Grid Scheme Research Articles

Abnormal line loss identification system of low voltage distribution network based on HPLC communication technology

AbstractPower cable is mainly responsible for the transmission and distribution of electric energy in the power grid. The performance of a power cable greatly affects the reliability and security of the power supply. In order to solve the problem of cable aging caused by long‐term operation and various internal and external factors, this paper proposes an abnormal line loss identification method for a low‐voltage distribution network station area, aiming at focusing on the monitoring of cable aging. The transmission characteristic model based on the transmission line theory and the dielectric constant model of the aging cable insulation layer is established, and the internal relationship between the transmission characteristic and the aging characteristic is analyzed. The characteristic extraction algorithm is used to extract the characteristics of the transmission characteristic curve. Through simulation analysis, for the abnormal line loss fault, the location accuracy of different fault locations is basically at the level of 0.1–0.3%. The simulation of local defects in the cable shows that the change of material dielectric constant is more clear for the characterization of cable aging. The monitoring method in this paper is helpful to provide the relevant basis for the line maintenance plan and the operation strategy of the power grid and is of great significance to ensure the safe and stable operation of the power grid.

LVRT Control Strategy for Three-Phase Grid Connected PV System

LVRT Control Strategy for Three-Phase Grid Connected PV System

AVC Planning Strategy of Power Grid Based on Genetic Algorithm Improved Neural Network Quantile Regression

Aiming at the security risk of power system instability, this paper proposes a parameter optimization AVC planning strategy based on neural network. Based on a variety of power grid operation modes, the strategy innovatively uses genetic algorithm to improve the neural network quantile regression control variables to obtain state variables. This method can reduce the frequency of invalid operations, make the AVC control strategy more stable, and improve system security. In the actual case, the improved neural network quantile regression of genetic algorithm improves the accuracy by at least 29% compared with multiple linear regression.

Placement and Capacity of EV Charging Stations by Considering Uncertainties With Energy Management Strategies

At the present context, Plug-in electric vehicles (PEVs) are gaining popularity in the automotive industry due to their low CO2 emissions, simple maintenance, and low operating costs. As the number of PEVs on the road increases, the charging demand of PEVs affects distribution network features, such as power loss, voltage profile, and harmonic distortion. Furthermore, one more problem arises due to the high peak power demand from the grid to charge the PEVs at the charging station (CS). In addition, the location of CS also affects the behavior of EV users and CS investors. Hence, this paper applies CS investor, PEV user, and distribution network operator who could approach to CS's optimal location and capacity. Integrating renewable energy sources (RESs) at the charging station is suggested to lower the energy stress on the grid. Moreover, to keep down the peak power demand from the grid and utilize renewable energy more efficiently, energy management strategies (EMS) have been applied through the control of charging and discharging of the battery storage system (BSS). In addition, vehicle to grid (V2G) strategy is also applied to discharge the EV battery at charging station. Furthermore, the uncertainties related to PEV charging demand and PV power generation are addressed by the Monte Carlo Simulation (MCS) method.

A non-unit transmission line protection scheme for MMC-HVDC grids based on a novel distance criterion

Ultra-fast, selective, and reliable protection is significant for MMC-HVDC grids. The methods utilizing the characteristics of fault current limiting reactor (FCLR) are unsatisfactory to detect high resistance faults. In this paper, a novel distance criterion is proposed to form the non-unit protection scheme. The line-zero-mode fault equivalent circuit is built to analyze the characteristics of fault traveling waves at the inductive terminal considering the influence of MMC and the refraction and reflection at the fault point. A multi-resolution morphological gradient algorithm (MMGA) is employed to extract the geometric features of the fault traveling waves. The magnitude of the first modulus maxima of the line-mode fault voltage after MMGA constitutes the start-up criterion. The estimated velocity and the change direction of the line-mode components are adopted to identify if the fault happens in-region. The 4-terminal ±500 kV MMC-HVDC grid built in PSCAD/EMTDC demonstrates that the proposed scheme can accurately identify various faults. The sensitivity analysis shows that the proposed scheme is almost immune to the size of FCLR, the equivalent parameters of MMC, the noise environment, and the DCCB breaking process. The proposed scheme has low requirements for sampling frequency and can be utilized to identify the temporary fault.

