Actual Power System Research Articles

Online Evaluation System of Power Grid Efficiency

Transmission network is an important part of power system. The operation efficiency of transmission network is one of the important indexes of power system. At present, there is still much room to improve the efficiency of China's transmission network. There is a lack of a suitable system to evaluate the operation efficiency of transmission network. In order to effectively evaluate the efficiency of transmission network, this paper establishes the evaluation index system of transmission network operation efficiency and applies it to the actual power system. The test results verify the feasibility of the proposed index system.

A small-sample faulty line detection method based on generative adversarial networks

This paper presents a small-sample faulty line detection method for a small current grounded system (SCGS) using improved generative adversarial networks (GANs) to overcome the problems of low accuracy and poor economy associated with traditional methods. First, we collected real-time fault data of the dispatching system as the original sample and used the linear interpolation and normalization methods to preprocess the data. We extracted and labeled the features of the original sample to construct a feature vector that represents the single-phase grounded fault. Then, to solve the problem of insufficient faulty samples, this paper used the GAN to generate synthetic samples to expand the training sample size. To stabilize the GAN training, the Wasserstein distance was introduced to improve the GAN loss function (WGAN). Finally, for the synthetic samples, we used Batch Normalization (BN) and an Early Stopping algorithm to train the lightweight depthwise separable convolutional network (DSCN) classifier and obtain a faulty line detection model with fast convergence and high accuracy. With the data of an actual dispatching system in China as an example, the proposed method determined the faulty line within 100–200 ms with an accuracy of more than 96%, which is approximately 26% higher than the accuracy of traditional methods. Compared with mainstream machine learning algorithms, the proposed method realizes the self-extraction of faulty features and simplifies the algorithm. Moreover, the accuracy of the proposed method is much higher than that of other machine learning algorithms on small samples. It is worth noting that this method needs only the existing real-time dispatching data and does not need to install additional data acquisition and fault detection equipment, eliminating the complicated equipment installation and debugging process and greatly reducing equipment costs human operations and maintenance costs. The proposed method has been implemented in an actual power system in China for two years. The results show that it is highly accurate and cost-effective, performs well in real time, and has bright prospects for future applications.

Monitoring of subsynchronous oscillation in a series‐compensated wind power system using an adaptive extended Kalman filter

The characteristics of subsynchronous oscillation (SSO) in series-compensated wind power systems are significantly affected by the system's operating condition. Besides the variation in the magnitude and frequency of the SSO during an SSO event, the fundamental frequency may also deviate from its nominal value. This study aims at capturing the dynamics of both subsynchronous and fundamental frequency components simultaneously. This work first explores the strengths and weaknesses of various Kalman filtering based frequency tracking algorithms for joint tracking of the fundamental and SSO components. Then, it proposes a novel adaptive extended Kalman filtering (AEKF) algorithm, in which the process noise covariance is updated online by maximising the probability density function of the predicted error. The process noise covariance factor changes to positive non-zero value whenever the frequency of the fundamental component deviates. Thus, the proposed AEKF extracts the time-varying subsynchronous component while also tracking the small variations in the fundamental frequency. The tracking performance of the AEKF is validated on computer-generated test signals as well as on the electromagnetic transient simulation model of an actual wind power system facing SSO. The captured fundamental and subsynchronous dynamics can be used for designing monitoring, protection, and control schemes for the SSO.

Evolutionary Approach-Based Methodology for Egyptian Utility Restoration (Dept.E)

Restoration of a large electric grid after a partial or complete system blackout is a difficult task complicated by many factors, including unknown cause, abnormal operating conditions, infrequently used procedures and unpredictable system configurations. Large utilities must have different scenarios and tools to deal with this problem. The coordination and overall organization of the several aspects of the restoration process will largely determine the effectiveness of the restoration and its speed of progress. The most basic determinants of this organization are the relative roles played by the operator and the computer. Thus there arises a choice between two basic organizing principles: operator dominated principle or computer dominated principle. In actual power system operation, severe restoration situations occur infrequently. Therefore, when they do occur, operators have had little first-hand, on-the job experience. Even so, they are under pressure to restore the system as quickly as possible, while paying close attention to many technical details. On other hand the great progress in both artificial intelligence software and computer hardware, increases the tendency to fully automated the restoration problem, so that the operator plays the role of an observer or supervisor. In mathematical terms, the restoration problem may be described as a multi-objective, multi-stage, combinatorial, nonlinear, constrained optimization problem. Evolutionary Approach (EA) technique is one of the most promising artificial intelligence techniques because it is proven to be both very fast and effective when applied to a diverse set of optimization problems. In this paper a proposed Evolutionary Approach-based methodology is used to solve the restoration problem of a large electric system with multiple generation units and transmission loops. The methodology is applied to restore a sector of Egyptian Utility after a complete blackout. The obtained results show effectiveness and validity of the proposed methodology compared to pure human experience in Egyptian National Energy Control Center.

