Impact of high PV penetration into distribution networks under contingencies

This paper analyzes the static voltage stability of distribution networks with photovoltaic (PV) generators under contingencies. The analysis is carried out on a widely used 16-bus test system. The paper treats the Q-V characteristics of the distribution grid for various PV penetration levels. Simulation results show that a higher penetration of PV increases the static coltage stability of the system. However, the tripping of multiple PV generators due to external disturbances, overloading and loss of distribution lines reduces the voltage stability margin of the system.

A control methodology for DFIG type wind turbines connected to distribution networks

This paper proposes a decentralised controller design for doubly-fed induction generators (DFIGs) to enhance dynamic performance of distribution networks. The change in the output power due to the variable nature of wind is considered as an uncertain term in the design algorithm. In addition, the interconnection effect of the other subsystems are considered in the design process. The H norm of the uncertain system is found out and simultaneous output-feedback linear controllers are designed based controller is verified on a 16 bus distribution test system for severe disturbances. Simulation results indicate that the designed controller is robust against uncertainties in operating conditions

D-STATCOM control in distribution networks with composite loads to ensure grid code compatible performance of photovoltaic generators

This paper proposes an optimal linear quadratic Gaussian (LQG) controller for D-STATCOM to improve the dynamic performance of distribution networks with photovoltaic generators. The controller is designed based on the H∞ norm of the uncertain system. The change in system model due to the variation of load compositions in the composite load is considered as an uncertain term in the design algorithm. The performance of the designed controller is demonstrated on a widely used test system. Simulation results indicate that the proposed controller can be a potential solution for improving the voltage stability of distribution networks.

Characteristics and applications of energy storage system to power network - A review

Maintaining reliability and stability of a power systems in transmission and distribution level becomes a big challenge in present scenario. Grid operators are always responsible to maintain equilibrium between available power generation and demand of end users. Maintaining grid balance is a bigger issue, in case of any unexpected generation shortage or grid disturbance or integration of any renewable energy sources like wind and solar power in the energy mix. In order to compensate such imbalance and to facilitate more renewable energy sources with the grid, energy storage system (ESS) started to be playing an important role with the advancement of the state of the art technology. ESS can also help to get reduction in greenhouse gas (GHG) emission by means of integrating more renewable energy sources to the grid. There are various types of Energy Storage (ES) technologies which are being used in power systems network from large scale (above 50MW) to small scale (up to 100KW). Based on the characteristics, each storage technology has their own merits and demerits. This paper carried out extensive review study and verifies merits and demerits of each storage technology and identifies the suitable technology for the future. This paper also has conducted feasibility study with the aid of E-SelectTM tool for various ES technologies in applications point of view at different grid locations. This review study helps to evaluate feasible ES technology for a particular electrical application and also helps to develop smart hybrid storage system for grid applications in efficient way.

Performance study of a wind-grid system in a semi- arid region and major integration issues

The phenomenal growth in economy experienced in developed countries throughout the 20th century has largely been driven by the availability of conventional energy sources for electricity generation. However, increased concern about fossil fuels and adverse effect of carbon dioxide emission in to atmosphere changed the conventional power system to a viable one by integrating renewable energy sources into the existing system. Among the Renewable Energy (RE) sources, wind energy is one of the fastest growing technologies in reducing the Green House Gas (GHG) emissions in to the atmosphere due to its continuous availability throughout a period. Hence, this paper discusses the performance of a wind-grid connected system in a semi-arid region by conducting a case study. Wilson promontory, one of the best locations for wind generation in Victoria is considered as a case study. Hybrid Optimization Model for Electric Renewable (HOMER) is used as a simulating tool for this analysis. This study also presents the influences of storage system in the proposed Hybrid Power System (HPS) allowing energy to be stored during higher generations or lower load demands. In addition this paper also discusses the major integration issues to facilitate the large scale wind energy into the grid for reliable power generation and distribution.

