Grid Frequency Regulation Research Articles

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.

A segmented optimal PID method to consider both regulation performance and damping characteristic of hydroelectric power system

Hydropower has become the main force of grid frequency regulation due to its regulation flexibility and rapid response characteristics. However, when the operating conditions are changed, the continued pursuit of a faster response speed deteriorates the damping characteristics of the system with wider water-head, causing low-frequency oscillations, threatening the power station's safety and stability and the power grid. In this study, an improved quantized damping method is applied. The settling time and damping coefficient variation under different PID parameters and operating conditions are recorded, revealing the contradiction between regulation performance and damping characteristics. Then the segmented optimal PID controller is proposed to balance this contradiction. The twin-delayed deep deterministic policy gradient learning algorithm enables the controller to find the optimal policy online. With the settling time-damping threshold control strategy, the controller optimizes parameters according to operating conditions, and changes parameters when reaching the threshold. The results show that, compared with using a set of PID parameters, the damping of the hydropower system is increased by 0.35 from negative to positive. In contrast, the settling time increases by 11.63s within limits. The proposed controller ensures the safe and coordinated operation of the power grid and the power station of the hydroelectric power system with a wide water-head.

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.

A Two-Layer Fuzzy Control Strategy for the Participation of Energy Storage Battery Systems in Grid Frequency Regulation

To address the frequency fluctuation problem caused by the power dynamic imbalance between the power system and the load when a large number of new energy sources are connected to the grid, a two-layer fuzzy control strategy is proposed for the participation of the energy storage battery system in FM. Firstly, considering the coordination of FM units responding to automatic power generation control commands, a comprehensive allocation strategy of two signals under automatic power generation control commands is proposed to give full play to the advantages of two FM signals while enabling better coordination of two FM units responding to FM commands; secondly, based on the grid FM demand and battery FM capability, a double-layer fuzzy control strategy is proposed for FM units responding to automatic power generation control commands in a coordinated manner under dual-signal allocation mode to precisely allocate the power output depth of FM units, which can control the fluctuation of frequency deviation within a smaller range at a faster speed while maintaining the battery charge state; finally, the proposed Finally, the proposed control strategy is simulated and verified in Matlab/Simulink. The results show that the proposed control strategy can control the frequency deviation within a smaller range in a shorter time, better stabilize the fluctuation of the battery charge level, and improve the utilization of the FM unit.

Optimal Grid Supporting Power-to-Gas (GS-P2G) Concept for Grid Voltage and Frequency Regulation

Optimal Grid Supporting Power-to-Gas (GS-P2G) Concept for Grid Voltage and Frequency Regulation

Research on the integrated application of battery energy storage systems in grid peak and frequency regulation

To explore the application potential of energy storage and promote its integrated application promotion in the power grid, this paper studies the comprehensive application and configuration mode of battery energy storage systems (BESS) in grid peak and frequency regulation. Based on the performance advantages of BESS in terms of power and energy response, integrated multiplexing of peak and valley filling (PSVF) application on long-time scales and frequency regulation (FR) application on short-time scales are explored. First, the theoretical feasibility of its comprehensive multiplexing application is explored from technical and economic perspectives. Then, the requirements of both models for decoupling and coupling are analyzed, and their specific composite control strategies and implementations are discussed in further detail. Finally, based on a techno-economic evaluation model, the effectiveness of each control strategy was simulated and evaluated to find the optimal BESS control and configuration in the combined application of PSVF and FR. Thus, it provides theoretical and technical support for the functional reuse of BESS in engineering practice.