Research on Economic Evaluation Methods of Offshore Oil Multi-Platform Interconnected Power System Considering Petroleum Production Characteristics

Offshore oil multi-platform interconnected power system is developing rapidly. The proposal of an effective economic evaluation method that fits the actual production situation of offshore oilfields is very meaningful for the planning and construction of multi-platform interconnected power systems. This article proposes the electric depreciation, depletion, and amortization (DD&A) barrel oil cost S and maximum expected benefit per unit power generation Ie as economic indicators, considering the actual production characteristics and life cycle of the oil field. In order to build a complete economic evaluation system, this article also introduces the N−1 pass rate ηN−1, voltage qualification rate γ, power supply reliability ASAI (Average Service Availability Index), and other reliability indicators to evaluate the offshore power system. When calculating the weight of the indicators, analytic hierarchy method (AHP) was applied to calculate subjective weights, and an entropy method was applied to calculate objective weights. To unify the two weights, the ideal point method is proposed to obtain compound weights. Finally, this article selects an offshore oil field in Bohai Bay, China as example, and analyses short-term small-scale, long-term large-scale, and actual power system as calculation examples in different planning periods. The analysis result verifies the effectiveness of the economic evaluation method.

A Power Hardware-in-the-Loop Based Method for FAPR Compliance Testing of the Wind Turbine Converters Control

A task for new power generation technologies, interfaced to the electrical grid by power electronic converters, is to stiffen the rate of change of frequency (RoCoF) at the initial few milliseconds (ms) after any variation of active power balance. This task is defined in this article as fast active power regulation (FAPR), a generic definition of the FAPR is also proposed in this study. Converters equipped with FAPR controls should be tested in laboratory conditions before employment in the actual power system. This paper presents a power hardware-in-the-loop (PHIL) based method for FAPR compliance testing of the wind turbine converter controls. The presented PHIL setup is a generic test setup for the testing of all kinds of control strategies of the grid-connected power electronic converters. Firstly, a generic PHIL testing methodology is presented. Later on, a combined droop- anFd derivative-based FAPR control has been implemented and tested on the proposed PHIL setup for FAPR compliance criteria of the wind turbine converters. The compliance criteria for the FAPR of the wind turbine converter controls have been framed based on the literature survey. Improvement in the RoCoF and and maximum underfrequency deviation (NADIR) has been observed if the wind turbine converter controls abide by the FAPR compliance criteria.

The Different LVRT Control Strategy of Wind Generator Suppressing for Transient Overvoltage by DC Commutation Failure

At present, the characteristics of large capacity DC and high proportion of new energy centralized delivery is showed for power system of China. The ability of UHVDC to transmit new energy is severely reduced for caused transient overvoltage after AC/DC contingencies and further research is urgently needed. Firstly, the transient overvoltage caused by DC commutation failure is analyzed based on the large-scale wind power centralized delivery of the actual power system. Then, the physical mechanisms of transient overvoltage of converter station and wind farms resulted are analyzed by the actual power system DC commutation failure contingencies recorder. The impact of wind generator low voltage ride through (LVRT) active/reactive power characteristics for transient overvoltage is emphatically analyzed. Finally, all the analysis results are verified through simulation of practical case systems. The study can provide technical references to safe and stable operation of the power system in new situation.

