Showing papers in "Iet Generation Transmission & Distribution in 2018"

Whale optimisation algorithm for automatic generation control of interconnected modern power systems including renewable energy sources

Abstract: Till this moment, the model of interconnected power systems in the automatic generation control (AGC) loops relies only on the synchronous generating units. In today's world, a high level of penetration of renewable energy sources (RES) is integrated to the power grids. This paper presents a novel power system model, which includes both conventional generating units and RES for studying the AGC problem of such systems. The control strategy in the AGC loops is based on the proportional-integral-derivative (PID) controller, which is optimally designed by the whale optimization algorithm (WOA). It represents a great challenge to this controller to deal with the RES uncertainties. The effectiveness of the WOA-based PID controller is compared with other computation evolutionary algorithms-based PID controller. The system performance is evaluated under different operating conditions. For achieving a realistic study, 1) real wind speed data that extracted from Zafarana location in Egypt are used, 2) solar irradiation and temperature data that extracted from a field test are implemented, and 3) an irregular wave energy condition is applied. The validity of the control strategy is verified using the simulation results, which are carried out using MATLAB environment.

Hybrid method for short-term photovoltaic power forecasting based on deep convolutional neural network

Abstract: Photovoltaic (PV) electric power has been widely employed to satisfy rising energy demands because inexhaustible renewable energy is environmentally friendly. In order to mitigate the impact caused by the uncertainty of solar radiation in grid-connected PV systems, a hybrid method based on a deep convolutional neural network (CNN) is introduced for short-term PV power forecasting. In the proposed method, different frequency components are first decomposed from the historical time series of PV power through variational mode decomposition (VMD). Then, they are constructed into a two-dimensional data form with correlations in both daily and hourly timescales that can be extracted by convolution kernels. Moreover, the time series of residue from VMD is refined into advanced features by a CNN, which could reduce the data size and be easier for further model training along with meteorological elements. The hybrid model has been verified by forecasting the output power of PV arrays with diverse capacities in various hourly timescales, which demonstrates its superiority over commonly used methods.

Detection and classification of micro-grid faults based on HHT and machine learning techniques

Abstract: This study presents a novel micro-grid protection scheme based on Hilbert-Huang transform (HHT) and machine learning techniques. Initialisation of the proposed approach is done by extracting the three-phase current signals at the targeted buses of different feeders. The obtained non-stationary signals are passed through the empirical mode decomposition method to extract different intrinsic mode functions (IMFs). In the next step using HHT to the selected IMFs component, different needful differential features are computed. The extracted features are further used as an input vector to the machine learning models to classify the fault events. The proposed micro-grid protection scheme is tested for different protection scenarios, such as the type of fault (symmetrical, asymmetrical and high impedance fault), micro-grid structure (radial and mesh) and mode of operation (islanded and grid connected) and so on. Three different machine learning models are tested and compared in this framework: Naive Bayes classifier, support vector machine and extreme learning machine. The extensive simulated results from a standard IEC micro-grid model prove the effectiveness and reliability of the proposed micro-grid protection scheme.

Market framework for local energy trading: a review of potential designs and market clearing approaches

Abstract: Massive deployment of distributed energy resources (DERs) along with innovations in information and communication technologies have changed the power system from a hierarchical structure to a more deregulated model by introducing new generations at lower levels. This change raises operational and market challenges. Local energy trading provides opportunities to manage these DERs by encouraging localised trading. The concept of local energy trading at the distribution level is widely broadcasted for implementation in the power system. In the design of electricity markets for local energy trading, a clear definition of market participants, their objective, and purpose of market clearing should be established. This design depends on the changing needs of the power system and can be performed from different viewpoints. Classification and organisation of the literature on potential designs for local energy trading can help researchers to develop their future steps properly. This study presents a comprehensive review on this topic and provides a systematic classification of the market players, market clearing objectives, and approaches. Several research works are analysed against different criteria, including scalability, overheads requirements, and network constraints management.

