Volatility forecasting with range models: An evaluation of new alternatives to the CARR model

The aim of this paper is to analyze the forecasting ability of the CARR model proposed by Chou (2005) using the S&P 500. We extend the data sample, allowing for the analysis of different stock market circumstances and propose the use of various range estimators in order to analyze their forecasting performance. Our results show that there are two range-based models that outperform the forecasting ability of the GARCH model. The Parkinson model is better for upward trends and volatilities which are higher and lower than the mean while the CARR model is better for downward trends and mean volatilities.

Light pollution and energy efficiency: a case study of the village of Vialonga

Since industrialization and the formation of larger urban centers in the nineteenth century, pollution of the environment was always present in daily life in various ways, namely in the form of light. Light pollution can cause various consequences, both for humans and for their ecosystem, producing effects on environmental, social, economic and scientific level. In Portugal, the lighting is responsible for 3% of total electricity consumption, energy costs are in some cases more than 50% towards the costs incurred by municipalities with energy, checking-in recent years a trend similar to that improvement of illumination levels in the region (about 4 to 5% per year). Proper use of lighting brings many benefits both to the citizen and environment, since greater energy efficiency can contribute to reducing CO2 emissions, energy costs, as well as to decrease the use of resources not-renewable and/or contamination of renewable resources, which can occurs in the process of obtaining electricity. The present study has a main goal to analyze the illuminance levels associated to the public lighting of the village of Vialonga, Vila Franca de Xira (Portugal), to verify if it is efficient. The aim is also to relate the efficiency of street lighting with the existence of light pollution.

Effect of the number of shells on the pressure and energy of two-dimensional free bubble clusters

We have performed Surface Evolver simulations of two-dimensional hexagonal bubble clusters consisting of a central bubble of area lambda surrounded by s shells or layers of bubbles of unit area. Clusters of up to twenty layers have been simulated, with lambda varying between 0.01 and 100. In monodisperse clusters (i.e., for lambda = 1) [M.A. Fortes, F Morgan, M. Fatima Vaz, Philos. Mag. Lett. 87 (2007) 561] both the average pressure of the entire Cluster and the pressure in the central bubble are decreasing functions of s and approach 0.9306 for very large s, which is the pressure in a bubble of an infinite monodisperse honeycomb foam. Here we address the effect of changing the central bubble area lambda. For small lambda the pressure in the central bubble and the average pressure were both found to decrease with s, as in monodisperse clusters. However, for large,, the pressure in the central bubble and the average pressure increase with s. The average pressure of large clusters was found to be independent of lambda and to approach 0.9306 asymptotically. We have also determined the cluster surface energies given by the equation of equilibrium for the total energy in terms of the area and the pressure in each bubble. When the pressures in the bubbles are not available, an approximate equation derived by Vaz et al. [M. Fatima Vaz, M.A. Fortes, F. Graner, Philos. Mag. Lett. 82 (2002) 575] was shown to provide good estimations for the cluster energy provided the bubble area distribution is narrow. This approach does not take cluster topology into account. Using this approximate equation, we find a good correlation between Surface Evolver Simulations and the estimated Values of energies and pressures. (C) 2008 Elsevier B.V. All rights reserved.

Solid-State Bipolar Marx Converter with Output Transformer and Energy Recovery

The purpose of this paper is to present and discuss a general HV topology of the solid-state Marx modulator, for unipolar or bipolar generation connected with a step-up transformer to increase the output voltage applied to a resistive load. Due to the use of an output transformer, discussion about the reset of the transformer is made to guarantee zero average voltage applied to the primary. It is also discussed the transformer magnetizing energy recovering back to the energy storage capacitors. Simulation results for a circuit that generates 100 kV pulses using 1000 V semiconductors are presented and discussed regarding the voltage and current stress on the semiconductors and result obtained.

A DC-DC Step-Up mu-Power Converter for Energy Harvesting Applications, Using Maximum Power PointTracking, Based on Fractional Open Circuit Voltage

A DC-DC step-up micro power converter for solar energy harvesting applications is presented. The circuit is based on a switched-capacitorvoltage tripler architecture with MOSFET capacitors, which results in an, area approximately eight times smaller than using MiM capacitors for the 0.131mu m CMOS technology. In order to compensate for the loss of efficiency, due to the larger parasitic capacitances, a charge reutilization scheme is employed. The circuit is self-clocked, using a phase controller designed specifically to work with an amorphous silicon solar cell, in order to obtain themaximum available power from the cell. This will be done by tracking its maximum power point (MPPT) using the fractional open circuit voltage method. Electrical simulations of the circuit, together with an equivalent electrical model of an amorphous silicon solar cell, show that the circuit can deliver apower of 1132 mu W to the load, corresponding to a maximum efficiency of 66.81%.

