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).

Real-time energy resources scheduling considering short-term and very short-term wind forecast

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process it is necessary the update of generation and consumption operation and of the storage and electric vehicles storage status. Besides the new operation condition, it is important more accurate forecast values of wind generation and of consumption using results of in short-term and very short-term methods. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented.

ANN based day-ahead spinning reserve forecast for electricity market simulation

Electricity market players operating in a liberalized environment require adequate decision support tools, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. This paper deals with short-term predication of day-ahead spinning reserve (SR) requirement that helps the ISO to make effective and timely decisions. Based on these forecasted information, market participants can use strategic bidding for day-ahead SR market. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

ANN based day-ahead ancillary services forecast for electricity market simulation

Adequate decision support tools are required by electricity market players operating in a liberalized environment, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services (AS) represent a good negotiation opportunity that must be considered by market players. Based on the ancillary services forecasting, market participants can use strategic bidding for day-ahead ancillary services markets. For this reason, ancillary services market simulation is being included in MASCEM, a multi-agent based electricity market simulator that can be used by market players to test and enhance their bidding strategies. The paper presents the methodology used to undertake ancillary services forecasting, based on an Artificial Neural Network (ANN) approach. ANNs are used to day-ahead prediction of non-spinning reserve (NS), regulation-up (RU), and regulation down (RD). Spinning reserve (SR) is mentioned as past work for comparative analysis. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

Metaheuristic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Metaheuristhic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Renewable power forecast to scheduling of thermal units

In this work is discussed the importance of the renewable production forecast in an island environment. A probabilistic forecast based on kernel density estimators is proposed. The aggregation of these forecasts, allows the determination of thermal generation amount needed to schedule and operating a power grid of an island with high penetration of renewable generation. A case study based on electric system of S. Miguel Island is presented. The results show that the forecast techniques are an imperative tool help the grid management.

Distributed energy resources scheduling considering real-time resources forecast

Energy resource scheduling is becoming increasingly important, such as the use of more distributed generators and electric vehicles connected to the distribution network. This paper proposes a methodology to be used by Virtual Power Players (VPPs), regarding the energy resource scheduling in smart grids and considering day-ahead, hour-ahead and realtime time horizons. This method considers that energy resources are managed by a VPP which establishes contracts with their owners. The full AC power flow calculation included in the model takes into account network constraints. In this paper, distribution function errors are used to simulate variations between time horizons, and to measure the performance of the proposed methodology. A 33-bus distribution network with large number of distributed resources is used.

A crop-land allocation model: A case study in La Rioja, Spain

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Differential exploitation of cashew - a low conflict crop - by sympatric humans and chimpanzees

Modification of natural areas by human activities mostly has a negative impact on wildlife by increasing the geographical and ecological overlap between people and animals. This can result in escalating levels of competition and conflict between humans and wildlife, for example over crops. However, data on specific crops and crop parts that are unattractive to wildlife yet important for human livelihoods are surprisingly scarce, especially considering their potential application to reducing crop damage by wildlife. Here we examine the co-utilization of a nationally important and spatially abundant cash crop, cashew Anacardium occidentalis, by people and chimpanzees Pan troglodytes verus inhabiting a forested–agricultural matrix in Cantanhez National Park in Guinea-Bissau. In this Park people predominantly harvest the marketable cashew nut and discard the unprofitable fruit whereas chimpanzees only consume the fruit. Local farmers generally perceive a benefit of raiding by chimpanzees as they reportedly pile the nuts, making harvesting easier. By ensuring that conflict levels over crops, especially those with high economic importance, remain low, the costs of living in proximity to wildlife can potentially be reduced. Despite high levels of deforestation associated with cashew farming, these findings point to the importance of cashew as a low-conflict crop in this area.

Archaeometallurgical study of the Proto-historic collection of Moinhos de Golas (North Portugal): a forecast for technological changes?

This work presents the archaeometallurgical study of a group of metallic artefacts found in Moinhos de Golas site, Vila Real (North of Portugal), that can generically be attributed to Proto-history (1st millennium BC, Late Bronze Age and Iron Age). The collection is composed by 35 objects: weapons, ornaments and tools, and others of difficult classification, as rings, bars and one small thin bent sheet. Some of the objects can typologically be attributed to Late Bronze Age, others are of more difficult specific attribution. The archaeometallurgical study involved x-ray digital radiography, elemental analysis by micro-energy dispersive X-ray fluorescence spectrometry and scanning electron microscopy with energy dispersive spectroscopy, microstructural observations by optical microscopy and scanning electron microscopy. The radiographic images revealed structural heterogeneities frequently related with the degradation of some artefacts and the elemental analysis showed that the majority of the artefacts was produced in a binary bronze alloy (Cu-Sn) (73%), being others produced in copper (15%) and three artefacts in brass (Cu-Zn(-Sn-Pb)). Among each type of alloy there’s certain variability in the composition and in the type of inclusions. The microstructural observations revealed that the majority of the artefacts suffered cycles of thermo-mechanical processing after casting. The diversity of metals/alloys identified was a discovery of great interest, specifically due to the presence of brasses. Their presence can be interpreted as importations related to the circulation of exogenous products during the Proto-history and/or to the deposition of materials during different moments at the site, from the transition of Late Bronze Age/Early Iron Age (Orientalizing period) onwards, as during the Roman period.

