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As an essential apparatus in resonance grounding systems, the arc suppression coil is widely used in rejecting the single‐line‐to‐ground (SLG) fault of distribution networks. However, the resistive ground‐fault current cannot be compensated by an arc suppression coil (ASC). As a novel active arc suppression device, the hybrid flexible arc suppression device (HFASD) composed of ASC and flexible arc suppression device (FASD) can eliminate the capacitive component of ground‐fault current and the resistive component of ground‐fault current. After the SLG fault occurs, the FASD from stand‐alone mode to grid‐connected mode may lead to switching transients, affecting the stability of distribution networks. The soft grid connection (SGC) strategy can achieve low or without transient response during the grid synchronization of FASD to the grid. Thus, the HFASD based on SGC strategy and segmented proportional‐integral‐differential (SPID) and second‐order generalized integrator phase‐locked loop (SOGI‐PLL) control method is proposed for rejecting the current and voltage overshoot responses during the process of grid synchronization of FASD in this paper. Simulation and experimental results verify the effectiveness of the proposed method, and the benefit of the proposed method is indicated in comparison with the non‐SGC (NSGC) strategy. [ABSTRACT FROM AUTHOR]

Improving network power quality through harmonic reduction requires recognition of Harmonic Sources (HSs) to drive them to compensate their harmonics. This paper proposes a new method for equitable distribution of the Harmonic Compensation Cost of the network among the HSs based on the Harmonic Contribution Matrix. Each element of the Harmonic Contribution Matrix is the harmonic contribution of a specific source to the harmonic voltage of a specific bus. The output of the proposed method is a penalty curve for each HS over time. The amount of the fine estimated for each individual HS per hour is a function of not only the contribution of that HS to the harmonic voltage of different buses, but also the contribution of the Harmonic Compensation Cost from the perspective of each bus, nominal voltage of each bus, and the sensitivity of each bus to the harmonic voltage. The proposed algorithm is evaluated on the IEEE 14‐bus network and Esfahan regional electrical power network in Iran. The simulation results demonstrate the capability of the proposed method to allocate the hourly penalty curve to the HSs. [ABSTRACT FROM AUTHOR]

User-side load monitoring is a key technology to realize smart utilization of electric power. Since the traditional intrusive load monitoring involves a comparatively large economic cost and execution complexity, this paper studies a way to rapidly identify residential power load in a nonintrusive monitoring mode. A template-filtering-based nonintrusive, rapid residential load identification algorithm is proposed, which is based on frequency-domain analysis of current signals, in combination with the current model when the nonintrusive monitoring load is in operation, and by making use of the fact that the spectrum components of the current signals working independently are completely contained in the hybrid current spectrum. Characteristic currents of the various loads in the power grid are acquired a priori to establish the characteristic filter, and 0-1 valuation is performed on their spectrum components to get the template filter. The template filter is then used to filter the hybrid current signals captured in the nonintrusive mode, and the operation status of the loads is judged and determined after quantification of the filtered frequency components. For the same type of load under different operating conditions, the template filter can be commonly used. Efficiency of the algorithm is verified by making use of the actually collected power consumption data, which is able to accurately identify the load operation status. Furthermore, the algorithm is shown to be highly efficient and can be realized via fast Fourier transform (FFT), and its hardware packaging can be easily realized. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In this paper, an online algorithm of automatic power factor correction (APFC) for distribution power grids is presented. The algorithm depends on Pearson similarity of voltage and current signals, which can easily be measured locally using voltage and current transformers, respectively. The proposed method not only evaluates the original power factor (PF), but also functions the APFC more quickly. In this work, the compensation index and reactive power compensation can be identified using new mathematical formulas based on the cross-correlation coefficients calculated between the phase voltage and current signals. Moreover, the coefficients are useful for detecting any abnormal condition. The method performance is examined on a large-scale network with real parameters' data, which is simulated using the alternative transient program (ATP) environment, and the proposed algorithm is developed in MATLAB package. Numerous simulation results confirm the APFC relay feasibility, and the unity PF can be achieved. Besides, the proposed algorithm is characterized by its high operating speed, safety and accuracy for PF compensation, where its performance accuracy is greater than 99.7%. The approach offers novel operating/tripping curves based on the correlation coefficients for both power factor correction (PFC) and protection functions. Therefore, it is described with high level of functionality integration, and its security and sensitivity are controllable easily using the correlation settings. [ABSTRACT FROM AUTHOR]

