Nonlinear numerical modelling of lightning strike effect on composite panels with temperature dependent material properties

This paper presents a physics based modelling procedure to predict the thermal damage of composite material when struck by lightning. The procedure uses the Finite Element Method with non-linear material models to represent the extreme thermal material behaviour of the composite material (carbon/epoxy) and an embedded copper mesh protection system. Simulation predictions are compared against published experimental data, illustrating the potential accuracy and computational cost of virtual lightning strike tests and the requirement for temperature dependent material modelling. The modelling procedure is then used to examine and explain a number of practical solutions to minimize thermal material damage. © 2013 Elsevier Ltd.

Principal Component Analysis of Wide Area Phasor Measurements for Islanding Detection – A Geometric View

This paper presents a new technique for the detectionof islanding conditions in electrical power systems. This problem isespecially prevalent in systems with significant penetrations of distributedrenewable generation. The proposed technique is based onthe application of principal component analysis (PCA) to data setsof wide-area frequency measurements, recorded by phasor measurementunits. The PCA approach was able to detect islandingaccurately and quickly when compared with conventional RoCoFtechniques, as well as with the frequency difference and change-ofangledifference methods recently proposed in the literature. Thereliability and accuracy of the proposed PCA approach is demonstratedby using a number of test cases, which consider islandingand nonislanding events. The test cases are based on real data,recorded from several phasor measurement units located in theU.K. power system.

Impacts of compressed air energy storage plant on an electricity market with a large renewable energy portfolio

Renewable energy generation is expected to continue to increase globally due to renewable energy targets and obligations to reduce greenhouse gas emissions. Some renewable energy sources are variable power sources, for example wind, wave and solar. Energy storage technologies can manage the issues associated with variable renewable generation and align non-dispatchable renewable energy generation with load demands. Energy storage technologies can play different roles in each of the step of the electric power supply chain. Moreover, large scale energy storage systems can act as renewable energy integrators by smoothing the variability. Compressed air energy storage is one such technology. This paper examines the impacts of a compressed air energy storage facility in a pool based wholesale electricity market in a power system with a large renewable energy portfolio.

A new method for transmission loss allocation considering the circulating currents between generators

A new method is presented for transmission loss allocation based on the separation of transmission loss caused by load and the loss due to circulating currents between generators. The theoretical basis for and derivation of the loss formulae are presented using simple systems. The concept is then extended to a general power system using the Ybus model. Details of the application of the proposed method to a typical power system are presented along with results from the IEEE 30 bus test system. The results from both the small system and the standard IEEE test system demonstrate the validity of the proposed method.

Enhanced AIMD based decentralized residential charging of EVs

Moving from combustion engine to electric vehicle (EV)-based transport is recognized as having a major role to play in reducing pollution, combating climate change and improving energy security. However, the introduction of EVs poses major challenges for power system operation. With increasing penetration of EVs, uncontrolled coincident charging may overload the grid and substantially increase peak power requirements. Developing smart grid technologies and appropriate charging strategies to support the role out of EVs is therefore a high priority. In this paper, we investigate the effectiveness of distributed additive increase and multiplicative decrease (AIMD) charging algorithms, as proposed by Stu¨dli et al. in 2012, at mitigating the impact of domestic charging of EVs on low-voltage distribution networks. In particular, a number of enhancements to the basic AIMD implementation are introduced to enable local power system infrastructure and voltage level constraints to be taken into account and to reduce peak power requirements. The enhanced AIMD EV charging strategies are evaluated using power system simulations for a typical low-voltage residential feeder network in Ireland. Results show that by using the proposed AIMD-based smart charging algorithms, 50% EV penetration can be accommodated, compared with only 10% with uncontrolled charging, without exceeding network infrastructure constraints.