Stability and control of mixed AC–DC systems with VSC-HVDC: a review

Abstract: Voltage-source converter-high-voltage direct current (VSC-HVDC) systems have become an attractive option for integrating remote and far-from-shore renewable energy resources to main AC grids. The desire for greater power transfer capability and the difficulty in securing right-of-way for new AC lines in many countries is also resulting in the increased use of embedded VSC-HVDC systems operating in parallel with existing AC lines. It has been stated that the control and operation of VSC-HVDC systems are of particular concern for weak grids with fewer large synchronous generation units (a highly probable case for many grids in future). If the anticipated proliferation of VSC-HVDC links continues, several aspects of system stability will be significantly impacted. This study presents an overview of the effects of VSC-HVDC control and operation on power system stability. The structure, control, control tuning, and modelling of VSC-HVDC is briefly summarised to provide context for subsequent discussion of the system dynamics. An extensive critical review of the previous research into mixed AC-DC systems incorporating VSC-HVDC is then provided including voltage stability, small and large-disturbance angle stability, high-frequency interaction, and frequency stability. Finally, recommendations are presented to guide critical future research.

Sub-synchronous oscillation mechanism and its suppression in MMC-based HVDC connected wind farms

Abstract: A subsynchronous oscillation (SSO) phenomenon in a wind farm integrated with a modular multilevel converter (MMC)-based high-voltage direct current (HVDC) transmission system has been recently observed in the real world. An attempt is made in this paper to contribute to the understanding of the root cause of the SSO in the MMC-HVDC connected wind farms. For that, the small-signal impedance model of the MMC is first developed based on the harmonic state-space (HSS) modelling method. An inherent low-frequency resonance peak in the MMC excluding any control influence is identified by its terminal impedance. Arguably, this could be the reason why the SSO occurs in the MMC-HVDC connected wind farms. In addition to that, the influence factors, such as main circuit parameters, controller parameters, and power level, on the stability of the interconnected system are examined, which can provide guidelines for the system design in order to guarantee the stability of the interconnected system. Based on the mechanism analysis, a stabilization control for suppressing the SSO in the MMC-HVDC based wind farms is also proposed. Finally, the theoretical analysis and stabilization control are validated by both time-domain simulations and field measurements in a real MMC-HVDC connected wind farm in China.

Provision of flexible ramping product by battery energy storage in day-ahead energy and reserve markets

Abstract: The variability and uncertainty of renewable energy resources introduce significant challenges to power system operation. One particular example is the occurrence of ramp capability shortage in real-time dispatch, which can cause power balance violations and price spikes. To meet the increasing need for ramp capability, some independent system operators in the USA have led initiatives to promote the implementation of flexible ramping product (FRP). More potential FRP providers, apart from conventional generators, are being explored, among which battery energy storage (BES) appears to be a feasible option owing to its good controllability and fast responsive characteristics. This study proposes an optimisation model for a BES aggregator to optimally provide FRP in day-ahead energy and reserve markets, aiming to maximise its monetary benefits. The basic concept of FRP is first introduced, including comparisons with traditional ancillary services, pricing mechanisms, and the extensions of market models to integrate FRP. The modes and strategies for BES aggregators to participate in the electricity markets are then addressed. Case studies indicate that an aggregator can gain more profit by optimally allocating its resources among various products than only providing energy and reserves. A sensitivity analysis on several key factors is also conducted.

Unbalanced harmonic power sharing and voltage compensation of microgrids using radial basis function neural network-based harmonic power-flow calculations for distributed and decentralised control structures

Abstract: A new hierarchical control scheme is proposed to improve power sharing of multi-distributed energy resources (DERs) microgrids including non-linear and unbalanced loads. The electronically coupled DERs are responsible to perform the harmonic and unbalance compensation to reduce the voltage harmonics at the point of common coupling (PCC) and improve power quality. The proposed scheme uses a complementary control loop for small/large-signal stability enhancement, and moreover exploits new concept for fundamental and harmonic virtual impedance scheme for positive and negative sequences based on IEEE standards. Compared to conventional virtual impedance methods that add only line current feed-forward terms to the voltage reference, here, the line current and voltage at the PCC regulate the virtual impedance at fundamental and harmonic frequencies, respectively. So, mismatches in the feeder and line impedances are compensated. Also, a harmonic power calculation is presented based on the non-linear mapping capability of radial basis function neural networks to obtain voltage harmonics and active and reactive powers for balanced/unbalanced operation modes. To show the effectiveness of the proposed control scheme, offline time-domain simulation studies have been performed on a sample microgrid using MATLAB/Simulink software and OPAL-RT real-time digital simulator for verification.

