Abstract:The rapidly increasing penetration of electric vehicles in modern metropolises has been witnessed during the past decade, inspired by financial subsidies as well as public awareness of climate change and environment protection. Integrating charging facilities, especially highpower chargers in fast charging stations, into power distribution systems remarkably alters the traditional load flow pattern, and thus imposes great challenges on the operation of distribution network in which controllable resources are rare. On the other hand, provided with appropriate incentives, the energy storage capability of electric vehicle offers a unique opportunity to facilitate the integration of distributed wind and solar power generation into power distribution system. The above trends call for thorough investigation and research on the interdependence between transportation system and power distribution system. This paper conducts a comprehensive survey on this line of research. The basic models of transportation system and power distribution system are introduced, especially the user equilibrium model, which describes the vehicular flow on each road segment and is not familiar to the readers in power system community. The modelling of interdependence across the two systems is highlighted. Taking into account such interdependence, applications ranging from long-term planning to short-term operation are reviewed with emphasis on comparing the description of traffic-power interdependence. Finally, an outlook of prospective directions and key technologies in future research is summarized.

Abstract:Synchrophasor devices guarantee situation awareness for real-time monitoring and operational visibility of smart grid. With their widespread implementation, significant challenges have emerged, especially in communication, data quality and cybersecurity. The existing literature treats these challenges as separate problems, when in reality, they have a complex interplay. This paper conducts a comprehensive review of quality and cybersecurity challenges for synchrophasors, and identifies the interdependencies between them. It also summarizes different methods used to evaluate the dependency and surveys how quality checking methods can be used to detect potential cyberattacks. This paper serves as a starting point for researchers entering the fields of synchrophasor data analytics and security.

Abstract:Several factors have led to the decline of electricity generation from coal over the past decade, and projections forecast high rates of growth for wind and solar technologies in coming years. This analysis uses hourly generation data from large coal-fired power stations to determine how operations have been modified in recent years and describes the implications of these changes for plant equipment and unit reliability. The data shows increasing variability in intraday generation output that affects nearly all of the units in the sample, but the magnitude of increase varies widely among plants. Outage patterns were examined as was the relationship between renewable energy growth in a region and the changes in coal plant operations. Aggregate direct and indirect costs associated with running coal plants as load-following units have not yet been quantified in large-scale studies on a sector-wide basis, largely due to differences in how specific equipment responds to output fluctuations. Due to findings from the hourly generation data analysis and the high degree of potential impact on coal plant equipment, the study suggests the development of a new modeling tool that will represent the costs of running coal-fired power plants at lower capacity factors.

Abstract:Active splitting control utilizes real-time decision and system-level splitting to prevent cascading blackouts and to maintain power supply under severe disturbances. Splitting strategy searching (SSS) is one of the most crucial issues in active splitting control for deciding ‘‘where to split’’. SSS determines the splitting surface in real time to properly divide the asynchronous generators into isolated islands with an optimal control effect. In this paper, an SSS approach that focuses on island stability is presented. The proposed SSS approach is designed to ensure a rational stability margin and regulation ability on each island during and after the transient process of system splitting. This method includes the active/reactive power flow feasibility constraints and voltage/angle stability constraints in the steady state, as well as the frequency response capability constraints in the transient process. By considering the island stability constraints in the SSS, the proposed approach can avoid the splitting strategies with poor stability performance. Therefore, the major advantage of the proposed approach is ensuring better island static and transient stability during and after the splitting control. In addition, the entire model is formulated as a mixedinteger second-order cone programming (MISOCP) model. Thus, it can be rapidly solved by using commercial optimization solvers. Numerical simulation of a realistic provincial power system in central China demonstrates the validity of the proposed approach and the necessity of considering the island stability issues.

Abstract:In this study, controller parameters of static var compensators (SVCs) at planned locations are optimized to mitigate fault-induced delayed voltage recovery issues and improve angular stability of a multi-machine power system. The problem is formulated as a nonlinear optimization problem involving constraints on post-fault trajectories of voltages and frequencies. This paper proposes a mesh adaptive direct search based algorithm interfaced with a power system simulator for optimization of SVC controller parameters. The proposed method is tested on the NPCC 140-bus system to optimize controller parameters for three SVCs. Simulations on critical contingencies verify that post-fault transient voltages and generator speeds can both quickly recover and transient stability of the system is improved.

