Modified Discrete PSO to Increase the Delivered Energy Probability in Distribution energy Systems

This paper proposes a PSO based approach to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The statistical failure and repair data of distribution components is the main basis of the proposed methodology that uses a fuzzyprobabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A Modified Discrete PSO optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

DC Fuzzy Multicriteria Approach to Increase the Probability of Delivering Power in Distribution Networks

This paper proposes a methodology to increase the probability of delivering power to any load point through the identification of new investments. The methodology uses a fuzzy set approach to model the uncertainty of outage parameters, load and generation. A DC fuzzy multicriteria optimization model considering the Pareto front and based on mixed integer non-linear optimization programming is developed in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power to all customers in the distribution network at the minimum possible cost for the system operator, while minimizing the non supplied energy cost. To illustrate the application of the proposed methodology, the paper includes a case study which considers an 33 bus distribution network.

Increase of the Delivered Power Probability in Distribution Networks using Pareto DC Programming

A methodology to increase the probability of delivering power to any load point through the identification of new investments in distribution network components is proposed in this paper. The method minimizes the investment cost as well as the cost of energy not supplied in the network. A DC optimization model based on mixed integer non-linear programming is developed considering the Pareto front technique in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power for any customer in the distribution system at the minimum possible cost for the system operator, while minimizing the energy not supplied cost. Thus, a multi-objective problem is formulated. To illustrate the application of the proposed methodology, the paper includes a case study which considers a 180 bus distribution network

Cost Allocation Model for Distribution Networks Considering High Penetration of Distributed Energy Resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitiveenvironment of electricity markets impose the use of new approaches in several domains. The networkcost allocation, traditionally used in transmission networks, should be adapted and used in the distribu-tion networks considering the specifications of the connected resources. The main goal is to develop afairer methodology trying to distribute the distribution network use costs to all players which are usingthe network in each period. In this paper, a model considering different type of costs (fixed, losses, andcongestion costs) is proposed comprising the use of a large set of DER, namely distributed generation(DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehi-cles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). Theproposed model includes three distinct phases of operation. The first phase of the model consists in aneconomic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen’s andBialek’s tracing algorithms are used and compared to evaluate the impact of each resource in the net-work. Finally, the MW-mile method is used in the third phase of the proposed model. A distributionnetwork of 33 buses with large penetration of DER is used to illustrate the application of the proposedmodel.

Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the whole system. The work presented in this paper comprises a methodology able to define the cost allocation in distribution networks considering large integration of DG and DR resources. The proposed methodology is divided into three phases and it is based on an AC Optimal Power Flow (OPF) including the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity.

Recovery of acid and base from brackish water by bipolar membrane electrodialysis

Nesta dissertação pretendeu-se estudar a viabilidade do uso de eletrodiálise com membranas bipolares (BM) na recuperação de ácido clorídrico e de hidróxido de sódio a partir de um efluente industrial que contém 1.4 mol/L de cloreto de sódio. Estas membranas mostraram ser uma ferramenta eficiente para a produção de ácidos e bases a partir do respetivo sal. Foi feita uma seleção de diferentes membranas bipolares (Neosepta, Fumatech e PCA) e aniónicas (PC-SA e PC-ACID 60) na tentativa de encontrar a combinação mais adequada para o tratamento do efluente. Dependendo do critério, o melhor arranjo de membranas é o uso de PC-ACID 60 (membrana aniónica), PC-SK (membrana catiónica) e membranas bipolares do tipo Neosepta para maior pureza dos produtos; membranas bipolares Fumatech para maior eficiência de dessalinização e membranas bipolares PCA para um maior grau de dessalinização. Tecnologicamente foi possível obter uma dessalinização de 99.8% em quatro horas de funcionamento em modo batch com recirculação de todas as correntes. Independentemente da combinação usada é recomendável que o processo seja parado quando a densidade de corrente deixa de ser máxima, 781 A/m2. Assim é possível evitar o aumento de impurezas nos produtos, contra difusão, descida instantânea do pH e uma dessalinização pouco eficiente. A nível piloto o principal fornecedor de membranas e unidade de tratamento “stack” é a marca alemã PCA. Sendo assim realizaram-se ensaios de repetibilidade, contra difusão, avaliação económica e upscaling utilizando as membranas bipolares PCA. A nível económico estudou-se o uso de dois tipos de unidades de tratamento; EDQ 380 e EDQ 1600, para diferentes níveis de dessalinização (50, 75 e 80%). Tendo em conta a otimização económica, é recomendável uma dessalinização máxima de 80%, uma vez que a eficiência de processo a este ponto é de 40%. A aplicação do método com a unidade EDQ 1600 para uma dessalinização de 50% é a mais vantajosa economicamente, com custos de 16 €/m3 de efluente tratado ou 0,78 €/kg Cl- removido. O número de unidades necessárias é 4 posicionados em série.

