Academic literature on the topic 'Emissions trading Mathematical models'
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Journal articles on the topic "Emissions trading Mathematical models"
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Qiu, Xiao Ming, and Jia Sheng Yang. "Emissions Trading System and Supporting Policies under an Emissions Reduction Framework." Advanced Materials Research 518-523 (May 2012): 4863–68. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.4863.
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This paper, through building mathematical models, makes an analysis on the emissions trading system under an abatement framework. And the authors obtained four conclusions: (1) The impact by environmental taxes on the existing firms’ choices of optimal discharging amounts is uncertain, the existing firms’ discharging amounts will be on the decrease with the increased prices of emissions permits, and paid initial emissions allowances will reduce the existing firms’ profits; (2) Under an intertemporal trading system, the existing firms’ holding the permits conforms to the principle of profit maximization; (3) Under the intertemporal trading system, the prices for emissions permits for the entrant firms are always on the rise and so are their access costs into the industries, thus frustrating local governments’ efforts in attracting investments; and (4) Emissions reduction policies are good regulatory instruments for promoting local economic welfare and realizing sustainable development. The paper also gives some suggestions for triggering and activating the emissions trading system and formulating supportive policies.
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Pasicko, Robert, Slavica Robic, and Zeljko Tomsic. "Modelling CO2 emissions impacts on Croatian power system." Thermal Science 14, no. 3 (2010): 655–69. http://dx.doi.org/10.2298/tsci1003655p.
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Today?s electrical energy landscape is characterized by new challenges such as deregulation, liberalization of energy markets, increased competition, growing demands on security of supply, price insecurities, and demand to cut CO2 emissions. All mentioned challenges are calling for consideration of various options (like nuclear, coal, gas or renewable scenarios) and for better understanding of energy systems modelling in order to optimize proper energy mix. Existing models are not sufficient any more and planners will need to think differently in order to face these challenges. European emission trading scheme (EU ETS) started in 2005 and it has great influence on power system short term and long term planning. Croatia is obliged to establish a national scheme for trading of greenhouse gas emission allowances from the year 2010, which will be focused on monitoring and reporting only until accession to EU when it will be linked with EU ETS. Thus, for Croatian power system it is very important to analyze possible impacts of CO2 emissions. Analysis presented in this paper was done by two different models: mathematical model, based on short run marginal costs (SRMC, relevant for fuel switch in existing power plant and merit order change) and long run marginal costs (LRMC, relevant for new investment decisions); and electricity market simulation model PLEXOS, which was used for modelling Croatian power system during development of the Croatian energy strategy in 2008. Results of the analysis show important impacts that emission trading has on Croatian power system, such as influence of emission price rise on price of electricity and on emission quantity, and changes in power plants output that appear with emission price rise. Breakeven point after which gas power plant becomes more competitive than coal is 62 ?/tCO2 for SRMC and 40 ?/tCO2 for LRMC. With CO2 prices above 31 ?/tCO2 wind is more competitive than gas or coal, which emphasizes importance that emission price has on competitiveness of renewables.
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Tsai, Wen-Hsien. "Carbon Taxes and Carbon Right Costs Analysis for the Tire Industry." Energies 11, no. 8 (August 14, 2018): 2121. http://dx.doi.org/10.3390/en11082121.
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As enterprises are the major perpetrators of global climate change, concerns about global warming, climate change, and global greenhouse gas emissions continue to attract attention, and have become international concerns. The tire industry, which is a high-pollution, high-carbon emission industry, is facing pressure to reduce its carbon emissions. Thus, carbon prices and carbon trading have become issues of global importance. In order to solve this environmental problem, the purpose of this paper is to combine mathematical programming, Theory of Constraints (TOC), and Activity-Based Costing (ABC) to formulate the green production decision model with carbon taxes and carbon right costs, in order to achieve the optimal product mix decision under various constraints. This study proposes three different scenario models with carbon taxes and carbon right used to evaluate the effect on profit of changes in carbon tax rates.
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André, Francisco J., and Luis Miguel de Castro. "Market Power in Output and Emissions Trading." Games 11, no. 4 (October 12, 2020): 43. http://dx.doi.org/10.3390/g11040043.
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This article focuses on the strategic behavior of firms in the output and the emissions markets in the presence of market power. We consider the existence of a dominant firm in the permit market and different structures in the output market, including Cournot and two versions of the Stackelberg model, depending on whether the permit dominant firm is a leader or a follower in the output market. In all three models, the firm that dominates the permit market is more sensitive to its initial allocation than its competitor in terms of abatement and less sensitive in terms of output. In all three models, output is decreasing and the permit price is increasing in the permit dominant firm’s initial allocation. In the Cournot model, permit dominance is fruitless in terms of output and profit if the initial allocation is symmetric. Output leadership is more relevant than permit dominance since an output leader always tends to, ceteris paribus, produce more and make more profit whether it also dominates the permit market or not. This leadership can only be overcompensated for by distributing a larger share of permits to the output follower, and only if the total number of permits is large enough. In terms of welfare, Stackelberg is always superior to Cournot. If the initial permit allocation is symmetric, welfare is higher when the same firm dominates the output and the permit market at the same time.
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Lucas, D. D., C. Yver Kwok, P. Cameron-Smith, H. Graven, D. Bergmann, T. P. Guilderson, R. Weiss, and R. Keeling. "Designing optimal greenhouse gas observing networks that consider performance and cost." Geoscientific Instrumentation, Methods and Data Systems 4, no. 1 (June 16, 2015): 121–37. http://dx.doi.org/10.5194/gi-4-121-2015.
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Abstract. Emission rates of greenhouse gases (GHGs) entering into the atmosphere can be inferred using mathematical inverse approaches that combine observations from a network of stations with forward atmospheric transport models. Some locations for collecting observations are better than others for constraining GHG emissions through the inversion, but the best locations for the inversion may be inaccessible or limited by economic and other non-scientific factors. We present a method to design an optimal GHG observing network in the presence of multiple objectives that may be in conflict with each other. As a demonstration, we use our method to design a prototype network of six stations to monitor summertime emissions in California of the potent GHG 1,1,1,2-tetrafluoroethane (CH2FCF3, HFC-134a). We use a multiobjective genetic algorithm to evolve network configurations that seek to jointly maximize the scientific accuracy of the inferred HFC-134a emissions and minimize the associated costs of making the measurements. The genetic algorithm effectively determines a set of "optimal" observing networks for HFC-134a that satisfy both objectives (i.e., the Pareto frontier). The Pareto frontier is convex, and clearly shows the tradeoffs between performance and cost, and the diminishing returns in trading one for the other. Without difficulty, our method can be extended to design optimal networks to monitor two or more GHGs with different emissions patterns, or to incorporate other objectives and constraints that are important in the practical design of atmospheric monitoring networks.
