The forecasted residential load of a smart grid system under time of usepricing (TOU) is taken in the present study . The revenue under TOU pricing was very high when fed with utility grid and the system becomes very expensive for residential customers. The hourly load of a day is taken as input data to HOMER Software and the same load is assumed throughout the year. The day to day load variation is assumed as 10 percent and seasonal variation is 20 percent. The graphical representation daily load variation and monthly load profile by HOMER is shown in Fig. 3.
Elect ricit y dem and traditionally exhibit s a subst antial peak during a sm all num ber of hours each day. Policym akers are aw are of t he pot ential efficiency savings t hat m ay be generat ed from a shift in energy consum ption aw ay from peak t im es. Sm art m eters, in conjunct ion w it h t im e-of-use (TOU) pricing, can facilit ate an im provem ent in energy efficiency by providing consum ers wit h enhanced inform at ion about electricit y consum ption and cost s, and t hereby encourage a shift aw ay from consum ption during peak hours. In 2009-10, t he Irish Commission for Energy Regulation (CER) co-ordinat ed a random ised cont rolled t rial in t he Irish residential elect ricity m arket . Sm art m et ers, w hich replaced t he exist ing mechanical m eter readers, w ere int roduced in approxim at ely 5,000 households. Part icipants w ere divided int o cont rol and treatm ent groups, w it h t reat ment groups exposed t o a variet y of TOU t ariffs and inform ation st im uli (in-hom e display (IHD) unit s, m ont hly billing, et c.). Dat a w as collect ed over approxim ately 18 m ont hs, w it h t he first half year being used as a cont rol period. This paper analyses t he response of Irish households t o t he introduction of TOU t ariffs and inform ation st im uli. We examine how households responded t o t he different TOU t ariffs, at different tim es of t he day (peak, day and night) and in conjunct ion w it h different inform at ion st imuli. Finally, w e examine t he variation in our result s across households of differing socio-econom ic st at us (as proxied by educat ion levels). We find t hat TOU t ariffs and inform at ion st imuli have a significant effect in reducing electricit y consum ption in Ireland, part icularly during peak hours. However, w hile households reduce peak dem and significant ly aft er t he int roduct ion of TOU t ariffs and associated inform at ion, there is lit tle increm ent al response t o increasing differentials bet w een peak and off-peak prices.
Another phenomenon adding to the congestion levels is the increasing price of property in Dublin city which is encouraging long distance commuting. Road usepricing is one of the measures that has recently been the subject of a scoping study (Oscar Faber, Goodbody, TCD and TORG, 1999) to establish its potential in addressing the likely shortfall between transport demand and supply in the short to medium term. Another project, entitled EUROPRICE, funded by EU DGXVII, the aim of which was to examine the potential user response to distance and time based pricing in Dublin, has recently been completed and forms the subject of this paper. Both projects have raised the profile of restrictive transport demand management measures on the transport agenda in Dublin.
Link cruise times are made up of free flow times on links plus the delays on those links. Analysing the link cruise times in FIGURES 2 and 3, there is very little change running through from that of the initial level output for the base test, Test 1, and levels output after the cordon has been applied in Tests 2 through 5. This is found for all of the test runs within the simulation network (see FIGURE 3 where results for the total time simulated are graphed). For the complete network, presented in FIGURES 4 and 5, there is a sharp drop in the pcu.hrs followed by a smaller, but consistent, drop as the elasticity is increased, proceeding from Test 2 to 5. This suggests that although the over capacity queues are decreasing throughout the complete network, the simulation network is remaining congested due to demand, while the buffer network is becoming the beneficiary of a decrease in delays.
For application we extend the canonical polynomial representation analy- sis to a Wold decomposition of call option prices. There, we show how a GARCH(1,1) model can be used to construct an empirical pricing kernel for call option by a signal extraction procedure for unobservable pricing kernel. To the best of our knowledge that procedure is new. However, (Chernov, 2003, pp. 332-333) also assumed an unobservable pricing kernel but used a two stage estimation proce- dure that involves first stage estimation of parameters from a continuous time as- set pricing model. At the second stage, he used an equivalent martingale measure, that includes parameters from the first stage asset pricing model, together with the asset(s) payoff to construct the pricing kernel. He then used a derivative pricing relation that includes parameters of the underlying asset pricing model ion order to derive “independent” equations. Whereupon, “simultaneous equations” are solved to infer the pricing kernel in second stage estimation. Our “two stage” procedure is distinguished because we calibrate second stage residuals from a discrete risk pricing model for the underlying asset under consideration, after a first stage Wold decomposition of a call option on the asset.