A risk-averse optimization model for trading wind energy in a market environment under uncertainty

In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.

A Step-up mu-Power Converter for Solar Energy Harvesting Applications, using Hill Climbing Maximum Power Point Tracking

This paper presents a step-up micro-power converter for solar energy harvesting applications. The circuit uses a SC voltage tripler architecture, controlled by an MPPT circuit based on the Hill Climbing algorithm. This circuit was designed in a 0.13 mu m CMOS technology in order to work with an a-Si PV cell. The circuit has a local power supply voltage, created using a scaled down SC voltage tripler, controlled by the same MPPT circuit, to make the circuit robust to load and illumination variations. The SC circuits use a combination of PMOS and NMOS transistors to reduce the occupied area. A charge re-use scheme is used to compensate the large parasitic capacitors associated to the MOS transistors. The simulation results show that the circuit can deliver a power of 1266 mu W to the load using 1712 mu W of power from the PV cell, corresponding to an efficiency as high as 73.91%. The simulations also show that the circuit is capable of starting up with only 19% of the maximum illumination level.

Application of adaptive neuro-fuzzy inference for wind power short-term forecasting

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Numerical results are presented and conclusions are duly drawn. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Real-time energy resources scheduling considering intensive wind penetration

The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem due to the high quantity of variables and constraints. In this paper the main goal is to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixedinteger non-linear programming approach. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Hybrid Wavelet-PSO-ANFIS Approach for Short-Term Electricity Prices Forecasting

A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system, is proposed in this paper for short-term electricity prices forecasting in a competitive market. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Finally, conclusions are duly drawn.

Energy resource scheduling in a real distribution network managed by several virtual power players

Smart Grids (SGs) appeared as the new paradigm for power system management and operation, being designed to integrate large amounts of distributed energy resources. This new paradigm requires a more efficient Energy Resource Management (ERM) and, simultaneously, makes this a more complex problem, due to the intensive use of distributed energy resources (DER), such as distributed generation, active consumers with demand response contracts, and storage units. This paper presents a methodology to address the energy resource scheduling, considering an intensive use of distributed generation and demand response contracts. A case study of a 30 kV real distribution network, including a substation with 6 feeders and 937 buses, is used to demonstrate the effectiveness of the proposed methodology. This network is managed by six virtual power players (VPP) with capability to manage the DER and the distribution network.

Hydro energy systems management in Portugal: Profit-based evaluation of a mixed-integer nonlinear approach

In this paper, a novel mixed-integer nonlinear approach is proposed to solve the short-term hydro scheduling problem in the day-ahead electricity market, considering not only head-dependency, but also start/stop of units, discontinuous operating regions and discharge ramping constraints. Results from a case study based on one of the main Portuguese cascaded hydro energy systems are presented, showing that the proposedmixed-integer nonlinear approach is proficient. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

Energy resource scheduling considering reactive power management

The reactive power management is an important task in future power systems. The control of reactive power allows the increase of distributed energy resources penetration as well as the optimal operation of distribution networks. Currently, the control of reactive power is only controlled in large power units and in high and very high voltage substations. In this paper a reactive power control in smart grids paradigm is proposed, considering the management of distributed energy resources and of the distribution network by an aggregator namely Virtual Power Player (VPP).

Protection of wind energy systems against the indirect effects of lightning

This paper is concerned with the protection of wind energy systems against the indirect effects of lightning. As wind energy is gaining increasing importance throughout the world, lightning damages involving wind energy systems have come to be regarded with more attention. Nevertheless, there are still very few studies in Portugal regarding lightning protection of wind energy systems using models of the Electro-Magnetic Transients Program (EMTP). Hence, a new case study is presented in this paper, based on a wind turbine with an interconnecting transformer, considering that lightning strikes the soil near the tower at a distance such that galvanic coupling occurs through the grounding electrode. Computer simulations obtained by using EMTP-RV are presented and conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.

Short-term scheduling considering five-minute and hour-ahead energy resource management

The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.