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Although smart home has received wide attention in recent years, numerous scholars focus more on energy optimization strategy than energy dispatch hardware device (named energy router). Meanwhile, this energy router should have several features, i.e., high renewable energy utilization, energy multi-port and low volume. Thus, this paper designs a nine-port energy router regarding smart home and proposes a multimode hierarchical management strategy for this energy router. First, for the multi-port demand of wind, solar, storage and utilization, this paper presents a nine-port energy router to improve the renewable energy consumption and power supply flexibility. In addition, to reduce the volume of the energy router, a non-isolated AC/DC hybrid topology is constructed through embedding the integrated power electronic converters, which achieves the miniaturization of the energy router. In order to improve the renewable energy utilization rate, the decentralized module control is proposed for the components of energy router to provide the voltage and frequency support for system, and realizes the power sharing of distributed generations (DGs). Furthermore, the power exchange control with three-mode switching is proposed to guarantee the global energy flow balance under complex conditions. Eventually, the feasibility of the energy router is verified by the simulation and experiments. [ABSTRACT FROM AUTHOR]

State-of-charge (SoC) imbalance and bus voltage deviation are two of the main problems in autonomous dc microgrids. Based on this concern, this paper presents an improved dual-quadrant SoC weighted control strategy and a distributed optimization control method to achieve SoC balance, ensuring accurate power-sharing and bus voltage recovery. Firstly, this paper couples the injected/released power with the current SoC and observed average SoC value to weight the droop coefficient, which is based on the charge/discharge mode for the energy storage system. Then a secondary controller is designed based on distributed optimal control to eliminate the bus voltage deviation caused by the line impedance difference. The proposed optimal control method optimizes the average bus voltage to the nominal value and achieve accurate power-sharing by constructing the correlated variables and voltage independent intermediate variables exchanged among bulk energy storage units (ESUs). Since the voltage observer cannot accurately observe the true average bus voltage under the communication delay, the proposed distributed optimal control method without the voltage observer can ensure that the average bus voltage is optimized to the nominal value, thus improving the robustness of the control system. Finally, the correctness and effectiveness of the proposed method are verified in Simulink/MATLAB. [ABSTRACT FROM AUTHOR]

Virtual synchronous generator (VSG)-based control approaches for AC machine drivers have attracted much attention in recent years. The contradiction between the strong motor loading capacity and the small DC voltage fluctuation is disregarded in previous studies. A larger virtual inertia is required to raise the torque gain and drive the motor with heavier loads, thus resulting in greater DC voltage variations. A systematic method is proposed for the optimal design of the virtual inertia for VSG-based motor starting systems to achieve the maximal motor loading capacity and the low DC voltage fluctuation in this paper. Firstly, the relationship between the virtual inertia and the loading capacity is revealed on the basis of the closed-loop analysis. Considering the DC voltage variation, the constraint on the maximal value of the virtual inertia is proposed from the energy-balance perspective despite the unknown contribution of the DC capacitors to the virtual inertia. To fully exploit the energy storage capacity of the DC capacitors and raise the upper limit of the virtual inertia under the same permitted DC voltage variation, a modified DC voltage reference is introduced. Extensive simulation and experimental results are presented to validate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Soft open points (SOPs) are power electronic devices which can replace conventional normally open points in distribution networks. SOPs enable full control of active power flow between the interconnected feeders and can inject reactive power at each node to which they are connected. SOPs integrated with energy storage (ES) have been recently proposed to realize both spatial and temporal flexibility in active distribution networks. The flexibility provided by integrated ES-SOP devices will allow network operators to run their networks closer to their limits, but only if there is appropriate management of the uncertainty arising from demand and renewable generation. The only existing model of an ES-SOP uses nonconvex nonlinear equations, neglects uncertainty, and represents converter losses in an oversimplistic manner. This paper presents a robust mixed-integer convex model for the optimal scheduling of integrated ES-SOPs to ensure a zero probability of constraint violation. Losses of the subsystems comprising the ES-SOP are modeled using a proposed binary-polynomial model, enabling efficient scheduling of the energization state of subsystems to reduce no-load losses. The ES-SOP is considered in this paper to be owned by the network operator to: 1) manage power flow constraints, 2) minimize cost of losses, and 3) maximize arbitrage profit. [ABSTRACT FROM AUTHOR]

This paper proposes a direct damping feedback control method against power system oscillations under small or large disturbances. For a targeted oscillation mode, this control method continuously minimizes the difference between the real-time estimated damping ratio and a desired value by changing power outputs of selected inverter-based resources. The method adopts a proportional-integral controller whose parameters are tuned using a nonlinear single-input-single-output model on damping estimation and control with a single-oscillator equivalent regarding the targeted power system mode. Also, optimization of these controller parameters considers both robustness and time performance in damping control. The paper also proposes utilizing a “zero-th order” parametric resonance phenomenon to simplify the controller design. Tests on a small power system and a 140-bus 48-machine Northeast Power Coordinating Council system validate the effectiveness of the proposed damping controller utilizing battery-based energy storage systems. [ABSTRACT FROM AUTHOR]

The dual-active bridge (DAB) topology is commonly preferred in bidirectional applications due to several attractive features, including auto-adjust of power flow, galvanic insulation, wide voltage gain, and zero voltage switching (ZVS) capability over some power ranges. However, the efficiency of the converter drops at light loads because the ZVS range is directly dependent on the circulating current. Assuming that the processed power is variable, the DAB converter's design must find a compromise between extending ZVS ranges and reducing the reactive power processing to ensure higher efficiency. Aiming this compromise, many papers propose hybrid approaches in which the modulation strategy is selected according to the processed power. However, this is not a simple solution because it demands multivariable control and offline optimizations. This paper proposes a modulation strategy to ensure ZVS and reduce the circulating current for the DAB converters. While the usual phase-shift modulation provides ZVS operation in a range of 40% to 100% of rated power, the proposed asymmetrical pulse-width modulation can obtain ZVS operation in a range of 2% to 100% of rated power. Experimental results demonstrated that the proposed strategy improves the converter efficiency for all power ranges, especially at light loads. [ABSTRACT FROM AUTHOR]