MOPSO/FDMT-based Pareto-optimal solution for coordination of overcurrent relays in interconnected networks and multi-DER microgrids

Abstract: The minimisation of discrimination time between main and backup overcurrent (OC) relays is one of the most important issues in power system relays coordination. On account of the massive computation burden and complexities for determining power system breakpoint, the implementation of the previously reported OC protection methods in large interconnected networks is almost impossible or at least cumbersome. In this regard, a variety of optimisation algorithms have been presented for coordination between relays and finding optimal operation time (OT) of the protection system. The previously reported single-objective optimisation algorithms have some limitations/drawbacks regarding OT of relays and their coordination. In this study, a new multi-objective optimisation algorithm is presented for coordination of OC relays in interconnected networks, based on multi-objective particle swarm optimisation (MOPSO) and fuzzy decision-making tool (FDMT). Then, using some useful assumption and recommendations of IEC-6090 and fault calculations for the microgrids including distributed energy resources, the proposed method is generalised for OC relay coordination in microgrids. Finally, the proposed method has been successfully implemented on different test systems and the obtained results have been compared with other reported methods to prove accuracy, authenticity, and efficiency of the MOPSO/FDMT-based protection and relay coordination algorithm.

Demand response potential evaluation for residential air conditioning loads

Abstract: Residential air conditioning loads with energy storage characteristics can quickly participate in the demand response, making it an important demand response resource. It can improve resource utilisation and the flexibility of power grid operation through the effective regulation. However, the degree of residential air conditioning to participate in demand response is affected by the outdoor temperature, users' comfort settings, thermal storage and insulation properties of buildings. Moreover, the difficulty of assessing the demand response potential is further increased by the uncertainty of the influencing factors. To guide the residential air conditioners to participate in the power grid operation, the aggregated air conditioner model is established to describe the relationship among the total power, the external environment, and the indoor temperature. The demand response potential model is established from the amount and the duration of demand response. The effects of outdoor temperature, indoor temperature adjustment and the number of air conditioners participating in the response are quantitatively evaluated. Finally, the accuracy of the aggregated model and demand response potential model are verified by numerical simulation.

Comprehensive control strategy of virtual synchronous generator under unbalanced voltage conditions

Abstract: The virtual synchronous generator (VSG) is emerging as an effective approach for controlling converter to mimic the traditional synchronous generator (SG). VSG can provide virtual inertia, handle both reactive and active power, which is grid-friendly for integrating distributed generations. Generally, when grid voltage is unbalanced, the negative sequence voltage components will appear. Due to traditional VSG control strategy does not consider the negative sequence components and cannot eliminate them, thus it will lead to current unbalance and power oscillations. To address these problems, a comprehensive control strategy of VSG under unbalanced voltage conditions is proposed. Herein, the basic principle of VSG and inherent reasons for VSG current unbalance and power fluctuation are demonstrated with quantitative analysis. The cascaded control framework and design process of the comprehensive control strategy are presented, integrating the traditional VSG control algorithm, novel current reference generator and typical current regulator. Additionally, related critical issues such as sequence components extraction and control parameter design are discussed. The proposed control strategy can flexibly meet different operation demands, including current balancing and suppression of active power or reactive power oscillations. The validity and effectiveness of the proposed control strategy are verified with simulation and experimental results.

Cost-based optimal siting and sizing of electric vehicle charging stations considering demand response programmes

Abstract: Here, the optimal placement and sizing of electric vehicle charging stations (EVCSs) are presented. High penetration of electric vehicles (EVs) and resulted losses in network would consequently impose more complexity to solution of application problem of EVCSs. To overcome this problem, the model would consider the incentive-based demand response programmes (DRPs), which is handled by particle swarm optimisation algorithm. Minimising investment cost, connection cost, total cost of losses, and demand response (DR) cost are the objective functions of this problem here. Finally, the proposed model is applied to a test system and results are discussed. By comparing the results obtained through different scenarios, it is concluded that the application of DRP results in a distinct reduction in grid losses and total costs.

AI based approach to identify compromised meters in data integrity attacks on smart grid

Abstract: False data injection attacks can pose serious threats to the operation and control of power grid. The smarter the power grid gets, the more vulnerable it becomes to cyber-attacks. Various detection methods of cyber-attacks have been proposed in the literature in recent past. However, to completely alleviate the possibility of cyber-threats, the compromised meters must be identified and secured. In this study, the authors are presenting an artificial intelligence (AI)-based identification method to correctly single out the malicious meters. The proposed AI-based method successfully identifies the compromised meters by anticipating the correct measurements in the event of the cyber-attack. New York Independent System Operator load data is mapped with the IEEE 14-bus system to validate the proposed method. The efficiency of the proposed method is compared for artificial neural network and extreme learning machine-based AI techniques. It is observed that both the techniques identify the corrupted meters with high accuracy.