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Lucas, D. D., C. Yver Kwok, P. Cameron-Smith, H. Graven, D. Bergmann, T. P. Guilderson, R. Weiss, and R. Keeling. "Designing optimal greenhouse gas observing networks that consider performance and cost." Geoscientific Instrumentation, Methods and Data Systems Discussions 4, no. 2 (December 23, 2014): 705–49. http://dx.doi.org/10.5194/gid-4-705-2014.
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Abstract. Emission rates of greenhouse gases (GHGs) entering into the atmosphere can be inferred using mathematical inverse approaches that combine observations from a network of stations with forward atmospheric transport models. Some locations for collecting observations are better than others for constraining GHG emissions through the inversion, but the best locations for the inversion may be inaccessible or limited by economic and other non-scientific factors. We present a method to design an optimal GHG observing network in the presence of multiple objectives that may be in conflict with each other. As a demonstration, we use our method to design a prototype network of six stations to monitor summertime emissions in California of the potent GHG 1,1,1,2-tetrafluoroethane (CH2FCF3, HFC-134a). We use a multiobjective genetic algorithm to evolve network configurations that seek to jointly maximize the scientific accuracy of the inferred HFC-134a emissions and minimize the associated costs of making the measurements. The genetic algorithm effectively determines a set of "optimal" observing networks for HFC-134a that satisfy both objectives (i.e., the Pareto frontier). The Pareto frontier is convex, and clearly shows the tradeoffs between performance and cost, and the diminishing returns in trading one for the other. Without difficulty, our method can be extended to design optimal networks to monitor two or more GHGs with different emissions patterns, or to incorporate other objectives and constraints that are important in the practical design of atmospheric monitoring networks.
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Weiss, Ray F., and Ronald G. Prinn. "Quantifying greenhouse-gas emissions from atmospheric measurements: a critical reality check for climate legislation." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 369, no. 1943 (May 28, 2011): 1925–42. http://dx.doi.org/10.1098/rsta.2011.0006.
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Emissions reduction legislation relies upon ‘bottom-up’ accounting of industrial and biogenic greenhouse-gas (GHG) emissions at their sources. Yet, even for relatively well-constrained industrial GHGs, global emissions based on ‘top-down’ methods that use atmospheric measurements often agree poorly with the reported bottom-up emissions. For emissions reduction legislation to be effective, it is essential that these discrepancies be resolved. Because emissions are regulated nationally or regionally, not globally, top-down estimates must also be determined at these scales. High-frequency atmospheric GHG measurements at well-chosen station locations record ‘pollution events’ above the background values that result from regional emissions. By combining such measurements with inverse methods and atmospheric transport and chemistry models, it is possible to map and quantify regional emissions. Even with the sparse current network of measurement stations and current inverse-modelling techniques, it is possible to rival the accuracies of regional ‘bottom-up’ emission estimates for some GHGs. But meeting the verification goals of emissions reduction legislation will require major increases in the density and types of atmospheric observations, as well as expanded inverse-modelling capabilities. The cost of this effort would be minor when compared with current investments in carbon-equivalent trading, and would reduce the volatility of that market and increase investment in emissions reduction.
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Han, Qiang, Zhenlong Yang, Zheng Zhang, and Liang Shen. "Offline and Online Channel Selection of Low-Carbon Supply Chain under Carbon Trading Market." Mathematical Problems in Engineering 2021 (January 4, 2021): 1–17. http://dx.doi.org/10.1155/2021/6627937.
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This paper investigates the low-carbon product manufacturer’s different decision behavior in the offline traditional retail channel and online e-commerce channel when the carbon trading market has been established. The low-carbon product manufacturer is both in the carbon trading market and product market. In the former market, the manufacturer can gain profits by selling its emission quota. In the latter market, the manufacturer has two sales channel options, the traditional offline retailer and the online e-commerce platform. These two channels make two supply chains, the manufacturer-led offline one and the e-commerce platform-led online one. This paper combines the carbon trading market with the product market, formulates different Stackelberg game models, compares the manufacturer’s decision under two channels and the impact of channels on the carbon emission, does sensitivity analysis, and verifies the conclusions with numerical examples. Our findings are (1) the establishment of the carbon market will help the manufacturer reduce its carbon emission, especially for those sensitive to the carbon price and those with too much emissions; (2) whether the manufacturer turns to the online channel depends on the consumers’ sensitivity to the sales service, and consumers’ attention will guide the way to the online mode; (3) which mode is conducive to carbon emission reduction relies on the product type: the e-commerce platform does well for daily necessities of mass production while the traditional channel is better for experience goods.
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Helena Božić. "THE PURPOSES AND METHODS OF ENERGY SYSTEM MODELING." Journal of Energy - Energija 55, no. 5 (January 20, 2023): 530–49. http://dx.doi.org/10.37798/2006555398.
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This article describes the purpose of energy system modeling and the classification of planning models according to approaches and methodologies. The advent of modern computers and computer programs has simplified the use of planning models. Such models employ powerful mathematical algorithms and databases which can solve highly complex problems in a relatively short time. This has led to energy-ecology-economy (E3) models, which are simultaneously able to consider questions in connection with energy supply, ecology and economics. The characteristics of a MARKAL model are presented separately through an example of integration with other planning models. It is demonstrated that the application of an optimizing MARKAL model for the planning of the energy supply system of the Republic of Croatia is of great significance for the analysis of the energy market of South Eastern Europe, the use of renewable energy sources, energy efficiency and emission trading.
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Wang, Xiaoya. "The impact of China's entry into the carbon trading market on European carbon prices." BCP Business & Management 34 (December 14, 2022): 1542–50. http://dx.doi.org/10.54691/bcpbm.v34i.3210.
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As the world's largest greenhouse gas emission country, the success or failure of the Chinese national carbon emissions trading market will largely determine climate change’s further development. Chinese national carbon market, which was opened on July 16, 2021, will also exert spillover effects on carbon trading markets in other countries, including the European carbon emissions trading market, which will have a more significant impact. This paper uses the double difference model(DID), sets the price of European certification emission reduction(CER) as the dependent variable, and takes China's entering into the carbon emissions trading market and the RMB exchange rate as the independent variable to test the influences of China's entering in the carbon emissions trading market on the European CER price. After that, non-linear machine learning models such as support vector machines are used to fit and predict the price of European CER, which further verifies that the opening of the Chinese national carbon emissions trading market contributes to a decline in European CER price.
