Dgenco market balancing - cost repartition under light regulation markets

In this paper we present a new methodology, based in game theory, to obtain the market balancing between Distribution Generation Companies (DGENCO), in liberalized electricity markets. The new contribution of this methodology is the verification of the participation rate of each agent based in Nucléolo Balancing and in Shapley Value. To validate the results we use the Zaragoza Distribution Network with 42 Bus and 5 DGENCO.

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.

The Portuguese law on social economy

This study is a reflection on the Portuguese Framework Law on Social Economy, highlighting, from a critical point-of-view, its contribution to the explicit institutional and legal recognition of the social economy sector. It does so by defining the concept of social economy and listing the entities engaged in this sector, by defining its guiding principles and the mechanisms for its promotion and encouragement, and also by describing the creation of a tax and competition regime which will take into account its specificities. The setting up of this foundations of the social economy was based on the constitutional principle of protection of the social and cooperative sector, which substantiates the adoption of differentiating solutions in view of the positive discrimination of this sector.

Molinate quantification in environmental water by a glutathione-S-transferase based biosensor

A glutathione-S-transferase (GST)based biosensor was developed to quantify the thiocarbamate herbicide molinate in environmental water.The biosensor construction was based on GST immobilization onto a glassy carbon electrode via aminosilane–glutaraldehyde covalent attachment. The principle supporting the use of this biosensor consists of the GST inhibition process promoted by molinate. Differential pulse voltammetry was used to obtain a calibration curve for molinate concentration, ranging from 0.19 to 7.9 mgL -1 and presenting a detection limit of 0.064 mgL- 1. The developed biosensor is stable,and reusable during 15 days.The GST-based biosensor was successfully applied to quantify molinate in rice paddy field floodwater samples. The results achieved with the developed biosensor were in accordance with those obtained by high performance liquid chromatography. The proposed device is suitable for screening environmental water analysis and, since no sample preparation is required, it can be used in situ and in real-time measurements.

Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

Self-similarity principle: the reduced description of randomness

A new general fitting method based on the Self-Similar (SS) organization of random sequences is presented. The proposed analytical function helps to fit the response of many complex systems when their recorded data form a self-similar curve. The verified SS principle opens new possibilities for the fitting of economical, meteorological and other complex data when the mathematical model is absent but the reduced description in terms of some universal set of the fitting parameters is necessary. This fitting function is verified on economical (price of a commodity versus time) and weather (the Earth’s mean temperature surface data versus time) and for these nontrivial cases it becomes possible to receive a very good fit of initial data set. The general conditions of application of this fitting method describing the response of many complex systems and the forecast possibilities are discussed.

Simple laccase-based biosensor for formetanate hydrochloride quantification in fruits

This work describes the development of an electrochemical enzymatic biosensor for quantification of the pesticide formetanate hydrochloride (FMT). It is based on a gold electrode modified with electrodeposited gold nanoparticles and laccase. The principle behind its development relies on FMT's capacity to inhibit the laccase catalytic reaction that occurs in the presence of phenolic substrates. The optimum values for the relevant experimental variables such as gold nanoparticles electrochemical deposition (at − 0.2 V for 100 s), laccase immobilization (via glutaraldehyde cross-linking), laccase concentration (12.4 mg/mL), substrate selection and concentration (5.83×10−5 M of aminophenol), pH (5.0), buffer (Britton–Robinson), and square-wave voltammetric parameters were determined. The developed biosensor was successfully applied to FMT determination in mango and grapes. The attained limit of detection was 9.5×10−8 ± 9.5×10−10 M (0.02 ± 2.6×10−4 mg/kg on a fresh fruit weight basis). Recoveries for the five tested spiking levels ranged from 95.5 ± 2.9 (grapes) to 108.6 ± 2.5% (mango). The results indicated that the proposed device presents suitable characteristics in terms of sensitivity (20.58 ± 0.49 A/μM), linearity (9.43×10−7 to 1.13×10−5 M), accuracy, repeatability (RSD of 1.4%), reproducibility (RSD of 1.8%) and stability (19 days) for testing of compliance with established maximum residue limits of FMT in fruits and vegetables.