Multiple Energy Storage Systems Research Articles

Inertia Emulation Uncorrelated With Electromechanical Dynamics to Improve Frequency Transients Using Center of Inertia (COI) Frequency Signal

This paper proposes an inertia emulation method that uses the frequency of the center of inertia (COI) as the feedback signal, aiming to slow the frequency change rate and raise the frequency nadir during frequency-dropping events. An approximated model depicting the COI frequency dynamics is first introduced, which shows the COI frequency signal has low observabilities of electromechanical modes. Thus, this feature enables the proposed inertia emulation to react quickly to steep frequency changes without suffering any adverse impacts caused by electromechanical dynamics, such as excessively saturating the controlled objects. Moreover, the electromechanical dynamics associated with small-signal stability properties will not be interrupted by the proposed inertia emulation. In addition, a simple yet effective computing procedure is proposed to configure the critical parameters, as the inertia emulation is implemented with multiple flywheel-based energy storage systems. Simulation results obtained based on two large interconnected systems verify the effectiveness of the proposed inertia emulation in terms of improving the frequency transients as well as its limited correlation with the electromechanical dynamics of the system. The signal transmission latency's impacts on the proposed inertia emulation are also investigated and discussed.

Energy management and economic analysis of multiple energy storage systems in solar PV/PEMFC hybrid power systems

Energy management and economic analysis of multiple energy storage systems in solar PV/PEMFC hybrid power systems

FPGA-Based Real-Time Simulation for Multiple Energy Storage Systems

Combining the renewable energy system, the Energy Storage (ES) station can maintain stable power transfer between renewable energy systems and power grid. This paper works on real-time simulation for multiple energy storage systems under different operating modes. Then taking a large number of ES converters and power grid into account, a modified electromagnetic transient program (EMTP) algorithm is proposed which is fit for the field-programmable gate array (FPGA)-based real-time simulation. By compressing the steps of the traditional EMTP algorithm, the simulation can be completed only by updating the history current source in each simulation cycle. In the meantime, the system is decoupled and multiple subsystems are simulated independently. Furthermore, to fully utilize the high parallelism of FPGA, we design and build a CPU-FPGA-based real-time simulation platform to implement the ES station. Using the simulation platform, we build a model of ES station and connect to the grid through an inverter. The whole system is tested in a single FPGA under different scenarios.

Location-dependent distributed control of battery energy storage systems for fast frequency response

This paper proposes a distributed strategy to control multiple battery energy storage systems (BESS) delivering fast frequency response in low-inertial power systems with high penetration of renewable energy sources. A novel distributed control algorithm is designed to optimise the operation of an arbitrary number of BESS while incorporating frequency-related constraints to meet the service requirements of fast frequency response. The proposed algorithm uses a consensus-based alternating direction method of multipliers (ADMM) method to solve the formulated optimisation problem. Since the BESS contribution to the system frequency response depends on the BESS locations in the network, a location-dependent term is incorporated into the control strategy to account for the effect of BESS locations on the frequency response. Using a multi-agent system framework the proposed control strategy can be implemented in a distributed fashion to efficiently utilise and coordinate the flexibility of multiple storage systems. Simulation studies demonstrate the effectiveness of incorporating both a location term and frequency-related constraints into the control strategy to provide a cost-effective improved frequency response as well as the suitability of the proposed solution to coordinate a large and arbitrary number of BESS.

Distributed Control of Battery Energy Storage Systems for Improved Frequency Regulation

In this paper a distributed control strategy for coordinating multiple battery energy storage systems to support frequency regulation in power systems with high penetration of renewable generation is proposed. The approach is based on an online convex optimisation framework that considers both the operating costs of storage systems and the frequency regulation requirements. The proposed framework uses a dynamic regret based on the last available information up to the current point in time of renewable generation and demand, which are uncertainty sources. The approach provides more accurate control than the currently employed prediction-based algorithms and it can be implemented in a distributed manner using a multi-agent system framework that facilitates plug-and-play functionality. The effectiveness and scalability of the proposed strategy is assessed through several case studies.

