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.

A simulation tool for demand response programs implementation

The design and development of simulation models and tools for Demand Response (DR) programs are becoming more and more important for adequately taking the maximum advantages of DR programs use. Moreover, a more active consumers’ participation in DR programs can help improving the system reliability and decrease or defer the required investments. DemSi, a DR simulator, designed and implemented by the authors of this paper, allows studying DR actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. DemSi considers the players involved in DR actions, and the results can be analyzed from each specific player point of view.

Using data mining techniques to support DR programs definition in smart grids

In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

Solving a signalized traffic intersection problem with an hyperbolic penalty function

Mathematical Program with Complementarity Constraints (MPCC) finds many applications in fields such as engineering design, economic equilibrium and mathematical programming theory itself. A queueing system model resulting from a single signalized intersection regulated by pre-timed control in traffic network is considered. The model is formulated as an MPCC problem. A MATLAB implementation based on an hyperbolic penalty function is used to solve this practical problem, computing the total average waiting time of the vehicles in all queues and the green split allocation. The problem was codified in AMPL.

Numerical experiments with a modified regularization scheme for mathematical programs with complementarity constraints

On this paper we present a modified regularization scheme for Mathematical Programs with Complementarity Constraints. In the regularized formulations the complementarity condition is replaced by a constraint involving a positive parameter that can be decreased to zero. In our approach both the complementarity condition and the nonnegativity constraints are relaxed. An iterative algorithm is implemented in MATLAB language and a set of AMPL problems from MacMPEC database were tested.

Contribution of traffic and tobacco smoke in the distribution of polycyclic aromatic hydrocarbons on outdoor and indoor PM2.5

Traffic emissions and tobacco smoke are considered two main sources of polycyclic aromatic hydrocarbons (PAHs) in indoor and outdoor air. In this study, the impact of these sources on the level of fine particulate matter (PM2.5) and on the distribution of 15 PAHs regarded as priority pollutants by the US-EPA on PM2.5 were evaluated and compared. Outdoor and indoor PM2.5 samples were collected during winter 2008 in Oporto city in Portugal, for sampling periods of 12 and 24 hours, respectively. The outdoor PM2.5 were sampled at one site directly influenced by traffic emissions and the indoor PM2.5 samples were collected at one home directly influenced by tobacco smoke and another one without smoke. A methodology based on microwave-assisted extraction and liquid chromatography with fluorescence detection was applied for the efficient PAHs determination in indoor and outdoor PM2.5. PAHs in indoor PM2.5 concentrations were significantly influenced by the presence of traffic and tobacco smoking emissions. The mean of ΣPAHs in the outdoor traffic PM2.5 was not significantly different from the value attained in the indoor without smoking site. The tobacco smoke increased significantly PAHs concentrations on average about 1000 times more, when compared with the outdoor profile samples suggesting that tobacco smoking may be the most important source of indoor PAHs pollution.

Determination of tartaric acid in wines by FIA with tubular tartrate-selective electrodes

A flow injection analysis (FIA) system comprising a tartrate- (TAT) selective electrode has been developed for determination of tartaric acid in wines. Several electrodes constructed for this purpose had a PVC membrane with a complex of quaternary ammonium and TAT as anion exchanger, a phenol derivative as additive, and a more or less polar mediator solvent. Characterization of the electrodes showed behavior was best for membranes with o-nitrophenyl octyl ether as solvent. On injection of 500 μL into a phosphate buffer carrier (pH = 3.1; ionic strength 10–2 mol/L) flowing at 3 mL/min, the slope was 58.06 ± 0.6 with a lower limit of linear range of 5.0 × 10–4 mol/L TAT and R2 = 0.9989. The interference of several species, e.g. chloride, bromide, iodide, nitrate, gallic acid, tannin, sucrose, glucose, fructose, acetate, and citrate, was evaluated in terms of potentiometric selectivity coefficients. The Hofmeister series was followed for inorganic species and the most interfering organic ion was citrate. When red and white wines were analyzed and the results compared with those from an independent method they were found to be accurate, with relative standard deviations below 5.0%.

