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Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM PUBLISHER]

This paper presents a distributed optimal power supply–demand management method by using negawatt trading in a real-time electricity market. In the negawatt trading, power consumers reduce their own power demand and receive monetary reward from the market operator. This paper discusses a power adjustment method via negawatt trading by including charge or discharge power from energy storage systems. In order to derive appropriate electricity incentive prices for consumers and to use energy storage systems in power grids efficiently, we deal with a power adjustment problem by using some future power supply information from generators. We then show a novel market algorithm to solve this problem in a distributed manner through market trading. Finally, numerical simulation results illustrate the effectiveness of our proposed method. [ABSTRACT FROM PUBLISHER]

This paper presents a novel power flow control system for a remote military microgrid with hybrid energy storage. A combination of batteries and supercapacitors (SCs) is managed by the novel control system to increase the battery life by redirecting the higher frequency current that would have to flow in the battery if SCs were not present. This paper offers a practical solution to manage the SC current and ensure that the SCs are never overcharged or commanded to support the system when they are discharged to the lower operating limit chosen. The new controller allows the independent selection of the low-pass filter parameter and the number of SCs. By making the most out of these two degrees of freedom, we investigate different configurations, identifying the one achieving the highest cash flow for the overall system. Modeling, simulations, and experimental verification are presented and linked to the sensitivity analysis of the economics of the military microgrid. [ABSTRACT FROM AUTHOR]

This paper examines the problem of designing integrated systems of photovoltaic (PV) arrays and battery cells in a manner that achieves self-balancing by design. This paper focuses on two topologies for integrating PV and battery cells, both of which connect PV generation to each battery cell directly, either with or without dc–dc conversion. This paper proves, using Lyapunov stability methods, that both the topologies are globally, asymptotically self-balancing. This means that initial differences among battery cells in either the state of charge or other internal state variables are guaranteed to diminish asymptotically with time. This self-balancing behavior reduces the amount and hence the cost of the power electronics needed for energy storage integration into PV farms significantly compared to conventional integration topologies—an argument substantiated using a financial assessment in this paper. This paper extends previous work by the authors on self-balancing PV energy storage systems in four significant ways. First, the proof of self-balancing is provided using equivalent-circuit battery models of arbitrary order, as opposed to first-order models. Second, this proof is provided for multiple integration topologies, instead of just one. Third, we demonstrate this self-balancing behavior experimentally, using a hardware-in-the-loop setup, for the first time. Finally, we perform a cost benefit analysis of our hybrid topologies in comparison to a benchmark system in order to quantify the integration cost reduction due to self-balancing. [ABSTRACT FROM AUTHOR]

This paper proposes unconventional control techniques for a portable power supply consisting of electric double-layer capacitors (EDLCs), a dc–dc converter, and a low-impedance load such a plasma load. Between the EDLCs and the plasma load consuming high power, a dc–dc converter is required to control the output voltage from the rapidly decreasing voltage of EDLCs. In addition, the dc–dc converter should maintain a set point by responding to arcs occurred in plasma process. This paper proposed hybrid analog and digital controls for a nonideal boost converter which was setup by theoretical analysis. The proposed system is verified with experiment and simulation. As a result, the proposed control method can maintain the constant output voltage longer than a traditional analog pulsewidth modulation control. [ABSTRACT FROM AUTHOR]

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]