Dissertations / Theses on the topic "Emissions trading Mathematical models"
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Aiyegbusi, Olufemi. "The Alberta carbon market : an exploration of alternative policy options through agent-based modeling." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Management, c2012, 2012. http://hdl.handle.net/10133/3434.
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Our study examines some design alternatives for a carbon market by exploring the fledgling Alberta carbon market. We attempt to evaluate the performance of these designs on the bases of trade volume, cost efficiency and stability. To achieve this we construct an empirically-calibrated but simple agent-based model, certain aspects of which we selectively modify to incorporate various design options. We make comparisons among these options based on data simulated from the ensuing family of models.
We find strong evidence that in general, market design features such as source-of-credits, the scale of the market, and pricing-mechanism are very important considerations that influence the performance of the market. In addition, we find support for the notion that the level of the price cap relative to the average cost of abatement in the market matters, and beyond a threshold, higher price caps are associated with lower levels of performance.vii, 155 leaves ; 29 cm
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Luo, Yan, and 罗妍. "Three essays on noise and institutional trading." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B44549246.
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Song, Na, and 宋娜. "Mathematical models and numerical algorithms for option pricing and optimal trading." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hub.hku.hk/bib/B50662168.
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Research conducted in mathematical finance focuses on the quantitative modeling of financial markets. It allows one to solve financial problems by using mathematical methods and provides understanding and prediction of the complicated financial behaviors. In this thesis, efforts are devoted to derive and extend stochastic optimization models in financial economics and establish practical algorithms for representing and solving problems in mathematical finance.
An option gives the holder the right, but not the obligation, to buy or sell an underlying asset at a specified strike price on or before a specified date. In this thesis, a valuation model for a perpetual convertible bond is developed when the price dynamics of the underlying share are governed by Markovian regime-switching models. By making use of the relationship between the convertible bond and an American option, the valuation of a perpetual convertible bond can be transformed into an optimal stopping problem. A novel approach is also proposed to discuss an optimal inventory level of a retail product from a real option perspective in this thesis. The expected present value of the net profit from selling the product which is the objective function of the optimal inventory problem can be given by the actuarial value of a real option. Hence, option pricing techniques are adopted to solve the optimal inventory problem in this thesis.
The goal of risk management is to eliminate or minimize the level of risk associated with a business operation. In the risk measurement literature, there is relatively little amount of work focusing on the risk measurement and management of interest rate instruments. This thesis concerns about building a risk measurement framework based on some modern risk measures, such as Value-at-Risk (VaR) and Expected Shortfall (ES), for describing and quantifying the risk of interest rate sensitive instruments. From the lessons of the recent financial turmoils, it is understood that maximizing profits is not the only objective that needs to be taken into account. The consideration for risk control is of primal importance. Hence, an optimal submission problem of bid and ask quotes in the presence of risk constraints is studied in this thesis. The optimal submission problem of bid and ask quotes is formulated as a stochastic optimal control problem.
Portfolio management is a professional management of various securities and assets in order to match investment objectives and balance risk against performance. Different choices of time series models for asset price may lead to different portfolio management strategies. In this thesis, a discrete-time dynamic programming approach which is flexible enough to deal with the optimal asset allocation problem under a general stochastic dynamical system is explored. It’s also interesting to analyze the implications of the heteroscedastic effect described by a continuous-time stochastic volatility model for evaluating risk of a cash management problem. In this thesis, a continuous-time dynamic programming approach is employed to investigate the cash management problem under stochastic volatility model and constant volatility model respectively.published_or_final_version
Mathematics
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Doctor of Philosophy
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Kaharabata, Samuel K. "Non-disturbing methods of estimating trace gas emissions from agricultural and forest sources." Thesis, McGill University, 1999. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=35903.
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Two approaches, one using an atmospheric diffusion model and the other an atmospheric tracer, were used to predict the source strength of trace gases from observations of the downwind concentration field. Both approaches do not disturb the prevailing environmental and physical conditions nor the existing biogenic processes. An analytical solution to the advection-diffusion equation was used to back-calculate the source strength from the downwind concentration measurements of (i) single and multipoint (4 and 16 points) trace gas (sulphur hexafluoride (SF6) and methane (CH4)) release experiments conducted over microplots over an open field, and (ii) single point source SF6 release experiments conducted over a forested terrain. Best predictions of the source strength (to within +/-20%) were obtained from concentration observations made along the centreline of the diffusing plumes with the predictions improving when observations at the mean plume height were used. The diffusion model was then used to compute footprint estimates for neutral and unstable conditions, for tower and aircraft based observation platforms above the forest. They showed spatially constrained footprints in the surface layer, due to effective vertical coupling, so that observations from towers and low flying aircraft must be expected to be very site specific, and scaling up to larger areas will have to be done with careful consideration of surface mosaics. Above-canopy sampling of trace gases to determine volatile organic compound emissions were then interpreted in terms of footprint considerations. This was accomplished by defining the upwind canopy areas effectively sampled under the given wind and stability conditions. The analysis demonstrated, for example, that the variability observed in measured isoprene fluxes could be accounted for by varying numbers of randomly distributed clumps of emitter species within a varying footprint. It suggested that heterogeneity of the forest canopy, in terSulphur hexafluoride was also used as an atmospheric tracer in order to estimate CH4 emissions from manure slurry and cattle housed in barns and feedlots. (Abstract shortened by UMI.)
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Rouah, Fabrice. "Essays on hedge funds, operational risk, and commodity trading advisors." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103290.
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Hedge funds report performance information voluntarily. When they stop reporting they are transferred from the "live" pool of funds to the "defunct" pool. Consequently, liquidated funds constitute a subset of the defunct pool. I present models of hedge fund survival, attrition, and survivorship bias based on liquidation alone. This refines estimates of predictor variables in models of survival, leads to attrition rates of hedge funds to be roughly one half those previously thought, and produces larger estimates of survivorship bias. Survival models based on liquidated funds only, lead to an increase in survival time of 50 to 100 percent relative to survival based on all defunct funds.In addition to refining estimates of survival time, it is useful to examine how the double fee structure of hedge funds and Commodity Trading Advisors (CTA) affects the incentives of their managers. Young CTAs are usually very small --- they hold few financial assets --- and may not meet their operating expenses with their management fee alone, so their incentive is to take on risk and post good returns. As they grow, their incentive to take on risk diminishes. CTAs in their fifth year diminish their volatility by 25 percent relative to their first year, and diminish returns by 70 percent. We find CTAs to behave more like indexers as they grow, concerned with more with capital preservation than asset management.