The increasing number of Plug‐in Electric Vehicles (PEV) connected to the grid will create challenges to be addressed and opportunities that can be ceased. One challenge is the load shape dynamics, which might result in increasing the loading level on the distribution lines. On the other hand, there is an opportunity to use the PEV stored energy to provide ancillary services to the grid. Therefore, this paper proposes a new PEV charging mechanisms that not only aid in ancillary service provision, but also help in reducing the charging cost and avoiding the extra investment in peak generation units while maximizing the integrated PEVs. The proposed approach utilizes three stages to ensure the satisfaction of PEV owners with different preferences and to respect the grid limitations. The main objective is to develop different charging mechanisms for charging PEV's in the parking lots to ensure the maximum satisfaction of the PEV owners by fulfilling their charging requirements with the minimum possible cost. The developed algorithm relies on a moving time window to address the real‐time changes and considers the participation of PEVs in the frequency regulation and peak shaving. The effectiveness of the proposed algorithm is verified through simulation using real data. [ABSTRACT FROM AUTHOR]

To collect end-user data in a transformer area, this paper reports a collection algorithm based on the longest independent path methods for the first time. The algorithms are successfully applied to one experimental area and one actual area. The operation processes are detailed. Simulation proves that the algorithm can precisely search for data of end users. Important information is also obtained for power-line carrier meter reading and for improving the quality of the power supply in an area by using the algorithm. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In this research work, an admissible searching‐based algorithm A‐star and binary search tree is proposed to unravel the optimal phasor measurement unit (PMU) placement problem (OPPP) for achieving full interconnected power network observability considering contingencies. The proposed method is an advanced version of the best‐first search method that finds minuscule paths to the best solution. Moreover, it is an optimal and complete search method. Optimal signifies that the proposed method is guaranteed to unravel the minimum cost from origin to the terminus point and Complete denotes that it is going to determine all the possible paths that are available to us from the origin to the destination. The binary tree is used for this purpose as its structural design is well‐matched with the proposed method. Integrating an A‐star algorithm and binary search tree enhances the optimization and performance toward unraveling the OPPP. Also, for more than one solution of OPPP, redundancy measurement is taken into consideration. The proposed method is applied on standard IEEE‐14, ‐30, ‐118, New England‐39, and northern regional power grid (NRPG) 246‐bus test systems. Furthermore, to check the scalability of the proposed method, the Polish 2383‐bus system is considered. The obtained experimental results were compared to established procedures published in peer‐reviewed journals, and the proposed methodology outperformed the other comparison approaches. Thus, the proposed method successfully accomplishes complete observability of the power networks. [ABSTRACT FROM AUTHOR]

Identifying problems in insulators is a task that requires the experience of the operator. Contaminated insulators generally do not represent a system failure, however, due to higher surface conductivity, they may suffer from electrical discharges and may result in irreversible failures. The identification of possible failures in inspections can help to forecast faults to improve reliability in the power grid. Based on this need, this article presents a study on fault prediction in distribution insulators, through a laboratory evaluation in a contaminated insulator, where 13.8 kV (root mean square) was applied considering an ultrasound detector connected to a computer for data set acquisition. In the sequence, a time series prediction, using a hybrid deep learning technique defined as wavelet long short‐term memory (LSTM), was performed. The hybrid LSTM was proposed considering feature extraction through the wavelet energy coefficient. Finally, for a complete evaluation, deeper LSTM layers were included, and both the training method and the hardware configuration were evaluated. The wavelet LSTM algorithm showed interesting accuracy results when compared to classic prediction algorithms like the non‐linear autoregressive exogenous model. [ABSTRACT FROM AUTHOR]

This study presents a new re-scheduling method for generating units in the form of optimal power flow (OPF) problem, considering small signal stability (SSS) constraint of power system in normal operation and N−1 contingency of transmission lines outage. In base case, total operation cost is minimized, considering voltage stability margin and N−1 line contingency. The SSS of system is studied by using modal analysis. In case of unstable modes in the generator(s) rotor angle, the generators scheduling should be re-dispatched. Using modal analysis and sensitivity matrix, the generators are divided into three groups: increasing power generators, decreasing power generators, and unchanged power generators. In order to increase the accuracy of re-scheduling program, two new technical and economic indexes are introduced. The output power of the candidate generators is increased/decreased based on the indexes to stabilize generator(s) with unstable rotor angle (URA). The salient feature of proposed method is its capability on stabilizing system with one or more URA generators with minimum changes in base case OPF results. The Validity of proposed method is studied on IEEE 39-bus 10-machine, and IEEE 69-bus 16-machine test systems. The obtained results verify effectiveness of proposed re-dispatch algorithm in case of single or multiple URA generator(s). [ABSTRACT FROM AUTHOR]

One of the most effective approaches to reduce carbon emissions is the integration of renewable energy sources into electrical power networks. Currently, wind turbines are the fastest growing among all renewable sources. With the integration of wind farms into electrical grids, the economic emission dispatch (EED) problem is becoming more complicated due to the stochastic availability of wind energy. In this study, a new approach is proposed to solve the EED problem incorporating wind farms. The problem is formulated as a chance-constrained problem to deal with the stochastic characteristic of wind power. A novel chaotic sine–cosine algorithm (CSCA) is proposed to provide the optimal generation schedule to minimise simultaneously the generation cost and emission. Some weakness has been encountered in exploitation and exploration capabilities in standard sine cosine algorithm (SCA). Hence, the chaos is integrated into the original SCA to improve its performance. In addition, a new mutation strategy is added to the SCA. In this study, the new algorithm is based on three mutually exclusive equations. The new technique is applied on the 69-bus ten-unit and 40-unit test systems with and without wind energy. The results performed by CSCA are compared with those generated by other recent techniques. [ABSTRACT FROM AUTHOR]

