Control Of Storage System Research Articles

Control of Flywheel Energy Storage Systems in the Presence of Uncertainties

In this paper, an optimal nonlinear controller based on model predictive control (MPC) for a flywheel energy storage system is proposed in which the constraints on the system states and actuators are taken into account. In order to control the system in the presence of modeling uncertainties and under the influence of external disturbances, tube-based MPC is utilized as a robust controller. Simulation results demonstrate the merits of the proposed method in controlling the dc link voltage and the fly wheel speed.

Review on the optimal placement, sizing and control of an energy storage system in the distribution network

Abstract Energy storage system (ESS) has developed as an important element in enhancing the performance of the power system especially after the involvement of renewable energy based generation in the system. However, there are a few challenges to employ ESS in distribution network, one of which is to ensure the best location and capacity so as to take the full advantage of installing ESS in the grid. In this paper, an extensive literature review on optimal allocation and control of ESS is performed. Besides, different technologies and the benefits of the ESS are discussed. Some case studies of ESS application in different part of the world are also presented. Finally, this paper emphasizes the future improvement of ESS control and performance to solve more complicated problems originated from the participation of renewable energy generation in the power system.

Reduced Capacitance Battery Storage DC-Link Voltage Regulation and Dynamic Improvement Using a Feedforward Control Strategy

This paper proposes a feedback/feedforward control strategy to attenuate the dc-link voltage variations in a reduced-capacitor battery energy storage system. It also identifies the impact of dc-link voltage variations on a battery energy storage system's response dynamics and power capabilities. It shows that addition of a feedforward controller to the existing feedback controller improves the dc-link voltage regulation and consequently the response dynamics of the reduced-capacitor battery energy storage system. It formulates a power setpoint change as a disturbance to the battery energy storage control system. The battery energy storage system is analyzed using an averaged-value modeling technique. Small-signal analysis is then used to tune feedforward controller parameters. The performance of the proposed controller is evaluated via an electromagnetic transient software (PSCAD/EMTDC), and the findings are experimentally validated using a laboratory-sized test bench.

Optimal Power Flow Control of a Grid-Connected Hydrokinetic-Pumped Hydro Storage System for Residential Load Profile

Optimal Power Flow Control of a Grid-Connected Hydrokinetic-Pumped Hydro Storage System for Residential Load Profile

Electricity Price Forecasting for Operational Scheduling of Behind-the-Meter Storage Systems

Electricity price forecast plays a key role in strategic behavior of participants in competitive electricity markets. With the growth of behind-the-meter energy storage, price forecasting becomes important in energy management and control of such small-scale storage systems. In this paper, a forecasting strategy is proposed for real-time electricity markets using publicly available market data. The proposed strategy uses high-resolution data along with hourly data as inputs of two separate forecasting models with different forecast horizons. Moreover, an intra-hour rolling horizon framework is proposed to provide accurate updates on price predictions. The proposed forecasting strategy has the capability to detect price spikes and capture severe price variations. The real data from Ontario's electricity market is used to evaluate the performance of the proposed forecasting strategy from the statistical point of view. The generated price forecasts are also applied to an optimization platform for operation scheduling of a battery energy storage system within a grid-connected micro-grid in Ontario to show the value of the proposed strategy from an economic perspective.

Intelligent control of household Li-ion battery storage systems

The increase in electricity prices along with a decrease in the price of storage systems has led to a rapid expansion of the PV-battery home storage system market. In order to be economically viable PV-storage systems must fulfil certain performance criteria, and the system control strategy has a large impact on the overall system performance.At KIT the performance of 20 commercially available PV-battery systems has been evaluated based on several criteria, one of these is intelligent control. A detailed study of the relationship between battery ageing and control strategy of 6 of these systems with NMC-based cells is part of the evaluation. It is shown that an intelligent control strategy can prevent calendar ageing. How large the effect is obviously depends on the dimensioning of the system and the sensitivity of capacity fade at different SOC levels. It is observed that a difference in battery lifetime caused by calendar ageing of up to 1.5 years is possible.In order to complement these results it is interesting to also consider the effects of intelligent control strategies (or the lack thereof) on the PV power fed into the grid. The feed-in of PV power to the grid is often regulated by law, and if the battery is fully charged too early in the day the system operator is forced to throttle the PV-system during the midday peak. An intelligent charging regime with accurate load and generation forecasts can prevent this, but could also lead to a reduction in self-sufficiency if the prediction is incorrect. It is shown that between 62 kWh and 104 kWh per year are lost due to the reason that most storage systems don’t possess a charging strategy to prevent throttling of the PV-generator.Since the effects of battery ageing and unwanted PV throttling are not independent it is useful to evaluate them in parallel and in combination with results on battery and system efficiency. The goal is to determine the economic impact of intelligent control and the resulting interplay between each of these factors.

