Interconnected Power Grid Research Articles

Frequency control at the power sending side for large-scale HVDC asynchronous interconnection between Yunnan power grid and the rest of CSG

For a large-scale high voltage direct current (HVDC) asynchronous interconnected power grid, the frequency issue at the power sending side under DC faults is a crucial problem. To solve this problem, based on rotor motion equations, the effect of unbalanced power on the system frequency under DC faults is analyzed. The characteristics and dynamic development process of frequencies after the injection of disturbances are analyzed. In addition, the actions and coordinated strategies of various frequency control measures are also investigated. Based on the testing projects of an asynchronous interconnection in the China Southern Power Grid (CSG), the frequency features are studied according to the measured PMU data. The outcome shows that the frequency problem of the Yunnan Power Grid after an asynchronous interconnection can be solved and controlled. It also shows that the frequency limit control (FLC) is important for the frequency regulation of large scale HVDC asynchronous interconnected DC power grids. As demonstrated, DC FLC can effectively suppress the deviation of the transient frequency. However, reasonable frequency regulation parameters should be set and other area frequency control measures should be coordinated to maintain the frequency stability of the system.

Design of transformer protection scheme for DC system

Back-to-back flexible DC system can be used for interconnection of asynchronous power grids. In view of the different characteristics and operation modes of connected transformer equipment in back-to-back flexible DC system, this paper puts forward some special problems that need to be considered in the design of connected transformer protection, and puts forward a complete configuration scheme of connected transformer protection in view of its particularity. Finally, we establishes a real-time digital simulation model to verify the validity of the model using actual engineering parameters. The simulation results show that the theoretical analysis is correct and the proposed protection scheme can effectively guide the engineering application.

A control method of an additional damper for hydro turbine speed governor system in hydro-dominant power system

With the rapid development of the national inter-connected power grid, the fast automatic excitation regulators and fast turbine governor have been widely used. In the current system, some power plants adjust the response of turbine governor system to a very sensitive level to meet the primary frequency regulation assessment index, which, however, brings the negative damping intensively. Under the circumstances, the ultralow frequency oscillation (ULFO) phenomenon emerged in hydro-dominant power system. In order to solve the problem of ULFO, the hydro-turbine Governor Additional Damper (GAD) based on the phase compensation which adapt to the ULFO is developed. It is improved on the basis of traditional PSS and the design of the control system is relatively simple. As phase compensation based on the field testing and modeling of turbine governor, GAD can provide the power system with the positive damping, which contributes to improving the stability and security of the system. According to the impact of the mechanism of turbine governor on the dynamic stability of the power system and the research of modeling and parametric test, the proposed method not only supports positive damping, but also eliminates the negative damping of the speed governing system, which can significantly suppress the ultralow frequency oscillation and make it feasible to configure the GAD parameters accoraing to field test.

Measurement‐based wide‐area damping of inter‐area oscillations based on MIMO identification

Interconnected power grid exhibits oscillatory response after a disturbance in the system. One such type of oscillation, the inter-area oscillation has the oscillation frequency in the range of 0.1–1 Hz. The damping of inter-area oscillations is difficult with local controllers, but it can be achieved using a wide area damping controller (WADC). For effective control, the input to the WADC should be the most observable signal, and the WADC output should be sent to the most controllable generator. This study presents a measurement-based novel algorithm for multi-input-multi-output (MIMO) transfer function identification of the power system to estimate such oscillation frequencies. The wide-area control loop is estimated using the MIMO transfer function, and the WADC design is a combination of the discrete linear quadratic regulator and Kalman filtering for the damping of inter-area oscillations. Since the MIMO identification is performed using the actual measurements, the proposed method can accurately monitor changes in the power grid, whereas the conventional methods are derived from small-signal analysis of a linearized model that does not consider changing operating conditions. The overall algorithm is implemented and validated on a RTDS/RSCAD® and MATLAB® real-time co-simulation platform using two-area and IEEE 39-bus power system models.