Phasor measurement unit can monitor the variation of phase angle of power grid in real time, which is of great significance to ensure the safe and stable operation of power grid. Among them, the virtual phasor measurement algorithm based on discrete Fourier transform (DFT) has been widely used because of its simple principle and relatively easy implementation. However, the existing virtual phasor measurement algorithm only gives the dynamic error reduction effect under the fixed offset angle, and does not give the rule of the reduction effect with the different offset angle. The relationship between anti-harmonic interference capability and response speed with the different offset angles is not analysed. Therefore, this study deduces the pattern of dynamic error reduction effect, anti-harmonic interference ability and response speed with the different offset angles. The dynamic error reduction effect of the algorithm is the best when the offset angle is π/2, and the anti-harmonic interference ability of the algorithm is the strongest when the offset angle is π/3. The response speed of the algorithm increases linearly with the increase of the offset angle. On this basis, the correctness of the algorithm is verified by numerical simulation experiments. [ABSTRACT FROM AUTHOR]

The continuing growth of an offshore wind farm integrated into a power grid via high-voltage DC has posed great challenges for automatic generation control (AGC) of the power system. To address these challenges, a new concept of 'dynamic dispatch of AGC units (DDA)' under control performance standards from the view of economic dispatch (ED) has been proposed in the previous work, and proved to be an effective technique to co-operate the AGC units with different ramping rates and to fill the gap between ED and AGC. However, the existing DDA model is deterministic in nature, which can hardly deal with the uncertain forecasting error of the offshore wind power output. A novel stochastic DDA model based on chance-constrained programming is proposed considering a random offshore wind power forecasting error, and a hybrid algorithm combining the evolutionary programming algorithm and point estimate method is then developed to solve the stochastic model. Numerical results from a two-area test system with additional offshore wind power generation demonstrate the accuracy and computation efficiency of the hybrid algorithm and the benefits offered by the stochastic AGC dispatch method. [ABSTRACT FROM AUTHOR]

Renewable energy sources provide an important means of reducing reliance on conventional fuels. However, some renewable energy resources such as wind and solar energies are intermittent, and their uncertainty threatens the operating security of the power grid. To solve this problem, this study proposes the use of intervals to model the power output of renewable energy resources and the power load demand, and accordingly develops an interval voltage control model, i.e. interval reactive power optimisation model. The proposed model considers the control modes of renewable energy power generators and can safeguard the security of power grids by ensuring that the voltages reside within established limits. An adaptive genetic algorithm is employed to solve the proposed model, where a newly developed interval power-flow (IPF) calculation is used to solve the IPF equations, and penalty functions are applied to express inequality constraints. The proposed method is introduced in detail, and simulation results are presented to demonstrate its performance in comparison with a previously proposed interval voltage control method, as well as its applicability to large systems with various fluctuations of input data. The proposed approach provides robust convergence, obtains lower system power losses, and substantially reduces the computation time. [ABSTRACT FROM AUTHOR]

Efficient transient simulation of large power grid is of great importance for system operation and dispatching, fault repetition, operator training etc. Online stability estimation and testing on system control and protection require hard real-time performance of transient simulation. The conventional real-time simulation, which splits an entire grid into sub-grids and solves them in parallel, lacks generality for various case systems. This study proposes a new efficiency enhancement method without grid partitioning. Three key techniques are involved. First, parallel solving format is proposed to distribute two-layer computational burdens into central processing unit cores in balance. Second, to calculate the fault changing the grid structure, the inverse current compensation is employed instead of re-forming impedance matrix and repeating lower-upper (LU) decomposition. Third, dual-loop forward and backward substitutions to solve grid equations are modified to a single-loop iteration, which further improves the computational efficiency. At last, the validity and effectiveness of the proposed method are verified by tests. [ABSTRACT FROM AUTHOR]

Rational partitioning method of power grid is the premise and foundation to implement wide-area backup protection with multi-source information. This study shows the universal structure of a wide-area backup protection system based on regional centralised decision-making mode, and presents a multi-objective optimisation method of power grid partitioning. Under the premise of reliable protection, a multi-objective function is built, comprehensively considering the communication performance, overlap rate, and the balance of regional workloads. To obtain the optimal result, the brain storm optimisation (BSO) algorithm is used in this study. The method is applied on IEEE 11-bus and 39-bus test systems and simulated data is used to verify the effectiveness and feasibility of the optimisation method. [ABSTRACT FROM AUTHOR]