Energy Storage Control Strategy Research Articles

Research on Microgrid Superconductivity-Battery Energy Storage Control Strategy Based on Adaptive Dynamic Programming

Research on Microgrid Superconductivity-Battery Energy Storage Control Strategy Based on Adaptive Dynamic Programming

Minimum Suspension Loss Control Strategy of Vehicle-Mounted Flywheel Energy Storage Using Single-Winding Bearingless Synchronous Reluctance Motor

Minimum Suspension Loss Control Strategy of Vehicle-Mounted Flywheel Energy Storage Using Single-Winding Bearingless Synchronous Reluctance Motor

Review on Advanced Storage Control Applied to Optimized Operation of Energy Systems for Buildings and Districts: Insights and Perspectives

In the context of increasing energy demands and the integration of renewable energy sources, this review focuses on recent advancements in energy storage control strategies from 2016 to the present, evaluating both experimental and simulation studies at component, system, building, and district scales. Out of 426 papers screened, 147 were assessed for eligibility, with 56 included in the final review. As a first outcome, this work proposes a novel classification and taxonomy update for advanced storage control systems, aiming to bridge the gap between theoretical research and practical implementation. Furthermore, the study emphasizes experimental case studies, moving beyond numerical analyses to provide practical insights. It investigates how the literature on energy storage is enhancing building flexibility and resilience, highlighting the application of advanced algorithms and artificial intelligence methods and their impact on energy and financial savings. By exploring the correlation between control algorithms and the resulting benefits, this review provides a comprehensive analysis of the current state and future perspectives of energy storage control in smart grids and buildings.

Research on Mathematical Model of Energy Storage Assisted Wind Turbine Frequency Regulation Control Strategy

Abstract This paper proposes an improved frequency regulation strategy for the Doubly-Fed Induction Generator (DFIG) to mitigate the impact of wind power integration on system frequency. An energy storage system is used on the wind side to participate in the frequency regulation. The influence of wind power integration on the power system frequency is analyzed and an improved frequency control strategy for the DFIG is proposed. A control strategy for energy storage devices to support wind turbine frequency control is proposed. An energy storage device model is established that considers power correction based on the state of charge to avoid excessive charging and discharging. According to the operating state of the DFIG, a control strategy for the frequency regulation of the energy storage device is proposed. According to different wind speeds, a control strategy is proposed for the participation of the joint wind storage system in the frequency regulation. This control strategy can provide frequency support to the system when the wind turbine cannot participate in frequency regulation according to the different operating conditions of the wind turbine. After the wind turbine uses the improved frequency control strategy, it accelerates the recovery of the DFIG rotor speed while avoiding a secondary drop in the system frequency. In addition, when the energy storage device has a poor state of charge and the system frequency is good, it charges to restore the state of charge.

Deviation control strategy for electric vehicle virtual energy storage dispatching instruction execution

Abstract As flexible resources, electric vehicles (EVs) participate in the dispatching of power grid regulation. Due to the randomness of entering and exiting the station, each EV cluster cannot fully respond to the guiding power instructions issued by the operator, resulting in biased values. This paper establishes a deviation management and control model, and proposes a local deviation control strategy and a cross-cluster collaborative deviation control strategy based on the model, so as to fully utilize the deviation control capabilities of each EV’s virtual energy storage and minimize the power deviation. The effectiveness of the proposed deviation control strategy for scheduling instructions is verified by numerical examples.

Coordinated Frequency Modulation Control Strategy of Wind Power and Energy Storage Considering Mechanical Load Optimization

When a doubly fed induction generator (DFIG) participates in primary frequency modulation by rotor kinetic energy control, the torque of the generator is changed sharply and the mechanical load pressure of the shaft increases rapidly, which aggravates the fatigue damage of shafting. In order to alleviate the fatigue load of shafting, energy storage was added in the primary frequency modulation of a wind turbine, and a coordinated frequency modulation control strategy of wind power and energy storage based on fuzzy control was proposed. The wind-storage frequency modulation power command was allocated to reduce the response speed of the wind turbine to alleviate the load pressure on the shafting by the fuzzy controller considering the rotor speed range and the state of energy storage charge, and the remaining demand power was supplemented by energy storage. Finally, the joint simulation model based on GH Bladed–Matlab was used to verify the effectiveness of the proposed control strategy. Compared with the traditional integrated control of virtual inertia, the proposed method can reduce the load pressure and fatigue damage of the shafting while satisfying the requirement of frequency modulation.

