Frequency Regulation Of Power Grid Research Articles

Improving Energy Density of Supercapacitors to Increase Hold-Up Time for Frequency Regulation in Power Grids

Improving Energy Density of Supercapacitors to Increase Hold-Up Time for Frequency Regulation in Power Grids

A Method for Calculating the Adjustable Capacity of Feeder Load Aggregators Considering the User’s Wishes

Abstract With the deepening of China’s energy reform, large-scale renewable energy access has put forward higher requirements for the flexible adjustment ability of the power system. The research and application of mining flexible and adjustable resources on the user side to participate in the peak regulation and frequency regulation of the power grid have received extensive attention. With the gradual opening of the power market and the deepening of the reform of the power system, the feeder load aggregator has gradually become a new role in the power market, and the feeder load aggregator plays an important role in the centralized management of users, the optimization of distribution, and the realization of market-oriented transactions. However, the research on the participation of feeder loads in the auxiliary services of power grid peak regulation and frequency regulation is not perfect. In this context, this paper proposes a method for calculating the adjustable capacity of feeder load aggregators considering the wishes of users, in which the maximum voltage adjustable at the feeder and the change of the capacity of each user caused by the feeder voltage regulation are calculated by the feeder load aggregator through the power flow relationship, and finally the adjustable capacity declaration for the ancillary service market is completed.

Frequency regulation in a hybrid renewable power grid: an effective strategy utilizing load frequency control and redox flow batteries

Renewable energy sources (RESs) have become integral components of power grids, yet their integration presents challenges such as system inertia losses and mismatches between load demand and generation capacity. These issues jeopardize grid stability. To address this, an effective approach is proposed, combining enhanced load frequency control (LFC) (i.e., fuzzy PID- T IλDμ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${I}^{\\lambda }{D}^{\\mu }$$\\end{document}) with controlled energy storage systems, specifically controlled redox flow batteries (CRFBs), to mitigate uncertainties arising from RES integration. The optimization of this strategy's parameters is achieved using the crayfish optimization algorithm (COA), known for its global optimization capabilities and balance between exploration and exploitation. Performance evaluation against conventional controllers (PID, FO-PID, FO-(PD-PI)) confirms the superiority of the proposed approach in LFC. Extensive testing under various load disturbances, high renewables penetration, and communication delays ensures its effectiveness in minimizing disruptions. Validation using a standardized IEEE 39-bus system further demonstrates its efficiency in power networks grappling with significant renewables penetration. In summary, this integrated strategy presents a robust solution for modern power systems adapting to increasing renewable energy utilization.

Research on intelligent control system of permanent magnet motor for high-speed flywheel energy storage system based on deep learning

With the continuous development of society, more and more people pay attention to energy issues, and the realization of energy storage has become a hot research direction today. Despite advancements, the control system of the high-speed flywheel energy storage system’s permanent magnet motor still encounters issues in effectively regulating the magnetic suspension bearing and motor speed. In addressing this issue, a technical solution involves the implementation of an intelligent control system for the high-speed flywheel energy storage system’s permanent magnet motor, utilizing deep learning principles. This innovative approach employs deep neural networks to model, optimize, and regulate the flywheel energy storage system. The essence of flywheel energy storage lies in the conversion of electrical energy into mechanical energy, followed by its reconversion into electrical energy during output. It has the advantages of high energy density, high power density, long cycle life, fast charging and discharging, maintenance-free and environmental protection. A permanent magnet motor is a motor that uses permanent magnets to generate a magnetic field. It has the characteristics of high efficiency, high power density, and low rotor loss. It remains the most widely utilized motor in flywheel energy storage systems. An intelligent control system is characterized by its use of artificial intelligence technology to adapt, self-learn, and self-organize complex systems. This system is distinguished by its robust nonlinear processing capabilities and resilience to faults. The high-speed flywheel energy storage system permanent magnet motor intelligent control system based on deep learning can improve the performance, efficiency and reliability of the flywheel energy storage system, reduce costs and risks, and is suitable for electric vehicles, rail transit, power grid frequency regulation and other fields. In this paper, the convolutional neural network and PSO algorithm are used to obtain the PSNN neural network structure to predict the speed of the motor, so as to achieve its control. And the reliability of the structure is verified by experiments.