Multi-Timescale Model Predictive Control of Battery Energy Storage System Using Conic Relaxation in Smart Distribution Grids

This paper proposes a multi-timescale volt/var optimization for the optimal dispatch of battery energy storage system in smart distribution grids. It aims to coordinate the substation on-load tap changer operation on slow-timescale (hourly basis) with the photovoltaic inverters and battery storage operations on fast-timescale (15 min basis). This coordination is achieved by using two-stage stochastic programming and implemented via model predictive control. The power loss and energy purchase cost are reduced while maintaining voltages within limits. The forecasting uncertainties are modeled by generating a large number of random scenarios and then subsequently reducing scenario numbers to establish a tradeoff between computational burden and accuracy of the solution. The mixed-integer second-order cone program (MISOCP) is formulated with reduced scenarios, which achieves global optimum. Simulation results demonstrate the effectiveness of proposed MISOCP model in keeping the voltages within limits under forecasting uncertainties.

Novel Economic Analysis to Design the Energy Storage Control System of a Remote Islanded Microgrid

This paper presents a novel power flow control strategy, combined with an economic analysis, for an energy management system (EMS) involving a hybrid energy storage. The EMS operates a remote microgrid and directs the power flow to either batteries or supercapacitors to increase the life of the batteries. This paper demonstrates how the use of supercapacitors increases the lifetime of the batteries and ultimately how it affects the economics of the system. The proposed EMS controller also compensates for the 120-Hz ripple on the dc bus. Modeling, simulations, and experimental verification are presented together with the procedure to perform the assessment of the battery lifetime, according to the tuning parameters of the controller.

A Simple Multimode Hybrid Energy Storage System and factional order control strategy

In order to overcome shortcomings of battery as a single energy source for electric vehicles and improve performance of electric vehicles, a simple multimode hybrid energy storage system (HESS) with battery and supercapacitor (SC) is proposed in this paper. The proposed simple multimode HESS can achieve boost mode when energy flows from power sources to motor inverter to supply power and buck mode when the energy flows from the motor inverter to the SC to recover power. The flexible power management can be achieved with the simple multimode HESS. Meanwhile, a small number of switches and a simple structure is helpful to design control strategy. In addition, taking into account the fractional characteristics of the HESS circuit, a fractional model of the HESS operation mode is established, and a novel fractional sliding mode control strategy is proposed based on the above model. Simulations are presented to verify the effectiveness of the proposed simple multimode HESS. Results show that the fractional order control strategy has better dynamic performance when compared with integer-order control strategy under the condition of system startup and parameters changes.

Advanced control strategy for an energy storage system in a grid‐connected microgrid with renewable energy generation

The operating cost of the consumer can be reduced in an electricity market-based environment by shifting consumption to a lower price period. This study presents the design of an advanced control strategy to be embedded in a grid-connected microgrid with renewable and energy storage capability. The objectives of the control strategy are to control the charging and discharging rates of the energy storage system to reduce the end-user operating cost through arbitrage operation of the energy storage system and to reduce the power exchange between the main and microgrid. Instead of using a forecasting-based approach, the proposed methodology takes the difference between the available renewable generation and load, state-of-charge of energy storage system and electricity market price to determine the charging and discharging rates of the energy storage system in a rolling horizon. The proposed control strategy is compared with a self-adaptive energy storage system controller and mixed-integer linear programming with the same objectives. Empirical evidence shows that the proposed controller can achieve a lower operating cost and reduce the power exchange between the main and microgrid.

Discharge performance of blended salt in matrix materials for low enthalpy thermochemical storage

A novel study is undertaken on low cost thermochemical storage which utilizes temperatures which are compatible with low grade renewable energy capture. The discharge performance of thermochemical storage matrix materials is assessed using a custom developed experimental apparatus which provides a means of comparing materials under scaled reactor conditions. The basic performance of three salts (CaCl2, LiNO3 and MgSO4) was investigated and their subsequent performance using layering and blending techniques established that the performance could be increased by up to 24% through the correct choice of mixing technique. Layering the CaCl2 on the LiNO3 provided the most efficient thermal release strategy and yielded a thermal storage density of 0.2 GJ/m3. The research also uniquely highlights the important finding that incorrect mixing of the materials can lead to a significant reduction in efficiency with freely mixed CaCl2 and LiNO3 possessing a storage capacity of less than 0.01 GJ/m3 as a result of chemical interactions between the deliquesced materials in close proximity. The paper has impact for the design and control of thermochemical storage systems as it clearly identifies how performance can be improved or degraded by the choice and the structuring of the materials.