Communication-Free Power Management Strategy for the Multiple DAB-Based Energy Storage System in Islanded DC Microgrid

Along with the development of the renewable energy, such as the photovoltaics and the wind turbine, the energy storage system (ESS) is becoming as a critical part for the renewable-based microgrids. In this article, dual-active-bridge (DAB) dc-dc converter with bidirectional power flowing ability, wide soft-switching range, and ultrafast dynamic characteristic is adopted for integrating multiple energy storage units (ESUs) for balancing the power flowing between the renewable energy and the loads in a islanded dc microgrids. For the multiple DAB-based ESS, a communication-free power management strategy is proposed in this article to maintain the dc-link voltage for the islanded dc microgrid, and high robustness of the dc-link voltage can be ensured when the output voltage of energy storage equipment, the load condition, and the power sharing performance of the ESS are changed. The proposed strategy also ensures seamless ESU plug-in or plug-out operations. Finally, the small-scale simulation model and experimental platform are both employed to verify the effectiveness of the proposed communication-free power management scheme.

Analysis of power flow control strategies in heterogeneous battery energy storage systems

• A method for the systematic analysis of several power flow control strategies in a heterogeneous battery energy storage system is provided. • A comparison of five power flow control strategies in heterogeneous battery energy storage systems based on two distinct application-oriented scenarios is carried out. • Power flow control strategies are assessed by two target indicators, namely performance and efficiency. • A simulation model is set up and components are validated with measurements. • Performance and efficiency can be enhanced by using the appropriate power flow control strategy with respect to the individual scenario. This paper provides a method for the systematic analysis of several power flow control strategies (PFCS) in a heterogeneous multiple battery energy storage system (BESS). Due to the difficulty of comparing different PFCS in different scenarios and system configurations, in total five static and dynamic PFCS are investigated in two distinct application-oriented scenarios and are assessed by two target indicators, namely performance and efficiency. A simulation model based on a heterogeneous multiple BESS with a hierarchical control scheme is set up, the components of the model are validated and a real test bench verifies the functionality of the PFCS. Simulations in MATLAB/Simulink are carried out to analyze the performance and the efficiency of the applied PFCS in an energy- and a load-related application scenario. This approach allows a systematic comparison of PFCS in consideration of varying system parameters and different scenarios. The results suggest that depending on the objective to be achieved and the applied application scenario, the choice of the right PFCS is crucial. Thus, this paper provides a workflow to analyze the selection of proper PFCS. Furthermore, heterogeneity plays a decisive role in analyzing different PFCS, since operating limits of the BESS become more significant.

Consensus based SoC trajectory tracking control design for economic-dispatched distributed battery energy storage system.

The state-of-charge (SoC) of an energy storage system (ESS) should be kept in a certain safe range for ensuring its state-of-health (SoH) as well as higher efficiency. This procedure maximizes the power capacity of the ESSs all the times. Furthermore, economic load dispatch (ELD) is implemented to allocate power among various ESSs, with the aim of fully meeting the load demand and reducing the total operating cost. In this research article, a distributed multi-agent consensus based control algorithm is proposed for multiple battery energy storage systems (BESSs), operating in a microgrid (MG), for fulfilling several objectives, including: SoC trajectories tracking control, economic load dispatch, active and reactive power sharing control, and voltage and frequency regulation (using the leader-follower consensus approach). The proposed algorithm considers the hierarchical control structure of the BESSs and the frequency/voltage droop controllers with limited information exchange among the BESSs. It embodies both self and communication time-delays, and achieves its objectives along with offering plug-and-play capability and robustness against communication link failure. Matlab/Simulink platform is used to test and validate the performance of the proposed algorithm under load disturbances through extensive simulations carried out on a modified IEEE 57-bus system. A detailed comparative analysis of the proposed distributed control strategy is carried out with the distributed PI-based conventional control strategy for demonstrating its superior performance.

