Power flow based monetary flow method for electricity transmission and wheeling pricing

This paper proposes a transmission and wheeling pricing method based on the monetary flow tracing along power flow paths: the monetary flow-monetary path method. Active and reactive power flows are converted into monetary flows by using nodal prices. The method introduces a uniform measurement for transmission service usages by active and reactive powers. Because monetary flows are related to the nodal prices, the impacts of generators and loads on operation constraints and the interactive impacts between active and reactive powers can be considered. Total transmission service cost is separated into more practical line-related costs and system-wide cost, and can be flexibly distributed between generators and loads. The method is able to reconcile transmission service cost fairly and to optimize transmission system operation and development. The case study on the IEEE 30 bus test system shows that the proposed pricing method is effective in creating economic signals towards the efficient use and operation of the transmission system. (c) 2005 Elsevier B.V. All rights reserved.

Dispensing activity in a community pharmacy-based repeat dispensing pilot project

Objective: To measure changes in dispensing activity in a UK repeat dispensing pilot study and to estimate any associated cost savings. Method: Patients were provided with two successive three-monthly repeat prescriptions containing all of the items on their "repeat medicines list" and valid at a study pharmacy. Pharmacists consulted with patients at the time of supply and completed a patient-monitoring form. Prescriptions with pricing data were returned by the UK Prescription Pricing Authority. These data were used to calculate dispensing activity, the cost of dispensed items and an estimate of cost savings on non-dispensed items. A retrospective identification of items prescribed during the six months prior to the project was used to provide a comparison with those dispensed during the project and thus a more realistic estimate of changes. Setting: 350 patients from two medical practices in a large English City, with inner city and suburban locations, and served by seven pharmacies. Key findings: There were methodological challenges in establishing a robust framework for calculating changes. Based on all of the items that patients could have obtained from their repeat list, 23.8% were not dispensed during the intervention period. A correction was then made to allow for a comparison with usage in the six months prior to the study. Based on the corrected data, there was an estimated 11.3% savings in drug costs compared with the pre-intervention period. There was a marked difference in changes between the two practices, the pharmacies and individual patients. The capitation-based remuneration method was acceptable to all but one of the community pharmacists. Conclusion: The repeat dispensing system reduced dispensing volume in comparison with the control period. A repeat dispensing system with a focus on patients' needs and their use of medicines might be cost neutral.

Optimising market share and profit margin:SMDP-based tariff pricing under the smart grid paradigm

Smart grid technologies have given rise to a liberalised and decentralised electricity market, enabling energy providers and retailers to have a better understanding of the demand side and its response to pricing signals. This paper puts forward a reinforcement-learning-powered tool aiding an electricity retailer to define the tariff prices it offers, in a bid to optimise its retail strategy. In a competitive market, an energy retailer aims to simultaneously increase the number of contracted customers and its profit margin. We have abstracted the problem of deciding on a tariff price as faced by a retailer, as a semi-Markov decision problem (SMDP). A hierarchical reinforcement learning approach, MaxQ value function decomposition, is applied to solve the SMDP through interactions with the market. To evaluate our trading strategy, we developed a retailer agent (termed AstonTAC) that uses the proposed SMDP framework to act in an open multi-agent simulation environment, the Power Trading Agent Competition (Power TAC). An evaluation and analysis of the 2013 Power TAC finals show that AstonTAC successfully selects sell prices that attract as many customers as necessary to maximise the profit margin. Moreover, during the competition, AstonTAC was the only retailer agent performing well across all retail market settings.

Usage-Based versus Measure-Based Unit Pricing: Is There a Better Index of Value?

In many product categories, unit prices facilitate price comparisons across brands and package sizes; this enables consumers to identify those products that provide the greatest value. However in other product categories, unit prices may be confusing. This is because there are two types of unit pricing, measure-based and usage-based. Measure-based unit prices are what the name implies; price is expressed in cents or dollars per unit of measure (e.g. ounce). Usage-based unit prices, on the other hand, are expressed in terms of cents or dollars per use (e.g., wash load or serving). The results of this study show that in two different product categories (i.e., laundry detergent and dry breakfast cereal), measure-based unit prices reduced consumers’ ability to identify higher value products, but when a usage-based unit price was provided, their ability to identify product value was increased. When provided with both a measure-based and a usage-based unit price, respondents did not perform as well as when they were provided only a usage-based unit price, additional evidence that the measure-based unit price hindered consumers’ comparisons. Finally, the presence of two potential moderators, education about the meaning of the two measures and having to rank order the options in the choice set in terms of value before choosing, did not eliminate these effects.

