Robustness of Damping Control Implemented by Energy Storage Systems Installed in Power Systems

An energy storage system (ESS) installed in a power system can effectively damp power system oscillations through controlling exchange of either active or reactive power between the ESS and power system. This paper investigates the robustness of damping control implemented by the ESS to the variations of power system operating conditions. It proposes a new analytical method based on the well-known equal-area criterion and small-signal stability analysis. By using the proposed method, it is concluded in the paper that damping control implemented by the ESS through controlling its active power exchange with the power system is robust to the changes of power system operating conditions. While if the ESS damping control is realized by controlling its reactive power exchange with the power system, effectiveness of damping control changes with variations of power system operating condition. In the paper, an example power system installed with a battery ESS (BESS) is presented. Simulation results confirm the analytical conclusions made in the paper about the robustness of ESS damping control. Laboratory experiment of a physical power system installed with a 35kJ/7kW SMES (Superconducting Magnetic Energy Storage) was carried out to evaluate theoretical study. Results are given in the paper, which demonstrate that effectiveness of SMES damping control realized through regulating active power is robust to changes of load conditions of the physical power system.

Can we meet targets for biofuels and renewable energy in transport given the constraints imposed by policy in agriculture and energy?

The deployment of biofuels is significantly affected by policy in energy and agriculture. In the energy arena, concerns regarding the sustainability of biofuel systems and their impact on food prices led to a set of sustainability criteria in EU Directive 2009/28/EC on Renewable Energy. In addition, the 10% biofuels target by 2020 was replaced with a 10% renewable energy in transport target. This allows the share of renewable electricity used by electric vehicles to contribute to the mix in achieving the 2020 target. Furthermore, only biofuel systems that effect a 60% reduction in greenhouse gas emissions by 2020 compared with the fuel they replace are allowed to contribute to meeting the target. In the agricultural arena, cross-compliance (which is part of EU Common Agricultural Policy) dictates the allowable ratio of grassland to total agricultural land, and has a significant impact on which biofuels may be supported. This paper outlines the impact of these policy areas and their implications for the production and use of biofuels in terms of the 2020 target for 10% renewable transport energy, focusing on Ireland. The policies effectively impose constraints on many conventional energy crop biofuels and reinforce the merits of using biomethane, a gaseous biofuel. The analysis shows that Ireland can potentially satisfy 15% of renewable energy in transport by 2020 (allowing for double credit for biofuels from residues and ligno-cellulosic materials, as per Directive 2009/28/EC) through the use of indigenous biofuels: grass biomethane, waste and residue derived biofuels, electric vehicles and rapeseed biodiesel. © 2010 Elsevier Ltd. All rights reserved.

Capability Curve Based Enhanced Reactive Power Control Strategy for Stability Enhancement and Network Voltage Management

Reactive power has become a vital resource in modern electricity networks due to increased penetration of distributed generation. This paper examines the extended reactive power capability of DFIGs to improve network stability and capability to manage network voltage profile during transient faults and dynamic operating conditions. A coordinated reactive power controller is designed by considering the reactive power capabilities of the rotor-side converter (RSC) and the grid-side converter (GSC) of the DFIG in order to maximise the reactive power support from DFIGs. The study has illustrated that, a significant reactive power contribution can be obtained from partially loaded DFIG wind farms for stability enhancement by using the proposed capability curve based reactive power controller; hence DFIG wind farms can function as vital dynamic reactive power resources for power utilities without commissioning additional dynamic reactive power devices. Several network adaptive droop control schemes are also proposed for network voltage management and their performance has been investigated during variable wind conditions. Furthermore, the influence of reactive power capability on network adaptive droop control strategies has been investigated and it has also been shown that enhanced reactive power capability of DFIGs can substantially improve the voltage control performance.