Modified sub-gradient based combined objective technique and evolutionary programming approach for economic dispatch involving valve-point loading, enhanced prohibited zones and ramp rate constraints

A security constrained non-convex power dispatch problem with prohibited operation zones and ramp rates is formulated and solved using an iterative solution method based on the feasible modified sub-gradient algorithm (FMSG). Since the cost function, all equality and inequality constraints in the nonlinear optimization model are written in terms of the bus voltage magnitudes, phase angles, off-nominal tap settings, and the Susceptance values of static VAR (SVAR) systems, they can be taken as independent variables. The actual power system loss is included in the current approach and the load flow equations are inserted into the model as the equality constraints. The proposed modified sub gradient based combined objective technique and evolutionary programming approach (MSGBCAEP) with as decision variable and cost function as fitness function is tested on the IEEE 30-bus 6 generator test case system. The absence of crossover operation and adoption of fast judicious modifications in initialization of parent population, offspring generation and normal distribution curve selection in EP enables the proposed MSGBCAEP approach to ascertain global optimal solution for cost of generation and emission level shown in Table 6 and displayed in Figure 2 and Figure 3 respectively.

Approximate dynamic programming‐based decentralised robust optimisation approach for multi‐area economic dispatch considering wind power uncertainty

This study presents a fully decentralised robust optimisation (RO) approach for multi-area economic dispatch (MA-ED) in the presence of wind power uncertainty. Unlike traditional algorithms, the authors formulate this MA-ED problem as dynamic programming problem, and decompose the centralised robust MA-ED problem into a series of sub-problems based on approximate dynamic programming algorithm. The value functions are proposed for each area to iteratively estimate the impacts of its dispatches on the dispatches of other areas which make decisions subsequently. The proposed algorithm does not require a central operator but only needs to exchange a small amount of information among neighbouring areas to achieve fully decentralised decision-making. It is practical in cases where the centralised operator cannot be implemented considering the dispatch independence and the detailed data of one area is unavailable considering the privacy. Additionally, the accuracy, adaptability and computational efficiency of the proposed algorithm are illustrated using numerical simulations on two test systems and an actual power system.

Stochastic economic dispatch of power system with multiple wind farms and pumped‐storage hydro stations using approximate dynamic programming

The stochastic economic dispatch problem of power system with multiple wind farms and pumped-storage hydro stations is formulated as a specific stochastic dynamic programming (DP) model, i.e. stochastic storage model, it is impossible to obtain an accurate solution due to the curse of dimensionality. Based on the approximate DP (ADP) method, the stochastic storage model can be transformed into a series of mixed-integer linear programming (MILP) models by describing the approximate value functions (AVFs) as convex piecewise linear functions in post-decision states. The AVFs are first initialised using the results of the deterministic model under a forecast scenario of wind farm output and then trained by scanning stochastic sampling scenarios consecutively with the successive projective approximation routine algorithm. To obtain a near-optimal day-ahead dispatch scheme, the forecast scenario is substituted into the MILP models expressed by the trained AVFs and is solved forward through each time interval. The network constraints are incorporated by the while-loop detection of critical lines. Test results on an actual provincial power system and the modified IEEE 39-bus system, including the comparison among the ADP, DP, scenario-based and chance-constrained programming methods, demonstrate the feasibility and efficiency of the proposed model and algorithm.

Numerical Simulation Study on Structure Optimization and Performance Improvement of Hot Water Storage Tank in CHP System

The central heating technology with thermal storage technology is an important means to realize thermoelectric decoupling, meet heating demand, reduce primary energy consumption, and protect the ecological environment. For this paper, the numerical simulation method was used to study the temperature variation of large-capacity hot water storage tank (HWST) in an actual combined heat and power system. The influence of various factors, including the length diameter ratio, water supply temperature, and water supply flow, as well as the orifice diameter and number of the water distributor, on the flow uniformity and performance of the HWST was investigated. The results show that the heat storage efficiency and flow uniformity of the HWST can be improved by properly increasing the water supply flow, the orifice diameter, and number of the water distributor. Increasing the length diameter ratio can improve the flow uniformity, but it will reduce the heat storage efficiency of the HWST. Increasing the water supply temperature can increase heat storage efficiency of the HWST and accelerate the stratification of cold and hot water in the tank. Besides, the comprehensive analysis of the non-dimensional exergy loss calculation results, velocity field, and temperature field show that there is a certain coupling relationship between the non-dimensional exergy loss and flow uniformity at the initial stage of heat storage. In practical application, the influence of these factors on flow uniformity, heat storage efficiency, and non-dimensional exergy loss should be comprehensively considered in order to achieve the best heat storage and release performance of the HWST. This paper provides some engineering guidance for the application of large-capacity heat storage tanks in the combined heat and power (CHP) system.