Battery energy storage system (BESS) plays an important role in solving problems in which the intermittency has to be considered while operating distribution network (DN) penetrated with renewable energy. Aiming at this problem, this paper proposes a global centralized dispatch model that applies BESS technology to DN with renewable energy source (RES). The method proposed in this paper aims to minimize the power purchase cost considering network active loss cost as well as voltage deviation penalty cost. Later, second-order cone programming (SOCP) method as well as big M method are applied to make the problem tractable. Last, the method illustrated in this paper is applied and validated on a modified IEEE 33-bus benchmark system to verify the effectiveness of the proposed scheduling model. [ABSTRACT FROM AUTHOR]

The increasing penetration of distributed energy resources (DERs) may cause security and economic risks in the distributed network. In this paper, the optimal allocation of battery energy storage systems (BESS) is proposed to mitigate the risks in the radial distribution network by considering future uncertainties, such as the uncertainties of load and renewable energy. The interacting levels of the proposed hierarchical planning framework are (1) determination of the BESS location based on the calculated adjusted voltage violation risk; (2) obtaining the capacity of the BESS by solving an optimization problem assisted by supervised learning. In the previous works, the steady-state is evaluated by the DistFlow equations in the distribution system. In our paper, we have utilized a data-driven method to calculate the power flow and the voltage, thus leading to higher accuracy. Through case studies, the effectiveness of the proposed method is verified. Furthermore, the data-driven assisted optimization model reduces the computational burden to a large extent because massive state variables, the power flow constraints and voltage constraints are substituted. [ABSTRACT FROM AUTHOR]

This paper presents a simple pulse width modulation algorithm for control of an ultracapacitor based energy storage system used for source and load support applications. As opposed to dual loop control philosophy that is widely used for backup applications, this paper presents a simple single loop current control that is only useful for controlling the ultracapacitor based DC/DC converters used in source and load support applications. The proposed PWM blocking method necessitates the DC/DC converter to operate in five states and takes into consideration the essential operational limits associated with the ultracapacitors. The performance of the proposed algorithm is verified experimentally using a 24 V laboratory prototype setup. Further, the shortcomings of dual loop control when applied to source and load support applications are demonstrated. [ABSTRACT FROM AUTHOR]

A decentralized improved I-V droop control strategy for battery-supercapacitor (SC) hybrid energy storage system (HESS) is proposed in this paper. The dynamic power sharing between battery and SC is realized by replacing the constant droop coefficient in I-V droop control with virtual impedance, i.e. virtual inductance for battery side converter and virtual resistance for SC side converter. Besides, by injecting the virtual inductance in the battery side converter, negligible DC bus voltage deviation can be achieved without extra voltage compensator. Moreover, the state-of-charge (SoC) recovery is also considered to extend the service life of the HESS. Furthermore, in the proposed regulated power system, since the power allocation, DC bus stability and SoC recovery are decoupled from each other, the design of control parameters is simple. The corresponding design guideline is demonstrated in this paper. Finally, to verify the accuracy and feasibility of the theoretical analyses, hardware in the loop simulations have been conducted. [ABSTRACT FROM AUTHOR]

This paper presents a computation-efficient stochastic dynamic programming algorithm for solving energy storage price arbitrage considering variable charge and discharge efficiencies. We formulate the price arbitrage problem using stochastic dynamic programming and model real-time prices as a Markov process. Then we propose an analytical solution algorithm using a piecewise linear approximation of the value-to-go function. Our solution algorithm achieves extreme computation performance and solves the proposed arbitrage problem for one operating day in less than one second on a personal computer. We demonstrate our approach using historical price data from four price zones in New York Independent System Operator, with case studies comparing the performance of different stochastic models and storage settings. Our results show that the proposed method captures 50% to 90% of arbitrage profit compared to perfect price forecasts. In particular, our method captures more than 80% of arbitrage profit in three out of the four price zones when considering batteries with more than two-hour duration and realistic degradation cost. [ABSTRACT FROM AUTHOR]

In many power systems, the increased penetration of inverter-based renewable generation will cause a decrease in kinetic energy storage, leading to higher frequency excursions after a power disturbance. This is the case of the future Nordic Power System (NPS). The look-ahead study reported in this paper shows that the chosen units participating in Frequency Containment Reserves (FCR) cannot keep the frequency above the prescribed threshold following the outage of the largest plant. This analysis relies on a detailed model of the Northern European grid. The latter is compared to the classical single-mass equivalent, and the impact of voltage-dependent loads is assessed in some detail. Next, the paper focuses on emergency power control of the HVDC links that connect the NPS to the rest of the European grid, which can supplement or even replace part of the FCR. The proper tuning of that control is discussed. Finally, the analysis is extended to the HVDC links connecting the future North Sea Wind Power Hub under two configurations, namely low and zero inertia. The impact of outages in the latter sub-system is also assessed. The material to simulate the system with industrial software is made publicly available. [ABSTRACT FROM AUTHOR]