An interval type-2 fuzzy logic system-based method for prediction interval construction

This paper introduces a new non-parametric method for uncertainty quantification through construction of prediction intervals (PIs). The method takes the left and right end points of the type-reduced set of an interval type-2 fuzzy logic system (IT2FLS) model as the lower and upper bounds of a PI. No assumption is made in regard to the data distribution, behaviour, and patterns when developing intervals. A training method is proposed to link the confidence level (CL) concept of PIs to the intervals generated by IT2FLS models. The new PI-based training algorithm not only ensures that PIs constructed using IT2FLS models satisfy the CL requirements, but also reduces widths of PIs and generates practically informative PIs. Proper adjustment of parameters of IT2FLSs is performed through the minimization of a PI-based objective function. A metaheuristic method is applied for minimization of the non-linear non-differentiable cost function. Performance of the proposed method is examined for seven synthetic and real world benchmark case studies with homogenous and heterogeneous noise. The demonstrated results indicate that the proposed method is capable of generating high quality PIs. Comparative studies also show that the performance of the proposed method is equal to or better than traditional neural network-based methods for construction of PIs in more than 90% of cases. The superiority is more evident for the case of data with a heterogeneous noise. © 2014 Elsevier B.V.

Modelling and power quality analysis of a grid-connected solar PV system

Increased concern about global warming coupled with the escalating demand of energy has driven the conventional power system to be more reliable one by integrating Renewable Energies (RE) in to grid. Over the recent years, integration of solar PV forming a gridconnected PV is considered as one of the most promisingtechnologies to the developed countries like Australia to meet the growing demand of energy. This rapid increase in grid connected photovoltaic (PV) systems has made the supply utilities concerned about the drastic effects that have to be considered on the distribution network in particular voltage fluctuations, harmonic distortions and the Power factor for sustainable power generation. However, irrespective of thefact that the utility grid can accommodate the variability of load or irregular solar irradiance, it is essential to study the impact of grid connected PV systems during higher penetration levels as the intermittent nature of solar PV adversely effects the grid characteristics in meeting the load demand. Hence, keeping this in track, this paper examines the grid-connected PV system considering a residential network of Geelong region (38◦.09' S and 144◦.21’ E) and explores the level of impacts considering summer load profile with a change in the level of integrations. Initially, a PV power system network model is developed in Matlab-Simulink environment and the simulations are carried out to explore the impacts of solar PV penetration at low voltage distribution network considering power quality (PQ) issues such as voltage fluctuations, harmonics distortion at different load conditions.

The orexinergic system in rainbow trout Oncorhynchus mykiss and its regulation by dietary lipids

In this study, we report the distribution of orexin A (OXA), orexin B (OXB), and orexin receptor (OX2R) immunoreactive (ir) cells in the hypothalamus and gastrointestinal tract of Oncorhynchus mykiss fed diets with different dietary fatty acid compositions. Trout were fed five iso-energetic experimental diets containing fish oil, or one of four different vegetable oils (olive, sunflower, linseed, and palm oils) as the added dietary lipid source for 12 weeks. OXA, OXB, and OX2R immunoreactive neurons and nervous fibers were identified in the lateral and ventro-medial hypothalamus. OXA, OXB, and OX2R ir cells were found in the mucosa and glands of the stomach and in the mucosa of both the pyloric cecae and intestine. OX2R ir cells were localized in the mucosa layer of both the pyloric cecae and intestine. These immunohistochemical (IHC) results were confirmed via Western blotting. Antibodies against preproorexin (PPO) crossreacted with a band of ∼16 kDa in the hypothalamus, stomach, pyloric cecae, and intestine. Antibodies against OX2R crossreacted with a band of ∼38 kDa in the hypothalamus, pyloric cecae, and intestine. The presence and distribution of OXA, OXB, and OX2R ir cells in the hypothalamus and gastrointestinal tract did not appear to be affected by dietary oils. The presence of orexin system immunoreactive cells in the stomach, pyloric cecae, and intestine of rainbow trout, but not in the enteric nervous system, could suggest a possible role of these peptides as signaling of gastric emptying or endocrine modulation, implying a main local action played by orexins.