IEEE Reliability Society is pleased to announce a call for papers to be published in a special section of IEEE Transactions on Reliability with expected publication period in spring 2013, pending sufficient acceptable papers by that time. This issue will focus specifically on the challenges and technologies surrounding battery reliability and safety. The objective of this special issue is to highlight the pressing needs and potential solutions to challenges relating to battery safety and reliability. Further development of batteries for use as portable power sources and energy storage systems is regarded as a top priority for research and development. Technologies introduced over the past decade, from smaller and more powerful portable electronic devices to zero emission electric vehicles, are all indicative of the need for improved battery systems. However, the improvement of cell energy and power densities cannot come at the expense of safety, cost, and reliability. Penetration of new technologies such as electric vehicles into a traditionally fossil fuel dominated industry can be easily thwarted by claims of "lack of safety." Additionally, millions of dollars in financial losses can be incurred if a battery safety event results in a device recall. Therefore, it is important that advancements in reliability and performance run in parallel with advancements in safety. This special issue will be concerned with, but is not limited to, issues of: Battery Pack Thermal Management; Cell Thermal Modeling; Prognostics and Catastrophic Failure Pre-curser Detection; Design for Safety; Non-toxic and Environmental Friendly Next Generation Electrodes; Non-volatile Electrolytes; Safe Separators (enhanced separator shut-down); Cell Balancing; Abuse Tolerance; and Safe System Integration. [ABSTRACT FROM PUBLISHER]

This paper proposes an intelligent modeling and optimization method to set up the smart energy hub model for the multiple energy system and optimize the operation of its associated energy hub model automatically. The core idea of the proposed method is to divide the complex energy hub model into several simple energy hub models. In this paper, the proposed computerized algorithm, which is applied to the smart energy hub model division, includes an energy loop intelligent searching method, a real nodes arrangement method, and a virtual nodes insertion method. One case study for the multiple energy system of a residential district in Guangzhou city is performed to validate the effectiveness of the proposed method. Compared with the traditional calculation method, the proposed method guarantees global optimal operation decision for the whole multiple energy system and the computational burden is significantly reduced. [ABSTRACT FROM AUTHOR]

This paper introduces a supervised machine learning (ML) approach to predict and schedule the real-time operation mode of the next operation interval for residential PV/battery systems controlled by mode-based controllers. The performance of the mode-based economic model-predictive control approach is used as the benchmark. The residential load and PV data used in this paper are 1-min data downloaded from the Pecan Street Project website. The optimal operation mode for each control interval is first derived from the historical data used as the training set. Then, four ML algorithms (i.e., neural network, support vector machine, logistic regression, and random forest algorithms) are applied. We compared the performance of the four algorithms when using different number of features and length of the training sets extracted from different months of the year. Simulation results show that using the ML approach can effectively improve the performance of the mode-based control system and reduce the computation effort of local controllers because the training can be completed on a cloud-based ML engine. The work presented in this paper paves the way for using a shared-learning platform to design controllers of residential PV/storage systems. This may significantly reduce the cost for implementing such systems. [ABSTRACT FROM AUTHOR]

This paper proposes a dynamic programming (DP)-based stochastic model predictive control (SMPC) method for the economic operation of solar PV-powered ice-storage air-conditioning (PIAC) systems. The forecast data of PV generation and building cooling load are considered as stochastic variables in this paper. To deal with the uncertainties of the day-ahead forecast data, Latin hypercube sequential sampling, Cholesky decomposition and Simultaneous backward reduction are adopted to provide representative scenarios for SMPC. The value function matrix is employed to solve the receding-horizon optimization problem formulated by DP. With updated short-term forecast information, SMPC is able to reduce the impact of inaccurate forecasts on the operation of PIAC systems. A study of typical operation cases demonstrates the effectiveness of the proposed method, which ensures the satisfaction of cooling supply and yields solutions closer to the global optimality than the traditional MPC method. [ABSTRACT FROM AUTHOR]

Energy storage (ES) plays a significant role in modern smart grids and energy systems. To facilitate and improve the utilization of ES, appropriate system design and operational strategies should be adopted. The traditional approach of utilizing ES is the individual distributed framework in which an individual ES is installed for each user separately. Due to the cost inefficiency of the individual framework and the difficulty of applying this framework to the grid-scale ES, many studies have suggested the sharing strategy for the utilization of ES to further exploit the potentials of ES. This paper provides a comprehensive review of the papers on shared ES that are published in the last decade. In this review, we characterize the design of the shared ES systems and explain their potential and challenges. We also provide a detailed comparison of the literature on shared ES based on multiple criteria. Finally, we discuss some promising directions for the future study on shared ES. [ABSTRACT FROM AUTHOR]