Due to prevailing uncertainties of renewable energy and time coupling constraints of energy storage (ES), robustness and nonanticipativity of scheduling results directly influence the operational feasibility of regional microgrids. To this end, this paper proposes a new multistage generation scheduling method for regional microgrids with renewables and ES, which can simultaneously guarantee the robustness and nonanticipativity of scheduling solutions. First, a feasibility proposition is established based on the backward derivation thoughts, which addresses the feasibility requirements of microgrids against uncertainties of renewables and loads. Second, based on this feasibility proposition, a scenario-based multistage robust scheduling model with robust and nonanticipative constraints is presented, in which the uncertainties of transaction prices, renewables, and loads are simulated via representative scenarios to guarantee the economic performance of scheduling results. Third, with on/off decisions of thermal units as well as safe ranges of ES energy levels and thermal outputs derived from the scheduling model, a real-time rolling economic dispatch model is established to determine active and reactive power as well as nodal phase voltage values. Numerical tests implemented on a real regional microgrid illustrate efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, we consider a community energy storage (CES) system that is shared by various electricity consumers who want to charge and discharge the CES throughout a given time span. We study the problem facing the manager of such a CES who must schedule the charging, discharging, and capacity reservations for numerous users. Moreover, we consider the case where requests to charge/discharge the CES arrive in an online fashion and the CES manager must immediately allocate charging power and energy capacity to fulfill the request or reject the request altogether. The objective of the CES manager is to maximize the total value gained by all of the users of the CES while accounting for the operational constraints of the CES. We discuss an algorithm titled COmmunityEnergyScheduling that acts as a pricing mechanism based on online primal-dual optimization as a solution to the CES manager’s problem. The online algorithm estimates the dual variables (prices) in real-time to allow for requests to be allocated or rejected immediately as they arrive. Furthermore, the proposed method promotes charging and discharging cancellations to reduce the CES’s usage at popular times and is able to handle the inherent stochastic nature of the requests to charge/discharge stemming from randomness in users’ net load patterns and weather uncertainties. Additionally, we are able to show that the algorithm is able to handle any adversarially chosen request sequence and will always yield total welfare within a factor of $\frac {1}{\alpha }$ of the offline optimal welfare. [ABSTRACT FROM AUTHOR]

The shared energy storage service provided by independent energy storage operators (IESO) has a wide range of application prospects, but when faced with the interrelated and uncertain output of renewable energy on the supply side, how to size for energy storage capacity is a highly challenging problem. To this end, this paper firstly proposes a hybrid shared energy storage framework, in which the private energy storage of power suppliers and IESO jointly provide shared energy storage services for users. To generate low-dimensional scenarios that consider the correlation between the multiple uncertainties of wind and solar generation, combining the Kernel function estimation and the Gaussian mixture model forms the Bayesian estimation to fit the historical generation curve precisely. The uncertain output of same generation resources is coupled based on Kullback-Leibler divergence. The Frank-Copula function is used to couple the uncertain output between diverse generation resources. The energy storage planning problem is formulated as a Bayesian distributionally robust optimization model. The related algorithms are designed to solve the model. The effectiveness of the proposed uncertainties coupling and capacity sizing method is validated through a case study in the IEEE 118-bus system. [ABSTRACT FROM AUTHOR]

This paper proposes a combined active and reactive power flow control strategy for the flexible traction substation (FTSS). It fully uses the active and reactive power flexibility of FTSS to maximize regenerative braking energy (RBE) and photovoltaic (PV) energy utilization and improve power quality comprehensively. First, the active power flow optimization layer coordinates the active power outputs of the back-to-back converter (BTBC) and energy storage system to maximize the utilization of the available RBE and PV energy and balance the active power outputs of the traction transformer. Meanwhile, it controls PV output to limit the surplus energy injected into the utility grid further. Then, the model predictive control (MPC)-based reactive power flow optimization layer employs the spare capacity of BTBC to optimize the reactive power flow to improve the multiple power quality issues further, including negative sequence current (NSC), effective power factor (EPF), and traction network voltage fluctuations. To establish the MPC optimization problem, the NSC, EPF, and traction network incoming voltage sensitivity matrices with respect to the reactive power outputs of the traction transformer are first derived. Finally, the hardware-in-the-loop experiments, based on the data measurement from a high-speed railway traction substation, verify the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

The grid-connected inverter is a key device in the renewable energy power generation system and large-scale energy storage system, which the operational stability and reliability are the basis for the efficient and safe application of electrical energy. A real-time fault diagnosis method of a three-phase for grid-connected application combining a mixed logic dynamic (MLD) model and finitecontrol set model predictive control (FCS-MPC) is proposed. This paper not only realizes the open circuit fault diagnosis and location of the switching devices in the main power circuit, but also discusses the threshold issues and post-fault operations. The advantage of the proposed method is that it directly uses the control data and measurement signals of the controller without extra sensors and calculation, which will shorter the fault diagnosis time and occupy less calculation resource of the main processor. Simulation results illustrate the quickness of the fault identification and accurate position with robustness to the interference of the diagnosis method. Finally, the effectiveness of the diagnosis method was verified by a 1500 W experimental prototype in a laboratory. [ABSTRACT FROM AUTHOR]

Penetration of renewable energy resources (RERs) in the power grid continues to increase as we strive toward a greener environment for the future. While they have many advantages, most RERs possess little or no rotational kinetic energy, thereby threatening the frequency stability of future power grids. Energy storage systems (ESSs) can be used to mitigate this problem, as they are capable of providing virtual inertia to the system. This paper proposes a novel analytical approach for sizing ESSs to provide inertial support to the grid and maintain frequency stability in presence of RERs. This method analytically estimates the total inertia of the system using probability distributions of the outage states of conventional generators and RERs. RERs are modeled as multi-state units, considering the variability of their output power due to changes in weather conditions and also the forced outages of their equipment. The ESS is utilized to provide virtual inertia to the grid in the form of active power once the estimated system inertia falls below the minimum required during a disturbance. The efficacy of the proposed approach is tested on the IEEE 39 bus system and the results obtained by the analytical approach are validated using Monte Carlo simulation. [ABSTRACT FROM AUTHOR]

Different from the device-level research on MEMS shock reliability, this paper introduces an on-chip generation method of shock load, which realizes the in-situ shock test directly loaded on the microstructure. To achieve energy storage and rapid release, a crossbow-type shock load generating structure that can integrate the test sample is proposed. The shock behavior is characterized by the high-speed camera, and the simulation model is established by the finite element software LS-DYNA. Under the shock acceleration of more than 100,000 g, the high-speed switching waveform generated by the microscale mechanical shock was observed with an oscilloscope for the first time. And the shock contact process and the dynamic fracture process of single-crystal silicon (SCS) structures in less than $1\mu \text{s}$ were exhibited. This work has the potential to be used to evaluate the shock resistance reliability of MEMS microstructures in mechanical shock environments, as well as to study material dynamic properties and material failure behaviors at the microscale. [2022-0076] [ABSTRACT FROM AUTHOR]

