Storage Control Strategy Research Articles

Hybrid compressed air energy storage system and control strategy for a partially floating photovoltaic plant

For more efficient, reliable, and stable energy provision, energy storage plays a key role in the transition towards renewable energy sources. Compressed air energy storage (CAES) has been recognized as one of the most promising technology due to its high energy capacity, flexibility, scalability, long lifespan, maintainability, economical, and environmental viability. These potentials can be further improved by hybridizing CAES systems with thermal energy storage system. However, to realize the potentials of hybrid CAES systems, a control strategy is essential to manage the energy flow between the system components. Therefore, in this work, a novel energy management strategy is proposed to control a hybrid CAES system for a prototype of a partially floating photovoltaic plant (PFPV). The proposed control strategy is based on the rule-based approach and a mathematical model is presented to evaluate the system performance. The results indicate that, for an average hourly profile of the 5 kW PFPV platform through the year, a system round-trip efficiency of 34.1% can be obtained while the cycle and exergy efficiencies are 37.7% and 41%, respectively. Higher efficiency can be obtained by controlling the compressors operational range and rated power. Therefore, future work includes experimental work for results validation and optimization.

State of Charge Balancing Control Strategy for Wind Power Hybrid Energy Storage Based on Successive Variational Mode Decomposition and Multi-Fuzzy Control

To address the instability of wind power caused by the randomness and intermittency of wind generation, as well as the challenges in power compensation by hybrid energy storage systems (HESSs), this paper proposes a state of charge (SOC) balancing control strategy based on Successive Variational Mode Decomposition and multi-fuzzy control. First, a consensus algorithm is used to enable communication between energy storage units to obtain the global average SOC. Then, the Secretary Bird Optimization Algorithm (SBOA) is applied to optimize the Successive Variational Mode Decomposition (SVMD) and Variational Mode Decomposition (VMD) for the initial allocation of wind power, resulting in the smoothing power for hybrid energy storage and the grid integration power. Finally, considering the deviation between the current SOC of the storage units and the global average SOC, dynamic partitioning is used for multi-fuzzy control to adjust the initial power allocation, achieving SOC balancing control. Simulations of the control strategy were conducted using Matlab/Simulink, and the results indicate that the proposed approach effectively smooths wind power fluctuations, achieving stable grid integration power. It enables the SOC of the HESS to quickly align with the global average SOC, preventing the HESS from entering unhealthy SOC regions.

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

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.

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.

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.

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.

Research on the Cold Storage Characteristics of Ice Storage Photovoltaic Cold Storage

The ice-on-coil storage tank is one of the core devices in the latent heat cold storage system. The main objective of this study is to couple the solar photovoltaic cold storage with Cold Thermal Energy Storage technology. The internal ice-melting coil energy storage system used the water as a heat transfer fluid for adopting a day and night cold storage control strategy. The experiments were conducted for several days under the conditions of photovoltaic-driven cold storage with and without load for a continuous cold storage. The reasons for the occurrence of ice layers during ice accumulation and melting, as well as the operational economy of the system were analyzed. Moreover, the characteristics of the cold storage tank were summarized. Consequently, when the external ice thickness of the coil was within the range of 27 to 32mm, the ice storage rate reached 35.82% and achieved the optimal refrigeration efficiency in both the coil and the cold storage. The daily ice production in the cold storage tank decreased by an average of 22.06% during continuous operation with load compared to the unloaded operation. However, the daily refrigeration capacity increased by 45.774%. In addition, when cold thermal energy storage was coupled with solar photovoltaic technology, the refrigeration capacity decreased by 7.15% compared to using Cold Thermal Energy Storage technology alone, which resulting in an annual electricity cost saving of 30.20%.

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.