The eleven papers in this special section focus on the industrial and commercial potential of demand response (DR). Customers from this non-residential market base have great potential in providing flexibility for power systems through diverse demand response (DR) programs. Intelligent energy management can be carried out with DR in industrial and commercial facilities, especially if onsite control, information, and communication technologies are available, enabling also the inherent automation capabilities of heating, ventilation, and air conditioning systems. In the dawn of the Smart Grid era, with increasing distributed generation and the conversion of traditionally passive consumers to newly active energy players in the market, DR is being effectively considered for outage management and network reinforcement deferral. [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]

A modular multilevel converter control system, based on converter energy storage, is proposed in this paper for two different control modes: active power and dc voltage. The proposed control system decouples the submodule (SM) capacitor voltages from the dc bus voltage. One of the practical applications is the management of active redundant SMs. A practical HVDC system with 401-level MMCs, including 10% redundancy in MMC SMs, is used for validating and demonstrating the advantages of the proposed control system. This paper also presents a novel capacitor voltage balancing control based on \max–\min functions. It is used to drastically reduce the number of switchings for each SM and enhances computational efficiency. [ABSTRACT FROM AUTHOR]

The papers in this special section focus on electric power trains, with particular emphasis on state-of-the-art research and development and new design concepts. These papers were presented at the IEEE Vehicle Power and Propulsion Conference (VPPC) that was held in Hangzhou, China, in October 2016. [ABSTRACT FROM PUBLISHER]

Provides instructions and guidelines to prospective authors who wish to submit manuscripts. [ABSTRACT FROM AUTHOR]

In this paper, we investigate whether and under which conditions jointly owning a variable renewable source of electricity (VRES) and an electricity storage generates economies of scope in competitive electricity markets. Using a simple stochastic optimization model that assumes frictionless markets, we analytically show that no economic benefit arises from combining the two assets. This finding is in contradiction to large parts of the literature, which claim that it is in the economic interest of owners of VRES to additionally own electricity storage. We also identify circumstances where our argument does not hold and the combination of storage and VRES could theoretically make economic sense on the level of individual agents. In the last part of the paper, we demonstrate in a numerical case study of the German market that even in cases where our theoretical results do not hold, tying together storage and VRES may produce suboptimal results. [ABSTRACT FROM AUTHOR]

The use of base station (BS) sleep modes is one of the most studied approaches for the reduction of the energy consumption of radio access networks (RANs). Many papers have shown that the potential energy saving of sleep modes is huge, provided the future behavior of the RAN traffic load is known. This paper investigates the effectiveness of sleep modes combined with machine learning (ML) approaches for traffic forecast. A portion of an RAN is considered, comprising one macro BS and a few small cell BSs. Each BS is powered by a photovoltaic (PV) panel, equipped with energy storage units, and a connection to the power grid. The PV panel and battery provide green energy, while the power grid provides brown energy. This paper examines the impacts of different prediction models on the consumed energy mix and on QoS. Numerical results show that the considered ML algorithms succeed in achieving effective trade-offs between energy consumption and QoS. Results also show that energy savings strongly depend on traffic patterns that are typical of the considered area. This implies that a widespread implementation of these energy saving strategies without the support of ML would require a careful tuning that cannot be performed autonomously and that needs continuous updates to follow traffic pattern variations. On the contrary, ML approaches provide a versatile framework for the implementation of the desired trade-off that naturally adapts the network operation to the traffic characteristics typical of each area and to its evolution. [ABSTRACT FROM AUTHOR]