The limitation of theDC protection device confines the development of MV/LVDC grids. This paper presents a DC dynamic voltage restorer to exploit DC custom power devices for DC distribution networks in principle. It is based on an improved AC/DC dual active bridge and battery energy storage to maintain the voltage profile of sensitive loads in DC networks. The principle of the improved DC-DVR has been analyzed from the perspectives of the range of compensated voltage, current characteristics, and control strategy. Compared with other existing methods, the proposed DC-DVR features a simple structure, an easy control strategy, and the ability to mitigate both voltage sag and swell by injecting forward or reverse voltage. Experiment results demonstrate the correctness of the theoretical analysis and the feasibility of the proposed structure. A case study of DC doubly-fed induction generator (DFIG) interfaced with power grid is carried out, integrated with the proposed DC-DVR to verify the operation principle of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, an autonomous power management strategy is proposed for distributed energy storage units deployed in islanded microgrids with photovoltaic (PV) and droop controlled units. The proposed strategy offers controlled and selective prioritization of the charging/discharging actions while coordinating with PV and droop units to maintain power balance in the microgrid. The selective priority allows battery units with low state-of-charge (SOC) to keep charging, at a reduced or a full rate, while other battery units meet the demand. This is in contrast to the autonomous techniques in the literature where all units can only charge/discharge simultaneously. This is achieved by employing the proposed adaptive piecewise P/f characteristics, with breakpoints that enable seamless transition between power control and frequency regulation. The charging/discharging decisions and the amount of power exchanged with the microgrid, is determined autonomously at each unit using local measurements only. Also, the strategy offers a unidirectional shutdown mechanism where, below a certain SOC limit, it modifies the structure of the P/f characteristics so the unit cannot discharge, yet it can still charge anytime surplus generation becomes available. Simulation results from a detailed switching model, and also an averaged model, for prolonged simulation times, are used to validate the proposed strategy. [ABSTRACT FROM AUTHOR]

A hybrid Energy Storage Systems (ESS) consists of two or more energy storage technologies, with different power and energy characteristics. Using a hybrid ESS, both high-frequency and low-frequency power variations can be addressed at the same time. For an accurate sizing of a hybrid ESS, the use of high-resolution data is required. However, high-resolution data over long periods leads to large data sets, which are difficult to handle. In this paper, an improved motif discovery algorithm is introduced to find the most recurring daily consumption patterns within the time series of interest. The most recurring pattern is selected as the representative of the time series for sizing the hybrid ESS. Next, a simple optimization framework is proposed for selecting the cut-off frequency of a low-pass filter, used for allocating the power to different storage technologies. Finally, the proposed sizing approach is applied for sizing a hybrid battery-flywheel ESS at four different low voltage distribution grids in southern Germany using real measurement data. It is demonstrated that a hybrid ESS, with the characteristics derived from the most recurring patterns only, can effectively provide their intended grid services for most of the days during the whole period of the time series. [ABSTRACT FROM AUTHOR]

Behind-the-meter battery energy storage is used to mitigate non-dispatchability of customer-owned renewable sources. While serving their owners’ objectives, their underutilized capacities can be used to provide grid services to justify their cost. However, the integration of these resources extends the size and complexity of the network operation problem, imposing a processing burden on the central control system. In this paper, an agent-based distributed control framework is proposed that enables utilizing of the underutilized behind-the-meter capacities. In this framework, while the prosumer agents initially schedule their resources for daily cost management, a local customer aggregator agent performs day-ahead active and reactive power control on the underutilized behind-the-meter batteries to provide multiple grid services. A novel grouping algorithm is developed based on voltage sensitivity and a modified $k$ -means clustering method to assign customer groups to the local agents and establish the network subsystems. Mixed-integer linear programming is used to model and solve multiple optimization problems. The proposed framework is applied to the 123-bus distribution network. The simulation results show its effectiveness in terms of complexity and optimality, compared to the central control approach in allocating the unused behind-the-meter resources for two common industry needs: network bottleneck congestion relief and grid-edge voltage support. [ABSTRACT FROM AUTHOR]

This paper proposes a novel hybrid AC/DC microgrid architecture incorporating a central energy storage system (ESS) for both the AC and the DC sub-grids. To ensure effective operation of the proposed hybrid AC/DC microgrid architecture, a coordinated control strategy between the central ESS and the inter-linking converter (ILC) is proposed in the paper. The proposed central ESS provides voltage and frequency control to the AC sub-grid by measuring voltage and frequency at the point of common coupling (PCC) of the AC sub-grid, while providing DC voltage support to the DC sub-grid by measuring DC sub-grid’s PCC voltage. Furthermore, per-unit frequency and the DC sub-grid PCC voltage are utilized to transfer power between the two sub-grids via the ILC. Therefore, two control strategies are coordinating with each other and maintain stable operation. The central ESS eliminates the use of multiple ILCs and complex control schemes for charge and discharge control to maintain same state of charge levels at each ESS. Effectiveness of the proposed coordinated controller is verified by applying various load disturbances, faults, and under different modes of operation. [ABSTRACT FROM AUTHOR]

