Conditions and costs for renewables electricity grid connection: Examples in Europe

This paper compares conditions and costs for RES-E grid connection in selected European countries. These are Germany, the Netherlands, the United Kingdom, Sweden, Austria, Lithuania and Slovenia. Country specific case studies are presented for wind onshore and offshore, biomass and photovoltaic power systems, as based on literature reviews and stakeholder interviews. It is shown that, especially for wind offshore, the allocation of grid connection costs can form a significant barrier for the installation of new RES-E generation if the developer has to bear all such costs. If energy policy makers want to reduce the barriers for new large-scale RES-E deployment, then it is concluded that the grid connection costs should be covered by the respective grid operator. These costs may then be recouped by increasing consumer tariffs for the use of the grid.     

Analysis of a hydrogen station roll-out strategy to introduce hydrogen vehicles in Andalusia

The issue of the distribution of a sufficient infrastructure of hydrogen fueling stations to enable meeting of the initial demand and to satisfy the different roll-out scenarios has been addressed by different authors, in different geographies, and with different methods and approaches. In this paper, we use a spatial approach to study the prospect of a sequential roll-out strategy from the present time to 2030 for Andalusia, a region in southern Spain. In every stage, we identify main nodes and clusters by examining in which areas of this region the roll-out of fueling stations should start. Finally, we estimate the number and size of fueling stations for every stage, as well as the investment required for this infrastructure roll-out based on the estimated costs for each type of hydrogen fueling station over the aforesaid time.     

Spectral Analysis Combining a Bartlett Window With an Associated Inner Window

Usual methods of spectrum estimation allow very strong frequencies to affect the spectrum estimates at distant frequencies, because the weighting function (spectrum window) cannot be made identically zero over the rejected range of frequencies. To give bounds for this error, a pair of windows, one with positive side lobes (Bartlett), the other with negative side lobes (modified Bartlett), are used simultaneously. Thus we demonstrate the error reduction achieved by detrending and prewhitening an example economic time series. The details of the spectrum windows, and a discussion of confidence limits for the spectrum, are given in the appendix. A program for the IBM 650 is available.     

Benchmarking Current Conceptual High-Rise Design Processes

This paper presents an analysis of current conceptual design processes for high-rise buildings. We synthesize a method to document and measure these processes and use it to analyze data from several case studies and a survey of leading architectural and engineering design firms. We describe current high-rise conceptual design process in terms of the following: design team size, composition, and time investment; clarity of goal definition; number and range of design options generated; number and type of model-based analyses performed; and the criteria used for decision making. We identify several potential weaknesses in current design processes including lack of clarity in goal definition and a low quantity of generated and analyzed options. We argue that potentially higher performing designs are being left unconsidered and discuss the potential reasons and costs.     

Predicting completed project cost using bidding data

Neural network and regression models have been developed to predict the completed cost of competitively bid highway projects constructed by the New Jersey Department of Transportation. Bid information was studied for inclusion as inputs to the models. Data studied included the low bid, median bid, standard devi9 ation of the bids, expected project duration and the number of bids. A natural log transformation of the data was found to improve the linear relationship between the low bid and completed cost. The stepwise regression procedure was applied, and yielded the best performing predictive model. This regression model used only the natural log of the low bid as independent variable to predict the natural log of the completed cost. Radial basis neural networks were also constructed to predict the final cost. The best performing regres4 sion model produced superior predictions to the best performing neural network model. Hybrid models that used a regression model prediction as an input to a neural network were also studied and were found to also produce reasonable predictions. The calculated models produced good predictions of the completed project cost, but were found to be deficient in predicting very large cost increases. Simple models using the natural log of the low bid as input produced the best results. From the analysis it may be concluded that additional information about the variability of the bids submitted does not provide useful information for predicting the final project outcome.     

Chance-Constrained Time–Cost Tradeoff Analysis Considering Funding Variability

This paper proposes a chance-constrained programming model to incorporate the variability of funding, which is quantified by the coefficient of variation. The proposed model formulates financial feasibility as a stochastic constraint, transforms it into a deterministic equivalent at a prespecified confidence level, and solves the system by means of classical optimization techniques. The time–cost curve generated by the proposed model serves as a foundation for optimizing total project cost. To demonstrate the uniqueness of the proposed model, it is compared to previous approaches through a small building example.     

Derivative Asset Pricing with Transaction Costs: An Extension

This paper examines the optimal perfect hedging (super-replication) of an option by a cash-plus-riskless asset portfolio within the context of the binomial model. The cases discussed here were not covered by the earlier studies of Boyle and Vorst (1992) and Bensaid, Lesne, Pagès and Scheinkman (1992). It is argued that these cases are empirically important, and that there is some indication that they are encountered very often in practice in the Swiss options market. A new algorithm is developed to compute the option price lower bound (bid price) for such cases. It is then shown that, for most such cases, the portfolio hedging the short call when replication is not optimal coincides with the Merton (1973) lower bound.     

Remediation of RDX-Contaminated Water Using Alkaline Hydrolysis

The objective of this study was to assess the effectiveness of alkaline hydrolysis as an alternative ex situ technology for remediating groundwater contaminated with hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX). Treatment in both batch reactor and continuous stirred tank reactor (CSTR) was investigated. RDX reactivity was strongly dependent on the reaction pH investigated (11–13). The batch system achieved pseudo-first-order RDX reaction rates in the range of (0.8–27.7)×10?3?min?1, corresponding to half-life periods of 17.9?to?0.5?h, respectively. In the CSTR system operated at the initial RDX concentration of 4.5×10?3?mM, 99% RDX removal was achieved with the hydraulic retention time of 2?days and the reaction pH of 11.9. Formate and nitrite were produced as the major hydrolysates in the CSTR system, indicating a simultaneous reaction mechanism involving RDX ring cleavage and elimination of the ring nitrogen. The net OH? demand used only for RDX removal in the CSTR was found to be 1.5, 390, and 130?M OH?/M RDXremoved at pH values of 11.9, 11.5, and 11.0, respectively. A conceptual cost analysis indicated that the expense of alkaline treatment may be comparable to the expense of granular activated carbon treatment for long treatment periods (30?years or more), due to the potentially lower annual operational cost of alkali treatment.     

Adsorption of mixed polycyclic aromatic hydrocarbons in surfactant solutions by activated carbon

The adsorption behavior of three polycyclic aromatic hydrocarbons (PAH) in TX100 solution by activated carbon was studied aiming at surfactant recovery. Adsorption experiments were conducted in batch and column models. The adsorption data fitted well with the Langmuir isotherm model, Dubinin–Radushkevich isotherm models and pseudo-second-order kinetics model. Regarding column adsorption, the exhausting time of TX100 was shorter than the breakthrough time of PAH in the fixed AC column. This finding indicates the feasibility of reusing surfactants from soil-washing solutions. The total costs can reduce about $ 0.57 per 10 L washing solution with AC adsorption.     

Regional employment impact of rapidly escalating energy costs

This paper presents a methodology for incorporating price-induced technological substitution into a regional input-output forecasting model. The model was used to determine the employment impacts of rapidly escalating energy costs on the Riverside-San Bernardino (California) SMSA. The results indicate that the substitution effect between energy and other goods was dominated by the income effect. A reallocation of consumer expenditures from labour intensive to energy intensive goods occured, resulting in a two-to threefold increase in the unemployment rate among low-skilled individuals.