A day‐ahead bidding strategy for battery swapping and charging system participating in the regulation market

AbstractThe battery swapping mode is a promising way for electric vehicles (EVs) to participate in power grid frequency regulation. However, the operation mechanism and the uncertainty management in the process still lack research. Aiming at this issue, this paper proposes a day‐ahead bidding strategy for the battery swapping and charging system (BSCS) providing regulation reserve capacity in the ancillary service market. Firstly, a new BSCS‐based regulation model is established. Then, an ambiguity set based on Kullback–Leibler (KL) divergence is used to manage the uncertainty of regulation signals and battery swapping demands. Furthermore, a boundary expectation approach is proposed to turn the problem into robust optimization. Finally, after using the extreme scenario method (ESM) to generate extreme scenarios, a duality‐free column‐and‐constraint generation (C&CG) algorithm is employed to solve the problem. The case studies demonstrate that BSCS can provide economical and robust reserve capacity bidding plans in the day‐ahead market with the proposed strategy. At the same time, the BSCS‐based regulation service is simulated with the battery development trend in the future, and suggestions are given.

A coordinated control method of aggregate AC load for auxiliary frequency regulation service

Large-scale fixed frequency air-conditioners (FFAC) and inverter air-conditioners (IAC) are high-quality flexible load resources in the power system. This paper proposes a coordinated control method of aggregate air-conditioner (AC) load for auxiliary frequency regulation services. Firstly, a new method for evaluating the frequency regulation potential (FRP) of aggregate AC is proposed. This method can rapidly evaluate the FFAC and IAC’s potential of providing frequency regulation at all stages. Then the day-ahead frequency regulation capacity (FRC) of aggregate AC at each time period is determined based on the frequency and unit commitment constraints. Afterwards, a coordinated control method considering users’ comfort level is developed to ensure the sequential operation of each AC and support the frequency regulation of the power grid. Finally, a simulation is conducted to demonstrate that the proposed method can realize the coordinated control of FFAC and IAC and improve the frequency stability of the power system.

Small-signal synchronization stability of grid-forming converter influenced by multi time-scale control interaction

The grid-forming (GFM) converters that simulate the dynamics of synchronous generators (SGs) and actively participate in grid voltage and frequency regulation are increasingly employed as grid interfaces for renewable energy generation. Its synchronization stability with AC grid is also increasingly concerned in recent years. In this paper, the small-signal synchronization stability of GFM converters with virtual synchronous generator (VSG) control is investigated, with the influence of multi time-scale control interaction considered especially. First, based on multi time-scale dynamics analysis, an analogized Heffron–Phillips model is developed to physically depict the small-signal synchronization dynamics of VSG. The multi time-scale control interaction introduces an additional input torque to the equivalent motion of VSG’s synchronization behavior. Based on damping torque analysis, the synchronization stability is depended by the inherent damping component of VSG’s virtual rotor motion and the additional damping component introduced by multi time-scale control interaction. Qualitative and quantitative analysis reveal that the additional damping is negative and deteriorates the synchronization stability. When the negative additional damping is greater than the positive inherent damping, small-signal synchronization instability occurs due to insufficient damping. Finally, the influence factors including control parameters and grid strength are discussed.

Seq2Seq regression learning-based multivariate and multistep SOC forecasting of BESS in frequency regulation service

Battery Energy Storage Systems (BESS) has a fast response time and high ramping capability, making it suitable for smart grid frequency regulation service. However, providing the required regulation capacity without a problem at any point in time is bound with the BESS state of charge (SOC) development periodically. Moreover, knowing SOC variation in advance will help the BESS producers keep SOC at the desired level. The BESS SOC can be maintained in the admissible operation area to avoid the mismatch penalties while following regulation signals. Therefore, the maximum service reward can also be achieved. Unfortunately, forecasting the SOC of BESS in frequency regulation service is not a straightforward problem. The forecasting method should deal with multiple dependent variables that periodically determine SOC’s development. Moreover, developing a one-time manner multistep SOC forecasting model is also a challenge. To solve both problems, a sequence-to-sequence (seq2seq) regression learning architecture that has been proven to deal with sequentially interdependent data is adopted in our proposed forecasting framework. Various state-of-the-art memory cells in deep regression learning, i.e., long short-term memory (LSTM), gated recurrent unit (GRU), bi-directional (bi)-LSTM, and bi-GRU, were utilized and evaluated. The evaluation result shows that the developed models outperform the existing machine learning-based forecasting methods. The Bi-GRU cells provide the best performance in root mean square error (RMSE) and mean absolute error (MAE) evaluation metrics.