This paper has introduced two important indexes, turn-off surge voltage (TSV) on power switch and peak positive pole potential (PPPP) of storage batteries, which can be used to evaluate switching transient process of high-voltage energy storage system. Research on them is of great significance to power switch choice and high-voltage isolation design in engineering applications. Power switch response process at the turning off moment and transient process in freewheel stage have been analyzed by the established small-signal model of single power switch; then, a power switch test platform for hybrid energy storage system was built to verify it. Taking pulsed-power supply charging device with a novel inductor of low resistance and high inductance as a research object, this paper has analyzed dynamic process of the TSV and the PPPP at the turning off moment through establishing state space model of the whole system. Comparison shows that the numerical curves match the simulated curves well. Finally, the exactness of the employed model has been further verified in two pulse capacitor charging experiments. [ABSTRACT FROM AUTHOR]

In this paper, system properties of a physics-based model of a supercapacitor are computed using a local Lyapunov analysis and the solution of linear matrix inequalities. By considering the model as a Lurie system, bounds are computed for the resistance, capacitance, stored and dissipated energies for a charging profile, model stability, maximum reachable set with an input current impulse and the maximum voltage such that the potential difference across the double layer never exceeds the electrolyte overpotential. The bounds computed in this paper will aid the designers of supercapacitors, as the effect on the system properties caused by changes to the physical parameters can now be estimated. The theoretical results predicted by the analysis are compared against experimental data. [ABSTRACT FROM AUTHOR]

This paper proposes a novel solution for transient frequency compensation in weak 3-phase microgrids (MGs) based on a Luenberger observer and a transient frequency detector. Unlike in conventional grids, the low inertia of the generators coupled to an MG could make their rotor speeds to be affected by load changes, varying the grid frequency and compromising the grid quality and stability. This problem has been approached in the literature by the virtual inertia concept. However, the existing solutions are affected by the decoupling of the grid frequency reference and the frequency estimation bandwidth. The proposed paper addresses these problems by the use of a transient frequency drift estimator based on a transient detector and a Luenberger type observer that provides a nearly zero lag frequency estimation. The proposed alternative is analytically compared with the existing techniques and validated through simulation and exhaustive experimental results in an islanded MG. The developed method enables a 1 Hz reduction in the transient frequency deviation when compared with the existing alternatives and improves the system stability. [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]

As innovative energy-related technologies are rapidly developing, new elements are populating the electrical power grid, such as unpredictable renewable energies, plug-in electric vehicles (EVs), smart electrical home appliances, energy efficient homes/buildings, and distributed energy storage. All these elements induce a paradigm shift in power grids, which are evolving from producer-controlled structures to large, distributed, and customer-interactive ones, enhancing the coupling between the physical and the information layer. In order to be effectively employed on a large scale, all these elements must rely on automation, as well as on optimization methods, for the efficient management and consumption of energy resources under varying stochastic conditions. Driven by these changes, power grids have become complex and large-scale platforms with growing needs for automation and optimal energy management services, a concept that can be referred to as smart grids. [ABSTRACT FROM AUTHOR]

The increasing prevalence of technologies such as advanced metering and controls and continuously variable power electronic devices are enabling a radical shift in the way frequency regulation is performed in the bulk power system. This is a welcome development in light of the increase of unpredictable and variable generation. The idea of active participation of loads in frequency markets is not new, but the rapidly changing landscape of the power grid requires new techniques for successful integration of new types of resources; this paper works towards that end. Previously, it has been shown that residential HVAC systems can be aggregated and used to provide frequency regulation by utilizing their thermal energy capacity and flexibility of energy consumption. The virtual battery model—a first-order linear dynamical model—was analytically shown to be an accurate and simple model to capture the flexibility of residential HVAC systems. This paper presents a technique for creating the same battery-type models for many other types of systems, which can be much more complex. Our technique is based on stress testing detailed software models of physical systems. A realistic case study involving the terminal building of a small airport is presented as evidence of the effectiveness of the proposed techniques. [ABSTRACT FROM PUBLISHER]