Research on Damping Control Index of Ultra-Low-Frequency Oscillation in Hydro-Dominant Power Systems

In recent years, ultra-low-frequency oscillation (ULFO) is a prominent problem in power systems of dominant hydropower. In order to suppress ULFO, the most effective strategy is the governor parameters optimization to improve the system damping within the ultra-low-frequency band. However, no explicit standard has been established to stipulate the level of system damping for ULFO suppression. In this paper, the key factors that affect the amplitude and damping of ULFO are firstly analyzed. Then, the design principle of the damping control index of ULFO is put forward. According to it, a damping control index is proposed. After that, a case of ULFO in an actual power system proves the rationality of the proposed index. Finally, the application of the index in the Southwest China Power Grid illustrates its effectiveness and feasibility.

Design and Implementation of a Data-Driven Approach to Visualizing Power Quality

Numerous underlying causes of power-quality (PQ) disturbances have enhanced the application of situational awareness to power systems. This application provides an optimal overall response for contingencies. With measurement data acquired by a multi-source PQ monitoring system, we propose an interactive visualization tool for PQ disturbance data based on a geographic information system (GIS). This tool demonstrates the spatio–temporal distribution of the PQ disturbance events and the cross-correlation between PQ records and environmental factors, leveraging Getis statistics and random matrix theory. A methodology based on entity matching is also introduced to analyze the underlying causes of PQ disturbance events. Based on real-world data obtained from an actual power system, offline and online PQ data visualization scenarios are provided to verify the effectiveness and robustness of the proposed framework.

Dual cost‐sensitivity factors‐based power system transient stability assessment

In actual power system operation, there is a significant imbalance between the number of stable and unstable samples, and the misclassification costs of the two classes of samples are different. In addition to the class imbalance, there is another imbalance of regional samples in the feature space. In order to reduce the impact of class imbalance and regional imbalance on the performance of the model, a method of dual cost-sensitivity factors for transient stability assessment is proposed. The method sets the balance factor and modulating factor in the loss function of light gradient boosting machine. The former corrects the classification bias caused by class imbalance, and the latter focuses on improving the classification accuracy of overlapping area samples. Combining the two factors, the model not only improves the accuracy of unstable samples, but also reduces the misjudgement of stable samples. In online application, a fast update scheme with memory function is proposed. In this scheme, incremental learning is used to update the model with fewer samples and less computational time, so as to achieve better evaluation performance. Case studies on three power systems demonstrate the generalisation performance of the proposed model and the effectiveness of the update scheme.

Practical solutions for ground grid circulating currents caused by air‐core reactor

This study describes an actual problem with circulating current at the ground grid of an actual power system that has an air-core reactor. Such reactors generate a large amount of magnetic flux whose path can be closed through its underneath ground grid. This magnetic flux induces a voltage on the ground meshes and thus results in considerable circulating currents that pass through the ground meshes. Indeed, the main novelty of this study is investigating the effect of air-core reactors on the other nearby equipment and considering the air-core reactor's flux underneath ground meshes. This phenomenon occurred in a steel industrial plant and practically leads to severe damages to equipment through which the current has been flowing, including ground grid conductors, cable shields, and foundation armatures. This study addresses the origins of problems raised by the manufactured equipment in a reputable company based on both simulations and experimental studies. Based on the obtained results, several practical approaches are proposed and implemented to overcome the problems mentioned above.

Assessing the value of natural gas underground storage in the Brazilian system via stochastic dual dynamic programming

The Brazilian natural gas sector is currently characterized by low maturity and dynamism of the market. The stochastic behavior of the demand for natural gas added to its associated market price volatility motivates the usage of underground storage to provide supply flexibility and protection against price fluctuations. However, the existing literature lacks a proper analytical tool to assess the benefits of underground natural gas storage (UNGS) activity. In this work, it is proposed a stochastic dynamic programming model for long/medium-term operation planning to determine the optimal gas supply and storage policies. A markovian model characterizes the uncertainty over the thermoelectric demand and market price. The proposed model is efficiently solved using the stochastic dual dynamic programming algorithm for the Brazilian case study considering realistic data for the actual gas network and electric power system. For an exogenous but meaningful choice of underground storage location and size, it is observed the operational and economic benefits of the provided storage flexibility. Finally, our numerical simulations show that the economic benefit for the system surpasses the operational and capital expenses for the storage infrastructure in depleted fields and salt caverns.

