Browsing by Subject "Monte Carlo simulation"

Now showing 1 - 5 of 5

Open Access
Benefits of forecasting and energy storage in isolated grids with large wind penetration – The case of Sao Vicente
(Elsevier, 2017) Yuan, S.; Kocaman, A.S.; Modi, V.
For electric grids that rely primarily on liquid fuel based power generation for energy provision, e.g. one or more diesel gensets, measures to allow a larger fraction of intermittent sources can pay-off since the displaced is high cost diesel powered generation. This paper presents a case study of Sao Vicente, located in Cape Verde where a particularly high fraction of wind capacity of 5.950ï¿½MW (75% of the average demand) is installed, with diesel gensets forming the dispatchable source of power. This high penetration of intermittent power is managed through conservative forecasting and curtailments. Two potential approaches to reduce curtailments are examined in this paper: 1) an improved wind speed forecasting using a rolling horizon ARIMA model; and 2) energy storage. This case study shows that combining renewable energy forecasting and energy storage is a promising solution which enhances diesel fuel savings as well as enables the isolated grid to further increase the annual renewable energy penetration from the current 30.4% up to 38% while reducing grid unreliability. In general, since renewable energy forecasting ensures more accurate scheduling and energy storage absorbs scheduling error, this solution is applicable to any small size isolated power grid with large renewable energy penetration.
Open Access
A Monte Carlo study of Maxwell’s demon coupled to finite quantum heat baths
(2020-08) Güler, Umutcan
When Maxwell’s demon was introduced, it raised the question: Is there a way to decrease an isolated system’s entropy, even though it was forbidden by the second law of thermodynamics. Then, a new idea which considered information as a physical entity was emerged, and an equivalence between information entropy and thermodynamic entropy was suggested. Under the light of new understandings, the original question modified into "Is there a way to decrease thermodynamic entropy of a system by using information entropy?" This work aims to demonstrate such a machinery is possible to exist in real world. Building on the model of Mandal et al. [1], it inquires whether if such a system is possible to build in nano scales. According to the theoretical relations, the correspondences between internal energy and effective temperature of finite fermionic and bosonic gases for varying number of particles and volumes were tabulated. Subsequently, a series of Monte Carlo simulations were executed under different circumstances. The outcomes of the simulations illustrate that production of information entropy can be used to compensate the decrease of thermodynamic entropy. The results indicate that using either one of the quantum gases as a finite quantum heat bath does affect the efficiency of the refrigerator. Based on this, using fermionic gas is superior to bosonic gas in terms of swiftness of the refrigeration, if all other variables are identical. Further research is needed to analyze the behaviour of the finite quantum heat baths at extremely low temperatures.
Open Access
Multi-criteria analysis using latent class cluster ranking: An investigation into corporate resiliency
(Elsevier, 2014) Mistry, J.; Sarkis, J.; Dhavale, D. G.
In this paper, we introduce a multi-stage multiple criteria latent class model within a Bayesian framework that can be used to evaluate and rank-order objects based on multiple performance criteria. The latent variable extraction in our methodology relies on Bayesian analysis and Monte Carlo simulation, which uses a Gibbs sampler. Ranking of clusters of objects is completed using the extracted latent variables. We apply the methodology to evaluate the resiliency of e-commerce companies using balanced scorecard performance dimensions. Cross-validation of the latent class model confirms a superior fit for classifying the e-commerce companies. Specifically, using the methodology we determine the ability of different perspectives of the balanced scorecard method to predict the continued viability and eventual survival of e-commerce companies. The novel methodology may also be useful for performance evaluation and decision making in other contexts. In general, this methodology is useful where a ranking of elements within a set, based on multiple objectives, is desired. A significant advantage of this methodology is that it develops weighting scheme for the multiple objective based on intrinsic characteristics of the set with minimal subjective input from decision makers. © 2013 Elsevier B.V.
Open Access
Statistical arbitrage in jump-diffusion models with compound poisson processes
(Springer Nature, 2021-02-26) Akyildirim, E.; Fabozzi, J.F.; Goncu, A.; Sensoy, Ahmet
We prove the existence of statistical arbitrage opportunities for jump-diffusion models of stock prices when the jump-size distribution is assumed to have finite moments. We show that to obtain statistical arbitrage, the risky asset holding must go to zero in time. Existence of statistical arbitrage is demonstrated via ‘buy-and-hold until barrier’ and ‘short until barrier’ strategies with both single and double barrier. In order to exploit statistical arbitrage opportunities, the investor needs to have a good approximation of the physical probability measure and the drift of the stochastic process for a given asset.
Open Access
Statistical arbitrage: factor investing approach
(Springer Science and Business Media Deutschland GmbH, 2023-09-16) Akyıldırım, E.; Goncu, A.; Hekimoğlu, A.; Nguyen, D. K.; Şensoy, Ahmet
We introduce a continuous time model for stock prices in a general factor representation with the noise driven by a geometric Brownian motion process. We derive the theoretical hitting probability distribution for the long-until-barrier strategies and the conditions for statistical arbitrage. We optimize our statistical arbitrage strategies with respect to the expected discounted returns and the Sharpe ratio. Bootstrapping results show that the theoretical hitting probability distribution is a realistic representation of the empirical hitting probabilities. We test the empirical performance of the long-until-barrier strategies using US equities and demonstrate that our trading rules can generate statistical arbitrage profits. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.