Pricing farm-level agricultural insurance: a Bayesian approach

This paper applies Hierarchical Bayesian Models to price farm-level yield insurance contracts. This methodology considers the temporal effect, the spatial dependence and spatio-temporal models. One of the major advantages of this framework is that an estimate of the premium rate is obtained directly from the posterior distribution. These methods were applied to a farm-level data set of soybean in the State of the Parana (Brazil), for the period between 1994 and 2003. The model selection was based on a posterior predictive criterion. This study improves considerably the estimation of the fair premium rates considering the small number of observations.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Parametric and nonparametric statistical modelling of crop yield: implications for pricing crop insurance contracts

This article considers alternative methods to calculate the fair premium rate of crop insurance contracts based on county yields. The premium rate was calculated using parametric and nonparametric approaches to estimate the conditional agricultural yield density. These methods were applied to a data set of county yield provided by the Statistical and Geography Brazilian Institute (IBGE), for the period of 1990 through 2002, for soybean, corn and wheat, in the State of Paran. In this article, we propose methodological alternatives to pricing crop insurance contracts resulting in more accurate premium rates in a situation of limited data.

A phylogeny for the genus Isoodon and a range extension for I-obesulus peninsulae based on mtDNA control region and morphology

Short-nosed bandicoots, Isoodon, have undergone marked range contractions since European colonisation of Australia and are currently divided into many subspecies, the validity of which is debated. Discriminant function analysis of morphology and a phylogeny of Isoodon based on mtDNA control region sequences indicate a clear split between two of the three recognised species, I. macrourus and I. obesulus/auratus. However, while all previously recognised taxa within the I. obesulus/auratus group are morphologically distinct, I. auratus and I. obesulus are not phylogenetically distinct for mtDNA. The genetic divergence between I. obesulus and I. auratus (2.6%) is similar to that found among geographic isolates of the former (I. o. obesulus and I. o. peninsulae: 2.7%). Further, the divergence between geographically close populations of two different species (I. o. obesulus from Western Australia and I. a. barrowensis: 1.2%) is smaller than that among subspecies within I. auratus (I. a. barrowensis and I. auratus from northern Western Australia: 1.7%). A newly discovered population of Isoodon in the Lamb Range, far north Queensland, sympatric with a population of I. m. torosus, is shown to represent a range extension of I. o. peninsulae (350 km). It seems plausible that what is currently considered as two species, I. obesulus and I. auratus, was once one continuous species now represented by isolated populations that have diverged morphologically as a consequence of adaptation to the diverse environments that occur throughout their range. The taxonomy of these populations is discussed in relation to their morphological distinctiveness and genetic similarity.

Reinfection with Schistosoma haematobium following school-based chemotherapy with praziquantel in four highly endemic villages in Côte d'Ivoire

We present the comparative evaluation of school-based chemotherapy with praziquantel on Schistosoma haematobium reinfection patterns, 6, 12, 18 and 24 months after systematic treatment of schoolchildren in four villages of south-central Côte d'Ivoire. At baseline, very high S. haematobium infection prevalences of 88–94% were found in Taabo Village, located adjacent to a large man-made lake, and in Batera and Bodo, where small dams were constructed. In Assinzé, a village with no man-made environmental alterations, the baseline infection prevalence was significantly lower (67%). The parasitological cure rate, assessed 4 weeks after praziquantel administration in the village with the highest prevalence and intensity of infection, was high (82%), and showed a clear association with infection intensity prior to treatment. Six months after chemotherapy, significant reductions in the prevalence and intensity of infection were observed in all villages. However, infection prevalence was again high in Taabo Village (63%) and in Batera (49%). Different patterns of reinfection occurred in the four villages: rapid reinfection in Taabo Village to reach almost baseline infection prevalence 12 months post-treatment; slow but gradual increase in the prevalence and intensity of infection in Bodo; marked increase in prevalence and intensity of infection during the second year of the follow-up in Assinzé; and prevalence and intensity of infection that remained almost constant between 6 and 24 months post-treatment in Batera. Our study confirms that S. haematobium reinfection patterns largely depend on the local epidemiological setting, which is of central importance to tailoring treatment strategies that are well adapted to these different settings.

A real time pricing approach to deal with excessive wind power situations

The introduction of wind power generation in several countries around the world, including in European countries, where energy policy directives have encouraged the use of renewables, led to several changes in market and power systems operation. The intensive integration of these sources has led to situations in which the demand is lower than the available renewable resources. In these situations a part of the available generation is wasted if not used for storage or to supply additional demand. This paper proposes a real time demand response methodology based on changing the electricity price for the consumers expecting an increase in the demand in the periods in which that demand is lower than the available renewable generation. The consumers response to the changes in electricity price is characterized by their price elasticity of demand considered distinct for each consumer type. The proposed methodology is applied to the Portuguese power system, in the context of the Iberian electricity market (MIBEL). The renewable-based producers are considered as special producers, with special tariffs, and so it is important to use the energy available as it will be paid anyway. In this context, consumers are entities actively participating in the operation of the market.

Agent-based simulation of electronic marketplaces with decision support

This paper presents a Multi-Agent Market simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agents reactions.