Combined nonparametric prediction intervals for wind power generation

Prediction intervals (PIs) are a promising tool for quantification of uncertainties associated with point forecasts of wind power. However, construction of PIs using parametric methods is questionable, as forecast errors do not follow a standard distribution. This paper proposes a nonparametric method for construction of reliable PIs for neural network (NN) forecasts. A lower upper bound estimation (LUBE) method is adapted for construction of PIs for wind power generation. A new framework is proposed for synthesizing PIs generated using an ensemble of NN models in the LUBE method. This is done to guard against NN performance instability in generating reliable and informative PIs. A validation set is applied for short listing NNs based on the quality of PIs. Then, PIs constructed using filtered NNs are aggregated to obtain combined PIs. Performance of the proposed method is examined using data sets taken from two wind farms in Australia. Simulation results indicate that the quality of combined PIs is significantly superior to the quality of PIs constructed using NN models ranked and filtered by the validation set.

Teaching critical reflection: a tool for transformative learning in social work?

In an Australian Bachelor of Social Work degree, critical reflection is a process explicitly taught in a fourth year subject to students who have returned from their first field placement experience in agencies delivering social work programmes. The purpose of teaching critical reflection is to enable social work students to become autonomous and critical thinkers who can reflect on society, the role of social work and social work practices. The way critical reflection is taught in this fourth year social work unit relates closely to the aims of transformative learning. Transformative learning aims to assist students to become autonomous thinkers. Specifically, the critical reflection process taught in this subject aims to assist students to recognise their own and other people's frames of reference, to identify the dominant discourses circulating in making sense of their experience, to problematise their taken-for -granted ‘lived experience’, to reconceptualise identity categories, disrupt assumed causal relations and to reflect on how power relations are operating. Critical reflection often draws on many theoretical frameworks to enable the recognition of current modes of thinking and doing. In this paper, we will draw primarily on how post-structural theories, specifically Foucault's theorising, disrupt several taken-for-granted concepts in social work.

External policy influence and higher education reform in Ethiopia : understanding symbolic power of the World Bank

Increasingly national policy processes are intersected with and affected by global policy actors and ideas. In aid-recipient countries such as Ethiopia, donors use financial and non-financial means to influence national policy decisions and directions. This paper is about the non-financial influence of the World Bank (WB) in the Ethiopian higher education policy reform. Using Pierre Bourdieu’s concept of symbolic power as a ‘thinking tool’, the paper aims to shed light on forms of symbolic capital that the Bank uses to generate a ‘misrecognisable’ form of power that regulates the HE policy process in Ethiopia. The findings show that the WB transforms its symbolic capital of recognition and legitimacy to establish a ‘shared misrecognition’ and thereby make its policy prescriptions implicit and hence acceptable to local policy agents. The Bank uses knowledge-based regulatory instruments to induce compliance to its neoliberal policy prescriptions. The paper therefore underscores the value of symbol power as an analytical framework to understand elusive but critical role of donors in policy processes of aid recipient countries.

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.

A novel fuzzy multi-objective framework to construct optimal prediction intervals for wind power forecast

The forecasting behavior of the high volatile and unpredictable wind power energy has always been a challenging issue in the power engineering area. In this regard, this paper proposes a new multi-objective framework based on fuzzy idea to construct optimal prediction intervals (Pis) to forecast wind power generation more sufficiently. The proposed method makes it possible to satisfy both the PI coverage probability (PICP) and PI normalized average width (PINAW), simultaneously. In order to model the stochastic and nonlinear behavior of the wind power samples, the idea of lower upper bound estimation (LUBE) method is used here. Regarding the optimization tool, an improved version of particle swam optimization (PSO) is proposed. In order to see the feasibility and satisfying performance of the proposed method, the practical data of a wind farm in Australia is used as the case study.

A new fuzzy-based combined prediction interval for wind power forecasting

This paper makes use of the idea of prediction intervals (PIs) to capture the uncertainty associated with wind power generation in power systems. Since the forecasting errors cannot be appropriately modeled using distribution probability functions, here we employ a powerful nonparametric approach called lower upper bound estimation (LUBE) method to construct the PIs. The proposed LUBE method uses a new framework based on a combination of PIs to overcome the performance instability of neural networks (NNs) used in the LUBE method. Also, a new fuzzy-based cost function is proposed with the purpose of having more freedom and flexibility in adjusting NN parameters used for construction of PIs. In comparison with the other cost functions in the literature, this new formulation allows the decision-makers to apply their preferences for satisfying the PI coverage probability and PI normalized average width individually. As the optimization tool, bat algorithm with a new modification is introduced to solve the problem. The feasibility and satisfying performance of the proposed method are examined using datasets taken from different wind farms in Australia.

Optimal coordination of G2V and V2G to support power grids with high penetration of renewable energy

Electric vehicles (EVs) have recently gained much popularity as a green alternative to fossil-fuel cars and a feasible solution to reduce air pollution in big cities. The use of EVs can also be extended as a demand response tool to support high penetration of renewable energy (RE) sources in future smart grid. Based on the certainty equivalent adaptive control (CECA) principle and a customer participation program, this paper presents a novel control strategy using optimization technique to coordinate not only the charging but also the discharging of EV batteries to deal with the intermittency in RE production. In addition, customer charging requirements and schedules are incorporated into the optimization algorithm to ensure customer satisfaction, and further improve the control performance. The merits of this scheme are its simplicity, efficiency, robustness and readiness for practical applications. The effectiveness of the proposed control algorithm is demonstrated by computer simulations of a power system with high level of wind energy integration.