Security Assessment and Coordinated Emergency Control Strategy for Power Systems with Multi-Infeed HVDCs

Short-circuit faults in a receiving-end power system can lead to blocking events of the feed-in high-voltage direct-current (HVDC) systems, which may further result in system instability. However, security assessment methods based on the transient stability (TS) simulation can hardly catch the fault propagation phenomena between AC and DC subsystems. Moreover, effective emergency control strategies are needed to prevent such undesired cascading events. This paper focuses on power systems with multi-infeed HVDCs. An on-line security assessment method based on the electromagnetic transient (EMT)-TS hybrid simulation is proposed. DC and AC subsystems are modeled in EMTDC/PSCAD and PSS/E, respectively. In this way, interactions between AC and DC subsystems can be well reflected. Meanwhile, high computational efficiency is maintained for the on-line application. In addition, an emergency control strategy is developed, which coordinates multiple control resources, including HVDCs, pumped storages, and interruptible loads, to maintain the security and stability of the receiving-end system. The effectiveness of the proposed methods is verified by numerical simulations on two actual power systems in China. The simulation results indicate that the EMT-TS hybrid simulation can accurately reflect the fault propagation phenomena between AC and DC subsystems, and the coordinated emergency control strategy can work effectively to maintain the security and stability of systems.

Adaptive time division power dispatch based on numerical characteristics of net loads

Energy sustainable development is of strategic importance across the world. This is especially the case in China as it is the world’s largest energy consumer. However, renewable energies such as wind and solar energy are characterized with high intermittence and fluctuation. As the penetration of renewable power in the energy system increases, it is getting more challenging in power dispatch. In this paper, an adaptive time division power dispatch strategy based on numerical characteristics of net loads is proposed. In this strategy, a dispatch time division method is introduced in detail to divide the dispatching time according to the numerical characteristics of net loads. The sample entropy theory is utilized to calculate the complexity of the net loads, depending on which a specific thermal generating mode is provided. The experiment simulation is developed on an actual provincial power system in the northeast of China. The test results have confirmed that in the adaptive time division power dispatch strategy, the ramping power of thermal generators are decreased, the continuous and steady operation time of thermal generators are improved. As a result, this new strategy, can lead to improved energy efficiency of power systems as well as significant environmental benefits.

Data-Driven Estimation of Inertia for Multiarea Interconnected Power Systems Using Dynamic Mode Decomposition

The refined estimation of inertia can provide a reliable basis for power system operation and control. In this article, a data-driven approach for the estimation of inertia is proposed, and it can estimate the effective inertia of different areas in the interconnected power systems. Based on eigenstructure analysis, the intrinsic relationships between inertia and the eigenvalue and eigenvector are analyzed using a linearized dynamic equation. Furthermore, detailed mathematical expressions between inertia and the eigenvalue and eigenvector are established. In addition, dynamic mode decomposition is introduced to extract eigenvalues and eigenvectors from the synchronized measurements to ensure that the scheme proposed in this article can estimate the effective inertia by using only the outputs measured by the phase measurement unit. The effectiveness of the proposed approach is demonstrated through numerical simulations on the IEEE 16-machine 5-area test system and the real measurements of an actual power system.

Harmonic Contribution Evaluation Based on the Distribution-Level PMUs

With the rapid development of renewable energy resources, harmonics in modern distribution systems have become more serious owing to the wide adoption of power electronic devices. Today, distribution-level phasor measurement units (D-PMUs), which can provide synchronized harmonic data with high-time resolution, are being rapidly developed. To utilize the D-PMUs, a hierarchical harmonic contribution (HC) determination method is proposed in this paper for systems with multiple harmonic sources. The HCs were determined using a widely linear complex partial least squares (WL-CPLS) method, which is both accurate and efficient. In an actual power system, the D-PMUs are not fully installed at all buses and the harmonics monitored by each D-PMU are actually the aggregate effects of multiple harmonic sources in the subarea. Based on the above consideration, a hierarchical HC strategy is proposed to locate the main harmonic contributors, layer by layer. The proposed method can be applied to a radial distribution system with any number of D-PMU placements. The methodologies are explained and verified using the IEEE 37-bus system. The real case study results based on the demonstration project are also analyzed in this paper.