The Effects of Heat Transfer through the Ends of a Cylindrical Cavity on Acoustic Streaming and Gas Temperature

The longitudinal vibrational motion of a cylindrical cavity with gas, in which the acoustic streaming occurs, is considered. The motion is described by the system of equations for the dynamics and thermal conductivity of a viscous perfect gas, written in a cylindrical coordinate system associated with the cavity. The system of equations is solved numerically by the finite volume method with an implicit staggered grid scheme, while the convective–diffusion fluxes are approximated by the power law scheme. According to the boundary conditions, the lateral surface of the cavity is maintained at a constant equal initial temperature. The effects of heat transfer through the ends of the cavity are studied. Heat transfer is given by isothermal boundary conditions. The obtained solutions are compared with the solutions under adiabatic boundary conditions. It is shown for the first time that the effects of heat transfer manifest themselves with an increase in the nonlinearity of the process; when the frequency and amplitude of vibration increase, this is also facilitated by an increase in the radius of the cavity. The effects of heat transfer on the period average temperature, on the streaming velocity and on structure are established.

Fault Detection and Zonal Protection Strategy of Multi-Voltage Level DC Grid Based on Fault Traveling Wave Characteristic Extraction

Currently, DC breakers are commonly used in mainstream protection schemes for DC grids to eliminate faults. However, the cost of high voltage DC (HVDC) breakers is high, and equipping each DC line with DC breakers is expensive. In order to minimize the number of DC breakers while ensuring the reliability of the power supply, a zonal protection strategy suitable for multi-voltage level DC grids is proposed. Subsequently, the qualitative impact of partial power interruption caused by fault DC areas is analyzed in the system. The basic zonal principle of the multi-voltage level DC grid is formulated, taking into account unbalanced power, the mode of system-level control, and the type of converters. Additionally, a time sequence coordination strategy is derived in detail based on the characteristics of DC breakers, AC/DC converters, DC/DC converters, AC breakers, high-speed switches, and other fault removal components. Finally, a seven-terminal DC grid is modeled in the PSCAD/EMTDC simulation platform. According to the simulation analysis, the DC grid can adopt the converter with fault clearing ability or an AC circuit breaker to cooperate with the fast disconnector (FD) to complete fault clearing in the DC fault area under the proposed zonal protection coordination strategy.

F-LMS Adaptive Filter Based Control Algorithm With Power Management Strategy for Grid Integrated Rooftop SPV-BES System

The power quality performance of a grid-integrated rooftop solar photovoltaic (SPV) system is significantly affected by the local nonlinear loads. Further, during peak solar insolation and load demand, the SPV system experiences overvoltage and undervoltage at its point of interconnection. Both these issues infringe the IEEE std. 519 and 1547. Therefore, this paper presents a fractional least mean square (F-LMS) based control with the power management strategy (PMS) for the SPV-battery energy storage (BES) system. This presented control uses the SPV system's power converter to compensate load currents locally. By this means, the grid voltages and currents remain distortion-free. The introduced F-LMS algorithm is used as a pre-filter for load current. It estimates the load current fundamental component more accurately and swiftly than the existing LMS method. The designed PMS supervises the SPV array generation, BES power, and grid power to cater to both over and undervoltage issues and keeps the PIC voltage amplitude within the IEEE std. 1547 limits. In addition, this work enables the autonomous operation of SPV system during grid disruption, enhancing power resilience. The efficacy of the introduced work is experimentally verified.