Multiagent-Based Energy Trading Platform for Energy Storage Systems in Distribution Systems With Interconnected Microgrids

In this article, an agent-based transactive energy (TE) trading platform to integrate energy storage systems (ESSs) into the microgrids’ energy management system is proposed. Using this platform, two different types of energy storage market models are proposed to promote local-level (within the microgrid) and communal- or global-level ESSs’ participation in the intra- and intermicrogrid TE markets. Also, a reinforcement learning algorithm known as simulated-annealing-based $Q$ -learning is used to develop bidding strategies for ESSs to participate in the TE markets. Besides energy trading, the proposed system also accounts for the losses caused by energy transactions between ESSs and microgrids using a complex current-tracing-based loss allocation method. The overall efficacy of the proposed energy market management system is demonstrated using a modified IEEE 123-bus distribution system with multiple microgrids and ESSs. Based on simulation results, it is observed that the proposed model can effectively reinforce the balance between the supply and the demand in the microgrids using the mix of local and global ESSs.

Distributed Resilient Control for Energy Storage Systems in Cyber–Physical Microgrids

As a cyber-physical system (CPS), the security of microgrids (MGs) is threatened by unknown faults and cyberattacks. Most existing distributed control methods for MGs are proposed based on the assumption that secondary controllers of distributed generation units operate in normal conditions. However, the faults and attacks of the distributed control system could lead to a significant impact and consequently influence the security and stability of MGs. In this article, a distributed resilient control strategy for multiple energy storage systems (ESSs) in islanded MGs is proposed to deal with these hidden but lethal issues. By introducing an adaptive technique, a distributed resilient control method is proposed for frequency/voltage restoration, fair real power sharing, and state-of-charge balancing in MGs with multiple ESSs in abnormal condition. The stability of the proposed method is rigorously proved by Lyapunov methods. The proposed method is validated on test systems developed in OPAL-RT simulator under various cases.

Decentralized Cooperative Control of Multiple Energy Storage Systems in Urban Railway Based on Multiagent Deep Reinforcement Learning

Nowadays, the stationary energy storage systems (ESSs) are widely introduced to recover the regenerative braking energy in urban rail systems. And the multiple ESSs along the line, substations, traction, and braking trains in the traction power system make up a multienergy coupling system, whose energy efficiency is expected to be improved. With the aim of power flow optimization, a cooperative control strategy for multiple ESSs based on multiagent deep reinforcement learning is proposed in this article. Under the distributed control structure, the decision process of multiple ESS agents is formulated as a fully cooperative Markov game, in which each ESS makes independent decision and cooperates to improve the overall energy saving effect. And the value decomposition network, which decomposes the joint state-action value into value functions across agents, is adopted to stabilize the multiagent learning process. Three train operation scenarios are presented in simulation, and the power flow distributions are analyzed quantitatively to better evaluate the performance of the proposed cooperative strategy. A power hardware-in-the-loop (PHIL) experimental platform, which integrates the RT-LAB simulator and physical supercapacitor-based energy storage system (SCESS) is developed in this article to emulate the dc traction power system with multitrain operation. Based on the PHIL platform, the proposed cooperative control strategy is implemented experimentally. Both simulation and experimental results show that in comparison with genetic algorithm (GA), the proposed strategy optimizes the energy distribution between different SCESSs and trains, and improves the overall energy saving effect of the multi-SCESSs.

Novel Droop Control of Battery Energy Storage Systems Based on Battery Degradation Cost in Islanded DC Microgrids

This paper presents a new droop control method to reduce battery degradation costs in islanded direct current (DC) microgrids for multiple battery energy storage systems (BESSs). BESSs may have varying installation costs and battery cycle life characteristics depending on battery type, energy capacity, and maximum output power. These differences cause different battery degradation costs among BESSs despite exchanging the same amount of energy. To autonomously reduce the total battery degradation cost, an incremental cost (IC) of a BESS is used as a criterion for determining the state-of-charge level of BESSs and is calculated based on the battery cycle life curve containing the battery degradation information. By adopting an IC–voltage droop control, the BESSs can maintain an operating point of equal IC, an optimal point for cost minimization. Subsequently, small-signal stability analysis is performed using the state-space model of the proposed method. The case study validates that the proposed method can reduce the total battery degradation cost with a small-signal stable operation in islanded DC microgrids.