Constant-power management algorithms of a hybrid wind energy system

As a source of renewable energy, wind is known for the uneven amounts of power it yields owing to its naturally varying speed and the technical difficulties attendant upon wind turbine (WT)/permanent magnet synchronous generator (PMSG) and energy storage system (ESS) control. This is a serious problem which necessitates tackling if WT energy is to be relied upon producing a constant power. To solve these issues, the present paper develops and assesses a control system that is aimed to ensure the regular feeding of a given power grid with a steady energy flow. It investigates both components of the hybrid wind energy system (HWES), viz., the WT/PMSG ensemble constituting the principal element of wind energy harnessing and the ESS composed of batteries and supercapacitors. The control system suggested here consists of two supervision algorithms (basic/modified) developed according to the constraints of the different elements of HWES. While the first algorithm deals with the state of charge of the storage system, the second takes account the wind speed. The hybrid system is developed and simulated using MATLAB/Simulink. Satisfactory control results are obtained, which testify the efficiency of the basic/modified algorithm-based control system.

Hierarchical Control and Full-Range Dynamic Performance Optimization of the Supercapacitor Energy Storage System in Urban Railway

The installation of a stationary supercapacitor energy storage system in urban railway systems effectively improves the energy saving rate by means of recycling the train's regenerative braking energy. In this paper, a hierarchical control strategy, which consists of an energy management layer and a converter control layer, is proposed. In the energy management layer, the energy management state machine is introduced. In the converter control layer, based on the double closed-loop proportional-integral (PI) control strategy, a multiobjective optimization algorithm for the outer voltage loop is proposed, which optimizes the control parameters at each operating point, comprehensively considering undershoot suppression, rapidity, and antidisturbance performance of the system. The proposed control strategy is validated through simulation and laboratory experiment, and finally, applied in the Megawatt-level energy storage device of Beijing Batong Line.

Novel Distributed Optimal Control of Battery Energy Storage System in an Islanded Microgrid with Fast Frequency Recovery

Highly intermittent renewable energy sources pose new challenges to microgrid operation and control. Thus, many distributed control strategies have been proposed to solve this problem. However, for most previous studies, the system frequency fluctuation can be further controlled on the basis of the optimal control strategy. This paper proposes a novel distributed optimal control strategy of a battery energy storage system in an islanded microgrid to provide desired optimal control performance and fast frequency recovery. The proposed control strategy is implemented through a multi-agent system based on consensus algorithm, which only requires information collected through a local communication network. Furthermore, the measurement of supply–demand mismatch is replaced by the control signal obtained from a supplementary controller with the improved linear active disturbance rejection control algorithm. The stability of microgrid frequency can be greatly enhanced through this improvement. Finally, the validity of proposed method is demonstrated by various case studies which are given in this paper.

Performance Guaranteed Control of Flywheel Energy Storage System for Pulsed Power Load Accommodation

Pulsed power load (PPL) consumes a huge amount of energy within a very short period of time. Directly connecting a PPL to a shipboard power system (SPS) will cause large disturbance even instability during PPL deployment. As an important category of energy storage system (ESS), the flywheel ESS (FESS) is an ideal source for PPL accommodation. By powering the PPL separately with a sufficiently charged FESS, the negative impacts of PPL on SPS can be avoided. The paper presents an adaptive output-constrained control design that can realize fast charging of the FESS and simultaneously minimize the disturbance to system frequency. Major benefit of the algorithm is that transient response can be guaranteed to stay within user-defined, time-varying bounds. This property makes the algorithm different from typical adaptive control algorithms and very appealing for high-performance applications. By applying the standard Lyapunov synthesis, all closed-loop signals are proved to be bounded. Finally, the proposed control design is tested through simulations using SPS models with different details. Simulation results demonstrate the effectiveness of the proposed control design.

Fuzzy Logic Control of a Battery Energy Storage System for Stability Improvement in an Islanded Microgrid

In this study, the active and reactive power control of a battery energy storage system (BESS) using fuzzy logic control to maintain the voltage and frequency stability of the islanded Mae Sariang microgrid is presented. The main scope of the presented study is to cogitate the effectiveness of the BESS controller in view of fluctuations of frequency/voltage subjected to a disturbance occurring in the islanded microgrid. In the Mae Sariang microgrid system, the electricity is produced from two renewable energy resources (RESs), i.e., hydro and solar PV. The use of these clean energy sources has become a main problem, envisaging the output power uncertainties from RESs. Further, such power uncertainty raises power quality problems and leads to power failure. To overcome such problems, the proposed fuzzy logic control (FLC) approach is applied for the BESS controller to improve the stability of the islanded Mae Sariang microgrid. The proposed FLC is intended to provide the BESS with well-established attributes of dynamical response to disturbance, which is analyzed by a predictive model. The proposed FLC has been investigated and compared with the robust control method, which is analyzed by a mathematical model using the system identification technique. The modeling of the microgrid system with BESS is implemented and verified on the DIgSILENT PowerFactory software. The simulation result illustrates that both of the control approaches allow the dynamic stability of the microgrid and the maintenance of frequency and voltage within acceptable ranges. However, the proposed BESS fuzzy logic control is less prone to uncertainty than the BESS robust control. Furthermore, in the proposed BESS fuzzy logic control, the microgrid frequency and voltage rapidly return to their normal steady-state condition and the size of the BESS is smaller than the BESS robust control.