Operational risk is a major cause of hedge fund and CTA liquidation. In the banking industry, regulators have called upon institutions to develop models for measuring capital charge for operational losses, and to subject these models to stress testing. Losses are found to be inversely related to GDP growth, and positively related to unemployment. Since losses are thus cyclical, one way to stress test models is to calculate capital charge during good and bad economic regimes. We find loss distributions to have thicker tails during bad regimes. One implication is that banks will likely need to increase their capital charge when economic conditions deteriorate.
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Cheng, Xixin, and 程細辛. "Mixture time series models and their applications in volatility estimation and statistical arbitrage trading." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B40988053.
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Yuan, Jiangchuan. "Risk diversification framework in algorithmic trading." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51905.
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We propose a systematic framework for designing adaptive trading strategies that minimize both the mean and the variance of the execution costs. This is achieved by diversifying risk over sequential decisions in discrete time. By incorporating previous trading performance as a state variable, the framework can dynamically adjust the risk-aversion level for future trading. This incorporation also allows the framework to solve the mean-variance problems for different risk aversion factors all at once. After developing this framework, it is then applied to solve three algorithmic trading problems. The first two are trade scheduling problems, which address how to split a large order into sequential small orders in order to best approximate a target price – in our case, either the arrival price, or the Volume-Weighed-Average-Price (VWAP). The third problem is one of optimal execution of the resulting small orders by submitting market and limit orders. Unlike the tradition in both academia and industry of treating the scheduling and order placement problems separately, our approach treats them together and solves them simultaneously. In out-of-sample tests, this unified strategy consistently outperforms strategies that treat the two problems separately.
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Wang, Hanfeng, and 王漢鋒. "Essays on stock trading volume, volatility and information." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B38826185.
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Wu, Ching-Tang. "Construction of Brownian Motions in Enlarged Filtrations and Their Role in Mathematical Models of Insider Trading." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 1999. http://dx.doi.org/10.18452/14364.
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In dieser Arbeit untersuchen wir die Struktur von Gausschen Prozessen, die durch gewisse lineare Transformationen von zwei Gausschen Martingalen erzeugt werden. Die Klasse dieser Transformationen ist durch nanzmathematische Gleichgewichtsmodelle mit heterogener Information motiviert. In Kapital 2 bestimmen wir für solche Prozesse, die zunächst in einer erweiterten Filtrierung konstruiert werden, die kanonische Zerlegung als Semimartin-gale in ihrer eigenen Filtrierung. Die resultierende Drift wird durch Volterra-Kerne beschrieben. Insbesondere charakterisieren wir diejenigen Prozesse, die in ihrer eigenen Filtrierung eine Brownsche Bewegung bilden. In Kapital 3 konstruieren wir neue orthogonale Zerlegungen der Brownschen Filtrierungen. In den Kapitaln 4 bis 6 wenden wir unsere Resultate zur Charakterisierung Brownscher Bewegungen im Kontext nanzmathematischer Modelle an, in denen es Marktteilnehmer mit zusätzlicher Insider-Information gibt. Wir untersuchen Erweiterungen eines Gleichgewichtsmodells von Kyle [42] und Back [7], in denen die Insider-Information in verschiedener Weise durch Gaussche Martingale spezifiziert wird. Insbesondere klären wir die Struktur von Insider-Strategien, die insofern unaufallig bleiben, als sich die resultierende Gesamtnachfrage wie eine Brownsche Bewegung verhält.In this thesis, we study Gaussian processes generated by certain linear transformations of two Gaussian martingales. This class of transformations is motivated by nancial equilibrium models with heterogeneous information. In Chapter 2 we derive the canonical decomposition of such processes, which are constructed in an enlarged ltration, as semimartingales in their own ltration. The resulting drift is described in terms of Volterra kernels. In particular we characterize those processes which are Brownian motions in their own ltration. In Chapter 3 we construct new orthogonal decompositions of Brownian ltrations. In Chapters 4 to 6 we are concerned with applications of our characterization results in the context of mathematical models of insider trading. We analyze extensions of the nancial equilibrium model of Kyle [42] and Back [7] where the Gaussian martingale describing the insider information is specified in various ways. In particular we discuss the structure of insider strategies which remain inconspicuous in the sense that the resulting cumulative demand is again a Brownian motion.
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O'Beirne, Greg A. "Mathematical modelling and electrophysiological monitoring of the regulation of cochlear amplification." University of Western Australia. School of Biomedical and Chemical Sciences, 2005. http://theses.library.uwa.edu.au/adt-WU2006.0115.
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[Truncated abstract] The cochlea presumably possesses a number of regulatory mechanisms to maintain cochlear sensitivity in the face of disturbances to its function. Evidence for such mechanisms can be found in the time-course of the recovery of CAP thresholds during experimental manipulations, and in observations of slow oscillations in cochlear micromechanics following exposure to low-frequency tones (the “bounce phenomenon”) and other perturbations. To increase our understanding of these oscillatory processes within the cochlea, and OHCs in particular, investigations into cochlear regulation were carried out using a combination of mathematical modelling of the ionic and mechanical interactions likely to exist within the OHCs, and electrophysiological experiments conducted in guinea pigs. The electrophysiological experiments consisted of electrocochleographic recordings and, in some cases, measurement of otoacoustic emissions, during a variety of experimental perturbations, including the application of force to the cochlear wall, exposure to very-low-frequency tones, injection of direct current into scala tympani, and intracochlear perfusions of artificial perilymph containing altered concentrations of potassium, sodium, and sucrose. To obtain a panoramic view of cochlear regulation under these conditions, software was written to enable the interleaved and near-simultaneous measurement of multiple indicators of cochlear function, including the compound action potential (CAP) threshold, amplitude and waveshape at multiple frequencies, the OHC transfer curves derived from low-frequency cochlear microphonic (CM) waveforms, distortion-product otoacoustic emissions (DPOAEs), the spectrum of the round-window neural noise (SNN), and the endocochlear potential (EP). ... The mathematical model we have developed provided a physiologically-plausible and internally-consistent explanation for the time-courses of the cochlear changes observed during a number of different perturbations. We show that much of the oscillatory behaviour within the cochlea is consistent with underlying oscillations in cytosolic calcium concentration. We conclude that a number of the discrepancies between the simulation results and the experimental data can be resolved if the cytosolic calcium functions as two distinct pools: one which controls basolateral permeability and one which controls slow motility. This two-calcium-pool model is discussed.
Books on the topic "Emissions trading Mathematical models"
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Maeda, Akira. Haishutsuken seido no keizai riron =: The economics of emissions trading. Tōkyō: Iwanami Shoten, 2009.