A Comprehensive Review of Hybrid Energy Storage Systems: Converter Topologies, Control Strategies and Future Prospects

The ever increasing trend of renewable energy sources (RES) into the power system has increased the uncertainty in the operation and control of power system. The vulnerability of RES towards the unforeseeable variation of meteorological conditions demands additional resources to support. In such instance, energy storage systems (ESS) are inevitable as they are one among the various resources to support RES penetration. However, ESS has limited ability to fulfil all the requirements of a certain application. So, hybridization of multiple ESS to form a composite ESS is a potential solution. While integrating these different ESS, their power sharing control plays a crucial role to exploit the complementary characteristics of each other. Therefore, this article attempts to bring the numerous control strategies proposed in the literature at one place. Various control techniques implemented for HESS are critically reviewed and the notable observations are tabulated for better insights. Furthermore, the control techniques are classified into broad categories and they are briefly discussed with their limitations. From the carried-out analysis, the challenges faced towards the implementation of HESS for standalone and grid connected microgrid systems are presented. Finally, the future directions are laid out for the researchers to carry out the research and implementation of HESS technologies. Overall, this article would serve as a thorough guide on various control techniques implemented for HESS including their features, limitations and real-time applications.

Distributed Resilient Finite-Time Secondary Control for Heterogeneous Battery Energy Storage Systems Under Denial-of-Service Attacks

This article addresses the problem of distributed resilient finite-time control of multiple heterogeneous battery energy storage systems (BESSs) in a microgrid subject to denial-of-service (DoS) attacks. Note that DoS attacks may block information transmission among BESSs by preventing the BESS from sending data, compromising the devices and jamming a communication network. A distributed secure control framework is presented, where an acknowledgment (ACK)-based attack detection strategy and a communication recovery mechanism are introduced to mitigate the impact of DoS attacks by repairing the paralyzed topology graphs caused by DoS attacks back into the initial connected graph. Under this framework, a distributed resilient finite-time secondary control scheme is proposed such that frequency regulation, active power sharing, and energy level balancing of BESSs can be achieved simultaneously in a finite time; meanwhile, operational constraints can be satisfied at any control transient time. Moreover, based on theoretical analysis, the impact of the duration time of DoS attacks on the convergence time of the control algorithm can be explicitly revealed. Finally, validity and effectiveness of the proposed control scheme are demonstrated by case studies on a modified IEEE 57-bus testing system.

Dual-Consensus-Based Distributed Frequency Control for Multiple Energy Storage Systems

Intermittent renewable energy sources are being increasingly integrated into modern power networks. This leads to severe frequency fluctuations in the networks. Energy storage systems can be used for frequency restoration due to their capability to provide in-time active power compensations. This paper examines the frequency control problem for power systems with multiple distributed battery energy storage systems (BESSs). A dual-consensus-based approach is presented for distributed frequency control. It consists of three main components: 1) tuning of the BESS control gain; 2) design of control signals as inputs to BESSs for proportional use of the preserved energy; and 3) estimation of BESS parameters for control implementation. A static parameter and a time-varying parameter are defined, and their average values are estimated through static average consensus (SAC) and dynamic average consensus (DAC) algorithms, respectively. Case studies are conducted to demonstrate our dual-consensus control approach.

Minimizing Cost of Smart Grid Operations by Scheduling Mobile Energy Storage Systems

Energy storage systems (ESS) are effective solutions to reduce the cost of smart grid operations due to their ability to store and supply electricity on demand. Traditionally, ESS have been used to implement a plethora of cost reduction techniques for smart grid operations such as temporal supply-demand shifting, frequency regulation, voltage regulation etc. However, the stationary nature of ESS limits their flexibility, potentially leading to low utilization and risk being a stranded asset. In this work, we explore the use of Mobile ESS in implementing such cost reduction techniques in a grid consisting of multiple microgrids. We develop an algorithmic framework to assign multiple Mobile ESS to various microgrids of the smart grid across several days. Our framework attempts to maximize the cost reduction achieved due to Mobile ESS assignment minus the routing cost. We show that our algorithm is a polynomial time $1/e-$1/e-approximation for the NP-Hard problem of optimal assignment of MESS.