This article investigates energy storage requirements in the submodules of a class of converters known as hybrid cascaded modular multilvel converters (HC-MMCs). The complexities arising from the usage of different submodule types and their non-conventional arrangement necessitate detailed analysis of submodule capacitor voltage ripples, which are needed for development of guidelines for sizing submodule capacitors. This paper characterizes electric charge variations in the submodule capacitors to derive expressions for capacitor voltage ripples, and to determine the energy storage requirements of the converter. The paper uses detailed electromagnetic transient (EMT) simulations and experimental results on a laboratory-scale MMC setup to verify and validate its findings. [ABSTRACT FROM AUTHOR]

DC shipboard power systems have been considered as a promising solution for stricter environmental regulations on ships due to their main benefits in fuel savings with variable speed engines and easy integration of energy storage systems. In order to employ the dc solution in the shipboard power systems, the dc power systems have to be protected from a system fault with protection selectivity to minimize impacts of the fault or to avoid other undesirable situations in the system. For low-voltage dc shipboard power systems, a three-level protection has been proposed: 1) fast action (first)—bus separation by solid-state dc bus-tie switch; 2) medium action (second)—feeder protection by high-speed fuse; and 3) slow action (third)—generator–rectifier fault controls. This paper proposes a new method by means of additional bus capacitance added in main dc buses to help reliable operation of the three-level protection. The principle of the proposed method is introduced and the sizing of the additional bus capacitance is addressed in this paper. With the modeling of the dc shipboard power systems, the analyses of voltage drops for the bus separation failure and fault clearing time for the feeder protection are carried out to verify the proposed method. The results show that the proposed method not only mitigates the voltage drop for the bus separation failure, but also achieves the selectivity and the sensitivity for the feeder protection. [ABSTRACT FROM AUTHOR]

Integration of an energy storage system (ESS) into a distribution network not only affects the supply reliability of the customer, but also has distinct reliability implications and consequences to the utility. The reliability value associated with an ESS highly depends on the ownership, market, and regulatory structures. This paper presents a probabilistic framework to evaluate the reliability value of ESS to the distribution system considering aforementioned factors. In this regard, a new probabilistic reliability model of ESS is developed and integrated into a sequential Monte Carlo based simulation framework. The developed ESS model consists of the Markov-based component model and the mixed integer linear programming based formulation of operating strategies that incorporate different scenarios of ownership, market structures, and the ESS characteristics. The reliability/financial risk performance of the distribution system operator (DSO) with ESS under quality regulations are quantified. Furthermore, the developed ESS model is utilized to explore the prospect of investor-owned ESS providing supply recovery and distribution grid capacity services to the DSO. Case studies are conducted on a test distribution network to show the effectiveness of the proposed model. Finally, the paper presents discussions on important considerations for efficient utilization of ESS in active distribution systems. [ABSTRACT FROM AUTHOR]

The series bridge converter (SBC) is a modular multilevel converter (MMC) recently developed to enhance power density in high-voltage high-power applications. The MMC is a well-established solution, widely researched, and exploited in practical HVdc connections, thanks to its high power quality and high efficiency. However, the main limitation of the MMC is the relatively large energy storage, also due to the fact that power ripples in the submodule capacitors include a component at the fundamental ac frequency. As a result, volume becomes critical in applications such as offshore or city center in-feeds, where space is restricted and expensive. The SBC offers a more compact footprint by exploiting a series connection on the dc side and by operating the submodules with rectified waveforms, thus moving the minimum component of the instantaneous power to twice the ac fundamental and reducing capacitors size. The drawback of the converter is a more complex energy control compared to the MMC. This paper proposes the first experimental validation of the SBC, using a 2-kW laboratory-scale prototype. Since the basic converter design has been discussed in previous papers, the focus of this paper is on converter control design and experimental validation. [ABSTRACT FROM AUTHOR]