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Dobos, Imre. Szennyezési jogok hatása a vállalati termelési stratégiára. Budapest, Hungary: Budapesti Közgazdaságtudomanyi és Államigazgatási Egyetem, Vállalatgazdaságtan tanszék, 2002.
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Christian, Dunis, Laws Jason, and Naïm Patrick, eds. Applied quantitative methods for trading and investment. Chichester: Wiley, 2003.
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Tatsuyoshi, Saijō, ed. Haishutsuken torihiki: Riron to jikken ni yoru seido sekkei. Tōkyō: Keiō Gijuku Daigaku Shuppankai, 2013.
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Gaming the market: Applying game theory to create winning trading strategies. New York: Wiley, 1997.
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Rubinstein, Ariel. Decentralized trading, strategic behavior and the Walrasian outcome. Stanford, Calif: Institute for Mathematical Studies in the Social Sciences, Stanford University, 1986.
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Rubinstein, Ariel. Decentralized trading, strategic behavior and the Walrasian outcome. London: International Centre for Economics and Related Disciplines, 1987.
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Fell, John P. C. Technical trading rules and exchange rate volatility. Dublin: Research Department, Central Bank of Ireland, 1994.
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D, Feustel Elihu, ed. Conquering fantasy football: Drafting and trading to victory. Notre Dame, Ind: Academic Publications, 2011.
Find full textBook chapters on the topic "Emissions trading Mathematical models"
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Mutanov, Galimkair. "Currency Trading Methods and Mathematical Models." In Mathematical Methods and Models in Economic Planning, Management and Budgeting, 99–130. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-45142-7_4.
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Kohatsu-Higa, Arturo. "Models for Insider Trading with Finite Utility." In Paris-Princeton Lectures on Mathematical Finance 2004, 103–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73327-0_3.
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Nidhi M. B. and V. Madhusudanan Pillai. "Supply Chain Modelling Under Carbon Trading." In Emerging Applications in Supply Chains for Sustainable Business Development, 282–99. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5424-0.ch016.
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In the recent decades, carbon footprint assessment of an activity has been emerging as a major research area. The carbon trading called “CAP and TRADE system” is evolved out of the Kyoto Protocol and emission trading schemes and is experimented across countries to encourage organizations to control emission. The region or country fixes the CAP which is the limit for emissions emitted by an organization. This chapter depicts the performance evaluation of a supply chain under the carbon cap and trade scheme. A mathematical model is proposed which considers carbon emissions as a result of supply chain operation, carbon trading among members of the supply chain, and carbon trading with members of outside supply chain. A mixed integer linear programming (MILP) model is proposed for the performance evaluation of a forward supply chain having 4 stages. The analysis shows that carbon trading allows economic benefits as well as environmental benefits.
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"Chapter 7 Active Aerosol Emissions." In Mathematical Models in Environmental Problems, 154–64. Elsevier, 1986. http://dx.doi.org/10.1016/s0168-2024(08)70242-x.
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"Chapter 6 Mathematical Problems of Optimizing Emissions from Operating Industrial Plants." In Mathematical Models in Environmental Problems, 145–54. Elsevier, 1986. http://dx.doi.org/10.1016/s0168-2024(08)70241-8.
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Davis, Mark H. A. "4. Interest rates." In Mathematical Finance: A Very Short Introduction, 61–75. Oxford University Press, 2019. http://dx.doi.org/10.1093/actrade/9780198787945.003.0004.
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In ordinary life, there are many different interest rates—mortgage rates, rates on credit cards, and rates paid by savings accounts—which are mirrored in the commercial world by loans for short-term funding and longer term loans for business development and project finance. The reasons for so many different rates are market conditions and credit risk. ‘Interest rates’ discusses the trading of interest rates, focusing on the interbank market, which is the area where most trading takes place, most quant effort is deployed and in whose development mathematical finance has played a key role. The basic terminology—including zero coupon bonds, swap rate, yield curve generator, LIBOR rates, and whole yield models—are explained.
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Viadrova, Inna, and Irina Bitner. "MODERN METHODS OF THE BANK`S INVESTMENT DEVELOPMENT BASED ON THE PAIR TRADING MODELS." In Priority areas for development of scientific research: domestic and foreign experience. Publishing House “Baltija Publishing”, 2021. http://dx.doi.org/10.30525/978-9934-26-049-0-5.
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The article deals with the problem of analysis of banking activity and modern methods of investment development of the bank based on pairs trading models. The essence of the pair trading method as one of the most popular and qualitative methods of investment paper quality analysis is disclosed. The basis of the pairing trading method is defined as the beta-neutral portfolio strategy, which consists of creating a portfolio with a beta coefficient equal to zero, and the main advantage of which is the complete independence of the final paper yield from the market yield, it is only dependent on the future ratio of the value of one security to another. For the successful introduction of this method in banking activity, a clear algorithm for the construction of a paired trading model based on economic-mathematical methods and models is proposed. The proposed algorithm contains three stages in which the following steps are to be taken: analysis and selection of securities; development of a pairing trading model; development and regulation of the selected strategy. The implementation of the proposed algorithm begins with the selection of statistical data on the prices of securities, provides for the verification of data on stationarity, as well as the identification of a system for combining series, and the analysis of coefficients of the matching between prices of securities. As a result of the steps taken, pairs of securities are selected that are more closely related and a full economic analysis of the pairs is made, and the parameters of co-integration equations to pairs of paper are selected, evaluated and analyzed then the errors of the co-integration model are checked for stationary. In the work models of pairs trading are constructed for the realization of an aggressive strategy of trade spreads. In order to build an effective strategy for pairing trading, data on prices of securities, which are the most attractive to Ukrainian banks, namely, US Treasury bonds, have been examined. The hypothesis being tested in the paper is that it is necessary to identify a pair of securities with a sufficiently strong dependency where one should have a rapid growth or decline relative to the other, after which the sale of the revalued security and the purchase of the undervalued security is mandatory. The study found that for each pair of Treasury bonds, the ratio was satisfactory. This indicates that the resultant securities pairs are suitable as an investment that, with a well-designed strategy, will allow the bank to obtain optimum returns. The final step of the algorithm is the analysis of the results obtained, which includes a comprehensive analysis of the conducted research and effective decision-making. The application of the proposed algorithm will allow banks to make informed decisions on the choice and regulation of the strategy in exchange market changes in order to obtain a low level of risk and a high level of profit.
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Tura, Nina, Aino Kuitunen, Lauri Lättilä, and Samuli Kortelainen. "Increased Value Through Sharing in Multi-Sided Markets." In Green Business, 907–24. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7915-1.ch044.