A new implementation of the beam migration by using a model-driven variable grid strategy

Beam migration offers higher imaging accuracy, better flexibility, stability and adaptability than conventional ray migration, while the variable grid method achieves lower storage and higher efficiency under the same accuracy by means of different grid generation of the velocity model. However, the efficiency and accuracy of Gaussian beam migration are strongly affected by the algorithm used for Gaussian beam summation whose key step is to find the underground point at which the local beam contributes relevantly to the reconstruction of the Green's function. Conventionally, one uses Hale's recursive search method that firstly searches on a global coarse grid and then interpolated to a local fine one. Practical experience shows that this method can greatly improve the efficiency of the beam scanning, but causes some wavy discontinuities and imaging artifacts as well. To solve this problem, we present a new method called “model-driven variable grid strategy”. In this strategy, a key step is to establish a relationship between the vertical gradient of the velocity model and the local grid constants through local velocity gradient with respect to the global average velocity. Numerical tests on synthetic and field data show that the new method has a minimal need on computer resources and can largely improve the accuracy and efficiency of the beam migration in regions with complex geological structures.

Wavelet Analysis to Detect Ground Faults in Electrical Power Systems with Full Penetration of Converter Interface Generation

The requirements for the increased penetration of renewable energy sources in electrical power systems have led to a dominance of power electronic interfaces. As a result, short-circuit currents have been reduced by the thermal limitations of power electronics, leading to problems associated with the sensitivity, selectivity, and reliability of protective relays. Although many solutions can be found in the literature, these depend on communications and are not reliable in all grid topologies or under different types of electrical fault. Hence, in this paper, the analysis of ground fault currents and voltages using a wavelet transform in combination with a new algorithm not only detects such ground faults but also allows them to be cleared quickly and selectively in scenarios with low fault current contribution due to a full penetration converter-interface-based generation. To verify and validate the proposed protection system, different ground faults are simulated using an arc ground fault model in a grid scheme based on the IEEE nine-bus standard test system, with only grid-forming power converters as generation sources. The test system is modelled in the MATLAB/Simulink environment. Therefore, the protection relays that verify all the steps established in the new algorithm can detect and clear any ground defect. Simulations are also presented involving different fault locations to demonstrate the effectiveness of the proposed ground fault protection method.

A two-stage optimization method for Vehicle to Grid coordination considering building and Electric Vehicle user expectations

The formulation of the Vehicle to Grid (V2G) scheme should ideally consider both Electric Vehicle (EV) and building owners’ viewpoints. From the building owner’s viewpoint, the EVs should be present in the building and participate consistently to deliver the required power. From the EV owners’ viewpoint, participating in the V2G scheme should provide economic incentives while not compromising their travel needs. However, those proposed V2G algorithms up to this point in time had not considered any corrections required in response to unplanned changes in the EV travel plan. In this paper, a Two-stage optimization technique is proposed to determine the charging and discharging schedule for EVs participating in a vehicle-to-grid (V2G) programme at an office building. The EV owners’ travel convenience is focused with more attention in the proposed model by giving them two V2G options. Firstly, day-ahead optimization (DAO) is applied, based on the expected building load profile and EV behaviour, the optimal charging or discharging control of the EVs is obtained in order to save electricity bills by minimizing the maximum demand of the building. Subsequently, a real-time optimization (RTO) is performed to adjust the V2G operation based on actual vehicle behaviours which usually deviate from their estimations. Simulations are conducted and the preliminary results show that the proposed technique is able to adjust the EV charging or discharging in real-time with the aid of the day-ahead stage. The proposed model manages to capture a new ideal optimal maximum demand point and maintain the EV SOC profile as planned from the DAO stage in real-time when prediction deviation occurs. In addition, a comprehensive cost–benefit analysis in utilizing V2G in peak load reduction is also performed to gain insight into the potential savings and discharging rewards attributable to the building and EV owner respectively.