Frequency stability study of energy storage participation in new energy power system using virtual synchronous machine control

Aiming at the frequency stability of the power system under the increasing proportion of new energy sources, the study adopts the virtual synchronous machine-based energy storage adaptive control strategy and the frequency response model of the new power system. The energy storage adaptive control strategy coordinates the control of the battery’s charging state and the grid operation state by monitoring the grid operation parameters and the battery operation state in real time, so as to calculate the commanded power of the grid-connected converter. The results show that the system stability of adaptive virtual synchronization control improves when the electric transmission power increases from 205 to 510, while the system stability of virtual synchronization control decreases. The extended SFR model possesses excellent frequency matching ability when the new energy penetration rate is 8.497% and 15.66%. Virtual synchronous energy storage control strategy and the power system frequency response model can effectively predict and control the system frequency change to improve system stability under the increasing penetration rate of new energy.

Adaptive Virtual Inertial Control and Virtual Droop Control Coordinated Control Strategy for Hybrid Energy Storage Taking into Account State of Charge Optimization

For energy-storage-assisting conventional units to participate in the primary frequency regulation of a power system, firstly, based on the frequency regulation mechanism of virtual inertial control (VIC) and virtual droop control (VDC) of energy storage, we analyze the effect of the action timing of energy storage on the frequency deviation of the grid under two control methods and put forward a reasonable combination of the two control methods; on this basis, we also put forward hybrid energy storage adaptive VIC and VDC based on the demand of VIC and VDC on the power and capacity of energy storage. On this basis, based on the demand of VIC and VDC on the power and capacity of energy storage, a hybrid energy storage adaptive VIC and VDC coordinated control strategy based on supercapacitor–lithium batteries is proposed, whereby a high-power storage supercapacitor responds to inertial control signals to rapidly suppress a drop in frequency, and the high-capacity lithium battery responds to droop control signals to perform long-time droop control. The high-capacity lithium battery responds to the sagging control signal and is used to perform a long-time sagging power response; finally, in order to avoid the state of charge (SOC) of energy storage falling into a low/high working condition and losing the subsequent frequency regulation ability, an adaptive power control strategy of energy storage based on the improved logistic function is proposed. The simulation results show that under typical load disturbance, the SOC level of the proposed strategy increases by 19.17% and 30.16%, respectively, compared with that of the single-lithium strategy and no energy storage, and the SOC level of the supercapacitor and lithium battery increases by 29.4% and 2.1%, respectively, compared with that of logistic optimization.

Minimum Energy Demands of Energy Storages for Fast Frequency Response: Formulation, Solution, and Implementation

Energy storage (ES) is a kind of promising but costly fast-frequency-response (FFR) resource in low-inertia power systems. This paper addresses the minimum demand of a power system for energy capacities of ES to providing sufficient frequency support, including the formulation, the optimal solution, and its practical implementation. First, the minimum energy control problem of ESs for providing FFR with transient frequency constraints is formulated and then converted into an optimal frequency trajectory planning counterpart. This transformation makes the transient frequency constraint tractable and allows to identify the optimal frequency trajectory that minimizes energy demand for ESs, which leads to an analytical expression of the system minimum demand for ESs energy capacities to ensure frequency security. Moreover, by unfolding the optimal frequency trajectory, the optimal control strategy of ESs is derived explicitly for the first time. The theoretical result directs to a practical controller implementation, which is referred to as the decentralized optimal energy frequency control (DOEFC). Finally, simulations on the modified IEEE 39- bus system verify our results and demonstrate the superiority of the DOEFC in reducing the energy capacity demand of ESs, defending successive disturbances, and hedging against parameter errors.

A smooth grid connection strategy for compressed air energy storage based on adaptive PI control

In the context of the application of compressed air energy storage system participating in power grid regulation, a large capacity of compressed air energy storage accessed to or off from the power grid will bring instability to the system, and there will be voltage and current impact during off-grid operation, which will pose a threat to system security. Therefore, this paper puts forward the control strategy of compressed air energy storage for both grid-connected and off-grid, and proposes a smooth grid-connected strategy of compressed air energy storage based on adaptive PI control, which can better improve the problem of excessive impulse current during the connection of compressed air energy storage. Finally, a simulation model is built in MATLAB/Simulink to verify the effectiveness and superiority of the proposed control strategy.