This paper proposes a semi-consensus strategy for multi-functional hybrid energy storage systems (HESSs) in DC microgrids. Batteries in a HESS are regulated by conventional V-P droops and supercapacitors (SCs) are with integral droops (ID). Only batteries are assigned with local distributed compensators which exchange information through sparse communication links. Those SCs are exempted from data exchange process, which would save system investment costs. Within the semi-consensus scheme, the most essential function is the cooperation of V-P droop and ID that helps to naturally allocate low frequency components of load power to batteries and high frequency components to SCs, thus prolonging the overall life time of HESS. In addition to the transient power allocation function, there are other three functions endowed by the proposed strategy, which are autonomous DC bus voltage recovery to its nominal level, spontaneous SC state of charge (SOC) restoration, autonomous power sharing and SOC balancing among batteries. It is the simultaneous realization of above four functions with limit communications that makes up the main contributions in this paper. A generic mathematical modeling of HESS with the semi-consensus strategy is established. The model allows for dynamic analyses to theoretically validate the effectiveness of proposed method in both frequency and time domains. In-house experimental results are shown fully consistent with the dynamic analyses and also effectively corroborate the intended HESS multi-functional operations. [ABSTRACT FROM AUTHOR]

The modular multilevel DC converter (M2DC) exploits the interleaving between the three legs of an MMC to realize a promising uninsulated DC/DC converter to interconnect HVDC grids. This paper details a current and energies decoupled model of the M2DC. The major idea proposed in this paper is focused on the full energy control generating optimal current references to minimize the internal currents magnitude. The energy sum and difference models are fully detailed. Both current and energy control loops are based on the model inversion principle in order to control all the state variables. The proposed control is based a dynamic control developed with the model inversion principle associated with an optimization of the current magnitude deduced from a quasi-static analysis. All dynamics of the system are then explicitly controlled, which guarantee a good dynamic behavior during the transient. Therefore, current and energy controls are presented in detail. Simulation results show the dynamic behavior of the converter for various operating points. [ABSTRACT FROM AUTHOR]

Power grid resilience, reliability, and sustainability can be improved significantly by decomposing the large grids into networked microgrids (NMGs). However, the optimal energy management problem and preserving the security in NMGs are more complicated and challenging. This paper aims to propose a secured stochastic energy management framework for NMGs based on the modified blockchain approach, utilizing the directed acyclic graph (DAG). Using the decentralized and transparent blockchain technology will help to have higher security and lower risks within the network, thus eliminating the financial fraud and cutting down the total operational cost. In order to address the issues arising in the traditional blockchain models, mainly due to the storage and high complexities of hash address calculations, this paper proposes a new modified blockchain technology based on the DAG method. Also, a novel data restoration technique is developed to provide a way to restore the data with appropriate accuracy. The unscented transform (UT) approach is employed to model the uncertainties of forecast error in hourly load demand, solar power output, and wind turbines power output. Finally, the proposed model is tested on an NMG system with four MGs, including two residential MGs (as the noncrucial loads), a commercial MG (as the intermediate level loads), and a hospital MG (as the crucial loads). [ABSTRACT FROM AUTHOR]

We present a simple method to calculate the marginal capacity credit of energy limited resources with increased penetration. Energy limited resources are defined as any resource with limited hours of dispatch across a day, month, or year. This includes emission limited resources, time-limited demand response, and diurnal energy storage such as batteries and pumped storage. This paper focuses on 4 h energy limited resources with daily dispatch. The method modifies well-established effective load carrying capability methodology by optimally allocating limited capacity to the highest loss of load hours. Subsequent energy limited resources are iteratively stacked upon the prior solution, creating a marginal capacity credit curve with increased penetration of energy limited resources. Two systems are tested using this method. The initial capacity credit depends on system characteristics such as load and renewable penetration. Regardless, the capacity credit for energy limited resources declines steeply with penetration. [ABSTRACT FROM AUTHOR]