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The demand for more sustainable business models is increasing the need for current businesses to develop their business processes and value creation mechanisms. One way to improve sustainability is sharing resources and services in a new sharing economy paradigm. This chapter builds a conceptual model for taxi ridesharing to describe the value potential that is born by increasing the efficiency of taxi businesses. First, a framework for multisided markets is built to understand the different value elements of taxi ridesharing. Then, a conceptual mathematical model is introduced to understand the value symmetries including the cost saving potential and allocation from the perspectives of the customer and the supplier. The model shows that it is possible to have a system that creates value for both the taxi driver and the passenger, while simultaneously leading to significant reduction in CO2 emissions.
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Burlaka, Serhiy, and Natalia Telekalo. "MODERNIZATION OF THE POWER SUPPLY SYSTEM OF A DIESEL POWER PLANT." In Modernization of research area: national prospects and European practices. Publishing House “Baltija Publishing”, 2022. http://dx.doi.org/10.30525/978-9934-26-221-0-10.
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The research is devoted to solving important tasks of interdisciplinary research work on the topic: «Development of scientific and technical support for energy autonomy of the agro-industrial complex based on environmentally efficient use of agrobiomass for biofuel production», state registration number 0122U000844, implementation of which is planned for 2022–2024 at the expense of the state budget of Ukraine.This paper considers topical scientific and technical issues of improving the efficiency of machine units when working with mixed fuels. One of the most promising alternative fuels is biofuels, the use of which will reduce the consumption of petroleum fuels and reduce corrosion emissions into the atmosphere.A review of the literature sources of modern power systems and equipment using biofuels and their mixtures, the impact of fuel mixtures on engine operation and analysis of mathematical models for calculation by the methods of Lyshevsky O. S. and clarification of prof. Razleytseva M. F.An improved diesel engine power system has been developed, which electronically controls the composition of the dosed fuel mixture, a mixer for mixed fuel supply to the machine unit has been developed, the operation of the machine-tractor unit (MAT) model has been confirmed, and AIT physical and mathematical models have been developed. A method for calculating the continuity of the working fluid flow in the characteristic areas of modern power supply systems has been developed. The geometric parameters of the Savonius rotor of the developed mixer are calculated and optimized to the most appropriate design solution.The aim of the study is to increase the efficiency of biofuel use in diesel power plants by improving the fuel system of the fuel mixer.Research methods include theoretical and experimental studies of the process of obtaining and supplying biofuels using a mixing device, comparative studies of diesel power plant in bench conditions and operating conditions on this fuel using modern technical measuring instruments and methods of processing these data on personal computers using standard application packages Compass, FlowVision.
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Crouch, Dora P. "Introduction." In Geology and Settlement. Oxford University Press, 2004. http://dx.doi.org/10.1093/oso/9780195083248.003.0006.
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Cities are a constant interplay between tangible and intangible, visible and invisible factors. Long-lived cities can provide data to compensate for the brevity of our modern urban experience (Croce 1985). To overcome these gaps in research, just beginning to close, the city is a most useful unit of study. Ancient cities can serve as four-dimensional models (length, width, height, and time) of how humans survived in their ecological niches. Yet comparative studies of groups of cities—such as Rorig’s (1967) of German medieval trading cities of the Hanseatic League, Andrews’s (1975) of the urban design history of Maya cities, and Hohenberg and Lee’s (1985) of the economic history of European cities—ignore the geological setting. The setting of our study is the Mediterranean periphery where cities are united by their Greco-Roman historical and cultural relationships. From the twenty-five Greco-Roman sites studied in Water Management in Ancient Greek Cities, we have selected for further study 10 sites with sufficient geological information to form a basis of comparison. Our comparisons are based on the physical aspects—both form and function—of the local area, not the particular object. There are exciting possibilities, both intellectual and practical, in such an approach. Until recently, ancient Mediterranean cities have been investigated mainly by ancient historians and classical archaeologists. Cities, however, are so complex as to require every possible sort of investigation. Because each model and methodology leaves out too much, the use of a single model from one discipline, whether archaeological, mathematical, engineering, or historic, has limited usefulness. The documents of the classicists and the physical remains located by archaeologists seem to an urban historian like myself to be useful but incomplete sources that take for granted the geographical base, assume a past social organization, and may ignore the technological and scientific aspects of ancient urban life. As classicist M. H. Jameson (1990) has written, “The surviving literature from Classical Greece sheds light only incidentally on practical matters such as patterns of settlement and domestic architecture . . . [yet] conceptions drawn from literature, sometimes with dubious justification, continue to prevail.”
Conference papers on the topic "Emissions trading Mathematical models"
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Cheng, Frank, Yagil Engel, and Michael P. Wellman. "Cap-and-Trade Emissions Regulation: A Strategic Analysis." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/27.
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Cap-and-trade schemes are designed to achieve target levels of regulated emissions in a socially efficient manner. These schemes work by issuing regulatory credits and allowing firms to buy and sell them according to their relative compliance costs. Analyzing the efficacy of such schemes in concentrated industries is complicated by the strategic interactions among firms producing heterogeneous products. We tackle this complexity via an agent-based microeconomic model of the US market for personal vehicles. We calculate Nash equilibria among credits-trading strategies in a variety of scenarios and regulatory models. We find that while cap-and-trade results improves efficiency overall, consumers bear a disproportionate share of regulation cost, as firms use credit trading to segment the vehicle market. Credits trading volume decreases when firms behave more strategically, which weakens the segmentation effect.
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Karunarathne, Sumudu, Jeanette Larsen, and Lars Erik Øi. "Mathematical Models for Physicochemical Properties of Different Amine-based Solvents in Post combustion CO2 Capture." In 63rd International Conference of Scandinavian Simulation Society, SIMS 2022, Trondheim, Norway, September 20-21, 2022. Linköping University Electronic Press, 2022. http://dx.doi.org/10.3384/ecp192021.
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In order to reduce global CO2 emissions, CO2 capture based on absorption in an amine/water mixture is an established method. To develop such processes, correct physicochemical properties like densities and viscosities are important.The first objective of this work is to explore mathematical correlations for fitting viscosity data for aqueous Monoethanolamine (MEA) and Methyldiethanolamine (MDEA). A second objective is to evaluate the prediction of viscosity based on parameters independent of viscosity measurements.13 developed correlations have been evaluated by comparing the maximum deviation of fitted models to the measured property, and by determining the average absolute relative deviation (AARD%). Python 3.6, MATLAB R2020b and Excel were used as the tools for regression.The results indicated that viscosity for aqueous amines was better correlated by Eyring’s viscosity model based on NRTL (Non-Random-Two Liquid model) rather than a Redlich-Kister correlation. The achieved AARD% of aqueous MEA were 2.39 for Redlich-Kister, 1.87 for Eyring-NRTL and 1.88 for the segment-based Eyring-NRTL model. The same trend was achieved for aqueous MDEA with AARD% of 3.04, 2.23 and 1.88 for different approaches.The possibility of using data from vapor/liquid equilibrium parameters to predict viscosity in MEA/water and MDEA/water was evaluated. Using parameters in the equilibrium model NRTL from the simulation program Aspen HYSYS in a model from Karunarathne indicated that it is possible to predict viscosity reasonably well without experimental viscosity data.