Thermal performance and energy flow analysis of a PV/T coupled ground source heat pump system

Ground source heat pump (GSHP) system in cold regions will lead to a decrease in soil source temperature over the years after a long period of operation, and if no timely measures are taken, the system performance will get worse and worse, and even face the risk of shut down. The PV/T (photovoltaic/thermal) is an integrated energy supply system that can both improve the efficiency of solar energy utilization and weaken the soil temperature imbalance. In this paper, the thermal performance and year-round energy flow of the system are analyzed by the simulation model, and the effects of different soil thermal storage control strategies on the thermal storage performance in the transition season are explored. The results show that the coefficient of performance of the heat pump unit can reach 3.99 and 3.96 in the heating and cooling periods. The soil temperature only increases by 0.09 °C and 0.11 °C compared with the initial temperature after five and ten years of long-term system operation, respectively. In addition, after a comprehensive comparison of the thermal storage performance of different control strategies in the transition season, this study found that the temperature difference control strategy was superior to the time control strategy. Ultimately, the annual energy supply of the simulation system produces an additional 391.8 kWh of electricity in addition to meeting the energy demand for cooling, heating and power supply of the building, which realizes the zero-energy operation of the building.

Lithium-ion battery-pumped storage control strategy for smoothing wind-photovoltaic power fluctuation

Abstract Wind, as well as photovoltaic (PV), is widely used. Like loads, its power cannot be predicted, which results in the grid having to bear the power imbalance between wind-PV and loads, and substantial power fluctuations are not tolerated. Hybrid energy storage systems (HESS) containing multiple storage methods are considered effective solutions. In this paper, pumped storage and lithium-ion battery storage are fully considered, as they are supposed to have excellent performance and are highly complementary. We categorize the power imbalance into low, medium, and high according to the magnitude of the power imbalance. When the power fluctuation is low, the battery dominates. In contrast, the pumped storage dominates when the power fluctuation is high. Most importantly, when the power fluctuation is medium, we utilize an optimized first-order low-pass filter to allocate the power between the pumped storage and the lithium-ion battery. We change the filtering time in real-time according to the battery’s state of charge (SOC) to reasonably allocate the power between the pumped storage and the lithium-ion battery and ensure the SOC fluctuates within a reasonable range. This paper confirms the feasibility of the proposed strategy, where the pumped storage power fluctuates very little, in contrast, the battery power fluctuates significantly, and the SOC is always within the set reasonable range. Most importantly, the strategy proposed in this paper is straightforward to implement, which is crucial for engineering applications.

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.

Research on a hybrid optical storage control strategy based on a DC virtual synchronous generator and MPC

There are many problems in optical storage systems, including fault ride-through and disturbance, inadequate DC bus voltage support, and high state variable overshoot. The main problem is caused by the slow dynamic reaction speed of the energy storage system based on traditional PI control to the DC voltage of the optical storage system. A hybrid optical storage system control optimization strategy based on a DC virtual synchronous machines and improved model predictive control (MPC) was proposed in the paper as a solution to the aforementioned issues. A strategy based on DC virtual synchronous generator can improve the damping braces and overshoot suppression of DC voltage fluctuation during the disruption process of the energy storage system in the optical storage system. The dynamic response speed of energy storage in optical storage systems may be further increased based on the improved MPC. The effectiveness and validity of the control strategy proposed in the paper were verified by the simulation examples.

Industrial processes and the smart grid: overcoming the variability of renewables by using built-in process storage and intelligent control strategies

Manufacturers are facing pressure to reduce electricity costs. Onsite renewable energy generation may be a solution, but its high capital cost and intermittent power generation limit its use. Grid-responsive smart manufacturing could effectively incorporate renewables in industrial processes. This study integrates grid-responsive smart manufacturing with renewables on an industrial plant scale and demonstrates both a favourable economic and environmental outcome. A user-friendly decision-aid model for energy management is provided to manufacturers. A case study shows how solar panels, industrial batteries, smart pumping strategies, and various combinations of those elements can save on electricity costs. Dynamic simulation results demonstrate that grid-responsive smart manufacturing can effectively lower peak demand. The economic results show that grid-responsive smart manufacturing and renewables synergistically optimise cost reductions. The solar coupled with smart pumping scenario shows annual cost savings of $755,200, accounting for 4.6% of the total electricity cost. Smart pumping alone saves $371,900 annually with a 0.7-year payback period, demonstrating how the manufacturing sector can utilise its own processes in load shifting. This study supports that incorporating grid-responsive smart manufacturing with renewables can effectively reduce electricity costs and emissions for industry. Abbreviations: e: Equivalent; GHG: Greenhouse gas; PBP: Payback period; PV: Photovoltaics; SP: Setpoint; VFD: Variable speed drives

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.