Distributed multi-agent scheme to improve dynamic voltage stability of distribution networks

In this paper, a distributed multi-agent scheme is presented for reactive power management with renewable energy sources (RESs). The multi-agent system (MAS) framework is developed for distribution systems to improve the stability which is mostly dominated by voltage and the agents in this framework coordinate among themselves using online information and energy flow. In this paper, the agents basically perform two tasks- reactive power estimation and necessary control actions. The topology of distribution network is used to estimate the required reactive power for maintaining voltage stability where distributed static synchronous compensators (DSTATCOMs) are used to supply this reactive power. The DSTATCOM is controlled by using a linear quadratic regulator (LQR) controller within the agent framework. The proposed scheme is further compared with the conventional approach to validate the simulation results.

Resource distribution influences positive edge effects in a seagrass fish

According to conceptual models, the distribution of resources plays a critical role in determining how organisms distribute themselves near habitat edges. These models are frequently used to achieve a mechanistic understanding of edge effects, but because they are based predominantly on correlative studies, there is need for a demonstration of causality, which is best done through experimentation. Using artificial seagrass habitat as an experimental system, we determined a likely mechanism underpinning edge effects in a seagrass fish. To test for edge effects, we measured fish abundance at edges (0-0.5 m) and interiors (0.5-1 m) of two patch configurations: continuous (single, continuous 9-m2 patches) and patchy (four discrete 1-m2 patches within a 9-m2 area). In continuous configurations, pipefish (Stigmatopora argus) were three times more abundant at edges than interiors (positive edge effect), but in patchy configurations there was no difference. The lack of edge effect in patchy configurations might be because patchy seagrass consisted entirely of edge habitat. We then used two approaches to test whether observed edge effects in continuous configurations were caused by increased availability of food at edges. First, we estimated the abundance of the major prey of pipefish, small crustaceans, across continuous seagrass configurations. Crustacean abundances were highest at seagrass edges, where they were 16% greater than in patch interiors. Second, we supplemented interiors of continuous treatment patches with live crustaceans, while control patches were supplemented with seawater. After five hours of supplementation, numbers of pipefish were similar between edges and interiors of treatment patches, while the strong edge effects were maintained in controls. This indicated that fish were moving from patch edges to interiors in response to food supplementation. These approaches strongly suggest that a numerically dominant fish species is more abundant at seagrass edges due to greater food availability, and provide experimental support for the resource distribution model as an explanation for edge effects.

A Gradient-Type Method For Real-Time State Estimation Of Water Distribution Networks

Drinking water distribution networks risk exposure to malicious or accidental contamination. Several levels of responses are conceivable. One of them consists to install a sensor network to monitor the system on real time. Once a contamination has been detected, this is also important to take appropriate counter-measures. In the SMaRT-OnlineWDN project, this relies on modeling to predict both hydraulics and water quality. An online model use makes identification of the contaminant source and simulation of the contaminated area possible. The objective of this paper is to present SMaRT-OnlineWDN experience and research results for hydraulic state estimation with sampling frequency of few minutes. A least squares problem with bound constraints is formulated to adjust demand class coefficient to best fit the observed values at a given time. The criterion is a Huber function to limit the influence of outliers. A Tikhonov regularization is introduced for consideration of prior information on the parameter vector. Then the Levenberg-Marquardt algorithm is applied that use derivative information for limiting the number of iterations. Confidence intervals for the state prediction are also given. The results are presented and discussed on real networks in France and Germany.

Newly Automated System For Integrated Assessment Of The Conditions Of Underwater Gas Pipelines

