Energy Storage System In Microgrid Research Articles

Iterative Observer-Based Resilient Control for Energy Storage Systems in Microgrids Under FDI Attacks

Iterative Observer-Based Resilient Control for Energy Storage Systems in Microgrids Under FDI Attacks

Optimized control of hybrid energy storage systems for microgrids

Abstract The development of new energy sources is considered to be one of the important ways to solve the current energy shortage problem. Clean energy sources such as wind and light have attracted much attention. Still, the volatility and uncertainty of their output power create difficulties for the large-scale connection of the system to the power grid. Based on the microgrid system, this paper focuses on the energy optimization control problem of storage batteries and supercapacitors. A low-pass filter is used based on the charge state SOC expressed as a formula. The working state of the supercapacitor charge is divided into five regions, with each region having a corresponding reference value for output power correction. The capacity optimization model of the hybrid energy storage device is constructed, and the Gaussian variational quantum particle swarm algorithm (GM-QPSO) is used to optimize the capacity of the hybrid energy storage device. It is found that the capacity optimization method proposed in this paper not only improves the stability of the operation of the system but also ensures the overall economy of the system.

Energy-Efficient Storage System Optimization and Recent Trends in Enhancing Energy Management and Access Microgrid: A Review

Energy is a vital component of our everyday lives, driving advancements in human development, economic expansion, and efficiency. Implementing sustainable energy storage systems is an economically viable approach to improving energy efficiency and regulating the generation and consumption of power. This study extensively examines energy storage, delving into several techniques, their practical uses, and the most recent progress. It focuses on environmentally sustainable alternatives for the electricity sector, including batteries, flywheels, thermal storage, and pumped hydro storage. The influence of includes compelling case examples, such as using vanadium redox flow batteries in maritime hybrid propulsion systems and advancing portable hydrogen energy storage devices. The results are encouraging, indicating that these technologies have the potential to be adequate replacements for traditional fuel sources, particularly in isolated areas where there is a critical requirement for energy storage. Moreover, this study thoroughly examines the integration options for energy storage in microgrids. It explores the complex aspects of the models, assessment indices, and optimization methods used in designing energy storage systems. This paper explores the capabilities of software used to determine the optimal size for energy storage systems. Furthermore, this study introduces and examines uncertainty analysis in modeling energy storage devices. This state-of-the-art technology has been created to demonstrate the effectiveness of energy storage systems in microgrids, providing crucial data for future progress in the industry.

Lead-Acid Battery and Supercapacitor Based Hybrid Energy Storage Systems in Microgrid for Energy Control System

Lead-acid batteries are a common energy storage option in modern microgrid applications. This study suggests installing an Energy Management System (EMS) that is managed by a hybrid energy storage system (HESS) consisting of lead-acid batteries and supercapacitors (SCs). Lower operating costs and longer battery life are the goals. Lead acid battery state of charge (SOC) depletion and daily cycle stress are reduced by SCs, which control and supply the high-frequency, power-dense section of the load cycle. But it's crucial to size the HESS correctly, taking into account load demand, available power sources, and budgetary restrictions. This article explains an algorithm that outlines the HESS's energy management control. One of the main advantages of using HESS versus passive systems is that it reduces the overall size of the system. By estimating future load dynamics using load current, the proposed energy management system primes the system for impending changes.

Adaptation of Microinverter Reference Design for Integration with Battery Energy Storage Systems in Microgrids

The paper presents an adaptation of the microinverter platform from Texas Instruments to incorporate a battery energy storage system (BESS) alongside the development of the BESS system itself. Initially designed for unidirectional power flow between PV panels and an electric grid, the platform required modifications to accommodate bidirectional energy transfer for BESS integration. These modifications encompass software adjustments and hardware enhancements, which are all detailed within the paper. The electrical configuration includes selecting and deploying components such as DCDC power converters, microcontrollers, measured signals, and actuating signals to facilitate battery connection to the platform’s DC bus. Furthermore, a supervisory control and data acquisition (SCADA) system is devised for supervisory control and monitoring, with its implementation outlined. Control software tailored for the chosen microcontroller of the DCDC converters is described in terms of structure and functionality. A hardware-in-the-loop (HIL) methodology is employed to validate the proposed modifications and microgrid configuration. Utilizing the real-time simulator OPAL-RT, the paper presents experimental results and their analysis within the considered microgrid environment.