Results: Compared with NEO, SUG group showed shorter times to achieve train-of-four ratio of 0.9 (P<0.05) and an Aldrete score of 10 (P<0.05), a higher cost (€146.7 vs €3.6 [P<0.05]), plus a remarkable less duration of operating theater occupancy (P< 0.05). Sugammadex cost accounted for 2.58% of the total cost per surgery, while neostigmine cost accounted for 0.06%. Total time saved in SUG group was 19.4 hours, which could be used to perform 12 extra lapa- roscopic sleeve gastrectomies.
Credit default swaps (CDS), collateralized debt obligations (CDO), synthetic collat- eralized debt obligations (synthetic CDO) and standardized synthetic CDO indexes are the main products on the credit derivative market. The credit default swap is similar as the “plain vanilla” interest rate swap that is the most common type of swap. A swap is an agreement between two companies to exchange cash flows in the future. In the interest rate swap, a company agrees to pay the cash flows equal to the interest at a predetermined fixed rate on a notional principal for a number of years. In return, it receives interest at a floating rate on the same notional principal for the same period of time. The floating rate in many interest rate swap agreements is the LIBOR (London Interbank Offer Rate). For a floating-rate bond, interest is usually set at the beginning of the period to which it will apply and is paid at the end of the period. Analogously a credit default swap is a contract where one party makes advance or periodical payments to get a contingent payment from the other party, given a predefined credit event occurs within a period of time. It is used to transfer the credit risk from one party to the other. It is easy to understand the mechanics of the CDS from Figure 1.3.
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only one of the best tools to achieve demand side management in Electricity Industries for. The selection then the implementation of the appropriate dynamic pricing scheme is required for proper enhancement of the consumers electrical load profile as required by demand side management systems. This paper highlights how can we design and implement of IoT based energy efficient system using dynamic tariff schemes. This design can be innovate the pattern of energy consumption by the different categories of the consumers as per the rate of tariff vary according to the variation in load on the system. The consumers of electricity can be plan for their consumption according to essential use of electricity and non- essential use of electricity as per the dynamic tariff. Indirectly consumer of electricity can be scheduled their consumption to get benefits by optimum utilization of electricity as per tariff changes or vary. This proposed system can be contribute to increase the load factor of the power system during off peak period by encouraging the consumers of electricity with the help of providing variation of rate charged to the consumers, this will results in the production cost of electricity per unit will be reduced. It will beneficial to both side’s consumers as well as suppliers. This system provides monitoring facility to consumers to acquire knowledge of their consumption which will be helpful to plan their utilization of home appliance or domestic load.
As for the comparison between the proposed strategy of dynamic pricing and that of fixed-price, which would correspond to selling at the initial price the expected sales ratio of the initial inventory, simulations confirm that for most choices of parameter pairs, the amount sold and the revenue earned is improved. The graphs below correspond to the multiple case with two classes of products for sale and different selling periods, the initial in- ventory (seats) is x = 100 , in both cases, the number of sales periods is 10 in the first case, and 12 in the second. In both cases, the initial price is p 0 es 40€, the price range is [ 20,50 and the sets of weights used are ]
Dynamic pricing models in revenue management lack the ability to have mul- tiple firms selling multiple product classes. In this thesis, a framework is created that allows for the construction of revenue management models with multiple firms, each selling multiple product types and where the firms have the ability to alter their prices instantly based on market conditions. The framework is a finite repeated game, where the optimal price for each state can be calculated through backwards induction. Conditions for existence of pure strategy Nash Equilibria are proven and conditions for unique pure strategy Nash Equilibria are discussed. We illustrate the pricing dynamics in a 2x1 and a 2x3 model. We recreate the well-known Netessine and Shumsky airline duopoly model but allow the firms to use dynamic pricing rather than booking limits. We find that in all cases the revenues from a dynamic pricing approach exceed those from booking limits. Through the use of three examples we show that our model provides vastly increased revenues over traditional models as it considers cross-price elasticities and how firms should alter their prices in response to the quantity levels of all products in the market.
In the real tem perature data the amount by which tem perature drops (cold front) and rises (warm front) would vary depending on the time of the yeax. In order to account for these behaviour patterns the function T ($ (t) , t), which is given by the equation 24, is introduced into the weather like process. It is the amplitude of fronts and it changes for different time periods in the generated winter and summer months. T (4> (t) , t) is illus trated in figure 19 and is a function of time and the phase of the year. The parameters of the chosen functional form for this amplitude were roughly based on the amplitudes of fronts observed in the the Berlin data. Again, it is im portant to note th a t the ‘weather like’ process is constructed as a test data set, rather than a realistic model. For th a t reason, the 20th % percentile of the actual front amplitudes, observed in the Berlin d ata was chosen to represent the maximum amplitude of generated fronts. This allows us to generate ‘dram atic’ drops/rises th a t are not too unrealistic compared to the actual data.