Adaptive Clustering Quasi-Line Search Path Planning Algorithm Based On Sampling

In this paper, the adaptive clustering quasi-line search path planning algorithm (ACPP) is proposed from the viewpoint of non-convex optimization in an artificial potential field (APF). In ACPP, the initial path is the trajectory of the optimization process from the initial point to the target one. In a complex environment, the drivable area is divided by the edges into many relatively isolated regions, which leads to a non-convex path planning problem. Therefore, the clustering based on path nodes is set adaptively to make the potential function of each isolated region convex in the potential field. In each isolated region, the environment can be perceived by updating the parameters with sampling based on probability distribution functions, and these functions have similar influence to the cost function in optimization. Inspired by convex optimization, the quasi-line search algorithm is proposed for sampling points. Therefore, ACPP reduces the number of samples, dramatically, and has advantages of both sampling-based and APF-based algorithms in path planning. Based on the line segment based map which can be obtained from sensors readily, a gridding strategy is used to further reduce the time complexity. A series of simulation and experiential results validate the effectiveness of ACPP in virtual and real-world environments, respectively.

A Power Routing-Based Fault Detection Strategy for Multi-Terminal VSC-HVDC Grids

Fault detection is one of the most important research topics till today in the field of VSC-HVDC grids protection. In this subject, fast and reliable identification of faults is the most demanding issue, which still requires further study. In this respect, this paper proposes an index for fault detection, which is based on correlation between the powers of DC-link capacitor and the protected line. It is proved by an analytical time-domain transient expression that there is a direct correlation between these two powers under fault conditions. To implement this scheme, the routing of the discharged power of DC-link capacitor into the protected line is the key technique. To do so, the Pearson correlation factor is used in this paper, which efficiently captures the level and direction of the correlation between these two powers. The proposed method benefits from different salient features of very fast fault detection, accurate discrimination of faulted line from healthy lines, covering high-resistance faults, noise immunity, robustness against severe power reversal conditions, robustness against low sampling frequencies, not requiring extra sensor and communication infrastructure, etc. To evaluate the performance of the proposed approach, a complete set of fault scenarios are simulated on a meshed multi-terminal MMC-based VSC-HVDC network.

Flexibility dispatching strategy for power grid based on partition method of renewables penetration rate

With the proliferation of the penetration rate of renewable energy sources (RESs), more flexibility should be released to cope with the demand caused by the uncertainty of RESs output. Thus, it is paramount to divide different stages of the RESs penetration rate from the perspective of dispatching to represent the flexibility supply-demand relationship. Based on these considerations, this paper presents a novel approach to divide the level of RESs grid-connected with the aim to counteract the volatility and alleviate its effect of it. Herein, we define two specific stages with heterogeneous dispatching strategy, the first stage aiming at minimizing RESs power limit while the second stage takes the secure operation of the power grid as the optimal target by adjusting the optimization objectives of intraday rolling and real-time dispatching plan. Simulation results demonstrate the feasibility of the partition method.

Staggered scheme for the compressible fluctuating hydrodynamics of multispecies fluid mixtures.

We present a numerical formulation for the solution of nonisothermal, compressible Navier-Stokes equationswith thermal fluctuations to describe mesoscale transport phenomena in multispecies fluid mixtures. The novelty of our numerical method is the use of staggered grid momenta along with a finite volume discretization of the thermodynamic variables to solve the resulting stochastic partial differential equations. The key advantages of the numerical scheme are that it significantly simplifies the discretization of diffusive and stochastic momentum fluxes into a more compact form, and it provides an unambiguous prescription of boundary conditions involving pressure. The staggered grid scheme more accurately reproduces the equilibrium static structure factor of hydrodynamic fluctuations in gas mixtures compared to a collocated scheme described previously by Balakrishnan etal. [Phys. Rev. E 89, 013017 (2014)1539-375510.1103/PhysRevE.89.013017]. The numerical method is tested for ideal noble gases mixtures under various nonequilibrium conditions, such as applied thermal and concentration gradients, to assess the role of cross-diffusion effects, such as Soret and Dufour, on the long-ranged correlations of hydrodynamic fluctuations, which are also more accurately reproduced compared to the collocated scheme. We numerically study giant nonequilibrium fluctuations driven by concentration gradients and fluctuation-driven Rayleigh-Taylor instability in gas mixtures. Wherever applicable, excellent agreement is observed with theory and measurements from the direct simulation Monte Carlo method.