Research on Power Balance Control Method of Electronic Transformer

Aiming at the problem of poor output stability and power gain of the power electronic transformer of the microgrid energy storage system, a power balance control method for the power electronic transformer of the microgrid energy storage system based on parallel modular multi-level commutation control is proposed. The reactive power outer loop parameter fusion method is used to sample the power dynamic load parameters and information fusion processing for the transformers in the system. According to the static limit active power adjustment of the fuzzy parameter factors on the output voltage side of the DC port, the steady-state gain of the power electronic transformer of the microgrid energy storage system is calculated. The static current limiting adjustment method is used to construct the feedback compensation model of the power electronic transformer of the microgrid energy storage system. In the active power control loop, the optimal design of the power electronic transformer power balance control of the microgrid energy storage system is realized through transient stable power adjustment. The test results show that using this method to perform power balance control on the power electronic transformer of the microgrid energy storage system has high output stability and good active power balance, which improves the robustness and adaptability of the transformer balance control.

Aging Rate Equalization Strategy for Battery Energy Storage Systems in Microgrids

It is urgent to reduce the maintenance burden and extend the service life of recycled batteries used in microgrids. However, the corresponding balancing techniques mainly focus on the state of health (SOH) balancing for unique converter structures or with complex SOH estimators. This paper proposes an aging rate equalization strategy for microgrid-scale battery energy storage systems (BESSs). Firstly, the aging rate equalization principle is established based on the relationship among throughput, state of charge (SOC), and injected/output power of a BESS, which is obtained according to the semi-empirical life model of the battery. Second, based on the established principle, the droop coefficients of energy storage systems (ESUs) are designed in the lower-level control, which can ensure the aging rate equalization of ESUs in one. The upper-level control optimizes the output of multiple microgrids. Then, the stability of the proposed aging rate equalization strategy is proven by a small-signal analysis. The performance analysis shows that the proposed aging rate equalization can also realize SOC balance. Finally, the RTLAB hardware-in-the-loop tests are carried out to illustrate the outstanding performance of the proposed strategy for extending the battery service life and ensuring microgrid operation stability.

Green Energy Storage Solutions: A Research

One of the key elements of decarbonizing global energy networks and integrating renewable energy sources is green energy storage technology. Energy Storage Systems (ESS), which store surplus produced electricity and make it available on demand, are essential for reducing fluctuations. Electromechanical, electromagnetic, thermodynamic, chemical and hybrid approaches have all been used in the development of energy storage technologies. A comprehensive list of current papers in the literature section is compiled to illustrate the range of advancements in this field. This paper reviews green energy storage systems, focusing on their primary uses. Power utilities will benefit from this thorough analysis of energy storage systems; the researchers choose the finest and newest energy storage technology based on its practicality and affordability. These days, several nations use energy storage systems to plan for future energy needs. Variations in solar radiation cause a solar photovoltaic generator to overproduce electricity. The implementation of a hybrid energy storage system would help to increase the reliability of solar-powered power generation. The microgrid is a crucial component of the smart grid network for solar installations. This study looks at the microgrid's energy storage system for photovoltaic systems. The topologies and storage system configurations of the microgrid are analyzed together with power electronic interference, control systems, and optimization of the energy storage system and renewable sources. a general technique for sizing the HESS of PV systems using design space as well as pinch analysis. HESS scales that link generator ratings to storage capacity are developed in the proper sizes by using pinch analysis to load and resources data.

A bidirectional high voltage ratio DC–DC topology for energy storage systems in microgrid

AbstractThis study proposes a bidirectional DC–DC converter with low voltage stress on its semiconductor elements and high voltage gain. Bidirectional DC–DC converters play a crucial role in DC microgrid systems, and they have been used for many applications such as power flow management, battery storage systems, voltage regulation, and electric vehicle (EV) charging systems. This paper proposes a novel non‐isolated, bidirectional DC–DC converter with an improved voltage gain conversion ratio. In the structure of the proposed converter, the coupled inductor provides high voltage gain and is employed to reduce the overall voltage stress across the main switches. Additionally, a filter inductor on the input‐low voltage side of the converter reduces current ripple. In addition, a single switch is used in boost mode, which simplifies control of the converter. Furthermore, two power switches receive simultaneous pulses for adjusting the buck stage voltage gain. Also, in the following, the mathematical calculations and the small signal analysis for the proposed converter are provided. Furthermore, a 200 W prototype is finally implemented, and its results are validated by the theoretical analysis.