Model predictive control for a medium-head hydropower plant hybridized with battery energy storage to reduce penstock fatigue

A hybrid hydropower power plant is a conventional Hydro-Power Plant (HPP) augmented with a Battery Energy Storage System (BESS) to decrease the wear of sensitive mechanical components and improve the reliability and regulation performance of the plant. A central task of controlling a hybrid HPP is determining how the total power setpoint is split between the BESS and the hydraulic turbine (power setpoint splitting). This paper describes a Model Predictive Control (MPC) framework for hybrid medium- and high-head HPPs for the power setpoint splitting problem. The splitting policy relies on an explicit formulation of the mechanical loads incurred by the HPP’s penstock, which can be damaged due to fatigue when providing grid frequency regulation. By filtering out from the HPP’s power setpoint the components conducive to excess penstock fatigue and properly controlling the BESS, the proposed MPC maintains the same level of regulation performance while significantly decreasing damages to the hydraulic conduits. A proof-of-concept by simulations is provided considering a 230 MW medium-head plant. • The problem is to split the power setpoint between the hydraulic turbine and battery. • We formalize explicit plant stress constraints in the control problem. • MPC enforces penstock stress below fatigue limit, the battery acts as a slack variable. • Proof-of-concept by simulation on a 230 MW medium-head hydropower plant. • Results show effective fatigue reduction while delivering the same regulating power.

Multi-objective control of isolated power systems under different uncertainty approaches

This paper proposes and compares a set of multi-objective supervisory controllers for an isolated power system including a gas turbine operating in load following mode as a dominant source of generation, a battery energy storage system, and stochastic renewable generation. It analyzes their capability to coordinate the gas turbine and energy storage to provide isochronous speed control, achieving fast frequency regulation for the local grid, while the gas turbine can still operate with minimum deviation from its optimal loading and the storage system can follow a pre-scheduled reference state of charge trajectory. In more detail, we consider and compare different control strategies to handle model and disturbance uncertainties, including stochastic model predictive control under various parametrizations of the scenario approach, and robust control under the H ∞ paradigm. The various controllers are compared against a benchmark, i.e., a deterministic predictive control strategy. Instead of point-to-point comparisons for some arbitrary cases (i.e., worst-case or expected), empirical distributions of the controller’s performance for the whole probability spectrum are derived, leading to more accurate and representative comparisons. The analyzed performance indicators are nominal dynamic performance, constraint violation probabilities, and expected system operation performance. The results indicate the clear superiority of stochastic control over both robust and deterministic control in dealing with both parametric and disturbance uncertainty. Moreover, choosing an appropriate parametrization is shown to be essential to achieve both good nominal performance and lower violations probability, indicating that the superiority of stochastic control comes with the drawback of needing user-defined tuning from the designer. • Multi-objective optimal MIMO control of isolated power systems with energy storage. • Simultaneous grid frequency regulation and state-of-charge schedule tracking. • Performance metrics for robust and predictive control assessment under uncertainty. • Comparison of control parametrizations for scenario-based stochastic control.

Frequency Regulation of an Islanded Microgrid Using Hydrogen Energy Storage Systems: A Data-Driven Control Approach

Hydrogen energy storage (HES) systems have recently received attention due to their potential to support real-time power balancing in a power grid. This paper proposes a data-driven model predictive control (MPC) strategy for HES systems in coordination with distributed generators (DGs) in an islanded microgrid (MG). In the proposed strategy, a data-driven model of the HES system is developed to reflect interactive operations of an electrolyzer, hydrogen tank, and fuel cell, and hence the optimal power sharing with DGs is achieved to support real-time grid frequency regulation (FR). The MG-level controller cooperates with a device-level controller of the HES system that overrides the FR support based on the level of hydrogen. Small-signal analysis is used to evaluate the contribution of FR support. Simulation case studies are also carried out to verify the accuracy of the data-driven model and the proposed strategy is effective for improving the real-time MG frequency regulation compared with the conventional PI-based strategy.