Tie-Line Power Transmission Region in a Hybrid Grid: Fast Characterization and Expansion Strategy

The identification of a tie-line power transmission region is crucial for the secure operation of interconnected power grids. The characterization of a tie-line power transmission region with regional operational constraints is inherently a multi-parametric programming problem, which greatly suffers from a heavy computational burden. In this paper, we propose a fast boundary search approach to efficiently characterize the tie-line power transmission region in AC/DC hybrid grids. The multi-parametric programming method is improved in the following three aspects: (1) the search direction is fixed along the boundary of a region, which avoids the search inside a region; (2) the abundant search of subregions that share a boundary facet is avoided; and (3) a fast guess of the Karush-Kuhn-Tucker (KKT) condition is presented, which reduces the number of optimization calculations. Furthermore, an expansion strategy is presented to enlarge the tie-line power transmission region via quantifying the impact of system parameters on the transmission region. Simulations based on the IEEE 118-bus test system and a 661-bus utility system show that (1) the proposed method can be over 30 times faster than existing methods and (2) the proposed method successfully expands the tie-line power transmission region by identifying the key parameters.

Low frequency oscillation online identification based on synchronous phasor of distribution network

With the advancement of the interconnection process of power grid, the low-frequency oscillation (LFO) problems in the interconnected power grid greatly affect the economic and stable operation of the system. In recent years, the research of synchronous measurement system of distribution network has made great progress, which makes it possible to construct a new generation of low-cost, flexible and reliable online monitoring system of low-frequency oscillation based on the synchronous phasor of distribution network (LFO-DPMU). Based on this, the physical structure and processing flow of LFO-DPMU are constructed in this paper. The LFO-DPMU can extracts dominant mode of oscillation from the distribution network information in real time. For the identification algorithm, this paper selects Prony and HHT algorithm, which two kinds of commonly used oscillation identification algorithms in high-voltage power grid, and compare the characteristics of algorithm in anti-noise, stability and analysis efficiency. Then, combined with the characteristics of distribution network signal, this paper analyses the applicability of the two algorithms. Finally, two algorithms are used to extract the oscillation mode of the measured synchronous phasor signal of distribution network. The analysis result shows the feasibility and accuracy of the whole identification system.

An interconnected panorama of future cross-regional power grid: A complex network approach

The cross-regional interconnected power grid (CRIG), leading the development of our country, has a complex and lengthy evolution process that is influenced by numerous factors. It is an enormous challenge to propose a model that analyzes the evolution of CRIG. Therefore, the main objective of this study is to explore the evolutionary characteristics of CRIG by developing a complex network model. The results show that policy guidance has a significant impact on the evolution of China's CRIG and that given this influence, the degree of CRIG distribution will have an “edge-multi-core” shape and the network density will show an inverted “N” curve shape. In addition, we analyze the development trends in China's, which will achieve a “simpler” construction, namely, the levels of CRIG connections and the “community effect” will gradually fade over the CRIG evolution. Finally, we believe that renewable energy and micro-grid and electricity markets are the direct cause of structural changes occurring in China's CRIG. More attention should be paid to the security and coordination of cross-regional power grids to achieve interconnections in the future.

A Distributed Cooperative Control Strategy of Offshore Wind Turbine Groups with Input Time Delay

With large-scale development of offshore wind power and the increasing scale of power grid interconnection, more and more attention has been drawn to the stable operation of wind power units. When the wide area measurement system (WAMS) is applied to the power system, the time delay mainly occurs in the signal measurement and transmission of the power system. When 10MW wind turbines transmit information through complex communication network, time delay often exists, which leads to the degradation of performance and instability for system. This affects the normal operation of a wind farm. Therefore, in this paper, the distributed control problem of doubly fed wind turbines with input time delay is studied based on the Hamiltonian energy theory. Firstly, the Port-controlled Hamiltonian system with Dissipation (PCH-D) model is implemented with the Hamiltonian energy method. Then, the Casimir function is introduced into the PCH-D model of the single wind turbine system to stabilize the time delay. The wind turbine group is regarded as one network and the distributed control strategy is designed, so that the whole wind turbine cluster can remain stable given a time delay occurring in the range of 30–300 ms. Finally, simulation results show that the output power of the wind turbine cluster with input delay converges to the expected value rapidly and remains stable. Additionally, the system error caused by time delay is greatly reduced. This control method can effectively solve the problem of input time delay and improve the stability of the wind turbine cluster. Moreover, the method proposed in this paper can adopt the conventional time step of dynamic simulation, which is more efficient in calculation. This method has adaptability in transient stability analysis of large-scale power system, however, the third-order mathematical model used in this paper cannot be used to analyze the internal dynamics of the whole power converter.