Novel application of integral-tilt-derivative controller for performance evaluation of load frequency control of interconnected power system

Abstract: The primary aim of load frequency control (LFC) is to provide a good quality of electrical power to the consumers within a prescribed limit of frequency and scheduled tie-line power deviation. To achieve this objective, LFC needs highly efficient and intelligent control mechanism. Subsequently, here, a novel integral-tilt-derivative (I-TD) controller, fine-tuned by a powerful heuristic optimisation technique [called as water cycle algorithm (WCA)], is proposed for the LFC study of a two-area interconnected thermal-hydro-nuclear generating units. The studied system involves non-linearities like generation rate constraints, governor dead band, and boiler dynamics. To explore the effectiveness of the proposed controller, dynamic responses of the studied system, as obtained using I-TD controller, are compared to those yielded by other controllers such as tilt-integral-derivative and conventional proportional–integral–derivative controllers. The investigation demonstrates that the proposed I-TD controller delivers better performance in comparison to the other counterparts. Furthermore, sensitivity analysis is carried out to show robustness of the WCA tuned proposed I-TD controller by varying system parameters and loading condition. It is perceived that the proposed I-TD controller is robust and offers better transient response under varying operating conditions.

Hybrid feature selection approach for power transformer fault diagnosis based on support vector machine and genetic algorithm

Abstract: To further improve fault diagnosis accuracy, a new hybrid feature selection approach combined with a genetic algorithm (GA) and support vector machine (SVM) is presented in this study. Adaptive synthetic technique and arctangent transformation method are adopted to improve the statistical property of the training set (IEC TC10 dataset). Five filter methods based on different evaluation metrics are employed to rank 48 input features derived from dissolved gas analysis (DGA). Then, feature combination methods are applied to aggregate feature ranks and form a lower-dimension candidate feature subset. The GA–SVM model is implemented to optimise parameters and select optimal feature subsets. 5-fold cross-validation accuracy of the GA-SVM is used to evaluate fault diagnosis capability of feature subsets and finally, a novel subset is determined as the optimal feature subset. Accuracy comparison manifests the superiority of the optimal feature subsets over that of conventional approaches. Besides, generalisation and robustness of the optimal subset are validated by testing DGA samples from the local power utility. Results indicate that the optimal feature subset obtained by the proposed method can significantly improve the accuracies of power transformer fault diagnosis.

Diagnosis and clustering of power transformer winding fault types by cross-correlation and clustering analysis of FRA results

Abstract: The power transformer is one of the vital and substantial elements of each country's power grid which not only require high investment, but they are also important in terms of economy, social, political, and strategy. Since this equipment is exposed to different electrical and mechanical winding faults during operation, they should be monitored continuously. One of the main monitoring methods is the use of frequency response analysis (FRA), which has a high sensitivity. The main challenge of the FRA is that the detecting task of the status of the transformer is done by a specialist and with a visual evaluation of the records. To overcome this problem, first, frequency responses in the healthy and present states are calculated through simulation of electrical and mechanical fault in the winding of the transformer and then, new statistical methods are used to interpret FRA results based on the obtained transfer function. In this study, for the first time, clustering analysis and cross-correlation methods are used to interpret FRA results for clustering and diagnosis of different short circuits turns, axial displacement, and radial deformation. Results and simulations verify ability and advantage of these methods in detection and determination of different faults.

Application of μPMUs for adaptive protection of overcurrent relays in microgrids

Abstract: This study proposes a new application of micro-phasor measurement units (μPMUs) for adaptive coordination of overcurrent relays in microgrids. Mis-coordination of overcurrent relays usually arising from the variation of relays fault current and it can cause damage to equipment of network and raise operating costs. Fault current injection and direction to microgrid are highly dependent on network uncertainties; therefore, fault current is affected by line and power plant outages. This study proposes an algorithm to detect these uncertainties in online operation. Then, microgrid overcurrent relays coordination is optimised again. Uncertainties are line and power plant outages in transmission network and microgrid side and two distinct methods are used for each. For online detection of uncertainties in the transmission side, it is assumed that a μPMU is installed between transmission network and microgrid point of common coupling; so, the topology changes such as line outage is detected by monitoring of Thevenin impedance estimation that is obtained by μPMU measurements. Uncertainties detection in a microgrid is done by signals that are sent by μPMUs and installed all over the microgrid. All data are gathered and analysed in phasor data concentrators and then overcurrent relays coordination is updated with such changes.