A multi vector energy analysis for interconnected power and gas systems

This paper presents the first multi vector energy analysis for the interconnected energy systems of Great Britain (GB) and Ireland. Both systems share a common high penetration of wind power, but significantly different security of supply outlooks. Ireland is heavily dependent on gas imports from GB, giving significance to the interconnected aspect of the methodology in addition to the gas and power interactions analysed. A fully realistic unit commitment and economic dispatch model coupled to an energy flow model of the gas supply network is developed. Extreme weather events driving increased domestic gas demand and low wind power output were utilised to increase gas supply network stress. Decreased wind profiles had a larger impact on system security than high domestic gas demand. However, the GB energy system was resilient during high demand periods but gas network stress limited the ramping capability of localised generating units. Additionally, gas system entry node congestion in the Irish system was shown to deliver a 40% increase in short run costs for generators. Gas storage was shown to reduce the impact of high demand driven congestion delivering a reduction in total generation costs of 14% in the period studied and reducing electricity imports from GB, significantly contributing to security of supply.

A novel methodology for analysis of large scale interconnected power and gas systems

The European Union continues to exert a large influence on the direction of member states energy policy. The 2020 targets for renewable energy integration have had significant impact on the operation of current power systems, forcing a rapid change from fossil fuel dominated systems to those with high levels of renewable power. Additionally, the overarching aim of an internal energy market throughout Europe has and will continue to place importance on multi-jurisdictional co-operation regarding energy supply. Combining these renewable energy and multi-jurisdictional supply goals results in a complicated multi-vector energy system, where the understanding of interactions between fossil fuels, renewable energy, interconnection and economic power system operation is increasingly important. This paper provides a novel and systematic methodology to fully understand the changing dynamics of interconnected energy systems from a gas and power perspective. A fully realistic unit commitment and economic dispatch model of the 2030 power systems in Great Britain and Ireland, combined with a representative gas transmission energy flow model is developed. The importance of multi-jurisdictional integrated energy system operation in one of the most strategically important renewable energy regions is demonstrated.

A quality-scalable and energy-efficient approach for spectral analysis of heart rate variability

Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case. 

Determining generators' contribution to loads and line flows & losses considering loop flows

This paper presents a new method for calculating the individual generators' shares in line flows, line losses and loads. The method is described and illustrated on active power flows, but it can be applied in the same way to reactive power flows.

Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.

Track displacement and energy loss in a railway embankment

The mainline railway track between Dublin and Belfast was constructed during the 1850s, with substantial lengths of railway embankment constructed over soft, peaty soils. In recent years Northern Ireland Railways (NIR) has noticed that the sections of the railway track constructed on these peaty soils have been deteriorating at an increasing rate. Train speeds have been reduced in response to concerns that cyclic track displacements appear to be increasing over time in response to train loading. Track maintenance has also increased significantly. The research described in this paper was undertaken to quantify the response to cyclic train loading of two portions of this track founded on peaty soils. Track displacements were recorded using a sensor system specifically created for this project. The sensor consisted of a photosensitive array, mounted on the sleepers, and a laser, which was targeted onto the photosensitive array from a location outside the area of influence of train loading. Track deflections from 5 to 20 mm were measured under train speeds from near zero to over 120 km/h. The temporal variation in track displacement was used to calibrate an analytical (Winkler) model. This analysis suggests that the deformation of the embankment under train loading was not due to dynamic excitation but rather to static deformation of the poor-quality fill and soft foundation materials. As a consequence, the analytical model highlighted that train speed has limited effect on the magnitude of the deflection of the embankment within NIR operating speeds, but has the potential to significantly reduce the power lost to the damping within the embankment and subgrade.

Investigation of a ship's propeller jet using momentum decay and energy decay

Previous researchers use the velocity decay as an input to investigate the ship’s propeller jet induced scour. A researcher indicated that most of the equations used to predict the stability of various protection systems are often missing a physical background. The momentum decay and energy decay are currently proposed as an initial input for seabed scouring investigation, which are more sensible in physics. Computational fluid dynamics (CFD) and laser Doppler anemometry (LDA) experiments are used to obtain the velocity data and then transforming into momentum and energy decays. The findings proposed several exponential equations of velocity, momentum and energy decays to estimate the region exposed to the seabed scouring.

Electric Vehicles and Energy Storage: a case study on Ireland

Renewable energy is generally accepted as an important component of future electricity grids. In late 2008, the Government of the Republic of Ireland set a target of 10% of all vehicles in its transport fleet be powered by electricity by 2020. This paper examines the potential contributions Electric Vehicles (EVs) can make to facilitate increased electricity generation from variable renewable sources such as wind generation in the Republic of Ireland. It also presents an overview of the technical and economic issues associated with this target.