Improving Power System State Estimation Based on Matrix-Level Cleaning

Power system state estimation is heavily subjected to measurement error, which comes from the noise of measuring instruments, communication noise, and some unclear randomness. Traditional weighted least square (WLS), as the most universal state estimation method, attempts to minimize the residual between measurements and the estimation of measured variables, but it is unable to handle the measurement error. To solve this problem, based on random matrix theory, this paper proposes a data-driven approach to clean measurement error in matrix-level. Our method significantly reduces the negative effect of measurement error, and conducts a two-stage state estimation scheme combined with WLS. In this method, a Hermitian matrix is constructed to establish an invertible relationship between the eigenvalues of measurements and their covariance matrix. Random matrix tools, combined with an optimization scheme, are used to clean measurement error by shrinking the eigenvalues of the covariance matrix. With great robustness and generality, our approach is particularly suitable for large interconnected power grids. Our method has been numerically evaluated using different testing systems, multiple models of measured noise and matrix size ratios.

Development of the interconnected power grid in Europe and suggestions for the energy internet in China

The European power grid is one of the largest regional interconnected power grids in the world. It realizes a multinational grid operation, which is rare. The total installed capacity of the European power grid is the largest throughout the world. In addition, the integration and utilization of renewable energy in this grid is a great benchmark for other countries and can help promote energy transformation and achieve a high proportion of renewable energy consumption. Based on the analysis of the existing status of the European interconnected power grid and the development history of this power grid, this paper summarizes four key development stages of the European power grid. In addition, the characteristics of each stage and the development prospect of the European power grid are analyzed. On this basis, this paper gives suggestions for the development and construction of China’s energy internet; this can provide valuable reference for further studies on China’s energy internet.

Towards Assessing the Electricity Demand in Brazil: Data-Driven Analysis and Ensemble Learning Models

The prediction of electricity generation is one of the most important tasks in the management of modern energy systems. Improving the assertiveness of this prediction can support government agencies, electric companies, and power suppliers in minimizing the electricity cost to the end consumer. In this study, the problem of forecasting the energy demand in the Brazilian Interconnected Power Grid was addressed, by gathering different energy-related datasets taken from public Brazilian agencies into a unified and open database, used to tune three machine learning models. In contrast to several works in the Brazilian context, which provide only annual/monthly load estimations, the learning approaches Random Forest, Gradient Boosting, and Support Vector Machines were trained and optimized as new ensemble-based predictors with parameter tuning to reach accurate daily/monthly forecasts. Moreover, a detailed and in-depth exploration of energy-related data as obtained from the Brazilian power grid is also given. As shown in the validation study, the tuned predictors were effective in producing very small forecasting errors under different evaluation scenarios.

Study on Sustainable Development of the Transnational Power Grid Interconnection Projects under Diversified Risks Based on Variable Weight Theory and Bayesian Network

Transnational power grid interconnection is an important measure to promote the construction of energy Internet. It can meet the global power demand in a clean and green way, promote the UN’s concept of “sustainable energy,” and tackle climate changes. But, transnational power grid projects face many complex and variable risks due to their complex background and lacking experience. According to the characteristics of transnational power grid interconnection projects, a risk assessment index system including 10 indexes such as national relation, public participation, and available transmission capacity is constructed. Then, in order to overcome the shortcomings of traditional risk assessment methods, this paper proposes a risk assessment method combined with risk theory and probabilistic model, which can not only consider the uncertainties but also integrate the probability of accidents with consequences. Therefore, it can effectively assess the transnational power grid interconnection projects under diversified risks. In addition, in order to further magnify the impact of higher risks on such projects, a method combining traditional weighting method with the variable weight theory is proposed. The study in this paper provides certain guidance and decision-making support for different participants such as the government power sector, construction enterprises, and investment enterprises when they launch on sustainable development of the transnational project business, which have obvious practical significance.

