Modelling gas storage with compressed air energy storage in a system with large wind penetrations

Installed wind capacity in the European Union is expected to continue to increase due to renewable energy targets and obligations to reduce greenhouse gas emissions. Renewable energy sources such as wind power are variable sources of power. Energy storage technologies are useful to manage the issues associated with variable renewable energy sources and align non-dispatchable renewable energy generation with load demands. Energy storage technologies can play different roles in electric power systems and can be used in each of the steps of the electric power supply chain. Moreover, large scale energy storage systems can act as renewable energy integrators by smoothening the variability of large penetrations of wind power. Compress Air Energy Storage is one such technology. The aim of this paper is to examine the technical and economic feasibility of a combined gas storage and compressed air energy storage facility in the all-island Single Electricity Market of Northern Ireland and the Republic of Ireland in order to optimise power generation and wind power integration. This analysis is undertaken using the electricity market software PLEXOS ® for power systems by developing a model of a combined facility in 2020.

The technical merits of turbogenerating shown through the design, validation and implementation of a 1 dimensional engine model

Turbocompounding is the process of recovering a proportion of an engine’s fuel energy that would otherwise be lost in the exhaust process and adding it to the output power. This was first seen in the 1930s and is carried out by coupling an exhaust gas turbine to the crankshaft of a reciprocating engine. It has since been recognised that coupling the power turbine to an electrical generator instead of the crankshaft has the potential to reduce the fuel consumption further with the added flexibility of being able to decide how this recovered energy is used. The electricity generated can be used in automotive applications to assist the crankshaft using a flywheel motor generator or to power ancillaries that would otherwise have run off the crankshaft. In the case of stationary power plants, it can assist the electrical power output. Decoupling the power turbine from the crankshaft and coupling it to a generator allows the power electronics to control the turbine speed independently in order to optimise the specific fuel consumption for different engine operating conditions. This method of energy recapture is termed ‘turbogenerating’.

This paper gives a brief history of turbocompounding and its thermodynamic merits. It then moves on to give an account of the validation of a turbogenerated engine model. The model is then used to investigate what needs to be done to an engine when a turbogenerator is installed. The engine being modelled is used for stationary power generation and is fuelled by an induced biogas with a small portion of palm oil being injected into the cylinder to initiate combustion by compression ignition. From these investigations, optimum settings were found that result in a 10.90% improvement in overall efficiency. These savings relate to the same engine without a turbogenerator installed operating with fixed fuelling.

Regulation of arsenic mobility on basaltic glass surfaces by speciation and pH

The importance of geothermal energy as a source for electricity generation and district heating has increased over recent decades. Arsenic can be a significant constituent of the geothermal fluids pumped to the surface during power generation. Dissolved As exists in different oxidation states, mainly as As(III) and As(V), and the charge of individual species varies with pH. Basaltic glass is one of the most important rock types in many high-temperature geothermal fields. Static batch and dynamic column experiments were combined to generate and validate sorption coefficients for As(III) and As(V) in contact with basaltic glass at pH 3-10. Validation was carried out by two empirical kinetic models and a surface complexation model (SCM). The SCM provided a better fit to the experimental column data than kinetic models at high pH values. However, in certain circumstances, an adequate estimation of As transport in the column could not be attained without incorporation of kinetic reactions. The varying mobility with pH was due to the combined effects of the variable charge of the basaltic glass with the pH point of zero charge at 6.8 and the individual As species as pH shifted, respectively. The mobility of As(III) decreased with increasing pH. The opposite was true for As(V), being nearly immobile at pH 3 to being highly mobile at pH 10. Incorporation of appropriate sorption constants, based on the measured pH and Eh of geothermal fluids, into regional groundwater-flow models should allow prediction of the As(III) and As(V) transport from geothermal systems to adjacent drinking water sources and ecosystems.

Analysis of Two-Speed Wind Farm Operation From Grid-Side Measurements

This paper analyzes data captured by a phasor measurement unit at a wind farm, employing two-speed induction generators, and investigates aspects of the control system's interaction with the power system. Composite superimposed transient events are proposed as a method to improve the quality of the analysis and reduce errors caused by unknowns, such as wind speed variation. A Mathworks SimPowerSystems model validates the inertia contribution of the wind farm, which is an important parameter in power systems with high wind penetration. Transients caused by turbine speed transitions are identified and explained. The analysis also highlights areas where wind farm control should be improved if useful inertia contribution is to be provided.