Coordinated frequency support strategy for VSC-HVDC integrated offshore wind farm system

The large-scale offshore wind power integrated into the onshore power grid through voltage source converter-based high voltage direct current (VSC-HVDC) system is unable to provide inertia response and frequency support to the onshore power grid. To improve the frequency characteristics of the receiving-end power grid, a coordinated frequency control strategy combining VSC-HVDC and offshore wind power is proposed. The onshore converter adopts virtual inertia control, which uses DC capacitors to absorb or release energy for inertia support after the receiving-end grid is disturbed. Wind-farm-side VSC (WFVSC) obtains the frequency signal of the receiving-end power grid by detecting the local DC voltage. The offshore wind farm (OWF) transfers the frequency deviation into an additional power signal and sends it to the power controller to adjust the output, thereby performing inertia and primary frequency response. In addition, a secondary frequency regulation strategy for wind farms has been designed to achieve non-difference frequency regulation of the receiving-end power grid. Finally, a simulation model of VSC-HVDC integrated OWF system is constructed to demonstrate the proposed coordinated frequency control strategy for VSC-HVDC and OWF. The results indicate that the proposed control strategy can effectively enhance the frequency support capability of the receiving-end power grid.

Research on the double-layer clustering method of residential energy use characteristics under the background of energy system energy savings and carbon reduction

Accurate differentiation of energy consumption information of residential users is of great significance for load planning, scheduling, operation and management of power system, and is the basic premise for realizing intelligent perception of energy system and energy saving and carbon reduction. Considering that the conventional single-layer clustering method has limited clustering stability and clustering effect, this paper takes the key family feature factors as the modified feature quantity of quadratic clustering, and proposes a study of user energy characteristics based on double-layer clustering and modification. Firstly, the user’s energy consumption data is collected and pre-processed, and the user’s energy consumption curve is clustered and analyzed by using the integrated clustering algorithm based on voting and the advantages of each member algorithm. Then, the key family characteristic factors are obtained, and the results of one-layer clustering and key family characteristic factors are combined to carry out two-layer clustering of the same category of users in the form of questionnaire survey. Finally, the nonlinear mapping capability of Support Vector Machine (SVM) is used to reverse correct the results of the one-layer clustering. The actual algorithm data of the residents’ demand response experiment in a southeastern province are compared. The results show that compared with the single-layer clustering algorithm, the proposed method can accurately distinguish the energy consumption characteristics and adjustable potential of different users, and correct the wrong clustering results in the single-layer clustering. The clustering stability and clustering effect have been effectively improved.The example results show that the clustering results modified by SVM can better mine and distinguish user energy characteristics, and can be used to solve the problem of the current demand response clustering algorithm not being able to comprehensively and objectively describe the participation willingness and response-ability of residential users in the implementation process. It can also provide a basis for peak shaving and power grid frequency regulation.

Stability-Constrained Learning for Frequency Regulation in Power Grids With Variable Inertia

Stability-Constrained Learning for Frequency Regulation in Power Grids With Variable Inertia

Study on the dynamic characteristics, control strategies and load variation rates of the concentrated solar power plant

As more and more wind power and photovoltaic power are connected to the electrical power system, it brings great challenges to the stability of power grid. Concentrated solar power (CSP) plant with thermal energy storage (TES) can undertake the task of load regulation and frequency regulation in power grid by balancing the electricity demand and generation. However, the maximum load variation rates of the CSP plant are not known, which restricts sufficient utilization of its advantages. In this study, a dynamic simulation model of CSP plant was built by using the APROS, and the dynamic characteristics were investigated by applying the step disturbances to molten salt flowrate, molten salt temperature, and the opening of steam regulating valve. Based on the results of dynamic characteristics, the control strategies were developed with the consideration of thermal storage in system and the feedforward signal of setting load and load variation rate. Then, the maximum load increase and reduction rates within different load ranges were studied. The results indicated that steam regulating valve, molten salt flowrate and molten salt temperature could be used to control turbine power, steam pressure and steam temperature, respectively. The designed control system could effectively follow the load variation with load deviation less than 0.3 MW and steam temperature deviation less than 1.2 °C in the condition of load variation rate at 3% Pe·min−1, which was superior to the conventional control strategy not considering the thermal storage in system. The maximum load increase and reduction rates were 11.57% Pe·min−1 and 8.94% Pe·min−1 within the load range of 75%THA-100%THA, and they were 10.42% Pe·min−1 and 7.46% Pe·min−1 within the load range of 50%THA-75%THA, respectively. The above load variation rates were first demonstrated for CSP plant, which could provide important guidance for plant operation in load regulation task and the load dispatching on grid side.