Energy management system, generation and demand predictors: a review

Abstract: A microgrid can integrate distributed energy resources for satisfying load demand, moreover, solve reliability, safety and environment issues. Spinning reserves in microgrid such as battery, gas and diesel generator can provide support for more sustainable operation in distributed networks. Critical loads for microgrid are crucial for the system to support at any cost, whereas, a non-critical loads can be rescheduled based on the status of supply and demand mechanism. Microgrid is perfect for renewable energy integration, such as wind and solar, thus, it eliminates intermittency issues of these sources with proper operation and control strategy. In short, a proper secondary control is the key to achieve economic benefits from microgrid. Microgrid is also used to generate profit by sending excess power to the main grid via net metering approach and makes traditional consumer of power into producer at the same time. This study will provide insights into state-of-the-art energy management as well as generation/consumption prediction issues, practices and research status. This review study will embark the deep foundation to study the energy management or prediction related study for microgrids.

High impedance fault detection method based on the short-time Fourier transform

Abstract: A method to detect high impedance faults (HIFs) based on low-order harmonics is proposed. Short-time Fourier transform (STFT) is used to extract the main harmonic components of phase current, as magnitude and phase of the third harmonic and magnitude of the second and fifth harmonics, which are used to identify HIF occurrence. In addition, this study presents an analysis of the window length and type used in STFT and its suitability for the application. The method proposed is able to detect HIF occurrence at various points of the test system, as well as HIF happening on different soil surfaces. It is also capable of distinguishing HIF events from similar distribution system disturbances such as capacitor banks switching and feeder energising. Furthermore, it is effective when real HIF oscillography is applied, indicating its tolerance to typical noises present on real signals.

Fractional-order lead-lag compensator-based multi-band power system stabiliser design using a hybrid dynamic GA-PSO algorithm

Abstract: Power system stabilisers (PSSs) are supplementary controllers connected to the excitation system of synchronous generators to damp electromechanical oscillations. Multi-band PSSs are reported as advanced PSSs with the ability to damp out all oscillation modes present in the power systems. This study presents the design of a robust fractional-order multi-band power system stabiliser (Fo-MBPSS) using a meta-heuristic hybrid algorithm for dynamic stability improvement of multi-machine power systems. The large bandwidth, memory effect and flat phase contribution in the frequency response of fractional-order controllers are exploited to make the Fo-MBPSS perform well against a wide range of system uncertainties. The parameter tuning problem of Fo-MBPSS is transformed to an optimisation problem that is solved using a hybrid algorithm by combining a dynamic genetic algorithm (DGA) with a standard particle swarm optimisation (PSO) algorithm. The performance of the proposed DGA-PSO-Fo-MBPSS is evaluated through eigenvalue analysis, non-linear time-domain simulations and some performance indices, in two different multi-machine systems under different loading conditions and disturbances. The results are compared with PSO-based conventional MBPSS and PSO based Fo-MBPSS (PSO-Fo-MBPSS) to establish the fractional parameter effect on the improvement of the system dynamic response and the relevance of the proposed hybrid optimisation technique in achieving robustness.

Low-voltage ride-through of a droop-based three-phase four-wire grid-connected microgrid

Abstract: The ability of riding through the grid disturbances can increase the integration of microgrids into the distribution system. Consequently, a grid-connected microgrid should provide ancillary services such as low voltage ride-through (LVRT) capability and reactive power support to sustain the power system operations during abnormal grid conditions. The objective of this paper is to propose an LVRT scheme that improves the power quality of the entire microgrid. The developed method is implemented as the controller of the interface voltage-sourced converter (VSC) of a distributed energy resource and consists of primary and secondary control levels. The former includes the cascaded voltage and current control loops and the droop controller, while the latter controls the reactive power injection during the balanced/unbalanced voltage sags/swells. The proposed scheme is developed based on the independent control of each phase and does not require calculation of symmetrical components. Moreover, it can be employed in the VSC control systems with various reference frames and is effective for droop-based grid-connected microgrids with both single-phase and three-phase four-wire configurations. The proposed strategy is implemented using the hierarchical control system and preserves the plug and play capability. Several case studies are presented to verify the effectiveness of the proposed strategy.