Battery Energy Storage Participation in Primary Frequency Regulation Considering SOC Consistency

Abstract In recent years, battery energy storage has garnered increasing attention in the frequency regulation field due to its rapid and precise output characteristics. The focus of this paper is on the control strategy for battery energy storage that is involved in primary frequency regulation and addresses the coordination control issues of different storage units when implemented on a large scale. A control method is proposed that considers the consistency of the State of Charge (SOC) in battery energy storage, which is involved in primary frequency regulation. The control of the battery energy storage system is divided into upper-level and lower-level control. The upper-level control uses model predictive control to obtain the total frequency regulation power of the energy storage station. The lower-level control allocates the corresponding power based on the capacity of each battery energy storage unit. It introduces a proportional integral adjustment term related to the average SOC to achieve SOC consistency control for each unit. Simulation results demonstrate that, regardless of whether the capacities of various storage units are identical, the proposed method achieves good frequency regulation performance, restores SOC to the ideal range, and ensures SOC consistency among different storage units. This approach aids the efficient and safe operation of battery energy storage systems.

Multi-timescale optimal control strategy for energy storage using LSTM prediction–correction in the active distribution network

The daily output of wind power is inversely proportional to the load demand in most situations, which will lead to an increase in peak-to-valley difference and fluctuation. To solve this problem, this study proposes a long short-term memory prediction–correction-based multi-timescale optimal control strategy for energy storage. First, the proposed strategy performs a long short-term memory (LSTM) prediction on the power of wind power and load. Then, it establishes a predictive planning model to improve the effect of peak shaving and the operating income of energy storage. Finally, it uses the method of online correction of power lines for peak shaving to further optimize the energy storage power according to the error between the residual energy of energy storage and the planned residual energy in the actual peak shaving process. By comparing with traditional strategies, the proposed strategy is found to be significantly better than the constant power strategy and the power difference strategy in the peak shaving effect and operating income.

Online optimization and tracking control strategy for battery energy storage in DC microgrids

This paper proposes a fast time-varying optimal power flow (OPF) command tracking control algorithm for DC microgrids based on measurement feedback. The algorithm establishes a model by adding power command tracking constraints and considering the power, voltage, and current constraints of the microgrid. A forward-back generation DC power flow sensitivity calculation method is designed to calculate the power output of the energy storage at each node, and charging and discharging decisions are made based on the state of charge (SOC) of the energy storage system, current voltage, and charging and discharging scenarios previous and subsequent. By continuously issuing control decisions, the DC microgrid OPF command tracking solution is achieved. The measurement feedback control scheme used in this algorithm reduces model error and non-iterative calculation error, thus improving calculation and tracking accuracy. The algorithm is tested in a modified 28-node arithmetic system and suppresses voltage fluctuations caused by unstable PV active output effectively, while accurately tracking the power command of the upper level and meeting the voltage safety operation requirements of the microgrid.

Optimal battery energy storage planning and control strategy for grid modernization using improved genetic algorithm

The flexible operation of battery energy storage systems (BESS) to support electricity grid modernization requires optimal planning and an efficient control strategy. This paper proposes the optimal allocation of BESS with photovoltaic systems for microgrids to enhance grid reliability and flexibility. An adaptive BESS control strategy is developed to allow the BESS to operate in both redundant and peak shaving modes. An evolutionary programming-based genetic algorithm implemented with an optimal power flow control is proposed to determine the BESS’s optimal location, sizing, and charge/discharge operation. The objective function is to maximize the benefits of energy loss reduction and peak shaving enhancement while minimizing the installation cost. The proposed approach is conducted with MATLAB and DIgSILENT PowerFactory software, which uses an intelligent automatic data exchange process to solve the optimal solution. A practical 22 kV grid-connected microgrid of Thailand is used as a test system to demonstrate the effectiveness of the planning and control strategy for the BESS installation. The simulation test results show that the proposed optimal BESS allocation and control strategy can significantly reduce the microgrid’s energy loss and peak demand and increase energy shaving leading to enhanced grid resiliency and reliability.

Design and Optimization of Flywheel Energy Storage System for Rail Transit

At present, the urban rail transit system has problems such as energy waste in the braking process and unstable grid voltage in the start-stop state. Aiming at the problems caused by the start-stop state of rail transit, considering the energy saving and voltage stability requirements of system energy management, a flywheel energy storage system (FESS) specially used for rail transit is designed. The energy system (FESS) can feed back the braking energy stored by the flywheel to the urban rail train power system when the rail train starts to cause the voltage and frequency of the traction microgrid to change. This paper proposes a flywheel energy management system based on a permanent magnet synchronous motor (PMSM), which can realize efficient energy management through efficient control of the flywheel side motor. The flywheel side permanent magnet synchronous motor adopts an improved flywheel speed expansion energy storage control strategy based on current feedforward control to improve the fast response capability of the flywheel, ensuring the output power of the flywheel at high speed. In addition, a specific multi-threshold voltage single FESS control strategy is suggested, which improves the energy-saving and voltage-stabilizing performance of the system.