Distributed MPC for Frequency Regulation in Multi-Terminal HVDC Grids

High Voltage Direct Current (HVDC) lines allow large quantities of power to be
transferred between two points in an electrical power system. A Multi-Terminal HVDC (MTDC) grid consists of a meshed network of HVDC lines, and this allows energy reserves to be shared between a number of AC areas in an efficient manner. Secondary Frequency Control (SFC) algorithms return the frequencies in areas connected by AC or DC lines to their original setpoints after Primary Frequency Controllers have been called following a contingency. Where multiple
TSOs are responsible for different parts of a MTDC grid it may not be possible to implement SFC from a centralised location. Thus, in this paper a simple gain based distributed Model Predictive Control strategy is proposed for Secondary Frequency Control of MTDC grids which allows TSOs to cooperatively perform SFC without the need for centralised coordination.

Assessment of Domestic Load Suitable for Smart Consumer Load Participation

This study characterizes the domestic loads suitable to participate in the load participation scheme to make the power system more carbon and economically efficient by shifting the electricity demand profile towards periods when there is plentiful renewable in-feed.

A series of experiments have been performed on a common fridge-freezer, both completely empty and half full. The results presented are ambient temperature, temperature inside the fridge, temperature inside the drawer of the fridge, temperature inside the freezer, thermal time constants, power consumption and electric energy consumed.

The thermal time constants obtained clearly demonstrate the potential of such refrigeration load for Smart Customer Load Participation.

Stateful Intrusion Detection for IEC 60870-5-104 SCADA Security

Cyber threats in Supervisory Control and Data Acquisition (SCADA) systems have the potential to render physical damage and jeopardize power system operation, safety and stability. SCADA systems were originally designed with little consideration of escalating cyber threats and hence the problem of how to develop robust intrusion detection technologies to tailor the requirements of SCADA is an emerging topic and a big challenge. This paper proposes a stateful Intrusion Detection System (IDS) using a Deep Packet Inspection (DPI) method to improve the cyber-security of SCADA systems using the IEC 60870-5-104 protocol which is tailored for basic telecontrol communications. The proposed stateful protocol analysis approach is presented that is designed specifically for the IEC 60870-5-104 protocol. Finally, the novel intrusion detection approach are implemented and validated.

A self-learning teaching-learning based optimization for dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.

Domestic fridge-freezer load aggregation to support ancillary services

Grid operators and electricity retailers in Ireland manage peak demand, power system balancing and grid congestion by offering relevant incentives to consumers to reduce or shift their load. The need for active consumers in the home using smart appliances has never been greater, due to increased variable renewable generation and grid constraints. In this paper an aggregated model of a single compressor fridge-freezer population is developed. A price control strategy is examined to quantify and value demand response savings during a representative winter and summer week for Ireland in 2020. The results show an average reduction in fridge-freezer operating cost of 8.2% during winter and significantly lower during summer in Ireland. A peak reduction of at least 68% of the average winter refrigeration load is achieved consistently during the week analysed using a staggering control mode. An analysis of the current ancillary service payments confirms that these are insufficient to ensure widespread uptake by the small consumer, and new mechanisms need to be developed to make becoming an active consumer attractive. Demand response is proposed as a new ancillary service called ramping capability, as the need for this service will increase with more renewable energy penetration on the power system.

Comparison Method for Differentiation of IEC 61850 based Substation Configuration Files

The increased construction and reconstruction of smart substations has exposed a problem with version management of substation configuration description language (SCL) files due to frequent changes. This paper proposes a comparative approach for differentiation of smart substation SCL configuration files. A comparison model for SCL configuration files is built in this method, which is based on the SCL structure and abstract model defined by IEC 61850. The proposed approach adopts the algorithms of depth-first traversal, sorting, and cross comparison in order to rapidly identify differences of changed SCL configuration files. This approach can also be utilized to detect malicious tampering or illegal manipulation tailoring for SCL files. SCL comparison software is developed using the Qt platform to validate the feasibility and effectiveness of the proposed approach.