Resilience-based framework for switch placement problem in power distribution systems

Abstract: Optimal placement of switches can play a key role in providing resilience to power distribution systems against major faults caused by natural disasters. This study presents a resilience-based framework for optimal switch placement in distribution systems being consistent with the expansion plans of distributed generation units. At first, the impact of hurricanes on distribution system components is modelled using the geographic information system of distribution grid and the strength of components against extreme weather-related events. Then, a new resiliency index is proposed to assess the resilience of distribution grids. This index is involved in a mathematical model of the switch placement problem and the obtained formulation is modelled as a mixed integer linear programming optimisation problem. The presented framework is implemented on two test systems, i.e. an illustrative test system and Bus 4 of the Roy Billinton test system. The results prove the effectiveness of this approach to improving the resiliency of distribution systems.

Lightning flash algorithm for solving non-convex combined emission economic dispatch with generator constraints

Abstract: Due to the importance of global warming and environmental impacts that accumulated from emission of gaseous pollutants of fossil-fuelled power plants, the modern combined emission economic dispatch (CEED) is applied. This study proposes a new evolutionary lightning flash algorithm to solve dual-objective CEED problem considering different scenarios with wind power penetration, multiple fuel options and operation constraints on the generators. The lightning flash algorithm is formulated based on the movements of the cloud to ground lightning strikes in a thunderstorm. This method is tested on 11 benchmark functions and then it is applied on six different practical case study systems for solving non-convex CEED. The results of LFA on benchmark functions and the case study systems are compared with other methods and confirm the effectiveness and applicability of the proposed method with higher quality solution, less emission, less costs and better convergence against other methods for solving non-convex practical economic dispatch, CEED and dynamic dispatch problems.

Carrier mobility and trap distribution dependent flashover characteristics of epoxy resin

Abstract: Epoxy disc-type spacer, as the major insulator of gas insulated transmission line, plays a significant role in the reliability and safety of the entire power grid. While surface charge accumulation on the spacer could induce flashover and accelerate degradation of the insulator, which threats the operation of high-voltage DC transmission and grid. In this study, a corona discharging system was employed to charge the epoxy samples before the charge dissipation measured, and the surface flashover voltages of samples with different modification time under DC voltage were also measured, the results are obtained from the research. It is found that the carrier mobility and surface flashover voltage of samples are affected by modification time, and maximum value of both can be obtained when the sample is modified for 60 min. Under the combined voltages, the initial surface charge density and carrier mobility are affected by both pulse voltage and modification time. It is indicated that surface modification is an appropriate method which can significantly inhibit the surface charge accumulation, and improve the flashover characteristics of epoxy sample by increasing carrier mobility. The trap distribution characteristics suggested that the modification treatment and charging condition have a significant effect on the depth and density of trap.

Optimal operation of aggregated electric vehicle charging stations coupled with energy storage

Abstract: Charging stations are the basic infrastructure for accommodating the energy needs of electric vehicles (EVs). Companies are expected to invest in these charging stations by installing them at locations with a dense concentration of vehicles, such as parking places, commercial centres, and workplaces. In order for investors in EV charging stations to maximise their profits and mitigate the impact on the power grid, these stations would benefit from coupling with an energy storage system (ESS). ESS would be used to arbitrage energy and to balance out the time-variant and uncertain EV energy demand. This study proposes a framework to optimise the offering/bidding strategy of an ensemble of charging stations coupled with ESS in the day-ahead electricity market. The proposed framework accounts for degradation of the ESS, robust scheduling against price uncertainty, as well as stochastic energy demand from EVs. The results show the viability of the proposed framework in providing cost savings to an ensemble of EV charging stations.

Protection coordination scheme for distribution networks with high penetration of photovoltaic generators

Abstract: The installation of photovoltaic (PV) systems is gaining great attention due to the matured PV technology and the lowered price of PV modules. With an increasing penetration of PV systems, the selectivity of distribution network protection may be affected which results in undesirable de-energisation of loads, damage of network equipment, and reduction of reliability. This study presents a method to preserve the protection coordination considering future PV systems installation with any penetration level and different locations along the distribution feeder. Depending on the accessibility of protection device settings or PV control parameters, the proposed method modifies the existing characteristic curve of overcurrent devices or limits the output current of PV sources, respectively. The proposed strategy does not change the structure of existing distribution network protection system and can also be implemented in the old and non-programmable relays. Meanwhile, it does not need the communication links. The merits of the proposed method are demonstrated through several case studies using the Isfahan distribution network.