Analysis of Battery Testing Protocols in the Transition from the Lab to the Field: A Test Case Using Advanced Zn-MnO2 Batteries in Off-Grid Solar Microgrids

Understanding cycling performance of batteries under varying conditions is crucial for continued development of emerging chemistries. Currently much of this work is focused on cycling single cells in well-controlled lab experiments. There are few module cycling studies in the open literature. Studies of full-sized fielded systems are even rarer. As a result of this data gap, there is limited understanding of how single cell cycling can be used to predict performance of fielded systems prior to their deployment.Sandia National Laboratories (SNL) recently deployed an advanced Zn-MnO2 secondary battery energy storage system in an off-grid solar plus storage system. Using this deployment as a test case, we will detail how performance and degradation for batteries can vary between the lab and the field. We will also discuss ways that single cell and module lab cycling can be improved to better predict operation in fielded systems.In preparation for this deployment, SNL conducted single cell cycling experiments in the lab to simulate operation in the field and determine the expected life of the systems. The first test program utilized elements of the IEC 61427-1 standard for photovoltaic off-grid application to simulate the temperature and predicted state of charge (SOC) range the cells will be cycled during field operation. The simulated field cycling targeted SOC ranges of 10 to 40% and 80-100% over 150 cycles with temperature varied between -4 and 35oC to match the ambient conditions in the field during each season. The second type of cycling test was a temperature dependence study to determine how temperature impacted cell degradation. Cells were cycled at C/10 at their full SOC range and at a single temperature until they reached 40% capacity retention. Both cycling studies predicted that low temperature operation would increase the rate of degradation.The system was deployed in May of 2022, and since that time the SNL team has collected a significant amount of performance data to help analyze system level behaviors as compared to observations from cell level testing. These include battery interactions with the solar charge controller, limitations on power inverter settings, and variance between the average system level state of charge and the test protocol. Additionally, the team is analyzing conditions found in the field, with regards to ambient temperature, solar insolation and battery charging rates, and customer usage patterns for comparison with cell-level testing protocol.Observations of the deployed system’s performance indicate there is a need for more nuanced testing protocols for lab testing that can better approximate field conditions. These may include dynamic temperature ranges that vary throughout a charge/discharge cycle, and solar charging assumptions that account for reduced insolation due to cloud cover. This can help further inform the development of charge control algorithms, system hardware and software that can help improve the overall performance of solar microgrid energy storage systems.Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2023-02502A

Probabilistic sizing and scheduling co-optimisation of hybrid battery/super-capacitor energy storage systems in micro-grids

While established deterministic capacity planning models for single-component energy storage systems exist, little attention has been given to probabilistic sizing of hybrid energy storage systems (ESSs) using swarm-based meta-heuristic algorithms. This highlights two key research opportunities, namely: (1) studying the impact of preserving model-inherent characteristics and optimising daily system dispatch on narrowing reality gaps in hybrid ESS designs, and (2) the optimal integration of hybrid ESSs into grid-connected micro-grids based on their applications, with potentially significant financial implications for model designs. In response, this paper introduces a novel probabilistic hybrid ESS capacity planning optimisation model based on a state-of-the-art meta-heuristic algorithm. To demonstrate the effectiveness of the model within a community micro-grid scheme, a case study of an eco-village in Aotearoa New Zealand is presented. The simulation results indicate a ∼4 % and ∼36 % premium above the deterministic results respectively in the most likely case and worst-case probabilistic scenarios. On the other hand, the best-case stochastic estimate of the life-cycle cost of the hybrid ESS is found to be ∼39 % lower than that of the deterministic modelling. Additionally, the economics of temporal energy arbitrage using the battery bank is investigated, indicating that at the current capital cost of stationary LiFePO4 batteries and the present fixed feed-in-tariff (NZ$0.08/kWh), it is not economically viable to cycle the storage for arbitrage reasons alone. In conclusion, this paper highlights the critical need to incorporate probabilistic optimisation techniques and emphasises the importance of sizing and scheduling co-optimisation when designing hybrid ESSs for integration into grid-connected micro-grids.