Abstract:The influence of parameters on system states for parametric problems in power systems is to be evaluated. These parameters could be renewable generation outputs, load factor, etc. Polynomial approximation has been applied to express the nonlinear relationship between system states and parameters, governed by the nonlinear and implicit equations. Usually, sampling-based methods are applied, e.g., data fitting methods and sensitivity methods, etc. However, the accuracy and stability of these methods are not guaranteed. This paper proposes an innovative method based on Galerkin method, providing global optimal approximation. Compared to traditional methods, this method enjoys high accuracy and stability. IEEE 9-bus system is used to illustrate its effectiveness, and two additional studies including a 1648-bus system are performed to show its applications to power system analysis.

Abstract:The rapid development of renewable energy sources such as wind power has brought great challenges to the power grid. Wind power penetration can be improved by using hybrid energy storage (ES) to mitigate wind power fluctuation. We studied the strategy of smoothing wind power fluctuation and the strategy of hybrid ES power distribution. Firstly, an effective control strategy can be extracted by comparing constant-time low-pass filtering (CLF), variable-time low-pass filtering (VLF), wavelet packet decomposition (WPD), empirical mode decomposition (EMD) and model predictive control algorithms with fluctuation rate constraints of the identical grid-connected wind power. Moreover, the mean frequency of ES as the cutoff frequency can be acquired by the Hilbert Huang transform (HHT), and the time constant of filtering algorithm can be obtained. Then, an improved low-pass filtering algorithm (ILFA) is proposed to achieve the power allocation between lithium battery (LB) and supercapacitor (SC), which can overcome the over-charge and over-discharge of ES in the traditional low-pass filtering algorithm (TLFA). In addition, the optimized LB and SC power are further obtained based on the SC priority control strategy combined with the fuzzy control (FC) method. Finally, simulation results show that wind power fluctuation can be effectively suppressed by LB and SC based on the proposed control strategies, which is beneficial to the development of wind and storage system.

Abstract:Wind power curtailment is of great importance with the increase of large-scale wind power connected to the grid. A new concept of redundant wind power accommodated by dispatching electric water heaters (EWHs) is developed in the paper. Precise predictions of wind power and EWHs load power are the basis for this work. A hybrid multi-kernel prediction approach integrating an adaptive fruit fly optimization algorithm (AFOA) and multi-kernel relevance vector machine (MKRVM) is proposed to deal with the sample distribution of multisource heterogeneous features uncovered by an energy entropy method, where AFOA is used to determine the kernel parameters in MKRVM adaptively and avoid the arbitrariness. For the large computation of the prediction approach, parallel computation based on the Hadoop cluster is used to accelerate the calculation. Then, an economic dispatching model for accommodating wind power is built taking into account the penalty of curtailed wind power and the operating cost of EWHs. The proposed scheme is implemented in an intelligent residential district. The results show that the optimization performance of the hybrid prediction approach is superior to those of four usual optimization algorithms in this case. Regular or orderly scheduling of EWHs enables accommodation of superfluous wind power and reduces dispatch cost.

Abstract:This paper presents a method for managing congestion constraints in a hydro-thermal optimal power flow solution procedure. The congestion constraint is handled in this paper as an active power generation constraint. To achieve this solution, a power flow tracing technique is used to detect the generators contributing to line congestion to penalize them by reducing their outputs. The congestion is then removed by setting the maximum power of the affected generators to the penalized value. The proposed algorithm is implemented using MATLAB software. Finally, the performance of the proposed algorithm is tested and the results for the 5-bus, 30-bus, and 34-bus Nigerian power networks are presented.

Abstract:To effectively study the dynamics of power systems with large-scale wind farms (WFs), an equivalent model needs to be developed. It is well known that back-toback converters and their controllers are important for the dynamic responses of the wind turbine (WT) under disturbances. However, the detailed structure and parameters of the back-to-back converters and their controllers are usually unknown to power grid operators. Hence, it is difficult to build an accurate equivalent model for the WF using the component model-based equivalent modeling method. In this paper, a transfer function based equivalent modeling method for the WF is proposed. During modeling, the detailed structure and parameters of the WF are not required. The objective of the method is reproducing the output dynamics of the WF under the variation of the wind speed and power grid faults. A decoupled parameter-estimation strategy is also developed to estimate the parameters of the equivalent model. A WF that consists of 16 WTs is used to test the proposed equivalent model. Additionally, the proposed equivalent modeling method is applied to build the equivalent model for a real WF in Northwest China. The effectiveness of the proposed method is validated by the real measurement data.