Multi-Energy Cooperative Primary Frequency Regulation Analysis of a Hybrid Plant Station for Wind Power and Hydrogen Production Based on Ensemble Empirical-Mode Decomposition Algorithm

Wind curtailment and inadequate grid-connected frequency regulation capability are the main obstacles preventing wind power from becoming more permeable. The electric hydrogen production system can tackle the wind curtailment issue by converting electrical energy into hydrogen energy under normal operating circumstances. It can be applied as a load-reducing method during frequency regulation to help the system restore the power balance. First, this study proposes the concept of a hybrid plant station that combines the production of hydrogen and wind energy. This plant station will be referred to as a hybrid station with centralized hydrogen production and distributed energy storage. By mimicking the synchronous generator’s frequency control features, the primary frequency regulation mechanism of a hybrid plant station is examined. Secondly, due to the frequency regulation requirements of the power grid’s full-time domain hybrid power station, this paper proposes a hybrid plant station control strategy based on the EEMD variable parameter control algorithm. In frequency regulation power, the electric hydrogen production device load reduction responds to the low-frequency component, and the supercapacitor responds to the high-frequency component. The impact of the dynamic characteristics of alkaline electrolyzers on the frequency regulation effect is analyzed in this article, along with a comparison of the matching of various energy storage devices and electrolyzers in power grid frequency regulation. Finally, the feasibility and soundness of the proposed control strategy are confirmed by creating a simulation model representing a hybrid plant station involved in primary frequency management under various operational scenarios.

Power grid frequency regulation strategy of hybrid energy storage considering efficiency evaluation

With the rapid expansion of new energy, there is an urgent need to enhance the frequency stability of the power system. The energy storage (ES) stations make it possible effectively. However, the frequency regulation (FR) demand distribution ignores the influence caused by various resources with different characteristics in traditional strategies. Considering efficiency evaluation, an FR strategy is established to better utilize the advantages and complementarity of various ESs and traditional power units (TPUs). The strategy consists of two interacting modules. The power rolling distribution module optimizes the FR demand to the TPUs and ES stations with the minimum cost first. Then, it optimizes the demand of an ES station to its ES units based on the results of the efficiency evaluation module. The efficiency evaluation module assesses the comprehensive efficiency in cost, revenue, and performance by the EWM-based TOPSIS using the real-time status of different ES units from the power optimization module. A regional grid with a TPU and a hybrid ES station is used to validate the effectiveness of the proposed strategy. The results show that the FR resources are stimulated to improve their performance, and thus, the frequency performance of the system is improved by the proposed strategy.

Lithium ion batteries participating in frequency regulation for power grid under the thermoelectric coupling degradation mechanisms

Lithium-ion batteries (LIBs) play an important role for the global net-zero emission trend. They are suitable for the power interaction with the power grid with high penetration renewable energy. However, the detail evolution of the LIBs participating in frequency regulation (FR) service at low temperature is critical for the all-climate application, especially the capacity decay and the related economic loss. This study reveals that the primary degradation mechanisms for FR operation at low temperature include lithium plating of anode and lattice distortion of cathode. Surprisingly, FR with appropriate parameters for batteries at low temperature does not introduce additional capacity decay due to the great temperature rise brought about and the optimized interfacial mass transfer. This study then analyses the economy of electric vehicles (EVs) participating in FR service, which is called vehicle-to-grid (V2G). A better temperature control can improve the profit of 35.88 $/kW. An appropriate capability is also vital to improve the profit of FR service. Moreover, suitable FR conditions for LIBs can even bring a certain degree of capacity improvement at low temperature. This work guides the design criteria of non-destructive LIB interaction for future grid.

Modeling and Transient Response Analysis of Doubly-Fed Variable Speed Pumped Storage Unit in Pumping Mode

Doubly-fed variable speed pumped storage (VSPS) unit is an advanced hydropower system. In pumping mode, its input power can continuously be adjusted within a certain range via changing speed. Thus, it overcomes the major defect that the pumped storage unit cannot provide frequency regulation services to the power grid in pumping mode. However, for the pumping mode VSPS, how to establish its model is still a problem. In this article, an electromagnetic-electromechanical transient multi-time scale model of pumping mode VSPS is presented. This model depicts the intrinsic speed-power regulation characteristics and the extrinsic power-frequency coupling characteristics of pumping mode VSPS, which can be used for the power grid frequency regulation analysis. Firstly, the hydraulic subsystem model of VSPS is established within the electromechanical transient time scale. The model is built based on the variable speed characteristics of the reversible pump-turbine (RPT) in pumping mode and considers the hydrodynamics and additional friction effects of the wicket gate in the water conveyance system. Secondly, the electric subsystem model of VSPS is established within the electromagnetic transient time scale. The model mainly describes the operation characteristics of a doubly-fed induction machine (DFIM) and the control properties of the inner and outer loops of the back-to-back (BTB) converter system. Finally, comprehensive simulation and experimental results have fully verified the established model and theoretical analysis.

