910 resultados para Discrete time pricing model
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Nonlinear Dynamics, Vol. 29
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IEE Proceedings - Vision, Image, and Signal Processing, Vol. 147, nº 1
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The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.
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The use of renewables have been increased I several countries around the world, namely in Europe. The wind power is generally the larger renewable resource with very specific characteristics in what concerns its variability and the inherent impacts in the power systems and electricity markets operation. This paper focuses on the Portuguese context of renewables use, including wind power. The work here presented includes the use of a real time pricing methodology developed by the authors aiming the reduction of electricity consumption in the moments of unexpected low wind power. A more specific example of application of real time pricing is demonstrated for the minimization of the operation costs in a distribution network. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs.
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Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer’ loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.
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23rd International Conference on Real-Time Networks and Systems (RTNS 2015). 4 to 6, Nov, 2015, Main Track. Lille, France. Best Paper Award Nominee
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2015
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The objective of this paper is to re-examine the risk-and effort attitude in the context of strategic dynamic interactions stated as a discrete-time finite-horizon Nash game. The analysis is based on the assumption that players are endogenously risk-and effort-averse. Each player is characterized by distinct risk-and effort-aversion types that are unknown to his opponent. The goal of the game is the optimal risk-and effort-sharing between the players. It generally depends on the individual strategies adopted and, implicitly, on the the players' types or characteristics.
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In the framework of the classical compound Poisson process in collective risk theory, we study a modification of the horizontal dividend barrier strategy by introducing random observation times at which dividends can be paid and ruin can be observed. This model contains both the continuous-time and the discrete-time risk model as a limit and represents a certain type of bridge between them which still enables the explicit calculation of moments of total discounted dividend payments until ruin. Numerical illustrations for several sets of parameters are given and the effect of random observation times on the performance of the dividend strategy is studied.
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We derive an international asset pricing model that assumes local investorshave preferences of the type "keeping up with the Joneses." In aninternational setting investors compare their current wealth with that oftheir peers who live in the same country. In the process of inferring thecountry's average wealth, investors incorporate information from the domesticmarket portfolio. In equilibrium, this gives rise to a multifactor CAPMwhere, together with the world market price of risk, there existscountry-speciffic prices of risk associated with deviations from thecountry's average wealth level. The model performs signifficantly better, interms of explaining cross-section of returns, than the international CAPM.Moreover, the results are robust, both for conditional and unconditionaltests, to the inclusion of currency risk, macroeconomic sources of risk andthe Fama and French HML factor.
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The sandstone-hosted Beverley uranium deposit is located in terrestrial sediments in the Lake Frome basin in the North Flinders Ranges, South Australia. The deposit is 13 km from the U-rich Mesoproterozoic basement of the Mount Painter inlier, which is being uplifted 100 to 200 m above the basin by neotectonic activity that probably initiated in the early Pliocene. The mineralization was deposited mainly in organic matter-poor Miocene lacustrine sands and partly in the underlying reductive strata comprising organic matter-rich clays and silts. The bulk of the mineralization consists of coffinite and/or uraninite nodules, growing around Co-rich pyrite with an S isotope composition (delta S-34 = 1.0 +/- 0.3 parts per thousand), suggestive of an early diagenetic lacustrine origin. In contrast, authigenic sulfides in the bulk of the sediments have a negative S isotope signature (delta S-34 ranges from -26.2 to -35.5 parts per thousand), indicative of an origin via bacterially mediated sulfate reduction. Minor amounts of Zn-bearing native copper and native lead also support the presence of specific, reducing microenvironments in the ore zone. Small amounts of carnotite are associated with the coffinite ore and also occur beneath a paleosoil horizon overlying the uranium deposit. Provenance studies suggest that the host Miocene sediments were derived from the reworking of Early Cretaceous glacial or glaciolacustrine sediments ultimately derived from Paleozoic terranes in eastern Australia. In contrast, the overlying Pliocene strata were in part derived from the Mesoproterozoic basement inlier. Mass-balance and geochemical data confirm that granites of the Mount Painter domain were the ultimate source of U and BEE at Beverley. U-Pb dating of coffinite and carnotite suggest that the U mineralization is Pliocene (6.7-3.4 Ma). The suitability of the Beverley deposit for efficient mining via in situ leaching, and hence its economic value, are determined by the nature of the hosting sand unit, which provides the permeability and low reactivity required for high fluid flow and low chemical consumption. These favorable sedimentologic and geometrical features result from a complex conjunction of factors, including deposition in lacustrine shore environment, reworking of angular sands of glacial origin, deep Pliocene weathering, and proximity to an active fault exposing extremely U rich rocks.
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This paper assesses the empirical performance of an intertemporal option pricing model with latent variables which generalizes the Hull-White stochastic volatility formula. Using this generalized formula in an ad-hoc fashion to extract two implicit parameters and forecast next day S&P 500 option prices, we obtain similar pricing errors than with implied volatility alone as in the Hull-White case. When we specialize this model to an equilibrium recursive utility model, we show through simulations that option prices are more informative than stock prices about the structural parameters of the model. We also show that a simple method of moments with a panel of option prices provides good estimates of the parameters of the model. This lays the ground for an empirical assessment of this equilibrium model with S&P 500 option prices in terms of pricing errors.