Analysis of classification algorithms for crop detection using LANDSAT 8 images

Remote sensing - the acquisition of information about an object or phenomenon without making physical contact with the object - is applied in a multitude of different areas, ranging from agriculture, forestry, cartography, hydrology, geology, meteorology, aerial traffic control, among many others. Regarding agriculture, an example of application of this information is regarding crop detection, to monitor existing crops easily and help in the region’s strategic planning. In any of these areas, there is always an ongoing search for better methods that allow us to obtain better results. For over forty years, the Landsat program has utilized satellites to collect spectral information from Earth’s surface, creating a historical archive unmatched in quality, detail, coverage, and length. The most recent one was launched on February 11, 2013, having a number of improvements regarding its predecessors. This project aims to compare classification methods in Portugal’s Ribatejo region, specifically regarding crop detection. The state of the art algorithms will be used in this region and their performance will be analyzed.

Fertilization and cover crop effects on soil nitrogen and plant nutrition in a young guarana plantation

Fruit tree production is gaining an increasing importance in the central Amazon and elsewhere in the humid tropics, but very little is known about the nutrient dynamics in the soil-plant system. The present study quantified the effects of fertilization and cover cropping with a legume (Pueraria phaseoloides (Roxb.) Benth.) on soil nitrogen (N) dynamics and plant nutrition in a young guarana plantation (Paullinia cupana Kunth. (H.B. and K.) var. sorbilis (Mart.) Ducke) on a highly weathered Xanthic Ferralsol. Large subsoil nitrate (NO3-) accumulation at 0.3-3 m below the guarana plantation indicated N leaching from the topsoil. The NO3- contents to a depth of 2 m were 2.4 times greater between the trees than underneath unfertilized trees (P<0.05). The legume cover crop between the trees increased soil N availability as shown by elevated aerobic N mineralization and lower N immobilization in microbial biomass. The guarana N nutrition and yield did not benefit from the N input by biological fixation of atmospheric N2 by the legume cover (P>0.05). Even without a legume intercrop, large amounts of NO3- were found in the subsoil between unfertilized trees. Subsoil NO3- between the trees could be utilized, however, by fertilized guarana. This can be explained by a more vigorous growth of fertilized trees which had a larger nutrient demand and exploited a larger soil volume. With a legume cover crop, however, more mineral N was available at the topsoil which was leached into the subsoil and consequently accumulated at 0.3-3 m depth. Fertilizer additions of P and K were needed to increase subsoil NO3- use between trees.

Removal of Erythrosine B dye from water effluents using crop waste pumpkin seed hulls as adsorbent

Erythrosine B is widely used for coloring in various applications, especially in the food industry, despite its already proved toxicity and carcinogenicity. The agrowaste pumpkin seed hulls were applied as potential adsorbent for the removal of Erythrosine from aqueous solutions. Adsorption mechanism and kinetics were analyzed for design purposes. The seed hulls were characterized by specific techniques before and after dye retention. It was found that the attachment of Erythrosine B molecules on adsorbent surface may be attributed to the interactions between carboxyl and/or carbonyl groups of both dye and agrowaste wall components. A univariate approach followed by a factorial design was applied to study and analyze the experimental results as well as to estimate the combined effects of the process factors on the removal efficiency and dye uptake. Adsorption mechanism may be predominantly due to intraparticle diffusion, dependent on pore size. The four equilibrium models applied fitted the data well; the maximum adsorption capacity for Erythrosine was 16.4 mg/g. The results showed that adsorbent is effective for Erythrosine B removal for a large concentration range in aqueous solutions (5400 mg/L) in batch systems.

Grasses and legumes as cover crop in no-tillage system in northeastern Pará Brazil

Studies to select one or more species of coverage plants adapted to Amazonian soil and climate conditions of the Amazon are a promising strategy for the improvement of environmental quality, establishing no-till agricultural systems, and thereby reducing the impacts of monoculture farming. The aim of this study was to assess the persistence time, half-life time, macronutrient content and accumulation, and C:N ratio of straw coverage in a Ultisol in northeastern Pará. Experimental design was randomized blocks with five treatments and five replicates. Plants were harvested after 105 days, growth and biomass production was quantified. After 84 days, soil coverage was 97, 85, 52, 50, and 15% for signalgrass (Brachiaria brizantha) (syn. Urochloa), dense crowngrass (Panicum purpurascens), jack bean (Canavalia ensiformes), pearl millet (Pennisetum americanum) and sunn hemp (Crotalaria juncea,), respectively. Signalgrass yielded the greatest dry matter production (9,696 kg ha-1). It also had high C:N ratio (38.4), long half-life (86.5 days) and a high persistence in the field. Jack bean also showed high dry matter production (8,950 kg ha-1), but it had low C:N ratio (17.4) and lower half-life time (39 days) than the grasses. These attributes indicate that signalgrass and jack bean have a high potential for use as cover plants in no-till agricultural systems in the State of Pará.