A novel real-time distributed market framework at the distribution grid level is proposed in this paper. The framework coordinates information in a hierarchical manner, while aiming to achieve consensus by sharing physically coupled information among multiple regional operators. In principle, each region maximizes its individual social-welfare problem, which is the local (regional) version of the overall social-welfare maximization of the distribution grid. The individual problem incorporates the coupled physical information from its neighboring regions. The consensus among all regions is then enforced through the proposed consensus-alternating direction method of multipliers structured trust-region (CAST) algorithm. Upon achieving convergence, the distribution locational marginal price (DLMP) is recovered for each region, which is novel in a sense that on the one hand, it is computed in a distributed manner, i.e., with preserving local information, and on the other hand, it accurately represents loss allocation from its neighboring regions. The proposed methodologies are tested on an IEEE 33-bus distribution grid and on a 144-bus network with five regions. [ABSTRACT FROM AUTHOR]

Energy hub (EH) model, which connects the input and output energy by using the coupling matrix, is an important model for multiple energy system (MES) study. In a complex MES, it is very difficult to formulate the coupling matrix directly. This paper proposes a multi-step modeling method that separates the conversion process of the EH model into several steps and set up the EH model by multiplying the coupling matrix in each step. Then, the storage location and the concept of demand response are extended and integrated in the EH model. The EH model is difficult for the optimal operation calculation due to the nonlinearity caused by dispatch factors. This paper adds variable substitution in each step to reduce the EH model’s nonlinearity. A real residential district in Guangzhou, China, and a large-scale MES are conducted to validate the efficiency of proposed modeling and calculation method. The results show that the calculation method can reduce the computational burden significantly with global optimum obtained. [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]

In this paper, the damping ability of point of common coupling (PCC) voltage feedforward is analyzed in order to improve the stability of current control, in which interference with an LCL filter of a battery energy storage system (BESS) and synchronous inductance of a diesel generator is considered in a stand-alone microgrid. A BESS can be charged by a diesel generator when the state of charge of the battery bank is significantly insufficient and where the BESS operates with constant current constant voltage control and the diesel generator provides constant voltage constant frequency control. In this case, large synchronous when the diesel generator is in a steady state may severely cause the instability of current control. The stability analysis should be required to guarantee the paralleled operation between BESS and diesel generator. An equivalent circuit model of the diesel generator is needed to perform these processes. To bring availability of analysis, this paper considers a simple equivalent circuit model considering synchronous inductance in the steady state, and it has very large inductance corresponding 1 per unit. The resonance issue is attenuated by the damping ability of PCC voltage feedforward where it is possible to improve the stability by appropriately adjusting the gain of the voltage feedforward. The effects of the synchronous inductance and the feedforward loop are analyzed in the s-domain and z-domain. The gain of the voltage feedforward is determined to be 0.2 and 0.4 based on stability analysis. To verify the validity of the damping effect of PCC voltage feedforward, a demonstration site is constructed and the stability is verified through simulation and experiment with a full model, and total harmonic distortion of current is improved to 2.44%. [ABSTRACT FROM AUTHOR]

This paper presents the design of a new primary frequency control (PFC) market for hosting frequency response reserve (FRR) offers from both generators and loads. Traditionally, FRR is provided by synchronous generators. Advanced control and monitoring technologies have enabled loads to provide fast and discrete PFC, which is complementary to the slow and continuous governor response provided by synchronous generators. In this paper, the performance of the PFC provided by the load is benchmarked by the equivalent amount of PFC provided by the synchronous generators at each typical system inertia condition using the actual dynamic network models and operation data of the Electric Reliability Council of Texas (ERCOT) system. Then, a new real-time PFC market mechanism is proposed to accept and value the PFC offers from both generators and loads. A few case studies are presented to illustrate the new market mechanism and demonstrate its effectiveness for mitigating price spikes. The results of this paper are applicable to other low-inertia power grids similar to the ERCOT system for procuring ancillary services that are essential to host high penetration of renewable resources. [ABSTRACT FROM AUTHOR]