A computational tool to assist the analysis of the transformer behavior related to lightning

This paper proposes the application of computational intelligence techniques to assist complex problems concerning lightning in transformers. In order to estimate the currents related to lightning in a transformer, a neural tool is presented. ATP has generated the training vectors. The input variables used in Artificial Neural Networks (ANN) were the wave front time, the wave tail time, the voltage variation rate and the output variable is the maximum current in the secondary of the transformer. These parameters can define the behavior and severity of lightning. Based on these concepts and from the results obtained, it can be verified that the overvoltages at the secondary of transformer are also affected by the discharge waveform in a similar way to the primary side. By using the tool developed, the high voltage process in the distribution transformers can be mapped and estimated with more precision aiding the transformer project process, minimizing empirics and evaluation errors, and contributing to minimize the failure rate of transformers. (C) 2011 Elsevier Ltd. All rights reserved.

HOW TO EFFICIEN TLY INCORPORATE FACTS DEVICES IN OPTIMAL ACTIVE POWER FLOW MODEL

This paper presents for the first time how to easily incorporate facts devices in an optimal active power flow model such that an efficient interior-point method may be applied. The optimal active power flow model is based on a network flow approach instead of the traditional nodal formulation that allows the use of an efficiently predictor-corrector interior point method speed up by sparsity exploitation. The mathematical equivalence between the network flow and the nodal models is addressed, as well as the computational advantages of the former considering the solution by interior point methods. The adequacy of the network flow model for representing facts devices is presented and illustrated on a small 5-bus system. The model was implemented using Matlab and its performance was evaluated with the 3,397-bus and 4,075-branch Brazilian power system which show the robustness and efficiency of the formulation proposed. The numerical results also indicate an efficient tool for optimal active power flow that is suitable for incorporating facts devices.

Robust fault diagnosis in power distribution systems based on fuzzy ARTMAP neural network-aided evidence theory

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Simulation Tools of DC-DC Converters for Power Electronics Education

This paper presents interactive simulation tools to support the enhancement of power electronics education considering DC to DC converters. These interactive tools make use of the benefits of Java language to provide a dynamic and interactive visualization of simulations in steady-state for idealized non-isolated DC to DC converters. Additionally, this paper discusses the features and the usage of the interactive educational tools to serve as a first design tool for the laboratory experiments in the power electronics courses. In this way, some results were confronted with a well-known simulator package and with experimental results in order to validate the developed interactive simulation tools.

Simulation Tools for Power Electronics Courses Based on Java Technologies

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The instantaneous-space-phasor a powerful diagnosis tool

This paper presents the instantaneous-space-phasor (ISP) definition and describes its properties and possible applications for three-phase systems. It is shown that the ISP provides the mathematical base for a new approach to the measurement of active, reactive, and apparent power. Moreover, the ISP helps separate the positive and negative-sequence components and fits perfectly into the Buchholz-Goodhue apparent power definition.

Lubricating coating prepared by PIIID on a forming tool

In this work, the performance of a-C: H films produced by the hybrid Plasma Immersion Ion Implantation and Deposition technique as lubricating layers for a steel forming tool has been investigated. Hardened steel (AISI M2, 64 HRC) plates coated with a commercial TiN layer were used as substrates and the films were deposited in a vacuum chamber fitted with two parallel-plate electrodes. The discharges were generated in atmospheres composed of 91% C2H2 and 9% Ar by the application of radiofrequency power (13.56 MHz, 100 W) to the upper electrode while the lower one, also used as the sample holder, was biased with high voltage negative pulses (3.6 kV, 30 mu s, 300 Hz). A deposition time of 840 s was used. The effects of the gas pressure, p, on thickness, molecular structure, wettability, surface morphology and topography, hardness and friction coefficient of the films lwere investigated. Film thickness increased from 0.3 to 0.5 mu m when p was increased from 2.7 to 16.5 Pa. Generally, the films were slightly hydrophilic, with contact angles of around 84 degrees, and the deposition decreased the roughness of the steel. A polymer-like structure was detected in high pressure depositions and an amorphous carbon structure derived from the low pressure procedures. Hardness decreased from 8.2 to 7.0 GPa with increasing p. Improvement in tribological performance was indicated by the fall in the friction coefficient from 0.5 to 0.2 as the deposition pressure was reduced. Operating at the latter value (of mu) would lead to a significant reduction in wear and hence to significant economy in diverse industrial applications.

Distribution line models analysis for loss calculation within three-phase three-wire power flow algorithms

Three-phase three-wire power flow algorithms, as any tool for power systems analysis, require reliable impedances and models in order to obtain accurate results. Kron's reduction procedure, which embeds neutral wire influence into phase wires, has shown good results when three-phase three-wire power flow algorithms based on current summation method were used. However, Kron's reduction can harm reliabilities of some algorithms whose iterative processes need loss calculation (power summation method). In this work, three three-phase three-wire power flow algorithms based on power summation method, will be compared with a three-phase four-wire approach based on backward-forward technique and current summation. Two four-wire unbalanced medium-voltage distribution networks will be analyzed and results will be presented and discussed. © 2004 IEEE.