The momentum-conserving simulation for shallow water flows in channels with arbitrary cross-sections

The momentum-conserving staggered grid (MCS) scheme to simulate shallow water flows in channels of varying width and topography is revisited in this article. Here, we modify the MCS scheme so that it can be applied to channels of arbitrary cross-section. The scheme is validated using steady analytical solutions for channels with rectangular and trapezoidal cross sections. We found that the method was capable of solving a wide variety of test cases; including subcritical, supercritical and transcritical steady flows and flows with hydraulic jumps. This MCS scheme could handle both steady and unsteady problems. In the implementation of a channel with arbitrary cross sections, the simulation depicts the time-lapse evolution of the water level toward the steady state. These results were consistent with previous findings in the literature. All numerical experiments carried out here demonstrate the merits of the numerical MCS scheme.

An intelligent analysis method of security and stability control strategy based on the knowledge graph

The security and stability control system is the guarantee of the security and stability operation of the power grid. With the increasing scale of distributed new energy access to the power grid, the security and stability control strategy of the power grid is becoming more complex, and it is becoming increasingly important to correctly analyze and implement the security and stability control strategy. In order to ensure the correctness of the security and stability control strategy implemented by the security and stability control device, it is necessary to analyze the security and stability control strategy in detail. Therefore, this article proposes an intelligent analysis method of the security and stability control strategy based on the knowledge graph. First, this article introduces the ontology design method of the security and stability control strategy based on the knowledge graph, combines the characteristics and applications of the knowledge graph, analyzes the relationship between the elements of the strategy, and designs a clear-structured knowledge network. Second, this article analyzes the automatic construction technology of the graph, constructs the six-element ontology model of the security and stability control strategy, and realizes the human–computer interaction functions such as auxiliary decision making, strategy reasoning, and intelligent search based on the knowledge graph. Using artificial intelligence technology, this article takes the security and stability control strategy of a certain area’s security and stability control system as an example to model and manage. The results show that it can assist the tester to quickly retrieve the strategy, effectively improve the detection efficiency of the security and stability control strategy, avoid the omission and ambiguity caused by the manual understanding of the strategy, and ensure the accuracy and comprehensiveness of the security and stability control strategy detection.

A Similarity Comparison Based Pilot Protection Scheme for VSC-HVDC Grids Considering Fault Current Limiting Strategy

A Similarity Comparison Based Pilot Protection Scheme for VSC-HVDC Grids Considering Fault Current Limiting Strategy

Deep Learning-Based Robust DC Fault Protection Scheme for Meshed HVDC Grids

Deep Learning-Based Robust DC Fault Protection Scheme for Meshed HVDC Grids

Secure Identity-Based Designated Verifier Anonymous Aggregate Signature Scheme Suitable for Smart Grids

Safe and efficient collection of users’ electronic consumption data is a basic function of the smart grid. Anonymous aggregate signature is a fine option to realize this feature, which can not only reduce the computing cost of the data center (DC) but also protect the user’s identity information from leaking. The security proofs of all known identity-based aggregate signature (IBAS) schemes were completed in the random oracle model (ROM). Regrettably, these schemes are not necessarily secure in real life. In this article, we first propose the system model and security demands of an identity-based designated verifier anonymous aggregate signature (IB-DVAAS) scheme for smart grids. We then come up with a concrete scheme, only the designated DC can check the validity of an aggregate signature, but it cannot recognize the real identity of the signers. Next, we display the security proofs in the standard model. Finally, we conduct an analysis on performance for six aggregate signature schemes. Only three pairing operations are required and hash-to-point operations are not used, the calculation cost of the new scheme is lower than that of other schemes.