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Antoniou, Antonios, Cesar Celis, and Arturo Berastain. "A Mathematical Model to Predict Alkaline Electrolyzer Performance Based on Basic Physical Principles and Previous Models Reported in Literature." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-68815.
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Abstract Hydrogen production through electrolysis is an important research topic since the use of hydrogen as a fuel has the potential to significantly reduce gaseous emissions in near future. The electrolytic splitting of water into hydrogen and oxygen can be carried out using for instance electricity generated from renewable energy sources such as solar radiation. Electrolysis processes occurring in electrolyzer cells are complex phenomena and a clear and accurate mathematical representation of the referred processes is vital to accurate predict electrolyzer cells performance. So a comprehensive mathematical model capable of properly describing alkaline electrolyzer cells performance, in terms of efficiency and hydrogen production rate, is proposed in this work. The mathematical model is based on several physical concepts such as energy losses due to electron and ion transfer, entropy increase, electrolyte flow rate, and electrolyzer physical structure and construction material. Compared to existing models, the new proposed one is more complete as it includes more operational parameters (six) affecting cells performance. Once developed, the proposed model has been fine-tuned using experimental data available in literature. The results obtained using the new developed model are in good agreement with Ulleberg’s experimental data. Based on the work carried out here, it is concluded that developing a mathematical model based on physical principles is crucial in the comprehension of electrolysis related processes and how to utilize them in the simplest and most reliable way.
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LaViolette, Marc, and Michael Strawson. "On the Prediction of Nitrogen Oxides From Gas Turbine Combustion Chambers Using Neural Networks." In ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-50566.
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This paper describes a method of predicting the oxides of nitrogen emissions from gas turbine combustion chambers using neural networks. A short review of existing empirical models is undertaken and the reasoning behind the choice of correlation variables and mathematical formulations is presented. This review showed that the mathematical functions obtained from the underlying theory used to develop the semi-empirical model ultimately limit their general applicability. Under these conditions, obtaining a semi-empirical model with a large domain and good accuracy is difficult. An overview of the use of neural networks as a modelling tool is given. Using over 2000 data points, a neural network that can predict NOx emissions with greater accuracy than published correlations was developed. The coefficients of determination of the prediction for the previous published semi-empirical models are 0.8048 and 0.7885. However one tends to grossly overpredict and the other underpredict. The coefficient of determination is 0.8697 for the model using a neural network. Because of the nature of neural networks, this more accurate model does not allow better insight into the physical and chemical phenomena. It is however, a useful tool for the initial design of combustion chambers.
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Gulin, S. V., and A. G. Pirkin. "FEATURES OF BUSINESS-PROCESSES IN THE CREATION OF ELECTROTECHNOLOGICAL SYSTEMS FOR THE AGRICULTURAL INDUSTRIAL COMPLEX." In INNOVATIVE TECHNOLOGIES IN SCIENCE AND EDUCATION. DSTU-Print, 2020. http://dx.doi.org/10.23947/itno.2020.357-362.
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This article offers a universal methodology for the design, creation and operation of complex electrotechnological systems. This methodology is based on a system-process approach to business modeling. The article provides a detailed description of all private business processes that provide a full cycle of business engineering, and offers a General mathematical expression for a comprehensive assessment of the effectiveness of the business engineering process. The proposed methodology has been tested on the example of designing, creating and operating vegetation climate systems (VCS). This example shows that it is possible to conduct quite serious scientific research at the intersection of plant physiology and electric power engineering, which allows us to create modern self-adjusting systems for automatic microclimate control when growing plants. Application of engineering methods allows to increase the efficiency of development of information systems for automatic control of parameters of the most important physiological processes (photosynthesis, transpiration, etc.) in plants under the influence of environmental factors. The article outlines the prospects for the development of the subject area of engineering in the direction of solving specific problems to integrated energy engineering, and the energy business - from trading individual services to trading models and technologies.
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Di, Lei, Gaurav Manish Shah, Yiran Yang, and Cuicui Wei. "Greenhouse Gas Emission Analysis of Integrated Production-Inventory-Transportation Supply Chain Enabled by Additive Manufacturing." In ASME 2021 16th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/msec2021-63822.
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Abstract The manufacturing industry is a major source of greenhouse gas emissions (GHG). Additive manufacturing, owing to its multiple advantages, plays a critical role in innovating the current manufacturing industry, especially from a supply chain perspective. Currently, the majority of research on GHG emissions in the manufacturing industry is focused on traditional manufacturing, either single processes in the supply chain or specific case studies, indicating the lack of models on GHG emissions in additive manufacturing-enabled supply chain structures. In this work, a mathematical model is established to estimate the GHG emissions in both traditional manufacturing and additive manufacturing-enabled supply chains. To explore the advantages of additive manufacturing in terms of fast production and reduced or even eliminated the need for assembly and labor involvement, a unique integrated production-inventory-transportation structure is investigated in additive manufacturing case studies. The results indicate that a potential reduction of 26.43% of GHG emissions can be achieved by adopting the additive manufacturing technique in the supply chain. Also, the impacts of rush order rate, emission intensity, and vehicle GHG emission constant rate on the overall GHG emissions are investigated in the sensitivity analysis. Results indicate that a 20% variation in GHG emission intensity (the amount of CO2eq emissions caused by generating a unit of electricity) can lead to a 6.26% change in the total GHG emissions in additive manufacturing.
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Borissov, Anatoli, and James J. McCoy. "Supersonic Injection of Gaseous Fuel Described as Possible Solution for NOx Emissions From Large-Bore Gas Engines." In ASME 2002 Internal Combustion Engine Division Spring Technical Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/ices2002-448.