AC Tie-Line Power Oscillation Mechanism and Peak Value Calculation for a Two-Area AC/DC Parallel Interconnected Power System Caused by LCC-HVDC Commutation Failures

With the rapid development of ultra-high-voltage (UHV) AC/DC, especially the step-by-step upgrading of the UHV DC transmission scale, security presents new challenges. Commutation failure (CF) is a common fault in line commutated converter (LCC) high-voltage direct current (HVDC) power systems. Once failure happens, it may cause power oscillations in a system. In this paper, taking a two-area AC/DC parallel interconnected power system as the example, based on the impulse response model of second-order linear system, the mechanism of power oscillation on the AC tie-line caused by CF are clarified. It is proved that the peak value of the AC tie-line power oscillation is mainly determined by the DC power and the equivalent CF duration, the frequency and damping ratio of dominant area oscillation mode. Meanwhile, the peak time is mainly determined by the oscillation frequency. Finally, the correctness and effectiveness of the algorithms are verified by a simulation analysis of an extended IEEE-39-bus AC/DC parallel interconnected power system. These research results can provide a basis for the arrangement of the operating modes and the formulation of control measures for interconnected power grids.

A multi-level evaluation model for the recognition and assessment of impact factors associated with intercontinental power interconnection projects

The construction of intercontinental power grid interconnection projects is key to realizing the vision of Global Energy Interconnection, which is to solve global energy problems in a clean and sustainable manner. These projects may be influenced by a few factors that are neither technological nor economic, such as political, social, and international factors. This paper thus presents a multi-level model for recognizing which factor from a compiled list of 14 would impact a particular intercontinental interconnection project and for assessing the degree of the factor’s influence. In the first part of the model, the Analytic Hierarchy Process (AHP) method is used to recognize the project’s most significant impact factors. Using the recognition results, the second part of the model can assess the degree of the factor’s influence on the project based on ratings provided by experts. A comprehensive evaluation can thus be provided. As a case study, the proposed Saudi Arabia-Ethiopia power grid interconnection project connecting Asia and Africa was analyzed. Derived from a combination of multiple opinions from experts, evaluations from the model will be of direct benefit to decision-makers, investors, project implementers, and engineers, providing them with a deeper insight into the project.

Online Coherency Based Adaptive Wide Area Damping Controller for Transient Stability Enhancement

This paper proposes a novel wide-area control strategy to enhance the transient stability of a large inter-connected power grid. The proposed control strategy achieves maximal damping of the inter-area oscillations by calculating the optimal number of cluster centers based on a novel online coherency grouping. To achieve this objective, the critical electro-mechanical mode is selected using localness index method during transient conditions. In addition, the online identification of the full model is performed to estimate the states to be controlled during the grid disturbances. Thereafter, a discrete linear quadratic regulator (DLQR) is directly applied to the estimated states, and the corresponding signals are channelized through the loop of most controllable and observable machines of each coherent group. The efficacy of the proposed method is tested on IEEE 39 bus and IEEE 68 bus standard benchmark model. The results demonstrate faster damping with minimal computation burden compared to existing solutions such as a classical slow coherency and a multi-input multi-output (MIMO) based wide area damping controllers.

A deep reinforcement learning algorithm for the order optimization allocation of total power in the interconnected power grids

The integration of distributed generations (solar power, wind power), energy storage devices, and electric vehicles, causes unpredictable disturbances in power grids. It has become a top priority to coordinate the distributed generations, loads, and energy storages in order to better facilitate the utilization of new energy. Therefore, a novel algorithm based on deep reinforcement learning, namely the deep PDWoLF-PHC (policy dynamics based win or learn fast-policy hill climbing) network (DPDPN), is proposed to allocate power order among the various generators. The proposed algorithm combines the decision mechanism of reinforcement learning with the prediction mechanism of a deep neural network to obtain the optimal coordinated control for the source-grid-load. Consequently it solves the problem brought by stochastic disturbances and improves the utilization rate of new energy. Simulations are conducted with the case of the improved IEEE two-area and a case in the Guangdong power grid. Results show that the adaptability and control performance of the power system are improved using the proposed algorithm as compared with using other existing strategies.