Abstract:An active crowbar protective circuit is an effective and common approach for low voltage ride through (LVRT) of a doubly-fed induction generator (DFIG). The crowbar resistance value and its switching scheme both have crucial effects on safety recovery. The effects encountered are correlative dependence and interplay so that analyzing them from a single factor, as most existing LVRT control methods would do, obtains a partial optimal solution. This paper connects these two factors to analyze their coordination effects on the LVRT control, and to also investigate whether the global optimal performance of these factors can be achieved. The principles for resistance selection and the schemes for crowbar switching are discussed first. Next the coupling relationship is analyzed based on statistical sampling simulation data with different resistance values and various switching schemes. The results demonstrate that their coordination has critical influence on rotor peak current, DC-link voltage and reactive power. The optimal coordination will be different according to specific requirements. Hence the global optimal combination could be achieved when all requirements are taken into consideration.

Abstract:This paper proposes a day-ahead dispatch framework of thermostatically controlled loads (TCLs) for system peak load reduction. The proposed day-ahead scheduling framework estimates the user’s indoor thermal comfort degree through the building thermal inertia modelling. Based on the thermal comfort estimation, a dayahead TCL scheduling model is formulated, which consists of 3 stages: TCL aggregator estimate their maximal controllable TCL capacities at each scheduling time interval by solving a optimization model; ` the system operator performs the day-ahead system dispatch to determine the load shedding instruction for each aggregator; and ′ the TCL aggregators schedules the ON/OFF control actions of the TCL groups based on the instruction from the system operator. A heuristic based optimization method, history driven differential evolution (HDDE) algorithm, is employed to solve the day-ahead dispatch model of the TCL aggregator side. Simulations are conducted to validate the proposed model.

Abstract:Due to their heat/cool storage characteristics, thermostatically controlled loads (TCLs) play an important role in demand response programmers. However, modeling of the heat/cool storage characteristic of large numbers of TCLs is not simple. In this paper, the heat exchange power is adopted to calculate the power instead of the average power, and the relationship between the heat exchange power and energy storage is considered to develop an equivalent storage model, based on which the time-varying power constraints and the energy storage constraints are developed, to establish the overall day-ahead scheduling model. Finally, the proposed scheduling method is verified using the simulation results of a six-bus system.

Abstract:Distribution network reconfiguration (DNR) can significantly reduce power losses, improve the voltage profile, and increase the power quality. DNR studies require implementation of power flow analysis and complex optimization procedures capable of handling large combinatorial problems. The size of distribution network influences the type of the optimization method to be applied. Straightforward approaches can be computationally expensive or even prohibitive whereas heuristic or meta-heuristic approaches can yield acceptable results with less computation cost. In this paper, a customized evolutionary algorithm has been introduced and applied to power distribution network reconfiguration. The recombination operators of the algorithm are designed to preserve feasibility of solutions (radial structure of the network) thus considerably reducing the size of the search space. Consequently, improved repeatability of results as well as lower overall computational complexity of the optimization process have been achieved. The optimization process considers power losses and the system voltage profile, both aggregated into a scalar cost function. Power flow analysis is performed with the Open Distribution System Simulator, a simple and efficient simulation tool for electric distribution systems. Our approach is demonstrated using several networks of various sizes. Comprehensive benchmarking indicates superiority of the proposed technique over state-of-the-art methods from the literature.