Citrate selective electrodes for the flow injection analysis of soft drinks, beers and pharmaceutical products

Aiming the establishment of simple and accurate readings of citric acid (CA) in complex samples, citrate (CIT) selective electrodes with tubular configuration and polymeric membranes plus a quaternary ammonium ion exchanger were constructed. Several selective membranes were prepared for this purpose, having distinct mediator solvents (with quite different polarities) and, in some cases, p-tert-octylphenol (TOP) as additive. The latter was used regarding a possible increase in selectivity. The general working characteristics of all prepared electrodes were evaluated in a low dispersion flow injection analysis (FIA) manifold by injecting 500µl of citrate standard solutions into an ionic strength (IS) adjuster carrier (10−2 mol l−1) flowing at 3ml min−1. Good potentiometric response, with an average slope and a repeatability of 61.9mV per decade and ±0.8%, respectively, resulted from selective membranes comprising additive and bis(2-ethylhexyl)sebacate (bEHS) as mediator solvent. The same membranes conducted as well to the best selectivity characteristics, assessed by the separated solutions method and for several chemical species, such as chloride, nitrate, ascorbate, glucose, fructose and sucrose. Pharmaceutical preparations, soft drinks and beers were analyzed under conditions that enabled simultaneous pH and ionic strength adjustment (pH = 3.2; ionic strength = 10−2 mol l−1), and the attained results agreed well with the used reference method (relative error < 4%). The above experimental conditions promoted a significant increase in sensitivity of the potentiometric response, with a supra-Nernstian slope of 80.2mV per decade, and allowed the analysis of about 90 samples per hour, with a relative standard deviation <1.0%.

Construction and evaluation of cysteine selective electrodes for FIA analysis of pharmaceuticals

A flow injection analysis (FIA) system comprising a cysteine selective electrode as detection system was developed for determination of this amino acid in pharmaceuticals. Several electrodes were constructed for this purpose, having PVC membranes with different ionic exchangers and mediator solvents. Better working characteristics were attained with membranes comprising o-nitrophenyl octyl ether as mediator solvent and a tetraphenylborate based ionic-sensor. Injection of 500 µL standard solutions into an ionic strength adjuster carrier (3x10-3 M) of barium chloride flowing at 2.4mL min-1, showed linearity ranges from 5.0x10-5 to 5.0x10-3 M, with slopes of 76.4±0.6mV decade-1 and R2>0.9935. Slope decreased significantly under the requirement of a pH adjustment, selected at 4.5. Interference of several compounds (sodium, potassium, magnesium, barium, glucose, fructose, and sucrose) was estimated by potentiometric selectivity coefficients and considered negligible. Analysis of real samples were performed and considered accurate, with a relative error to an independent method of +2.7%.

Chlormequat selective electrodes: construction, evaluation and application at FIA systems

A flow injection analysis (FIA) system having a chlormequat selective electrode is proposed. Several electrodes with poly(vinyl chloride) based membranes were constructed for this purpose. Comparative characterization suggestedthe use of membrane with chlormequat tetraphenylborate and dibutylphthalate. On a single-line FIA set-up, operating with 1x10-2 mol L-1 ionic strength and 6.3 pH, calibration curves presented slopes of 53.6±0.4mV decade-1 within 5.0x10-6 and1.0x10-3 mol L-1, andsquaredcorrelation coefficients >0.9953. The detection limit was 2.2x10-6 mol L-1 and the repeatability equal to ±0.68mV (0.7%). A dual-channel FIA manifold was therefore constructed, enabling automatic attainment of previous ionic strength andpH conditions and thus eliminating sample preparation steps. Slopes of 45.5±0.2mV decade -1 along a concentration range of 8.0x10-6 to 1.0x10-3 mol L-1 with a repeatability ±0.4mV (0.69%) were obtained. Analyses of real samples were performed, and recovery gave results ranging from 96.6 to 101.1%.

Air pollution from traffic emissions in Oporto, Portugal: health and environmental implications

Air pollution represents a serious risk not only to environment and human health, but also to historical heritage. In this study, air pollution of the Oporto Metropolitan Area and its main impacts were characterized. The results showed that levels of CO, PM10 and SO2 have been continuously decreasing in the respective metropolitan area while levels of NOx and NO2 have not changed significantly. Traffic emissions were the main source of the determined polycyclic aromatic hydrocarbons (PAHs; 16 PAHs considered by U.S. EPA as priority pollutants, dibenzo[a,l]pyrene and benzo[j]fluoranthene) in air of the respective metropolitan area. The mean concentration of 18 PAHs in air was 69.9±39.7 ng m−3 with 3–4 rings PAHs accounting for 75% of the total ΣPAHs. The health risk analysis of PAHs in air showed that the estimated values of lifetime lung cancer risks considerably exceeded the health-based guideline level. Analytical results also confirm that historical monuments in urban areas act as passive repositories for air pollutants present in the surrounding atmosphere. FTIR and EDX analyses showed that gypsum was the most important constituent of black crusts of the characterized historical monument Monastery of Serra do Pilar classified as “UNESCO World Cultural Heritage”. In black crusts, 4–6 rings compounds accounted approximately for 85% of ΣPAHs. The diagnostic ratios confirmed that traffic emissions were the major source of PAHs in black crusts; PAH composition profiles were very similar for crusts and PM10 and PM2.5.