Analysis of Dynamic Voltage Fluctuation Mechanism in Interconnected Power Grid with Stochastic Power Disturbances

With the integration of large-scale renewable energy and various new types of loads, the stochastic fluctuation characteristic of the power has seriously affected the secure and stable operation of interconnected power grids. In addition to active power fluctuations of AC tie-lines that have been studied in the past, the problem of dynamic fluctuation of bus voltage is also increasingly prominent. Firstly, the typical power fluctuations of electric railway traction load, smelting load, and wind power generation in modern power systems are presented and the accompanying voltage fluctuations are analyzed. Secondly, the dynamic fluctuation mechanism and distribution characteristic of the system voltage under special forced oscillation and generalized forced oscillation are studied. It is found that when the periodic disturbance induces a special forced oscillation, the voltage fluctuation has the same mode information compared to the power angle fluctuation. And it also has obvious peak characteristics near the natural frequency. When the stochastic disturbance induces generalized forced oscillation, the voltage fluctuations can be decomposed into proportional and resonant components according to its frequency domain characteristic. Finally, the above conclusions are verified by the simulation results of an IEEE 4-generator 2-area system.

Research and Outlook on Northeast Asian Energy Interconnection

Northeast Asia is the most developed region in Asia with large energy demand, and plays an important role in the global economic development. Northeast Asia has been facing severe challenges in ensuring energy security, protecting the environment, and coping with climate change, because of their high dependency on fossil fuels and imports of oil from outside the region, and inverse distribution between energy resources and demand. In order to actively respond to climate change, promote the transition to low-carbon energy and sustainable development in the region, achieve the grand purpose of economic prosperity, social progress and ecological protection, this study is conducted with a focus on power grid interconnection in Northeast Asia. Based on the historical energy and power data in Northeast Asia, this paper studies the development trends of energy and power demand in future by combining qualitative and quantitative methods. Considering the distribution of clean energy bases, this paper proposes an energy interconnection scheme in Northeast Asia with high clear energy penetration scenario. To form the Asia-Europe energy interconnection, the construction of the Asia-Europe interconnection channels is briefly analyzed in this paper.

Research on optimization method of primary frequency modulation capability based on different ratios of hydropower

With the continuous development of China’s cross-regional interconnected power grid, large- capacity and long-distance transmission have become an important feature of China’s power grid. As the transmission capacity of single-return transmission lines continues to increase, the risk of frequency fluctuations increases, making grid operation scheduling more concerned with the performance of the unit’s primary frequency modulation. This paper tests the frequency stability of a power system under different scenarios, in which the proportion of water and thermal power in the system is different. The results represent that a system with a large proportion of hydropower has poorer frequency stability. This paper offers a method of primary frequency modulation, which proposed to improve the frequency stability of the system by increasing the time delay of the hydropower unit’s governor. The results of simulation prove that this method is an available solution to solve the problem of poor system frequency stability when a system has a high ratio of hydropower.

Virtual Generation Alliance Automatic Generation Control Based on Deep Reinforcement Learning

This article proposes a distributed hierarchical automatic generation control (AGC) framework with multiple regulation units in the performance-based frequency regulation market, named virtual generation alliance automatic generation control (VGA-AGC), aiming to achieve the coordination of control algorithm and AGC dispatch algorithm and adapt to the development trend of AGC from centralized framework to centralized-decentralized framework. The framework also involves a multi agent distributed multiple improved deep deterministic policy gradient (MADMI-TD3) algorithm that is characterized by excellent global search capability and optimizing speed. The algorithm can help create an optimal AGC strategy in a randomization environment so as to obtain an optimal cooperative control of AGC. According to a simulation verification on the LFC model for an interconnected power grid of a province, the algorithm is superior to the current algorithms and conventional engineering methods in terms of control performance and economic benefits. In other words, the algorithm can improve control performance and reduce the regulation mileage payment.