Authors: Arjmand Khaliq, Pemra Sohaib

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There is increasing trend of use of smart devices in the present age. The growth of computing techniques and advancement in hardware has also brought the use of sensors and smart devices to a high degree during the course of time. So use of smart devices for control, management communication and optimization has become very popular. This paper gives proposed methodology which involves sensing and switching unite for load, two way communications between utility company and smart phones of consumers using cellular techniques and price signaling resulting active participation of user in energy management .The goal of this proposed control methodology is active participation of user in energy management with accommodation of renewable energy resource. This will provide load adjustment according to consumer’s choice, increased security and reliability for consumer, switching of load according to consumer need and monitoring and management of energy.

Keywords: cellular networks, energy management, renewable energy source, smart grid technology

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Authors: Takashi Shimizu, Tomoaki Hashimoto

Abstract:

Recently, crystal growth technologies have made progress by the requirement for the high quality of crystal materials. To control the crystal growth dynamics actively by external forces is useuful for reducing composition non-uniformity. In this study, a control method based on model predictive control using thermal inputs is proposed for crystal growth dynamics of semiconductor materials. The control system of crystal growth dynamics considered here is governed by the continuity, momentum, energy, and mass transport equations. To establish the control method for such thermal fluid systems, we adopt model predictive control known as a kind of optimal feedback control in which the control performance over a finite future is optimized with a performance index that has a moving initial time and terminal time. The objective of this study is to establish a model predictive control method for crystal growth dynamics of semiconductor materials.

Keywords: model predictive control, optimal control, process control, crystal growth

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