Man-in-the-Middle Attack Test-bed Investigating Cyber-security Vulnerabilities in Smart Grid SCADA Systems

The increased complexity and interconnectivity of Supervisory Control and Data Acquisition (SCADA) systems in the Smart Grid has exposed them to a wide range of cyber-security issues, and there are a multitude of potential access points for cyber attackers. This paper presents a SCADA-specific cyber-security test-bed which contains SCADA software and communication infrastructure. This test-bed is used to investigate an Address Resolution Protocol (ARP) spoofing based man-in-the-middle attack. Finally, the paper proposes a future work plan which focuses on applying intrusion detection and prevention technology to address cyber-security issues in SCADA systems.

Day-Ahead Optimal Charging/Discharging Scheduling for Electric Vehicles in Micro-Grids

A micro-grid is an autonomous system which can be operated and connected to an external system or isolated with the help of energy storage systems (ESSs). While the daily output of distributed generators (DGs) strongly depends on the temporal distribution of natural resources such as wind and solar, unregulated electric vehicle (EV) charging demand will deteriorate the imbalance between the daily load and generation curves. In this paper, a statistical model is presented to describe daily EV charging/discharging behaviour. An optimisation problem is proposed to obtain economic operation for the micro-grid based on this model. In day-ahead scheduling, with estimated information of power generation and load demand, optimal charging/discharging of EVs during 24 hours is obtained. A series of numerical optimization solutions in different scenarios is achieved by serial quadratic programming. The results show that optimal charging/discharging of EVs, a daily load curve can better track the generation curve and the network loss and required ESS capacity are both decreased. The paper also demonstrates cost benefits for EVs and operators.

Rule-Based Intrusion Detection System for SCADA Networks

Increased complexity and interconnectivity of Supervisory Control and Data Acquisition (SCADA) systems in Smart Grids potentially means greater susceptibility to malicious attackers. SCADA systems with legacy communication infrastructure have inherent cyber-security vulnerabilities as these systems were originally designed with little consideration of cyber threats. In order to improve cyber-security of SCADA networks, this paper presents a rule-based Intrusion Detection System (IDS) using a Deep Packet Inspection (DPI) method, which includes signature-based and model-based approaches tailored for SCADA systems. The proposed signature-based rules can accurately detect several known suspicious or malicious attacks. In addition, model-based detection is proposed as a complementary method to detect unknown attacks. Finally, proposed intrusion detection approaches for SCADA networks are implemented and verified using a ruled based method.

Modal Extraction for Wind Turbines using Moving Window Subspace Identification

This paper proposes a method for wind turbine mode identification using the multivariable output error statespace (MOESP) identification algorithm. The paper incorporates a fast moving window QR decomposition and propagator method from array signal processing, yielding a moving window subspace identification algorithm. The algorithm assumes that the system order is known as a priori and remains constant during identification. For the purpose of extracting modal information for turbines modelled as a linear parameter varying (LPV) system, the algorithm is applicable since a nonlinear system can be approximated as a piecewise time invariant system in consecutive data windows. The algorithm is exemplified using numerical simulations which show that the moving window algorithm can track the modal information. The paper also demonstrates that the low computational burden of the algorithm, compared to conventional batch subspace identification, has significant implications for online implementation.

Wind Farm Induced Oscillations

The impact of power fluctuations arising from fixed-speed wind turbines on the magnitude and frequency of inter-area oscillations was investigated. The authors used data acquisition equipment to record the power flow on the interconnector between the Northern Ireland and Republic of Ireland systems. By monitoring the interconnector oscillation using a fast Fourier transform, it was possible to determine the magnitude and frequency of the inter-area oscillation between the Northern Ireland electricity system and that of the electricity supply board. Analysis was preformed to determine the relationship (if any) between the inter-area oscillation and the observed wind power generation at the corresponding time. Subsequently, regression analysis was introduced to model this relationship between the FFT output and the wind power generation. The effect of conventional generators on the magnitude and frequency of the inter-area oscillation was also considered.