Smart coordination schemes for multiple battery energy storage systems for support in distribution networks with high penetration of photovoltaics

The use of battery energy storage system (BESS) is one of the methods employed in solving the major challenge of overvoltage, experienced on distribution networks with high penetration of photovoltaics (PV). The overvoltage problem limits the penetration levels of PV into the distribution network, and the benefits that could be gained. This study presents three loosely-related schemes for the coordination of multiple BESSs in such networks. Through the efficient selection, coordination and timing of charge and discharge operations of the BESS, the scheme maintains bus voltages within statutory ranges during periods of high PV power generation and high network load demand. Network segmentation was used in two of the schemes to encourage more even utilisation of the BESS in order to maximise the economic benefits of the BESS. The algorithms for the schemes were implemented and demonstrated on two different distribution networks. Simulation results showed that the schemes met the objectives of mitigating overvoltage and more even cycling of the BESSs during their operating lifetimes.

Passive hybrid energy storage system based on lithium-ion capacitor for an electric motorcycle

Abstract This paper presents the multiple energy storage system usability for an electric motorcycle focused on passive hybrid topology. The studied hybridization is based on a passive parallel topology connecting lithium manganese nickel 18650-type cells and lithium-ion-capacitor to supply the motorcycle powertrain. The passive hybrid energy storage system design is fully addressed based on an extension of Ns/Np battery pack sizing maps to passive hybrid topology using lithium-ion-batteries and lithium-ion-capacitors. The improved sizing method is able to size simultaneously an integrated energy storage system made from two different cells chemistries. The proposed design optimizes the common voltage range and distribute the current according to the intrinsic cells characteristics. Relationship between dimensions are established to plot as a traditional two-dimensional map a four-dimension sizing problem. The benefits and performance improvements obtained by the Ns/Np hybrid design for a case study involving an electric motorcycle are presented and discussed based on root-mean-square and mean value of the current cell, standard deviation of the C-rate and instantaneous current peaks variation coefficient. The proposed configuration could reduce the stress on the battery cells by 42% on standard deviation and 36% on variation coefficient with a decrease of 9% in average current while reducing the root-mean square value by 15% on a specific motorbike race simulation.

Control of a population of battery energy storage systems for frequency response

The control of multiple battery energy storage systems (BESSs) to provide frequency response will be a challenge in future smart grids. This paper proposes a hierarchical control of BESSs with two decision layers: the aggregator layer and the BESS control layer. The aggregator layer receives the states of charge (SoC) of BESSs and sends a command signal to enable/disable the BESS control layer. The BESS controller was developed to enable the BESSs to respond from the highest to lowest SoC when the frequency drops, and from lowest to highest when it rises. Hence, the BESS’s response is prioritised to reduce the impact on the power system and end-users during the service. The BESS controller works independently when a failure occurs in the communication with the aggregator. The dynamic behaviour of the population of the controllable BESSs was modelled based on a Markov chain. The model demonstrates the value of aggregation of BESSs for providing frequency response and evaluates the effective capacity of the service. The model was demonstrated on the 14-machine South-East Australian power system with a 14.5 GW load. 254 MW of responsive capacity of aggregated batteries was effective in reducing the system frequency deviation below 0.2 Hz following a sequence of disturbances.

Distributed State-of-Charge Balance Control With Event-Triggered Signal Transmissions for Multiple Energy Storage Systems in Smart Grid

Modern power grid is increasingly integrated with battery energy storage systems (BESSs). This paper deals with the problem of state-of-charge (SoC) balance control for multiple distributed BESSs in smart grid. The BESSs are expected to work cooperatively to not only fulfil the overall power requirement but also meet the constraints of the same relative SoC variation rate. To achieve this objective, a distributed SoC balance control approach is presented with event-triggered signal transmissions. It is designed with the dynamic average consensus (DAC) mechanism for parameter estimations. The DAC enables distributed control of each BESS through communicating with its neighboring BESSs. Different from traditional periodic signal transmission, the event-triggered signal transmission embedded in our approach allows each BESS to transmit signal to its neighboring BESSs only when needed, thus reducing the communication traffic. Theoretical lower bounds are established for consecutive interevent intervals such that the Zeno behavior is excluded. Case studies are conducted to demonstrate the effectiveness of the presented approach.