Differential evolution combined with clonal selection for dynamic economic dispatch

Dynamic economic load dispatch (DELD) is one of the most important steps in power system operation. Various optimisation algorithms for solving the problem have been developed; however, due to the non-convex characteristics and large dimensionality of the problem, it is necessary to explore new methods to further improve the dispatch results and minimise the costs. This article proposes a hybrid differential evolution (DE) algorithm, namely clonal selection-based differential evolution (CSDE), to solve the problem. CSDE is an artificial intelligence technique that can be applied to complex optimisation problems which are for example nonlinear, large scale, non-convex and discontinuous. This hybrid algorithm combines the clonal selection algorithm (CSA) as the local search technique to update the best individual in the population, which enhances the diversity of the solutions and prevents premature convergence in DE. Furthermore, we investigate four mutation operations which are used in CSA as the hyper-mutation operations. Finally, an efficient solution repair method is designed for DELD to satisfy the complicated equality and inequality constraints of the power system to guarantee the feasibility of the solutions. Two benchmark power systems are used to evaluate the performance of the proposed method. The experimental results show that the proposed CSDE/best/1 approach significantly outperforms nine other variants of CSDE and DE, as well as most other published methods, in terms of the quality of the solution and the convergence characteristics.

Loss-of-Main Monitoring and Detection for Distributed Generations Using Dynamic Principal Component Analysis

In this paper, our previous work on Principal Component Analysis (PCA) based fault detection method is extended to the dynamic monitoring and detection of loss-of-main in power systems using wide-area synchrophasor measurements. In the previous work, a static PCA model was built and verified to be capable of detecting and extracting system faulty events; however the false alarm rate is high. To address this problem, this paper uses a well-known ‘time lag shift’ method to include dynamic behavior of the PCA model based on the synchronized measurements from Phasor Measurement Units (PMU), which is named as the Dynamic Principal Component Analysis (DPCA). Compared with the static PCA approach as well as the traditional passive mechanisms of loss-of-main detection, the proposed DPCA procedure describes how the synchrophasors are linearly
auto- and cross-correlated, based on conducting the singular value decomposition on the augmented time lagged synchrophasor matrix. Similar to the static PCA method, two statistics, namely T2 and Q with confidence limits are calculated to form intuitive charts for engineers or operators to monitor the loss-of-main situation in real time. The effectiveness of the proposed methodology is evaluated on the loss-of-main monitoring of a real system, where the historic data are recorded from PMUs installed in several locations in the UK/Ireland power system.

The significance of interconnector counter-trading in a security constrained electricity market

Throughout the European Union there is an increasing amount of wind generation being dispatched-down due to the binding of power system operating constraints from high levels of wind generation. This paper examines the impact a system non-synchronous penetration limit has on the dispatch-down of wind and quantifies the significance of interconnector counter-trading to the priority dispatching of wind power. A fully coupled economic dispatch and security constrained unit commitment model of the Single Electricity Market of the Republic of Ireland and Northern Ireland and the British Electricity Trading and Transmission Arrangement was used in this study. The key finding was interconnector counter-trading reduces the impact the system non-synchronous penetration limit has on the dispatch-down of wind. The capability to counter-trade on the interconnectors and an increase in system non-synchronous penetration limit from 50% to 55% reduces the dispatch-down of wind by 311 GW h and decreases total electricity payments to the consumer by €1.72/MW h. In terms of the European Union electricity market integration, the results show the importance of developing individual electricity markets that allow system operators to counter-trade on interconnectors to ensure the priority dispatch of the increasing levels of wind generation.

An efficient and robust case sorting for algorithm for transient stability assessment

An efficient and robust case sorting algorithm based on Extended Equal Area Criterion (EEAC) is proposed in this paper for power system transient stability assessment (TSA). The time-varying degree of an equivalent image system can be deduced by comparing the analysis results of Static EEAC (SEEAC) and Dynamic EEAC (DEEAC), the former of which neglects all time-varying factors while the latter partially considers the time-varying factors. Case sorting rules according to their transient stability severity are set combining the time-varying degree and fault messages. Then a case sorting algorithm is designed with the “OR” logic among multiple rules, based on which each case can be identified into one of the following five categories, namely stable, suspected stable, marginal, suspected unstable and unstable. The performance of this algorithm is verified by studying 1652 contingency cases from 9 real Chinese provincial power systems under various operating conditions. It is shown that desirable classification accuracy can be achieved for all the contingency cases at the cost of very little extra computational burden and only 9.81% of the whole cases need to carry out further detailed calculation in rigorous on-line TSA conditions.