A Review of the Application and Development of Flywheel Energy Storage

High power density, high efficiency and low loss are the characteristics of flywheel energy storage, which has broad application prospects in the field of rail transit. This paper introduces the basic structure and principle of flywheel energy storage, analyzes the energy storage density of the rotor in both metal and composite materials, and points out that composite materials such as T1000 fiber/resin have higher strength and lower density. The highest energy density. Finally, the development status of flywheel energy storage in rail transit, civil vehicles and other fields is summarized, and the future development prospects of power grid frequency regulation and uninterruptible power supply are prospected. This paper can provide a reference for in-depth research on flywheel energy storage materials.

Research on the Primary Frequency Regulation Control Strategy of a Wind Storage Hydrogen-Generating Power Station

Wind curtailment and weak inertia characteristics are two factors that shackle the permeability of wind power. An electric hydrogen production device consumes electricity to produce hydrogen under normal working conditions to solve the problem of abandoning wind. When participating in frequency regulation, it serves as a load reduction method to assist the system to rebuild a power balance and improve the wind power permeability. However, due to its own working characteristics, an electric hydrogen production device cannot undertake the high-frequency component of the frequency regulation power command; therefore, an energy storage device was selected to undertake a high-frequency power command to assist the electric hydrogen production device to complete the system frequency regulation. This paper first proposes and analyzes the architecture of a wind storage hydrogen-generating station for centralized hydrogen production with a distributed energy storage, and proposes the virtual inertia and droop characteristic mechanism of the wind storage hydrogen-generating station to simulate a synchronous unit. Secondly, an alkaline electrolysis cell suitable for large-scale engineering applications is selected as the research object and its mathematical model is established, the matching between different energy storage devices and their cooperation in power grid frequency regulation is analyzed, and a super capacitor is selected. A control strategy for the wind storage hydrogen-generating power station to participate in power grid frequency regulation with a wide time scale is then proposed. Using the first-order low-pass filter, the low-frequency component of the frequency regulation power command is realized by an electric hydrogen production device load reduction, and a high-frequency component is realized by the energy storage device. Finally, the effectiveness and rationality of the proposed control strategy are verified by establishing the simulation model of the wind storage hydrogen-generating power station with different initial wind speed states, comparing the system frequency dip values under the proposed multi-energy cooperative control strategy and a single energy device control strategy.

Optimization control and economic evaluation of energy storage combined thermal power participating in frequency regulation based on multivariable fuzzy double-layer optimization

Energy storage auxiliary thermal power participating in frequency regulation of the power grid can effectively improve operating efficiency of thermal power units, but how to realize power distribution between energy storage system and thermal power units is the key to the frequency regulation operation of energy storage and thermal power combined system. Aiming at problems that full power compensation strategy is not conducive to the sustainability of energy storage output, a frequency regulation optimization control strategy of thermal powers and energy storage combined system based on multivariable fuzzy double-layer optimization is proposed in this paper. According to the output and compensation weights of the fuzzy controller, the state of charge for energy storage system can be adjusted adaptively to help thermal power units improve the dynamic frequency regulation performance of power grid. The equivalent cycle life of energy storage system is calculated by the rain-flow counting method, and the economy of system is evaluated by the net present value method in the whole life cycle of energy storage system. The effectiveness of the proposed control strategy is verified by the simulation analysis on the actual operation data which can provide a theoretical basis for frequency regulation of automatic generation control.

