Agricultural development and arthropod-borne diseases: a review

A review is presented of the interrelationships between arthropod vectors, the diseases they transmit and agricultural development. Particular attention is given to the effects of deforestation, livestock development and irrigation on the abundance of vectors and changing patterns of diseases such as malaria, trypanosomiases, leishmaniasis, Chagas' and some arboviral infections. The question as whether keeping livestock diverts biting away from people and reduces diseases such as malaria - that is zooprophylaxis, or whether the presence of cattle actually increases biting populations is discussed.

Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. (C) 2012 Elsevier Ltd. All rights reserved.

Virtual power players demand response programs management based on locational marginal prices

Power systems have been suffering huge changes mainly due to the substantial increase of distributed generation and to the operation in competitive environments. Virtual power players can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Resource management gains an increasing relevance in this competitive context, while demand side active role provides managers with increased demand elasticity. This makes demand response use more interesting and flexible, giving rise to a wide range of new opportunities.This paper proposes a methodology for managing demand response programs in the scope of virtual power players. The proposed method is based on the calculation of locational marginal prices (LMP). The evaluation of the impact of using demand response specific programs on the LMP value supports the manager decision concerning demand response use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus network with intensive use of distributed generation.

Hybrid Wavelet-PSO-ANFIS Approach for Short-Term Electricity Prices Forecasting

A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system, is proposed in this paper for short-term electricity prices forecasting in a competitive market. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Finally, conclusions are duly drawn.

Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

Dynamic artificial neural network for electricity market prices forecast

This paper presents an artificial neural network applied to the forecasting of electricity market prices, with the special feature of being dynamic. The dynamism is verified at two different levels. The first level is characterized as a re-training of the network in every iteration, so that the artificial neural network can able to consider the most recent data at all times, and constantly adapt itself to the most recent happenings. The second level considers the adaptation of the neural network’s execution time depending on the circumstances of its use. The execution time adaptation is performed through the automatic adjustment of the amount of data considered for training the network. This is an advantageous and indispensable feature for this neural network’s integration in ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to the market negotiating players of MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).

Zonal prices analysis supported by a data mining based methodology

A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.

Electricity markets: transmission prices methods

In the context of electricity markets, transmission pricing is an important tool to achieve an efficient operation of the electricity system. The electricity market is influenced by several factors; however the transmission network management is one of the most important aspects, because the network is a natural monopoly. The transmission tariffs can help to regulate the market, for this reason transmission tariffs must follow strict criteria. This paper presents the following methods to tariff the use of transmission networks by electricity market players: Post-Stamp Method; MW-Mile Method Distribution Factors Methods; Tracing Methodology; Bialek’s Tracing Method and Locational Marginal Price. A nine bus transmission network is used to illustrate the application of the tariff methods.

Efficiency Measures in the Agricultural Sector: The Beginning

Copyright © 2013 Springer Netherlands.

Efficiency Measures in the Agricultural Sector: With Applications

Copyright 2013 Springer Netherlands.

Management of agricultural waste on a sample of farms on the island of São Miguel (Açores)

Dissertação de Mestrado em Ambiente, Saúde e Segurança.

Sorption of phenanthrene on agricultural soils

Polyaromatic hydrocarbon (PAH) sorption to soil is a key process deciding the transport and fate of PAH, and potential toxic impacts in the soil and groundwater ecosystems, for example in connection with atmospheric PAH deposition on soils. There are numerous studies on PAH sorption in relatively low organic porous media such as urban soils and groundwater sediments, but less attention has been given to cultivated soils. In this study, the phenanthrene partition coefficient, KD (liter per kilogram), was measured on 143 cultivated Danish soils (115 topsoils, 0–0.25-m soil depth and 28 subsoils, 0.25–1-m depth) by the single-point adsorption method. The organic carbon partition coefficient, KOC (liter per kilogram) for topsoils was found generally to fall between the KOC values estimated by the two most frequently used models for PAH partitioning, the Abdul et al. (Hazardous Waste & Hazardous Materials 4(3):211– 222, 1987) model and Karickhoff et al. (Water Research 13:241–248, 1979) model. A less-recognized model by Karickhoff (Chemosphere 10:833–846, 1981), yielding a KOC of 14,918 Lkg−1, closely corresponded to the average measured KOC value for the topsoils, and this model is therefore recommended for prediction of phenanthrene mobility in cultivated topsoils. For lower subsoils (0.25–1-m depth), the KOC values were closer to and mostly below the estimate by the Abdul et al. (Hazardous Waste & Hazardous Materials 4(3):211–222, 1987) model. This implies a different organic matter composition and higher PAH sorption strength in cultivated topsoils, likely due to management effects including more rapid carbon turnover. Finally, we applied the recent Dexter et al. (Geoderma 144:620–627, 2008) theorem, and calculated the complexed organic carbon and non-complexed organic carbon fractions (COC and NCOC, grams per gram). Multiple regression analyses showed that the NCOC-based phenanthrene partition coefficient (KNCOC) could be markedly higher than the COCbased partition coefficient (KCOC) for soils with a clay/OC ratio <10. This possibly higher PAH sorption affinity to the NCOC fraction needs further investigations to develop more realistic and accurate models for PAH mobility and effects in the environment, also with regard to colloid-facilitated PAH transport.

Evaluation of dynamic pass-through of carbon prices into electricity prices – a cointegrated VECM analysis

This paper addresses the impact of the CO2 opportunity cost on the wholesale electricity price in the context of the Iberian electricity market (MIBEL), namely on the Portuguese system, for the period corresponding to the Phase II of the European Union Emission Trading Scheme (EU ETS). In the econometric analysis a vector error correction model (VECM) is specified to estimate both long–run equilibrium relations and short–run interactions between the electricity price and the fuel (natural gas and coal) and carbon prices. The model is estimated using daily spot market prices and the four commodities prices are jointly modelled as endogenous variables. Moreover, a set of exogenous variables is incorporated in order to account for the electricity demand conditions (temperature) and the electricity generation mix (quantity of electricity traded according the technology used). The outcomes for the Portuguese electricity system suggest that the dynamic pass–through of carbon prices into electricity prices is strongly significant and a long–run elasticity was estimated (equilibrium relation) that is aligned with studies that have been conducted for other markets.

Multidimensional scaling analysis of electricity market prices

This paper studies the impact of energy and stock markets upon electricity markets using Multidimensional Scaling (MDS). Historical values from major energy, stock and electricity markets are adopted. To analyze the data several graphs produced by MDS are presented and discussed. This method is useful to have a deeper insight into the behavior and the correlation of the markets. The results may also guide the construction models, helping electricity markets agents hedging against Market Clearing Price (MCP) volatility and, simultaneously, to achieve better financial results.

Persistence characteristics in financial prices: evidence from the portuguese stock market returns

The objective of this article is to provide additional knowledge to the discussion of long-term memory, leaning over the behavior of the main Portuguese stock index. The first four moments are calculated using time windows of increasing size and sliding time windows of fixed size equal to 50 days and suggest that daily returns are non-ergodic and non-stationary. Seeming that the series is best described by a fractional Brownian motion approach, we use the rescaled-range analysis (R/S) and the detrended fluctuation analysis (DFA). The findings indicate evidence of long term memory in the form of persistence. This evidence of fractal structure suggests that the market is subject to greater predictability and contradicts the efficient market hypothesis in its weak form. This raises issues regarding theoretical modeling of asset pricing. In addition, we carried out a more localized (in time) study to identify the evolution of the degree of long-term dependency over time using windows 200-days and 400-days. The results show a switching feature in the index, from persistent to anti-persistent, quite evident from 2010.