An underwater gas pipeline is the portion of the pipeline that crosses a river beneath its bottom. Underwater gas pipelines are subject to increasing dangers as time goes by. An accident at an underwater gas pipeline can lead to technological and environmental disaster on the scale of an entire region. Therefore, timely troubleshooting of all underwater gas pipelines in order to prevent any potential accidents will remain a pressing task for the industry. The most important aspect of resolving this challenge is the quality of the automated system in question. Now the industry doesn't have any automated system that fully meets the needs of the experts working in the field maintaining underwater gas pipelines. Principle Aim of this Research: This work aims to develop a new system of automated monitoring which would simplify the process of evaluating the technical condition and decision making on planning and preventive maintenance and repair work on the underwater gas pipeline. Objectives: Creation a shared model for a new, automated system via IDEF3; Development of a new database system which would store all information about underwater gas pipelines; Development a new application that works with database servers, and provides an explanation of the results obtained from the server; Calculation of the values MTBF for specified pipelines based on quantitative data obtained from tests of this system. Conclusion: The new, automated system PodvodGazExpert has been developed for timely and qualitative determination of the physical conditions of underwater gas pipeline; The basis of the mathematical analysis of this new, automated system uses principal component analysis method; The process of determining the physical condition of an underwater gas pipeline with this new, automated system increases the MTBF by a factor of 8.18 above the existing system used today in the industry.

Multi-Objective Pipe Smoothing Genetic Algorithm For Water Distribution Network Design

This paper describes the formulation of a Multi-objective Pipe Smoothing Genetic Algorithm (MOPSGA) and its application to the least cost water distribution network design problem. Evolutionary Algorithms have been widely utilised for the optimisation of both theoretical and real-world non-linear optimisation problems, including water system design and maintenance problems. In this work we present a pipe smoothing based approach to the creation and mutation of chromosomes which utilises engineering expertise with the view to increasing the performance of the algorithm whilst promoting engineering feasibility within the population of solutions. MOPSGA is based upon the standard Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and incorporates a modified population initialiser and mutation operator which directly targets elements of a network with the aim to increase network smoothness (in terms of progression from one diameter to the next) using network element awareness and an elementary heuristic. The pipe smoothing heuristic used in this algorithm is based upon a fundamental principle employed by water system engineers when designing water distribution pipe networks where the diameter of any pipe is never greater than the sum of the diameters of the pipes directly upstream resulting in the transition from large to small diameters from source to the extremities of the network. MOPSGA is assessed on a number of water distribution network benchmarks from the literature including some real-world based, large scale systems. The performance of MOPSGA is directly compared to that of NSGA-II with regard to solution quality, engineering feasibility (network smoothness) and computational efficiency. MOPSGA is shown to promote both engineering and hydraulic feasibility whilst attaining good infrastructure costs compared to NSGA-II.

Social security effects on income distribution: a counterfactual analysis for Brazil

According to Diamond (1977), one of the reasons for the existence of social security systems is that they function as an income redistribution mechanism. There is an extensive literature that tests whether social security systems produce the desired results in developed countries (mainly for the U.S.A.). Nevertheless, there is not an obvious consensus about this social security property and there is little evidence for developing countries. In this article, we test this property for the Brazilian Social Security System. In addition, we also look at another question which has not been answered yet in the previous literature. Is the trend of social security systems increasingly progressive or regressive? We conclude that the changes in Brazilian Social Security legislation reduced inequality between 1987 and 1996, but only for the elderly. For the other age groups, there is a stable trend. Results for the period between 1996 and 2006 reveal that the Brazilian system is neutral for all cohorts. Therefore, we found out that social security systems are not an effective mechanism for income redistribution, as predicted by previous studies.

The distribution of average and marginal effective tax rates in European Union member states

Macro-based summary indicators of effective tax burdens do not capture differences in effective tax rates facing different sub-groups of the population. They also cannot provide information on the level or distribution of the marginal effective tax rates thought to influence household behaviour. I use EUROMOD, an EU-wide tax-benefit microsimulation model, to compute distributions of average and marginal effective tax rates across the household population in fourteen European Union Member States. Using different definitions of ‘net taxes’, the tax base and the unit of analysis I present a range of measures showing the contribution of the tax-benefit system to household incomes, the average effective tax rates applicable to income from labour and marginal effective tax rates faced by working men and women. In a second step, effective tax rates are broken down to separately show the influence of each type of tax-benefit instrument. The results show that measures of effective tax rates vary considerably depending on incomes, labour market situations and family circumstances. Using single averages or macro-based indicators will therefore provide an inappropriate picture of tax burdens faced by large parts of the population.