Power management optimization of electric vehicles for grid frequency regulation: Comparative study

Electric vehicles (EVs) have shown promise in providing ancillary services, e.g., frequency regulation. This is mainly due to their capacities and fast response. On the contrary, the rapid integration of EVs in the grid poses challenges, such as frequency and voltage stability. In order to mitigate the above-mentioned issues, several dispatching strategies have been introduced in the recent literature to optimize the charging/discharging rates of EVs. In this paper, a comparative study of power management strategies for secondary frequency regulation (SFR) employing a fleet of EVs is presented. A hierarchical control scheme is employed to compare two cases, namely control at the charging station (CS) level and novel control at the EVs level. Under both cases, a multi-objective optimization approach is utilized to define the optimal charging and discharging rates of EVs using a pattern search algorithm. Furthermore, the performance of the two models is experimented under contingency cases, a notable contribution of this study. Finally, simulations are carried out using OPAL-RT real time simulator to validate the performance of the two models based on real-time traces obtained from Pennsylvania, New Jersey, and Maryland (PJM) interconnection and California independent system operator (CAISO). To further validate the proposed model, a comparison with a mixed-integer linear programming (MILP) based model is presented.

System Frequency Control Method Driven by Deep Reinforcement Learning and Customer Satisfaction for Thermostatically Controlled Load

The intermittence and fluctuation of renewable energy aggravate the power fluctuation of the power grid and pose a severe challenge to the frequency stability of the power system. Thermostatically controlled loads can participate in the frequency regulation of the power grid due to their flexibility. Aiming to solve the problem of the traditional control methods, which have limited adjustment ability, and to have a positive influence on customers, a deep reinforcement learning control strategy based on the framework of soft actor–critic is proposed, considering customer satisfaction. Firstly, the energy storage index and the discomfort index of different users are defined. Secondly, the fuzzy comprehensive evaluation method is applied to evaluate customer satisfaction. Then, the multi-agent models of thermostatically controlled loads are established based on the soft actor–critic algorithm. The models are trained by using the local information of thermostatically controlled loads, and the comprehensive evaluation index fed back by users and the frequency deviation. After training, each agent can realize the cooperative response of thermostatically controlled loads to the system frequency only by relying on the local information. The simulation results show that the proposed strategy can not only reduce the frequency fluctuation, but also improve customer satisfaction.

Double-layer AGC frequency regulation control method considering operating economic cost and energy storage SOC consistency

Aiming at the problem of power grid frequency regulation caused by the large-scale grid connection of new energy, this paper proposes a double-layer automatic generation control (AGC) frequency regulation control method that considers the operating economic cost and the consistency of the state of charge (SOC) of the energy storage. At the regional control level, an economically optimized dynamic frequency regulation responsibility distribution between the unit and the energy storage is realized, and the idle time of energy storage is fully used for SOC management to effectively suppress the fluctuation of the energy storage SOC. At the energy storage station level, the cooperative control algorithm is used to ensure that the output and SOC of each energy storage unit are consistent, respectively. The effectiveness of the method is verified by establishing the dynamic model of the unit-storage combined frequency regulation of the regional power grid for simulation and comparison experiments. The method proposed in this paper considers the influence of different disturbance conditions on the AGC frequency regulation responsibility distribution between the unit and the energy storage and fully uses the frequency regulation characteristics of the energy storage's rapid and flexible response. It effectively improves the service life of energy storage and the comprehensive operation efficiency of the system while optimizing the frequency regulation operation cost, improving the frequency regulation performance, and increasing the frequency regulation compensation income.

A DoS attack intensity-aware adaptive critic design of frequency regulation for EV-integrated power grids

Vehicle to Grid (V2G) technology provides an economical, fast response and highly flexible capabilities for grid frequency regulation (FR). However, denial of service (DoS) attacks disrupt the communication links between V2G FR controllers and electrical vehicle (EV) aggregators leading to severe degradation of FR performance. Therefore, this paper proposes an attack intensity-aware adaptive critic design (AIACD) to improve FR performance under DoS attacks. In the proposed AIACD, a game framework is constructed to derive the optimal robust V2G FR controller, considering attack intensity and V2G power limits. The optimal V2G FR controller is approximated by neural networks to minimize a proposed attack intensity-aware cost function. The cost function is modeled as a function of both system states and attack intensity so that minimizing the cost function to optimize the V2G FR controller for the corresponding attack intensity. The IEEE 39-bus cases with three areas illustrate the effectiveness and advantages of the proposed AIACD under DoS attacks.