Modular multilevel converters (MMCs) have been recognized as the most attractive technology for high voltage direct current (HVDC) applications during the last years. Their advantages include the ability to freely control the internally stored energy in the distributed submodules (SMs) and to independently control AC and DC powers. Recent studies showed that an MMC can take advantage of this degree of freedom to supply ancillary services with low energy requirements such as frequency response or power oscillation damping by connecting energy storage systems (ESSs) to its SM capacitors. This paper proposes a modular DC-DC converter as an interface between the energy storage element and the SM capacitor. As it can be built with switches allowing a high switching frequency, it is shown that the volume of the passive components can be reduced in comparison with interface converters known in the literature. The proposed control strategy avoids to transfer the harmonics of a SM to the ESS that prevents to drastically oversize the system. The proposed control method also provides an appropriate energy exchange without affecting the control philosophy of an MMC and it addresses balancing issues. Simulations and a downscaled prototype confirm the relevance of the proposed control. As the proposed interface converter is able to track the power reference with fast dynamics, it provides the same system-level advantages as other interface converters known in the literature but with a reduced volume. [ABSTRACT FROM AUTHOR]

This paper proposes a dynamic valuation framework to determine the opportunity value of battery capacity degradation in grid applications based on the internal degradation mechanism and utilization scenarios. The proposed framework follows a dynamic programming approach and includes a piecewise linear value function approximation solution that solves the optimization problem over a long planning horizon. The paper provides two case studies on price arbitrage and frequency regulation using real market and system data to demonstrate the broad applicability of the proposed framework. Results show that the battery lifetime value is critically dependent on both the external market environment and its internal state of health. On the grid service side, results show that second-life batteries can provide more than 50% of the value compared to new batteries, and frequency regulation provides two times more revenue than price arbitrage throughout the battery lifetime. [ABSTRACT FROM AUTHOR]

Energy storage systems (ESSs) are being utilized to improve wind farms’ (WF) frequency support capability due to their high reliability, fast response and the dual role of energy users and suppliers. Nevertheless, the problem of how much capacity should each ESS possesses in order to better serve the WFs has never been investigated. With this perspective, this paper proposes an optimal ESS allocation (OEA) scheme for doubly fed induction generator (DFIG) based WFs to mitigate the impact of wake effect in frequency support. Firstly, the synchronous stability of wind turbines under frequency dips is analyzed with the concept of frequency support margin (FSM), and the detrimental impact of the wake effect is also investigated. Subsequently, the role of ESSs to improve wind turbines’ synchronous stability is demonstrated. To make the OEA scheme practical, the wind turbines in a WF are segmented into different clusters based on the received wind speed. Afterwards, the OEA problem is formulated, where the objective is to optimize the coherency of the wind turbine clusters’ FSM level. The simulation results show that ESS can provide secondary frequency support under major grid frequency drops, and the proposed OEA scheme can reduce the risk of loss of synchronous stability. [ABSTRACT FROM AUTHOR]

This paper presents a novel $\mathcal {H}_{2}$ filter design procedure to optimally split the Frequency Regulation (FR) signal between conventional and fast regulating Energy Storage System (ESS) assets, considering typical Communication Delays (CDs). The filter is then integrated into a previously validated FR model of the Ontario Power System (OPS) including Battery and Flywheel ESSs, which is used to analyze the impact of these ESSs, CDs, and limited regulation capacity in the FR process in a real system. The proposed methodology to split the FR signal is also compared with the existing FR process, with the results showing that the proposed $\mathcal {H}_{2}$ filter design and signal splitting strategy can improve the FR process performance significantly, in terms of reducing the Area Control Error (ACE) signal, and thus reduce the need for regulation capacity. [ABSTRACT FROM AUTHOR]

In order to improve the automatic generation control (AGC) performance of thermal generators, this paper presents a stochastic model predictive control (SMPC) approach for a battery/flywheel hybrid energy storage system (HESS) to distribute power. The approach combines an adaptive Markov chain for power demand prediction of HESS, a scenario tree generation and model predictive control strategy. To develop an effective prediction model to deal with the randomness of a thermal generator in response to AGC command, a Markov chain is used to describe the randomness of the HESS power demand, and a posteriori information is used to adapt to the fluctuation of the AGC command. A scenario tree generation approach is proposed to make better use of the Markov probability matrix. Based on these efforts, an SMPC approach is proposed for HESS energy management. Simulation results show that the regulation performance of the proposed approach outperforms conventional approaches, and that its performance is close to the model predictive control strategy with prescient information of the future power demand. In addition, compared with other approaches such as rule-based strategies, it does less damage to the battery and yields higher annual average net benefits in the whole life cycle. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed frequency control method for an off-grid inverter-based networked microgrid system (NMS) with loads, renewable generators and energy storage devices (ESDs). The frequency regulation problem is formulated as a model predictive control (MPC) problem that aims to maintain the supply-demand power balance within each microgrid and scheduled net power interchange among connected microgrids at minimal regulation costs. The charging/discharging efficiencies as well as energy capacities of ESDs, and constraints on bus voltages are also considered. The proposed MPC problem is solved by a distributed projection-based algorithm via information sharing between adjacent buses. The effectiveness of the proposed method is validated by simulations implemented in Matlab/Simulink. [ABSTRACT FROM AUTHOR]

This paper proposes an improved SOC balancing strategy for the modular energy storage system (ESS) based on low bandwidth communication (LBC) technology, aiming at solving the drawbacks of the conventional balancing strategy based on droop control. The proposed control scheme can improve the SOC balancing efficiency and remove the current deviation by using the SOC slope-adjusting and current-shifting approaches simultaneously. The average value of SOC can be derived through the LBC line, and the droop coefficient based on SOC can be controlled in the local control layer. Thus, the SOC of each sub-module can converge to the average SOC value in system dynamic process, and the balancing speed under the condition of low SOC difference between sub-modules can be improved. Furthermore, the current regulation performance in steady and transient states can be enhanced by using the proposed method. At last the effectiveness of the proposed strategy is verified by experimental results. [ABSTRACT FROM AUTHOR]