Experimentally validated partial least squares model for dynamic line rating

This study presents a model based on partial least squares (PLS) regression for dynamic line rating (DLR). The model has been verified using data from field measurements, lab tests and outdoor experiments. Outdoor experimentation has been conducted both to verify the model predicted DLR and also to provide training data not available from field measurements, mainly heavily loaded conditions. The proposed model, unlike the direct measurement based DLR techniques, enables prediction of line rating for periods ahead of time whenever a reliable weather forecast is available. The PLS approach yields a very simple statistical model that accurately captures the physical performance of the conductor within a given environment without requiring a predetermination of parameters as required by many physical modelling techniques. Accuracy of the PLS model has been tested by predicting the conductor temperature for measurement sets other than those used for training. Being a linear model, it is straightforward to estimate the conductor ampacity for a set of predicted weather parameters. The PLS estimated ampacity has proven its accuracy through an outdoor experiment on a piece of the line conductor in real weather conditions.

The reaction path of CO and Fe2O3 in a chemical-looping combustion system

The reaction mechanism of CO and Fe₂O₃ in a chemical-looping combustion (CLC) was studied based on density functional theory (DFT) at B3LYP level in this paper. The structures of all reactants, intermediate, transition structures and products of this reaction had been optimized and characterized. The reaction path was validated by means of the intrinsic reaction coordinate (IRC) approach. The result showed that the reaction was divided into two steps, the adsorbed CO molecule on Fe ₂O₃ surface formed a medium state with one broken Fe-O bond in step1, and in step2, O atom broken here oxidized a subsequent CO molecule in the fuel reactor. Thus, Fe₂O₃ molecule transport O from air to oxide CO continually in the CLC process. The activation energy and rate coefficients of the two steps were also obtained.

The optimized geometric structure of the (0001) surface of α-Fe 2O3

A tridimensional model of α-Fe₂O₃ and models of (0001) and (1102) surfaces on it were built. Then the structural optimization of the (0001) surface was presented which explored the influence of the system scale and the terminal surface configuration. Four different models including two different system scale structures (MODEL□ and MODEL□) and two different terminal structures (MODEL□ and MODEL□) were analyzed in this paper. It was concluded that the boundary effect was more important in a smaller system in the structure optimization. And the Fe-terminated was more stable than the O-terminated structure which was agreed with the experiences, this structural model can be used in further work including the monatomic adsorption/desorption and the chemical reactions on this surface.

Python PSS/E Simulation to Test Efficacy of Proposed PMU Based WAMS and Potential WAMPAC Applications

A PSS/E 32 model of a real section of the Northern Ireland electrical grid was dynamically controlled with Python 2.5. In this manner data from a proposed wide area monitoring system was simulated. The area is of interest as it is a weakly coupled distribution grid with significant distributed generation. The data was used to create an optimization and protection metric that reflected reactive power flow, voltage profile, thermal overload and voltage excursions. Step changes in the metric were introduced upon the operation of special protection systems and voltage excursions. A wide variety of grid conditions were simulated while tap changer positions and switched capacitor banks were iterated through; with the most desirable state returning the lowest optimization and protection metric. The optimized metric was compared against the metric generated from the standard system state returned by PSS/E. Various grid scenarios were explored involving an intact network and compromised networks (line loss) under summer maximum, summer minimum and winter maximum conditions. In each instance the output from the installed distributed generation is varied between 0 MW and 80 MW (120% of installed capacity). It is shown that in grid models the triggering of special protection systems is delayed by between 1 MW and 6 MW (1.5% to 9% of capacity), with 3.5 MW being the average. The optimization and protection metric gives a quantitative value for system health and demonstrates the potential efficacy of wide area monitoring for protection and control.

Identifying PV module mismatch faults by a thermography-based temperature distribution analysis

Photovoltaic (PV) solar power generation is proven to be effective and sustainable but is currently hampered by relatively high costs and low conversion efficiency. This paper addresses both issues by presenting a low-cost and efficient temperature distribution analysis for identifying PV module mismatch faults by thermography. Mismatch faults reduce the power output and cause potential damage to PV cells. This paper first defines three fault categories in terms of fault levels, which lead to different terminal characteristics of the PV modules. The investigation of three faults is also conducted analytically and experimentally, and maintenance suggestions are also provided for different fault types. The proposed methodology is developed to combine the electrical and thermal characteristics of PV cells subjected to different fault mechanisms through simulation and experimental tests. Furthermore, the fault diagnosis method can be incorporated into the maximum power point tracking schemes to shift the operating point of the PV string. The developed technology has improved over the existing ones in locating the faulty cell by a thermal camera, providing a remedial measure, and maximizing the power output under faulty conditions.