Abstract:From flexible interconnection among feeders to hybrid alternating current (AC) and direct current (DC) distribution structures of future smart distribution systems, medium-voltage DC distribution centers with flexibly interlinked multiple microgrids (MGs) will have wide applications on the demand side. A generic coordinated control framework based on a distributed cooperation scheme is proposed for such DC centers, as opposed to centralized control structures. A novel unified control only using local measurements is proposed for these interlinking converters. During normal power disturbances, automatic coordinated power control and mutual support among subsystems can be realized, thereby improving DC voltage and AC frequency stability to enable multiple MGs to be treated as a real unified cluster. Moreover, with this method, interlinking converters can realize seamless transition in power dispatching mode, common DC bus voltage control mode, and MG support mode without communication and control system switching. A simplified dynamic model has been developed to verify the proposed control strategy. This work is expected to provide a new solution for flexible interconnection and operational control of large-scale MG clusters.

Abstract:This paper presents a simplified small-signal stability analysis method for low voltage (LV) inverterbased microgrids, in a generalized manner. The simplification is based on a simplified microgrid structure that relies on dominating inverter coupling impedances with respect to interconnecting line impedances of LV distribution networks. The analysis is further simplified by analytically determining equilibrium points of system state variables in terms of known microgrid parameters. And it eliminates the additional analysis required for determination of the equilibrium points of the state variables. Simulation and analysis results show that the proposed method successfully predicts the instability boundaries of microgrid systems for resistive interconnecting lines.

Abstract:Voltage source converter (VSC) based high voltage direct current (HVDC) transmission is most suited for the wind farm as it allows flexibility for reactive power control in multi-terminal transmission lines and transmits low power over smaller distance. In this work, a novel method has been proposed to detect the fault, identify the section of faults and classify the pole of the fault in DC transmission lines fed from onshore wind farm. In the proposed scheme, voltage signal from rectifier end terminal is extracted with sampling frequency of 1 kHz given as input to the detection, classification and section discrimination module. In this work, severe AC faults are also considered for section discrimination. Proposed method uses fuzzy inference system (FIS) to carry out all relaying task. The reach setting of the relay is 99.9% of the transmission line. Besides, the protection covers and discriminates the grounding fault with fault resistance up to 300 X. Considering the results of the proposed method it can be used effectively in real power network.

Abstract:The use of overhead lines for power transmission in the future high-voltage and large-capacity voltagesource converter (VSC)-based direct current (DC) grid will significantly increase the probability of temporary faults. To eliminate potential adverse impacts such as erroneous protection, line-insulation failure, and even damage to power electronic devices resulting from a DC breaker reclosing operation with the traditional sequential autoreclosing strategy, a novel sequential auto-reclosing strategy for hybrid HVDC breakers (HHBs) in VSC-based DC grids is proposed. This strategy is based on the step-by-step operation of the transfer branch in the HHB. As a result, du/dt resulting from the HHB reclosing operation is greatly reduced, and therefore those potential negative impacts can be eliminated. Several other advantages are also presented. The feasibility and validity of the proposed strategy are verified in a four-terminal annular VSC-based DC grid electromagnetic transient model.

Abstract:The denoising and detection of transient disturbances are two important subjects for power quality monitoring and analysis. To effectively denoise and detect transient disturbances under noisy conditions, an improved iterative adaptive kernel regression method is proposed in this paper. The proposed method has advantages in that it does not need to estimate the noise variance or a filter threshold, and has both denoising and detection capabilities for transient disturbances. Simulation results demonstrate that the proposed method provides excellent denoising effects, which can not only suppress noise effectively but also preserve disturbance features of sudden change points well. Additionally, it provides good detection and location performance for single and combined transient disturbances, even under strong noise conditions. Finally, the effectiveness of the proposed method is further verified by using real disturbance data.

Abstract:This paper proposes an adjustable and distributionally robust chance-constrained (ADRCC) optimal power flow (OPF) model for economic dispatch considering wind power forecasting uncertainty. The proposed ADRCC-OPF model is distributionally robust because the uncertainties of the wind power forecasting are represented only by their first- and second-order moments instead of a specific distribution assumption. The proposed model is adjustable because it is formulated as a second-order cone programming (SOCP) model with an adjustable coefficient. This coefficient can control the robustness of the chance constraints, which may be set up for the Gaussian distribution, symmetrically distributional robustness, or distributionally robust cases considering wind forecasting uncertainty. The conservativeness of the ADRCC-OPF model is analyzed and compared with the actual distribution data of wind forecasting error. The system operators can choose an appropriate adjustable coefficient to tradeoff between the economics and system security.