This paper presents a fabric based asymmetric supercapacitor (ASC) with metal coated cloths as the electrode and the current collector. Graphite paste printed on silver coated textile (Berlin) is used as the negative electrode and nickel/copper/silver plated fabric (Nora Dell) as the positive electrode. Biocompatible polyvinyl alcohol (PVA)-potassium chloride (KCl) gel is used as the electrolyte for ASC fabrication. During the electrochemical process, the metal oxides formed on the Nora Dell fabric contributes to the pseudocapacitance, whereas the graphite electrode forms the electric double layer capacitance. Compared to the Berlin/graphite based symmetric SC, the fabricated ASC shows enhanced performance with an areal capacitance and energy density of 32 mF.cm−2 and $2.8~\mu $ Wh.cm−2 respectively at a scan rate of 25 mV. $\text{s}^{\mathbf {-1}}$. The cyclic stability and self-charging capability of the device with flexible solar cells are also demonstrated as a proof of concept for use in practical applications. The presented energy storage device has potential to be used as a safe and sustainable alternative needed to meet the rapid growth in the field of wearable electronics. [ABSTRACT FROM AUTHOR]

In this paper, a novel distributed model predictive control (DMPC) strategy based on voltage observer for multiple energy storage systems (ESs) is firstly proposed to achieve a tradeoff between voltage regulation and power sharing. In order to reduce the impact of communication delay on voltage observer, an improved DMPC consensus algorithm is proposed. This scheme improves the robustness of the system to the delay. Besides, a small-signal dynamic model of a DC microgrid with the improved DMPC controllers is established to analyze its dynamic performance. The time-domain simulation results are presented to verify that, under the constraints of the DC bus voltage, a flexible trade-off between voltage regulation and power distribution can be achieved. Besides, the communication delay problems can be reduced. [ABSTRACT FROM AUTHOR]

Due to their fast response ability and high ramping rates, pumped-storage hydropower (PSH) plants are playing an increasingly critical role in mitigating power generation fluctuations induced by the growing proliferation of renewable energy resources. However, because they are energy-limited resources, actual reserve deployment from PSHs would cause the deviation of state-of-charge (SOC) from the scheduled value, which, once accumulated over time, could induce potential violations of SOC limits and cause non-dispatchability of PSHs. In recognizing this potential issue, it can become important to securing the reserve schedule of PSHs and other energy limited resources preventively in the day-ahead market clearing. To ensure reserve dispatchability of PSHs despite SOC deviations, this paper proposes the reserve secure constraints, which are cast as a distributionally robust chance-constrained formulation by judiciously introducing random parameters to describe deployment ratios of scheduled regulation reserve from PSHs. These constraints are converted into tractable second-order cone constraints, and further approximated as linear constraints to be compatible with the current ISO day-ahead market clearing model. A modified IEEE 118-bus system with multiple PSHs is adopted to verify the proposed approach. [ABSTRACT FROM AUTHOR]

With the decrease in system inertia, frequency security becomes an issue for power systems around the world. Energy storage systems (ESS), due to their excellent ramping capabilities, are considered as a natural choice for the improvement of the frequency response following major contingencies. In this paper, we propose a new strategy for energy storage – frequency shaping control – that allows to completely eliminate the frequency Nadir, one of the main issues in frequency security, and at the same time tune the rate of change of frequency (RoCoF) to a desired value. With Nadir eliminated, the frequency security assessment can be performed via simple algebraic calculations, as opposed to dynamic simulations for conventional control strategies. Moreover, our proposed control is also very efficient in terms of the requirements on storage peak power, requiring less (up to 40% in one of the cases) power than conventional virtual inertia approach for the same performance. [ABSTRACT FROM AUTHOR]

This paper presents an optimal transient-stability control strategy that modulates the real power injected and absorbed by distributed energy-storage devices. These devices are located at the high-voltage bus of several generators in a synchronous power system. The system is broken into areas based upon groupings of generators. The control strategy consists of two parallel feedback loops. One loop focuses on preserving the synchronism of the generator to its own area. The second loop focuses on preserving the synchronism of a given area to the other areas. Each control loop strategy is based upon local and center-of-inertia frequency measurements. The strategy is derived from two perspectives. With the first, the goal is to remove as much kinetic energy gained during a disturbance as quickly as possible before it is converted to potential energy. With the second perspective, an optimal transient control cost-function is minimized. Both perspectives result in the same strategy. The performance of the control strategy is evaluated on a four-machine power system model and on a 34-generator reduced-order model of the western North-American grid. The results show that this control approach significantly improves the transient stability of power systems. [ABSTRACT FROM AUTHOR]

This paper presents a stochastic framework for the optimization of microgrids that has the functionality of providing flexibility services to System Operators (SOs) considering uncertainties in the energy forecast. The methodology is developed with the aim of being applied to complex microgrids composed of different distributed energy resources and hybrid energy storage systems (ESS). The associated optimization problem is operated in two stages: the first one performs a stochastic optimization of the microgrid in order to reserve an up/down regulation capacity with which to deal with the energy forecast uncertainties of the microgrid. The different microgrid devices are optimized by considering their operational costs in order to achieve their optimal operation in the Day-Ahead Market (DM). The second stage is used to re-schedule the initial planning according to the signal request and an economic offer from the SO. The control problem is developed using Stochastic Model Predictive Control (SMPC) techniques and Mixed-Integer Quadratic Programming (MIQP), owing to the presence of logic, integer, mixed and probabilistic variables. The simulation results show that the proposed methodology reduces the risk of undergoing up/down-penalty deviations in the Regulation Service Market (RM), also being able to provide flexibility services to the SOs, despite being subject to uncertainties in the energy forecast carried out for the microgrid. [ABSTRACT FROM AUTHOR]