Research on Control Strategy of Hybrid Energy Storage System Participating in Primary Frequency Regulation of Power Grid

With the ongoing development of China’s power system, there is a gradual increase in the proportion of new energy power generation. However, the randomness and volatility associated with new energy power generation can lead to increased frequency fluctuations in the power grid, posing a significant challenge to power system frequency regulation. In this paper, we investigate the control strategy of a hybrid energy storage system (HESS) that participates in the primary frequency modulation of the system. We analyze the advantages and disadvantages of various types of new energy storage from both technical and economic perspectives and perform an applicability analysis system to select lithium batteries and supercapacitor energy storage for forming a HESS. We propose a virtual droop control strategy to regulate the output of the HESS in the primary frequency regulation of the system. Finally, we build a simulation model that includes the HESS and power grid on the MATLAB/Simulink simulation platform and conduct a simulation analysis. The results show that the proposed strategy is superior and effective in controlling the HESS’s output when participating in the primary frequency modulation of the system.

Design and analysis for chemical process electrification based on renewable electricity: Coal-to-methanol process as a case study

Electrification of traditional large-scale chemical industry based on renewable electricity can greatly reduce process CO2 emission, and store intermittent renewable electricity into chemical products locally to decrease power grid frequency regulation caused by fluctuating renewable electricity. This study presents a framework for electrification of chemical industry from indirect and direct aspects using the state-of-art coal-to-methanol process as a case study. Traditional coal-to-methanol (Process 1) suffers from high CO2 emission due to mismatch of H/C ratio between coal and methanol. A pulverized coal gasification-integrated SOEC process (Process 2) has been investigated, the water–gas-shift unit is avoided and a simplified acid gas removal process is implemented to replace traditional acid gas removal unit in Process 2. Electric heaters and heat pump system are applied in Process 2 as direct electrification methods to form semi-electrified scenario (Process 3). To discuss the effect of electrification levels on process performances, a fully electrified process (Process 4) is also designed. The results show that: CO2 emissions of the four processes are 2.19, 0.71, 0.52 and 0.63 t/t MeOH, and energy efficiency are 57.40 %, 62.32 %, 64.31 % and 57.63 %, respectively. Production costs are 159.1, 294.3, 301.0 and 358.3 $/t MeOH, IRRs are 14, 31, 29 and 14.5 %, respectively. Through this research and analysis, we hope to explore integration potential of renewable electricity and traditional chemical industry, and design a greener methanol production route based on renewable electricity.

Research on Wind Power Prediction Based on A Gated Transformer

Wind power, as a type of renewable energy, has received widespread attention from domestic and foreign experts. Although it has the advantages of cleanliness and low pollution, its strong randomness and volatility can bring disadvantages to the stable operation of the power grid. Accurate power prediction can avoid the adverse effects of wind power, and is of great significance for power grid frequency regulation, peak shaving, and energy improvement. However, traditional wind power prediction methods can only achieve accurate predictions in the short term and perform poorly in medium- to long-term prediction tasks. To address this issue, a power prediction model based on a Gated Transformer is proposed in this paper. Firstly, it can extract features from different types of data sources, effectively capture their correlations, and achieve data fusion. Secondly, gating unit, dilated convolution unit, and multi-head attention mechanism are added to improve the Receptive field and generalization ability of the model. In addition, adding a decoder to guide data prediction further improves the accuracy of prediction. Finally, experiments are carried out with the data collected from typical wind farms. The results show that the proposed Gated Transformer achieves consistent state-of-the-art results in prediction tasks on different time scales.

Utilizing controlled plug-in electric vehicles to improve hybrid power grid frequency regulation considering high renewable energy penetration

This study proposes an incorporated strategy based on energy storage systems (ESSs) like plug-in electric vehicles (PEVs) with load frequency control (LFC) to enhance the frequency stability during high penetration of renewable energy sources (RESs). Furthermore, an innovative-cascaded controller is used in the LFC loop, and PEVs are considered in the two identical areas' multi-source power grids. The proposed control structure is based on using two terms, the first term is the fractional-order-proportional-derivative (FOPD), and the second cascaded term is a fractional-order-proportional-integral (FOPI) to form the cascaded (FO-(PD-PI)) controller. Additionally, the gains of the proposed controller are well designed, utilizing an improved version of the manta ray foraging optimization algorithm (MRFO) labeled as leader MRFO (LMRFO). The effectiveness of the proposed FO-(PD-PI) controller based on the LMFRO algorithm is validated by comparing its performance with that of other control approaches such as (i.e., the proportional-integral-derivative (PID) controller, the tilt-integral-derivative (TID) controller, and the fractional-order-PID (FOPID) controller) based on different optimizers. Different load perturbation patterns, a high penetration level of RESs, and the communication delay time are broadly implemented for ensuring the superiority of the proposed controller in penalizing the power grid perturbations. Furthermore, for validating the efficiency of the proposed controller, an IEEE 39 bus is used. As a result, the proposed integrated strategy is a viable and effective control scheme for modern power grids with high-RESs penetration.