Casualties distribution in human and natural hazards

Catastrophic events, such as wars and terrorist attacks, big tornadoes and hurricanes, huge earthquakes, tsunamis, floods, and landslides, are always accompanied by a large number of casualties. The size distribution of these casualties have separately been shown to follow approximate power law (PL) distributions. In this paper, we analyze the number of victims of catastrophic phenomena, in particular, terrorism, and find double PL behavior. This means that the data set is better approximated by two PLs instead of one. We have plotted the two PL parameters corresponding to all terrorist events occurred in every year, from 1980 to 2010. We observe an interesting pattern in the chart, where the lines, that connect each pair of points defining the double PLs, are roughly aligned to each other.

MnFe2O4@CNT-N as novel electrochemical nanosensor for determination of caffeine, acetaminophen and ascorbic acid

For the first time, a glassy carbon electrode (GCE) modified with novel N-doped carbon nanotubes (CNT-N) functionalized with MnFe2O4 nanoparticles (MnFe2O4@CNT-N) has been prepared and applied for the electrochemical determination of caffeine (CF), acetaminophen (AC) and ascorbic acid (AA). The electrochemical behaviour of CF, AC and AA on the bare GCE, CNT-N/GCE and MnFe2O4@CNT-N/GCE were carefully investigated using cyclic voltammetry (CV) and square-wave voltammetry (SWV). Compared to bare GCE and CNT-N modified electrode, the MnFe2O4@CNT-N modified electrode can remarkably improve the electrocatalytic activity towards the oxidation of CF, AC and AA with an increase in the anodic peak currents of 52%, 50% and 55%, respectively. Also, the SWV anodic peaks of these molecules could be distinguished from each other at the MnFe2O4@CNT-N modified electrode with enhanced oxidation currents. The linear response ranges for the square wave voltammetric determination of CF, AC and AA were 1.0 × 10−6 to 1.1 × 10−3 mol dm−3, 1.0 × 10−6 to 1.0 × 10−3 mol dm−3 and 2.0 × 10−6 to 1.0 × 10−4 mol dm−3 with detection limit (S/N = 3) of 0.83 × 10−6, 0.83 × 10−6 and 1.8 × 10−6 mol dm−3, respectively. The sensitivity values at the MnFe2O4@CNT-N/GCE for the individual determination of AC, AA and CF and in the presence of the other molecules showed that the quantification of AA and CF show no interferences from the other molecules; however, AA and CF interfered in the determination of AC, with the latter molecule showing the strongest interference. Nevertheless, the obtained results show that MnFe2O4@CNT-N composite material acted as an efficient electrochemical sensor towards the selected biomolecules.

A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context

In the traditional paradigm, the large power plants supply the reactive power required at a transmission level and the capacitors and transformer tap changer were also used at a distribution level. However, in a near future will be necessary to schedule both active and reactive power at a distribution level, due to the high number of resources connected in distribution levels. This paper proposes a new multi-objective methodology to deal with the optimal resource scheduling considering the distributed generation, electric vehicles and capacitor banks for the joint active and reactive power scheduling. The proposed methodology considers the minimization of the cost (economic perspective) of all distributed resources, and the minimization of the voltage magnitude difference (technical perspective) in all buses. The Pareto front is determined and a fuzzy-based mechanism is applied to present the best compromise solution. The proposed methodology has been tested in the 33-bus distribution network. The case study shows the results of three different scenarios for the economic, technical, and multi-objective perspectives, and the results demonstrated the importance of incorporating the reactive scheduling in the distribution network using the multi-objective perspective to obtain the best compromise solution for the economic and technical perspectives.

Cost allocation model for distribution networks considering high penetration of distributed energy resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.

Multi-criteria optimisation approach to increase the delivered power in radial distribution networks

This study proposes a new methodology to increase the power delivered to any load point in a radial distribution network, through the identification of new investments in order to improve the repair time. This research work is innovative and consists in proposing a full optimisation model based on mixed-integer non-linear programming considering the Pareto front technique. The goal is to achieve a reduction in repair times of the distribution networks components, while minimising the costs of that reduction as well as non-supplied energy costs. The optimisation model considers the distribution network technical constraints, the substation transformer taps, and it is able to choose the capacitor banks size. A case study based on a 33-bus distribution network is presented in order to illustrate in detail the application of the proposed methodology.

Exploring cinnamic acid scaffold: development of promising neuroprotective lipophilic antioxidants

New lipophilic hydroxycinnamic acid based derivatives were designed and synthesized and their antioxidant and neuroprotective activities evaluated. The chemical modification introduced in the cinnamic acid scaffold leads to compounds with amplified lipophilicity and in general with increased antioxidant activity when compared to natural models (caffeic and ferulic acids). The compounds did not display cytotoxicity and present a significant neuroprotective effect against 6-OH-DA induced damage to SH-SY5Y cells. Compound 6 stands out as an efficient radical scavenger and iron(II) chelator that ensures drug-like properties. Moreover, neuroprotection against oxidative damage was observed even at low concentration (1 μM). Therefore, compound 6 developed by a biology-oriented approach displays a combination of important features for a further optimization process that will generate a new effective antioxidant with therapeutic application for oxidative-stress-related events, namely neurodegenerative diseases.