Battery-based Energy Storage Transportation (BEST) is the transportation of modular battery storage systems via train cars or trucks representing an innovative solution for a) enhancing Variable Renewable Energy (VRE) utilization and load shifting, and b) providing a potential alternative for managing transmission congestions. This paper focuses on point b) and proposes a long-term transmission-planning model coordinated with both stationary and mobile storage units. The planning-problem objective function minimizes the total system cost, i.e., the sum of i) the investment cost of candidate transmission lines, stationary and mobile storage systems, and ii) the operation cost, including conventional generating units fuel consumption, load shedding penalty and BEST transportation costs. An alternative approach for BEST vehicle scheduling problem is implemented. The contribution lies in the accomplishment of the spatial-temporal scheduling of the mobile storage units by including the Number-of-nonzero mathematical function in the optimization model set of constraints instead of using additional binary variables as generally accomplished. The identification of either storage systems optimal location, or both optimal location and size of storage systems is also allowed. BEST usefulness is analyzed and discussed for a test-system emulating a reals system in China-Northwestern-grid with high VRE penetration divided in five regional areas, of which the most promising one for BEST implementation is identified. [ABSTRACT FROM AUTHOR]

DC fault is one of the most important and critical challenges for stable operation of DC microgrids. Resistive type superconducting fault current limiter (R-SFCL) is an ideal protective solution to limit DC fault current. However, the effect of only using SFCL may further deteriorate the DC bus voltage stability. This paper first analyzes the effect of R-SFCL on DC microgrid under different operation modes and different fault locations, and then presents a coordinated control method of SMES-battery hybrid energy storage system (HESS) and SFCL in ground fault. This method can not only reduce the fault current level but also regulate the DC bus voltage. Finally, the comparative study is conducted in PSCAD/EMTDC, the feasibility and superiority of the proposed method is verified. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid control method based on model predictive control (MPC) and iterative learning control (ILC) for the hybrid energy storage system (HESS) in the application of islanded microgrid with photovoltaic (PV) generation. The hybrid method helps to deal with the sudden change in generation and load power demands. MPC aims to regulate the current of the battery and the supercapacitor (SC) to track the dynamic current references. An improved quadratic programming algorithm is proposed to reduce the iterations in online optimization. To compensate for the steady-state error caused by the power loss in the power electronic devices, a controller based on ILC is designed to correct the dynamic current references of HESS. Simulation results are used to verify the proposed algorithm. Validations using hardware experimental results substantiate the improved performance of the proposed control method in terms of reduced voltage regulations. [ABSTRACT FROM AUTHOR]

With the high penetrations of diverse renewable energy resources and energy storage devices, the optimal planning of microgrids based on selected representative operating periods (ROPs) are facing significant challenges. This paper proposes a full data-driven planning method to cope with such challenges. The proposed method takes the full data, which contain all the information on load and meteorological conditions in the planning horizon as input, and applies a two-stage data processing approach to obtain weekly and hourly ROPs, while preserving the chronological order of the raw data. Two time series with different resolutions are established in the planning model in order to satisfy coarse time intervals required for investment decisions and conform to finer time scales required for operating decisions. The proposed method reduces the scale of data, speeds up the solution process, and surmounts the computational burdens in solving the planning model in the designated horizon. Numerical results on an industrial park microgrid in Shanghai demonstrate that the proposed method can provide more accurate ROP and planning results than competitive methods. [ABSTRACT FROM AUTHOR]

With the increasing wind power integration, the security and economy of the power system operations are greatly influenced by the intermittency and fluctuation of wind power. Due to the flexible operational modes for charging/discharging, the hybrid energy storage system (HESS) is composed of battery energy storage system and super-capacitor can effectively mitigate the wind power uncertainty. This paper proposes a probabilistic forecasting-based HESS sizing and control scheme to cost-effectively smooth wind power fluctuations. First, probabilistic wind power forecasting is combined with multivariate Gaussian copula to generate temporally correlated wind power scenarios. Then, an adaptive variational mode decomposition (VMD) method is proposed to extract the frequency components of each wind scenario and determine the pre-scheduled power of wind-HESS system adaptively. Finally, a two-stage stochastic optimization model is constructed to determine the capacity and correct the pre-scheduled power of HESS with the objective of minimizing total cost. Case studies based on actual data from a Danish wind farm demonstrate that the proposed HESS sizing and control scheme can significantly reduce the installation cost and operation cost of HESS and prominently smooth wind power fluctuations. [ABSTRACT FROM AUTHOR]

The installation of a ground energy storage system (ESS) in the substation can improve the recovery and utilization of regenerative braking energy. This paper proposes an energy management strategy (EMS) of adaptive threshold adjustment for ground ESS. In this regard, this paper analyzes the energy flow in traction power supply system (TPSS) with different headways and no-load voltage. According to the influence of charge and discharge threshold on the energy flow in TPSS, the laws of energy flow are formulated. Subsequently, an EMS based on fuzzy logic control (FLC) is designed. The proposed EMS is adaptive to the variation of headway and no-load voltage. By monitoring the charge-discharge effect of ESS and the variation of substation output energy within two adjacent periods, the charge-discharge threshold is adjusted adaptively to guarantee the recovery effect of regenerative braking energy. Finally, the simulation and field experiment of proposed EMS are carried out with ground energy storage device and actual line conditions of Beijing Batong line. The experiment results indicate the good performance of proposed EMS in terms of energy saving. [ABSTRACT FROM AUTHOR]

The technology of supercapacitor is vastly examined by researchers to cope with a lower power density of battery. It is validated that a hybrid battery-supercapacitor storage (HBSS) framework can improve the overall efficiency due to taking advantage of battery's higher energy density and supercapacitor's higher power density. Despite the extensive investigations on this hybrid storage scheme in the electric vehicle (EV) industry, its experimental implementation in the power grid to cope with non-dispatchable nature of wind and solar energy is still in its initial stages. As a result, this paper concentrates on analysis of its experimental implementation on a lab-scale hybrid microgrid located at Southern Illinois University, Carbondale, IL, USA containing two wind turbines and two photovoltaic (PV) modules. The objective of this work is to promote the utilization of the experimentally validated lab-scale HBSS in power industry. [ABSTRACT FROM AUTHOR]