Coordinated charging and discharging strategies for plug-in electric bus fast charging station with energy storage system

Abstract: Plug-in electric bus (PEB) is an environmentally friendly mode of public transportation and PEB fast charging stations (PEBFCSs) play an essential role in the operation of PEBs. Under effective control, deploying an energy storage system (ESS) within a PEBFCS can reduce the peak charging loads and the electricity purchase costs. To deal with the (integrated) scheduling problem of (PEBs charging and) ESS charging and discharging, in this study, the authors propose an optimal real-time coordinated charging and discharging strategy for a PEBFCS with ESS to achieve maximum economic benefits. According to whether the PEB charging loads are controllable, the corresponding mathematical models are, respectively, established under two scenarios, i.e. coordinated PEB charging scenario and uncoordinated PEB charging scenario. The price and lifespan of ESS, the capacity charge of PEBFCS and the electricity price arbitrage are considered in the models. Further, under the coordinated PEB charging scenario, a heuristics-based method is developed to get the approximately optimal strategy with computation efficiency dramatically enhanced. Finally, the authors validate the effectiveness of the proposed strategies, interpret the effect of ESS prices on the usage of ESS and provide the sensitivity analysis of ESS capacity through the case studies.

Economic planning approach for electric vehicle charging stations integrating traffic and power grid constraints

Abstract: Large-scale electric vehicle (EV) charging will bring new challenges to coordination of grid and transportation. To facilitate large-scale EV applications, optimal locating and sizing of charging stations have become essential. For the investors of a charging station, economic benefit is the primary and the only objective. In this context, this work studies the siting and sizing of EV stations based on the optimal economic benefit. Benefit changes with time, location and capacity. A planning model method considering net present value (NPV) and life cycle cost (LCC) is proposed to determine the site and the size of the charging stations. The model has integrated distribution network constraint, the user constraint and the traffic flow captured constraint. Origin–destination lines and voronoi diagram are selected to calculate the traffic flow and the service region of each charging station, respectively. The quantum genetic algorithm was adopted for a better convergence of the planning model. Finally, a coupled 33-node distribution system and a 36-node transportation system are used to simulate various scenarios in the coupled networks of grid and transportation. The simulation results show that by introducing a planning model method considering NPV and LCC, the charging station economical benefits can be further improved.

Load frequency control of a dynamic interconnected power system using generalised Hopfield neural network based self-adaptive PID controller

Abstract: A novel generalised Hopfield neural network (GHNN) based self-adaptive proportional-integral-derivative (PID) controller for load frequency control (LFC) is designed for a two-area interconnected power system with nonlinearities of generator rate constraint and governor dead band The control problem is conceptualized as an optimisation problem with an objective function as an area control error in terms of the PID controller parameters The differential equations governing the behaviour of the GHNN were solved to obtain the controller parameters K p , K i and K d To test the feasibility and robustness of the proposed controller, the system is tested in the presence of randomness in load demands, imprecisely modelled system dynamics, nonlinearities in the system model and uncertainties in the system parameter variations The proposed method is simulated using Matlab R2014b/Simulink and the results obtained have shown that the propounded controller performance is superior to the integral, PID and fuzzy-based proportional-integral controllers In addition, the Lyapunov stability analysis of the overall closed-loop system was carried out and the controller is implemented in real-time digital simulator run in hardware-in-the-loop to validate the effectiveness of the proposed method Furthermore, the proposed controller is applied to the three-area power system to test its adaptability

Efficient protection scheme for low-voltage DC micro-grid

Abstract: Detection of shorted DC faults and high-resistance faults on ring type low-voltage DC (LVDC) micro-grids imposes an elusive challenge. This research work proposes an efficient and reliable protection scheme for DC system in order to boost up LVDC system adoption on large scale, despite lack of proper standards and mature experience in DC system protection. In order to ameliorate these deficiencies, a wavelet transform-based fast fault protection scheme using local measurements has been proposed for eliminating threat to voltage source converters during fault. The features extracted using wavelet coefficients are utilised as key indicators to identify the fault with wide variations in operating conditions. The LVDC micro-grid system has been simulated using real-time digital simulator and the test results studied show a great potential ability in performing DC fault detection and classification task efficiently. Furthermore, the robustness of the proposed protection scheme is capable of fault line identification and setting up desired relay selectivity in the LVDC distribution system.