Selective recognition in potentiometric transduction of amoxicillin by molecularly imprinted materials

The indiscriminate use of antibiotics in foodproducing animals has received increasing attention as a contributory factor in the international emergence of antibiotic- resistant bacteria (Woodward in Pesticide, veterinary and other residues in food, CRC Press, Boca Raton, 2004). Numerous analytical methods for quantifying antibacterial residues in edible animal products have been developed over years (Woodward in Pesticide, veterinary and other residues in food, CRC Press, Boca Raton, 2004; Botsoglou and Fletouris in Handbook of food analysis, residues and other food component analysis, Marcel Dekker, Ghent, 2004). Being Amoxicillin (AMOX) one of those critical veterinary drugs, efforts have been made to develop simple and expeditious methods for its control in food samples. In literature, only one AMOX-selective electrode has been reported so far. In that work, phosphotungstate:amoxycillinium ion exchanger was used as electroactive material (Shoukry et al. in Electroanalysis 6:914–917, 1994). Designing new materials based on molecularly imprinted polymers (MIPs) which are complementary to the size and charge of AMOX could lead to very selective interactions, thus enhancing the selectivity of the sensing unit. AMOXselective electrodes used imprinted polymers as electroactive materials having AMOX as target molecule to design a biomimetic imprinted cavity. Poly(vinyl chloride), sensors of methacrylic acid displayed Nernstian slopes (60.7 mV/decade) and low detection limits (2.9×10-5 mol/L). The potentiometric responses were not affected by pH within 4–5 and showed good selectivity. The electrodes were applied successfully to the analysis of real samples.

New sensing materials of molecularly-imprinted polymers for the selective recognition of Chlortetracycline

As a result of the stressful conditions in aquaculture facilities there is a high risk of bacterial infections among cultured fish. Chlortetracycline (CTC) is one of the antimicrobials used to solve this problem. It is a broad spectrum antibacterial active against a wide range of Gram-positive and Gram-negative bacteria. Numerous analytical methods for screening, identifying, and quantifying CTC in animal products have been developed over the years. An alternative and advantageous method should rely on expeditious and efficient procedures providing highly specific and sensitive measurements in food samples. Ion-selective electrodes (ISEs) could meet these criteria. The only ISE reported in literature for this purpose used traditional electro-active materials. A selectivity enhancement could however be achieved after improving the analyte recognition by molecularly imprinted polymers (MIPs). Several MIP particles were synthesized and used as electro-active materials. ISEs based in methacrylic acid monomers showed the best analytical performance according to slope (62.5 and 68.6 mV/decade) and detection limit (4.1×10−5 and 5.5×10−5 mol L−1). The electrodes displayed good selectivity. The ISEs are not affected by pH changes ranging from 2.5 to 13. The sensors were successfully applied to the analysis of serum, urine and fish samples.

Trimethoprim-selective electrodes with molecularly imprinted polymers acting as ionophores and potentiometric transduction on graphite solid-contact

This work proposes a new biomimetic sensor material for trimethoprim. It is prepared by means of radical polymerization, having trimethylolpropane trimethacrylate as cross-linker, benzoyl peroxide as radicalar iniciator, chloroform as porogenic solvent, and methacrylic acid and 2-vinyl pyridine as monomers. Different percentages of sensor in a range between 1 and 6% were studied. Their behavior was compared to that obtained with ion-exchanger quaternary ammonium salt (additive tetrakis(p-chlorophenyl)borate or tetraphenylborate). The effect of an anionic additive in the sensing membrane was also tested. Trimethoprim sensors with 1% of imprinted particles from methacrylic acid monomers showed the best response in terms of slope (59.7 mV/decade) and detection limit (4.01×10−7 mol/L). These electrodes displayed also a good selectivity towards nickel, manganese aluminium, ammonium, lead, potassium, sodium, iron, chromium, sulfadiazine, alanine, cysteine, tryptophan, valine and glycine. The sensors were not affected by pH changes from 2 to 6. They were successfully applied to the analysis of water from aquaculture.