A Battery Energy Storage System Control Technique with Ramp Rate and C-Rate Parameter Consideration for AC Microgrid Applications

Active power control of a battery energy storage system (BESS) in an ac microgrid to solve an impact of increasing of renewable energy resources (RES) is presented. The variability of active power from these renewable energy resources affects the reliability of the power grid. A BESS is used to connect with an ac microgrid consisting of RES such solar cells to manage the rapid change in flow of active power, so the output active power from RES is regulated within the standard for connecting to the Thailand grid-connected code. Ramp rate effects and characteristics of a battery used in a BESS are considered in proposed control strategy to control the flow of active power. The micro energy management system (µEMS) for calculating the appropriate active power slope is also developed. Therefore, the frequency deviation in the microgrid is regulated by using a proposed both control technique and µEMS. The control of this method ensures that the frequency stability is within the standard range of ±1 Hz in a 50 Hz system. Simulation and experimental results of the proposed method are good agreement, and the active power of the BESS in an ac microgrid can be satisfactorily controlled.

Battery Energy Storage System Control for Intermittency Smoothing Using an Optimized Two-Stage Filter

A new method for the control of a battery energy storage system and its implementation on a 25 kW solar system to compensate solar power intermittency and improve distribution grid power quality is presented in this paper. The novelty of the proposed method is to provide a systematic way to optimize the size of the battery capacity for the desired level of solar power smoothing. This goal is achieved by designing a two-stage filter solution. The first stage is a fast response digital finite impulse response (FIR) filter that makes a trade-off between smoothing of the solar output and battery capacity. This paper proposes an optimal design of a minimum-length, low-group-delay FIR filter by employing convex optimization, discrete signal processing, and polynomial stabilization techniques. The new strategy proposed in this paper formulates the design of a length- $N$ low-group-delay FIR filter as a convex second-order cone programming, which guarantees that all the filter zeros are inside the unit circle (minimum-phase). A quasi-convex optimization problem is formulated to minimize the length of the low-group-delay FIR filter. The second-stage filter is designed to level the battery charging load. The effectiveness and performance of the proposed approach is demonstrated by simulation results and also over a real-case implementation.

Profit-Maximizing Planning and Control of Battery Energy Storage Systems for Primary Frequency Control

We consider a two-level profit-maximizing strategy, including planning and control, for battery energy storage system (BESS) owners that participate in the primary frequency control market. Specifically, the optimal BESS control minimizes the operating cost by keeping the state of charge (SoC) in an optimal range. Through rigorous analysis, we prove that the optimal BESS control is a “state-invariant” strategy in the sense that the optimal SoC range does not vary with the state of the system. As such, the optimal control strategy can be computed offline once and for all with very low complexity. Regarding the BESS planning, we prove that the minimum operating cost is a decreasing convex function of the BESS energy capacity. This leads to the optimal BESS sizing that strikes a balance between the capital investment and operating cost. This paper here provides a useful theoretical framework for understanding the planning and control strategies that maximize the economic benefits of BESSs in ancillary service markets.

Design, Control and Monitoring of an Offline Mobile Battery Energy Storage System for a Typical Malaysian Household Load Using PLC

Battery energy storage system (BESS) is used in many practical applications including uninterruptible power supplies (UPS), portable devices, electrical vehicles and renewable energy systems. To utilize BESS effectively, an efficient control operation is required. Various controllers have been introduced in the open literature. However, they are not considered the best fit due to their limitations. This includes their incapability of handling high-power rating BESS, low noise immunity, short life cycle and limited number of input and output interfaces. In this paper, the programmable logic controller (PLC) is used to control and monitor a 158.8 kWh offline BESS for a typical Malaysian household. TIA Portal V13 software by siemens is used to program the proposed PLC control. Human machine interface(HMI) system is used to monitor and simulate the control performance. The results show that the PLC approach provides an efficient and reliable control of the BESS in which a compact protection against the battery overcharging, under-discharging and overheating is achieved.