In complete, frictionless capital markets with no transaction costs and where the underlying securities follow geometric Brownian motions, the Black-Scholes framework  provides an elegant and tractable solution for pricing and hedging derivative securities, typically vanilla calls and puts. Unfortunately, actual financial markets are far more complex and empirical testing of the Black- Scholes model has highlighted its many shortcomings. Indeed, it is well docu- mented    that the observed properties of financial time series are not consistent with its underlying assumptions. Time-varying volatility, the presence How to cite this paper: Rémillard, B.,
Age-specific mortality rates are often disaggregated by different attributes, such as sex, state, ethnic group and socioeconomic status. In making social policies and pricing annuities at national and sub-national levels, not only is it important to forecast mortality accurately, but also, forecasts at sub-national levels should add up to the forecasts at the national level. This motivates recent developments of grouped functional time series methods (Shang, Han and Rob Hyndman., 2017) to reconcile age-specific mortality forecasts. We extend these grouped functional time series forecasting methods to multivariate time series and apply them to produce point forecasts of mortality rates at older ages, from which fixed-term annuities for different ages and maturities can be priced. Using the regional age-specific mortality rates in Japan obtained from the Japanese Mortality Database, we investigate the one-step-ahead to 15-step-ahead point forecast accuracy between the independent and grouped forecasting methods. The grouped forecasting methods are shown not only to be useful for reconciling forecasts of age-specific mortality rates at national and sub-national levels, but also to enjoy improved forecast accuracy. The improved forecast accuracy of mortality rates would be of great interest to the insurance and pension industries for estimating annuity prices, in particular at the level of population subgroups defined by key factors such as gender, region and socioeconomic grouping.
In this paper we have developed an inventory model with time dependent deterioration rate, shortage allowed with partial backlogging presuming trapezoidal type demand function with infinite replenishment. Three phases of trapezoidal demand function has been adopted with three different price and time dependent demand functions. During shortage, number of customer decrease as waiting time increases. Graphical analysis approach used to show concavity of profit function with respect to decision variables. Trapezoidal type demand function consists with three stages, in first stage demand increases then it reached to saturation in second stage in last demand rate decreases. This demand pattern is commonly observed in fruits, vegetables, sea foods items etc. Such model was firstly studied by  and  who proposed an Inventory model where deterioration rate is time dependent, with trapezoidal type demand and partial backlogging is allowed in the model.
Abstract: Many toll facilities have been faced with traffic shortfalls due to inaccurate and over-forecasted toll revenue projections. Therefore calculating optimal toll rates can be a difficult process. Toll rates are often set to reflect the revenue needed to pay back bonds issued to finance the roadway. This research provides an alternative approach to calculating toll rates where revenue can be maximized while still considering the socio-demographics of the region. Several different approaches used in the border region were explored and compared to field data on an existing toll facility in El Paso, Texas. An innovative simulation-based modeling approach was used to test both static and dynamic pricing algorithms. Static tolling results showed optimal toll rates of $0.14/mile and $0.08/mile for Border Highway West in the westbound and eastbound directions respectively. The Cesar Chavez Highway has optimal toll rates of $0.12 and $0.10/mile in the west and eastbound directions. The dynamic tolling approach showed a max toll rate of $1.56/mile for Cesar Chavez Highway (westbound) during the morning peak period and then incrementally decreased to the minimum toll rate. However, the eastbound direction never increased above the minimum toll rate of $0.08 mile. Border Highway West never increased above the minimum toll rate in either direction. The dynamic tolling algorithm prediction is more representative of the optimal tolling rates for the border region-with the exception of Cesar Chavez Highway westbound.
more to invest in an otherwise inaccessible market, raising the share price of the fund. In an era of liberalised markets, we suggest that an information hypothesis is more relevant, where investors respond negatively to information about increases in market inaccessibility. In this paper our contribution is to bring together both the topics of market integration and segmentation and closed-end fund pricing to examine the effect of time-varying direct and indirect investment barriers on the pricing of UK closed-end country funds in emerging markets. 2 We argue that closed-
Competitive behavior between players in a mature market can have a different structure than those in growing markets. Pricing component of the marketing mix is less relied upon to expand market share in growing markets, while there is a greater reliance upon product differentiation and building stronger brand equity. On the other hand, in mature markets, there is usually very little scope for product differentiation, so there is a greater reliance on pricing for competitive gains. Since market share expansion in a mature market comes directly from competitive sales declines, pricing strategy changes in one brand leads to a fairly