Energy management strategy of Battery Energy Storage Station (BESS) for power grid frequency regulation considering battery SOX

In recent years, the application of BESS in power system has been increasing. If lithium-ion batteries are used, the greater the number of batteries, the greater the energy density, which can increase safety risks. Considering the state of charge (SOC), state of health (SOH) and state of safety (SOS), this paper proposes a BESS real-time power allocation method for grid frequency regulation. This method establishes the battery charge criterion table, selects the required action unit, and finally solves it through the planning solver. It can realize the safety management of BESS and deal with extreme situations. It can complete a full charge calibration without disconnecting the battery from BESS, so that the SOC of each battery is consistent. The effectiveness of this method is proved by the model based on 50 MW/100 MWh BESS in Qinghai Golmud.

Voltage and frequency stabilization control strategy of virtual synchronous generator based on small signal model

Power system with large scale Inverter-based Resources (IBR) penetration is challenged with insufficient voltage and frequency support capacity. This paper restructures the control blocks of virtual synchronous generator (VSG) from the perspective of traditional synchronous generators’ control, the control path of the system over its active and reactive power output is clarified and simplified, which has facilitated the tuning of virtual inertia and damping parameters. Firstly, the small signal model of VSG control IBR is established, including instantaneous power calculation module, LC filter and power loop, voltage and current loops. In the meantime, the improved VSG voltage and frequency regulation control strategy is proposed based on the stability analysis of the small signal model. The stable operation range of the VSG control grid-connected inverter system is studied with the objective to improve the stability and robustness of the VSG-controlled grid-connected inverter system. Finally, MATLAB/Simulink simulation verifies the correctness of the proposed VSG’s dynamic model of power grid voltage and frequency regulation. The effectiveness of the restructures of VSG is verified as well. The results show that the control strategy not only improves the inertia of the system, but also enables the IBR to support the frequency and voltage of the system.

A Two-Layer Optimization Strategy for Battery Energy Storage Systems to Achieve Primary Frequency Regulation of Power Grid

A two-layer optimization strategy for the battery energy storage system is proposed to realize primary frequency regulation of the grid in order to address the frequency fluctuation problem caused by the power dynamic imbalance between the power system and load when a large number of new energy sources are connected to the grid. An integrated control mode combining virtual sag control and virtual inertia control is proposed in the adaptive regulation layer to provide fast frequency support for the grid while effectively reducing steady-state frequency difference fluctuation. The equal consumption micro-increment criterion is used in the equalization control layer to distribute the energy output of each group while maintaining a good battery charge level. The results of the final simulation in Matlab/Simulink show that the proposed control strategy can effectively improve the system’s primary frequency regulation performance.

Research on multi-energy cooperative participation of grid frequency inertia response control strategy for energy storage type doubly-fed wind turbine considering wind speed disturbance

With the proposal of carbon peaking and carbon neutralization, the penetration rate of wind power generation continues to increase. This paper focuses on the problem that doubly fed induction wind turbines are vulnerable to input “source” disturbances and have weak frequency modulation ability, which reduces the stability of the power grid. Based on the structural model of energy storage system embedded in doubly fed wind power generation system, it is compared the ability of super capacitor energy storage and releasing rotor kinetic energy to provide inertia response power and energy, and the feasibility of multi-energy coordinated inertia response is analyzed. Based on the inertia time constant of conventional synchronous generator set, the inertia time constant and actual inertia constant of energy storage doubly fed wind power generation system under variable wind speed are defined. An extended state observer is used to estimate the change of captured mechanical power caused by the change of wind speed, and a control strategy for doubly fed induction generator with super capacitor to participate in power grid frequency regulation is designed. Finally, considering the aggregation of wind power and the difference of the state of charge during the operation of distributed energy storage, the 3*3*3 wind farm model is established using Matlab/Simulink simulation software. The feasibility and advantages of the frequency modulation control strategy proposed in this paper are verified by building a power grid frequency modulation simulation involving wind farms and traditional generators.