Power and energy ratings are the most important parameters of Flywheel Energy Storage System (FESS) which have a crucial influence on its dynamic performance in frequency regulation applications. In order to achieve the optimum dynamic performance of FESS, an integrated model is required which includes key parameters of the power network and FESS. In this paper, an integrated transfer function of FESS connected to a single-bus aggregated power system is presented. The proposed model includes both power network and FESS parameters. Moreover, the model is linearized to facilitate the application of the parameter screening approach which recognizes the most influential parameters through Taguchi method. Afterwards, combined Response Surface Methodology (RSM)-GA optimization algorithm is utilized based on an accurate approximation of the system transfer function. In order to obtain FESS power and energy ratings on the basis of lowest capital price and best dynamic response objective functions, optimization algorithm is used. The simulation and experimental studies confirm the validity of the proposed modelling and optimization approach. [ABSTRACT FROM AUTHOR]

This paper provides an overview of hyperloop technologies, including a brief discussion of key components of a hyperloop system that determine the electric power requirements as a function of time. At-scale hyperloop systems do not yet exist, so a model was used to generate a set of load profiles for conceptual hyperloop realizations at four locations in the United States: two systems in California and one each in Colorado and Ohio. In all four cases, the modeled hyperloop load profiles included pulses in both active and reactive power. Grid modeling was performed to estimate the grid impacts and for discussing grid integration challenges. The paper discusses how energy storage systems might be used to eliminate the pulsating load characteristics or significantly reduce it to accommodate current grid planning guidelines. [ABSTRACT FROM AUTHOR]

Reflecting the uncertainty of renewable energy generations and loads, power system AGC signals are essentially random processes. For the sake of the optimal operation and control of the AGC participant, such as energy storage systems (ESSs) in a performance/mileage-based regulation market, taking the uncertain nature, especially the temporal correlation, of the AGC signals into consideration can be beneficial; hence, random process models of the AGC signals are needed. However, a continuous random process model of the AGC signal that jointly considers the probability distribution and the temporal correlation is still lacking. To fill this gap, this paper first presents a systematic methodology for modeling the continuous random processes of AGC signals based on stochastic differential equations (SDEs). It is shown that AGC signals may have a saturated stationary probability density function and a biexponential temporal correlation, which are very different from the renewable generations. To capture these special characteristics, SDEs are then carefully constructed, which are easy to use in optimization and control. Using the PJM traditional and dynamic regulation (RegD and RegA) signals and the signal received from a battery ESS (BESS) plant in Jiangsu, China for example, simulation shows that the SDE is able to simultaneously capture the probability distribution and temporal correlation accurately. [ABSTRACT FROM AUTHOR]

Multi-energy systems (MESs) make it possible to satisfy consumer's energy demand using multiple coupled energy infrastructures, thus increasing the reliability of the energy supply compared to separate energy systems (SESs). To accurately and efficiently assess and improve the reliability of MESs, this paper proposes a MES reliability and vulnerability assessment method using energy hub (EH) model. The energy conversion, transmission and storage in MESs are compactly and linearly described by EH model, making reliability and vulnerability assessment of MESs tractable. Indices for MES vulnerability assessment are proposed to find the key components for improving MES reliability. Multi-parametric linear programming (MPLP) with a self-adaptive critical region set is proposed to reduce the computational burden caused by iteratively solving LP problems for a large number of samples during the assessment process. The results of a case study show that the proposed reliability and vulnerability assessment method is able to effectively evaluate the energy supply reliability of different energy sectors in MES as well as find the critical component of an MES from reliability perspective to support its planning. The proposed algorithm, i.e., MPLP with a self-adaptive critical region set, can improve the computational efficiency by an order of magnitude compared to the traditional LP method. [ABSTRACT FROM AUTHOR]

With the introduction of massive renewable energy sources and storage devices, the traditional process of grid operation must be improved in order to be safe, reliable, fast responsive and cost efficient, and in this regard power flow solvers are indispensable. In this paper, we introduce an Interior Point-based (IP) Multi-Period AC Optimal Power Flow (MPOPF) solver for the integration of Stationary Energy Storage Systems (SESS) and Electric Vehicles (EV). The primary methodology is based on: 1) analytic and exact calculation of partial differential equations of the Lagrangian sub-problem, and 2) exploiting the sparse structure and pattern of the coefficient matrix of Newton-Raphson approach in the IP algorithm. Extensive results of the application of proposed methods on several benchmark test systems are presented and elaborated, where the advantages and disadvantages of different existing algorithms for the solution of MPOPF, from the standpoint of computational efficiency, are brought forward. We compare the computational performance of the proposed Schur-Complement algorithm with a direct sparse LU solver. The comparison is performed for two different applicational purposes: SESS and EV. The results suggest the substantial computational performance of Schur-Complement algorithm in comparison with that of a direct LU solver when the number of storage devices and optimisation horizon increase for both cases of SESS and EV. Also, some situations where computational performance is inferior are discussed. [ABSTRACT FROM AUTHOR]

The stationary supercapacitor energy storage system (SCESS) is one of effective approaches for the utilization of train's regenerative braking energy in urban rail systems. In this paper, the capacity configuration of SCESSs, the no-load voltage of substation, the control of onboard braking resistors and train operation diagrams are considered comprehensively. Based on the equivalent circuit model, the effects of traction power system parameters on the energy transmission between powering trains, braking trains and SCESSs are analyzed, and the relationships between the train operating parameters and system energy consumptions are revealed. A multi-variable synthetic optimization method is proposed to optimize the SCESS capacity, train operation diagrams and traction power system parameters collaboratively. In order to reduce the search space and improve the efficiency of the optimization algorithm, a hierarchical multi-objective optimization model is established, based on which the design variables and the control variables are optimized iteratively. And as the traffic density has a great impact on the regenerative braking energy distribution of the system, the optimization objective function fully considers the frequency distribution of headways throughout the day. Combined the Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) with the traction power flow simulator, the flowchart of the two-stage optimization algorithm is designed, and the pareto set of the multi-objective problem is obtained. The advantages of reducing system energy consumptions and configuration cost under the proposed algorithm are verified based on case studies of Beijing Batong Line. [ABSTRACT FROM AUTHOR]