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Both physical and mathematical models were built to describe the main processes in large-bore gas engines. Based on the detail modeling and analysis of cylinder airflow, fuel injection, mixing, combustion and NOx generation, it was possible to pinpoint the problem of abnormal NOx production, even for lean mixtures, that occurs in these engines. In addition, analysis of the experimental data of jet mixing using high-speed photographic evidence, as well as engine performance data, has helped in the understanding of the mixing process. This has resulted in the development of a new way of the mixing of fuel and air utilizing multiple-nozzle supersonic injection. The fuel injection system is designed to optimize the mixing of the methane fuel with the air in the cylinder of a large bore natural gas engine. The design goals of low-pressure (<130 psi), all-electronic valve actuation, and optimal mixing were all achieved with a unique valve/nozzle arrangement. Later, a laser induced fluorescence method was used to take high-speed photographs of the development of the fuel jet exiting the newly developed supersonic electronic fuel injector (SSEFI). This result, together with the results of numerous experimental testing of SSEFI on different engines (GMVH-6, GMW-10, V-250, UTC-165) are presented as evidence of the success of the SSEFI application for the improvement of engine performance, engine control and NOx reduction.
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Kasparinsky, Felix Osvaldovich. "Complex Indicators of the Multitrading System." In 24th Scientific Conference “Scientific Services & Internet – 2022”. Keldysh Institute of Applied Mathematics, 2022. http://dx.doi.org/10.20948/abrau-2022-14.
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The article summarizes the experience of 4 years of work on setting up the Metatrder 5 Internet terminal tools for a multitrading system, which was developed to increase the effectiveness of price change forecasts in the Forex market by applying a set of interrelated technical analysis indicators to data of different time scales (timeframes), as well as to optimization of work with a variety of financial instruments, with the simultaneous use of multiple accounts. Possible ways of integrating technical and fundamental analysis tools, advantages and disadvantages of using mathematical models to predict changes in prices of financial instruments are discussed. A unidirectional (monophasic) price change is proposed to be called the term "oscillation". To integrate classical Elliott wave models and harmonic patterns, the concept of a block consisting of 8 oscillations distributed between 2 packages has been introduced. It was found that a series of 4 blocks form modules with a variable structure. Alternative options for the distribution of block oscillations between trend and correction packages are discussed to be consistent with the Dow theory of driving factors and stages of price change. A method of target distribution of 16 technical analysis indicators of various types (oscillators, trend indicators, volume indicators) over 4 sections of the Analytical window: "Price", "Oscillation", "Trend" and "Control" is proposed. The main principle in the formation of complex indicators is the unmasking of trends of oscillating indicators by applying trend indicators to their data. The ways of setting up the technical analysis indicators involved to optimize their use as part of complex trend indicators are described in detail. Recommendations are given for determining a trading group from three adjacent Analytical windows in a 6- window Analytical display to optimally select a trading timeframe in accordance with the operational situation. Examples of using complex indicators for generating trading signals for opening and closing deals are given. The results of preliminary experiments on the use of complex indicators and Fibonacci levels to determine pivot points when building price channels are discussed. Plans have been outlined to create a unified methodology for the formation of various price channels using complex indicators, Fibonacci levels, Elliott waves and harmonic patterns.
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Chidambram, Siva Kumaran, Jin An Tan, Mohd Amaluddin Yusoff, and June Janesby Roy Jihok. "Predictive Analytics for Gas Turbine Driven Trains to Achieve Optimum Performance, Economics and Greenhouse Gas Emissions." In Offshore Technology Conference Asia. OTC, 2022. http://dx.doi.org/10.4043/31489-ms.
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Abstract The current gas turbine performance monitoring infrastructure in Shell Malaysia yields inaccuracies of ±15% with no links towards emissions and fuel economics. This has resulted in severe limitations towards the ability to improve greenhouse gas (GHG) performance and generate value. This paper describes a novel, data centric approach to derive meaningful insights and economics/carbon savings from existing data on Plant Information (PI) and SMART CONNECT, a Shell in house performance management IT tool. This project applies advanced analytics techniques based on historical data, supplemented by engineering performance models to derive robust outcomes. First, gas turbine and compressor modelling principles are programmed in Python and validated with engineering software such as UNISIM based on available operating data via PI. This yields a multivariate dataset tabulating the historical efficiency, power and fuel gas consumption of the fleet. The model is then utilized in a mathematical optimization algorithm and the optimized data used for training and validation of a Random Forest Regressor model. The performance model in Python is able to achieve accuracies of <1% absolute error when validated with UMSFM on the key performance parameters. Through parametric optimization, the Mean Squared Error (MSE) of the gas turbine and compressor powers is reduced to 0.55MW2 from its original 4.94MW2. The Heat Rate, Shaft Power, and gas generator exit pressures are also identified as the variables most correlated with efficiency. Lastly, the trained machine learning model demonstrated agreement with the dataset during testing, with a R2 value of 0.86 reflecting a strong correlation. With a predictive digital model in place, production programmers can accurately identify the key levers to optimize the machine operating point for optimum fuel gas consumption. Optimizing Gumusut Kakap's high pressure compressors can yield 62,400 USD in savings per annum from increased sales gas and and 880 tCO2e per annum of reduction in GHG emissions, for every 1% increase in efficiency. This approach is a novel concept, leveraging on expertise from both engineering and data science to enhance equipment performance, and can be replicated towards other types of equipment to achieve efficiency, economic and emissions improvements at scale.
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Reshetnikova, Liudmila G., Natalia B. Boldyreva, Anton P. Devyatkov, Mariya S. Tsyganova, and Danila V. Ovechkin. "Energy determinants of CO2 prices: results of exploratory data analysis." In Sustainable and Innovative Development in the Global Digital Age. Dela Press Publishing House, 2022. http://dx.doi.org/10.56199/dpcsebm.lysy5005.
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The key instrument for regulating the reduction of greenhouse gas (CO2) emissions is the emissions trading system (ETS), which Russia chose to create. One of the key issues for the ETS participants is the mechanism of CO2 pricing. Energy sources are the most important factors in the CO2 price. The study of the relationship between them and the CO2 price at foreign ETSs gives contradictory results. The paper investigates the relationship between energy variables and CO2 price using exploratory analysis tools as the first stage of machine learning. The univariate analysis showed that the laws of price distribution of futures contracts for CO2 and coal are further from normal in comparison with the prices of futures contracts for gas and Brent oil. Logarithmization improved the statistics of the data. Bivariate analysis showed a close relationship between the prices of CO2 and coal futures contracts. The price data for the other energy variables showed a weak to moderate relationship. Correlation analysis, taking into account the different time lags between the energy variables and CO2, indicates that it is appropriate to include past energy price information in the model. The close linear relationships of the energy variables suggest exploring opportunities to reduce the dimensionality of the data. Exploratory analysis revealed groups of data that would be appropriate to describe with different machine learning models. The presence of data groups in the resulting variable indicates the presence of other CO2 pricing factors that should be identified and taken into account in modeling.