Wavelet Packet-Fuzzy Optimization Control Strategy of Hybrid Energy Storage Considering Charge–Discharge Time Sequence

A hybrid energy storage system (HESS) can effectively suppress the high and low-frequency power fluctuations generated by wind farms under the intermittency and randomness of wind. However, for the existing power distribution strategies of HESS, power-type and energy-type energy storage have the problem of inconsistent charge–discharge states in the same time sequence, which makes it difficult to achieve optimal operation in terms of charge–discharge coordination and energy flow. To solve this problem, this study firstly adopts adaptive wavelet packet decomposition (WPD) to decompose the original wind power to acquire grid-connected power and HESS initial distribution power, to ensure that the supercapacitor and battery undertake the corresponding high and low-frequency power fluctuations, respectively; Then, for the inconsistent charge–discharge states, a charge–discharge time sequence optimization strategy based on the consistency index is proposed to correct the initial power distribution of HESS for the first time; Finally, aiming at the stage of charge (SOC) over-limit problem, the fuzzy optimization method is adopted to correct the HESS output power for the second time, which can reduce the unnecessary charge–discharge energy effectively. With typical daily output data of a 100 MW wind farm, the proposed control strategy is verified. The results show that it can make different energy storage technologies synchronously suppress wind power fluctuation in the same time sequence; compared with not considering charge–discharge time sequence optimization, the charge–discharge conversion times of the battery obtained by the proposed method are reduced from 71 to 14 times, and the charge–discharge conversion times of supercapacitor are reduced from 390 to 61 times; The cumulative reduction of unnecessary charge–discharge energy by HESS is 12.12 MWh. Besides, the SOC curves of HESS are controlled at a normal level, thus improving the economy and service life of HESS.

Power grid load frequency control based on Fractional Order PID combined with pumped storage and battery energy storage

With the increasing proportion of installed renewable energy power generation capacity and the introduction of quantitative energy storage policies for new energy power generation. In view of the influence of intermittent and volatility of distributed generation on the safe of power grid, it is​ particularly important in the future to equip reasonable energy storage to ensure the flexibility of power system. In this paper, a load frequency control (LFC) strategy of hybrid energy storage based on fractional order proportion integral derivative (FOPID) is proposed to solve the frequency modulation problem of battery energy storage system (BESS) and pumped storage station (PSS) participating in the interconnection network. Firstly, the LFC model is established under the nonlinear factors such as regulator dead zone and generation rate constraint on a two-area reheat steam turbine. Secondly, a FOPID controller is designed. Furthermore, the combined LFC simulation is carried out by adding BESS under the two working operations of PSS generating and pumping. Finally, the influence of demand response is considered in the hybrid energy storage control.

Frequency Control Strategy of Energy Storage and Thermal Power Unit Considering Cost and Performance

Considering differentiated frequency regulation(FR) characteristics between energy storages and thermal power units, a frequency control strategy considering cost and performance is proposed to realize the complementary advantages of them. A joint objective of minimizing total cost and minimizing the penalty for failure of energy storage to track a given signal is proposed. The technical characteristics of FR resources, such as power and creep rate, are adopted as constraints. The comparison results demonstrate that the suggested approach improves the FR regional grid’s performance and reduces the regulation cost.

Research on flywheel energy storage control strategy based on active disturbance rejection controller

Based on nonlinear busbar voltage in flywheel energy storage systems and frequent discharge characteristics, in order to improve the dynamic control derived from the analysis of a permanent magnet synchronous motor and its inverter set up model of DC bus and the active disturbance rejection principle and use the active disturbance rejection control (ADRC) technique to design the DC bus voltage adaptive controller, the first- and second-order ADRC controllers are compared with the traditional PI controller in MATLAB. In this work, we demonstrate that the voltage controller designed with the first- and second-order ADRCs was superior to a traditional PI in terms of dynamic performance control.

Control strategy for the magnetic energy storage and transfer system (MEST)

The Magnetic Energy Storage and Transfer system (MEST) aims at improving the power handling in supplying the SuperConducting (SC) coils of fusion experiments. It is based on smart use of Superconducting Magnetic Energy Storage technology and allows the introduction of a certain degree of decoupling between the grid and the load. The MEST operation is based on the storage and transfer of the needed energy between the Load Coil (LC) and an additional storage inductor named Sink Coil (KC); the energy transfer is realized via capacitors switched by fully controllable semiconductors.This paper focuses on the control system of the MEST and proposes a control strategy, based on two decoupled control loops, with the aim both to guarantee the desired current on the load coil and the compensation of the system losses. A model of the MEST with the proposed control system has been developed to analyze the performance through numerical simulations. The control strategy and the simulation results will be presented and discussed in the paper.