Optimization Method of Photovoltaic Microgrid Energy Storage System Based on Price-based DR

Extreme events lead to an increasing number of power outages in the distribution network. It is currently the most effective method to restore power supply after distribution network failure to connect distributed photovoltaic to the distribution network in the form of microgrids. However, the randomness of distributed PV output and load is the biggest obstacle limiting its development. Therefore, an optimization method of photovoltaic microgrid energy storage system (ESS) based on price-based demand response (DR) is proposed in this paper. Firstly, based on the influence of the uncertainty of the time of use (TOU) and load on the price-based DR, a price-based DR model is built. Then, taking the minimum difference between photovoltaic output and load demand as the optimization objective, the optimal operation model of price-based DR based on the fuzzy chance constrained program (FCCP) is established, and an optimization model of photovoltaic microgrid ESS based on FCCP is obtained. Finally, the fuzzy chance optimization problem is converted into a deterministic optimization problem through constraint equivalent treatment. The proposed method is verified by numerical simulations.

An Optimal Configuration Method for Microgrid Energy Storage Capacity via Combination of Empirical Modal Analysis and Convolutional Neural Network

This paper proposes a method that considers the bus net Fuzzy control strategy quickly and accurately for power. Due to the intermittent and fluctuating characteristics of distributed generation units in microgrid, the power quality will be reduced and the normal operation of microgrid will be affected. In this paper, empirical modal analysis fused with convolutional neural network algorithm is applied to the power control strategy of microgrid energy storage system to improve the economy and reliability of microgrid. The design process of the controller is analyzed, and fuzzy rules and membership functions are designed according to the effect requirements of the controller. Then, the center of gravity method is used to obtain the output power of the energy storage system. The simulation results show that the configuration scheme based on the optimization of the hybrid energy storage system in the whole life cycle in this paper not only ensures the stability of the energy storage system but also effectively avoids power fluctuations and stabilizes the peak shaving and valley filling rate. While improving the economy of the energy storage system, it also increases the service life of the energy storage system.

Modified Biogeography Optimization Strategy for Optimal Sizing and Performance of Battery Energy Storage System in Microgrid Considering Wind Energy Penetration

The nature of renewable energy resources (RERs), such as wind energy, makes them highly unstable, unpredictable, and intermittent. As a result, they must be optimized to reduce costs and emissions, increase reliability, and also to find the optimal size and location for RERs and energy storage systems (ESSs). Microgrids (MG) can be modified using ESSs to gradually reduce traditional energy use. In order to integrate RERs in a financially viable scheme, ESSs should be sized and operated optimally. The paper presents an enhanced biogeography-driven optimization algorithm for optimizing the operations and sizes of battery ESSs (BESSs) taking into account MGs that experience wind energy penetration in a way that migration rates are adaptively adjusted based on habitat suitability indexes and differential perturbations added to migration operators. An optimization problem was applied to a BESS to determine its depth of discharge and lifespan. This paper considers three different scenarios in using simulations and compares them to existing optimization methods for the purpose of demonstrating the effectiveness of the offered scheme. Out of all the case studies examined, the optimized BESS-linked case study was the least expensive. We also show that a BESS must be of an optimum size to function both economically and healthily. For economic and efficient functioning of MGs, it has been shown that finding the optimum size of the ESS is important and potentially extends battery lifespan. The IBBOA obtained a more precise size for BESS’s volume, and the final outcomes are compared in this paper with other methods.

Micro-grid with Vehicle-to-Grid Technology and DC Quick Charging Architecture

Abstract: Batteries from electric vehicles (EVs) can be used as potential energy storage systems in micro-grids. By storing energy when there is an excess (grid-to-vehicle) and supplying energy back to the grid (vehicle-to-grid), they can aid in micro-grid energy management. It is necessary to establish appropriate infrastructure and control mechanisms in order to implement this idea. This study presents an architecture for level-3 EV quick charging in a Vehicle to Grid-Grid to Vehicle system on a microgrid. A DC rapid charging station is modelled as part of a test micro-grid system for connecting EVs. Vehicle to Grid-Grid to Vehicle power transfer is demonstrated through simulation research. According to test results, EV batteries actively regulate power in the micro-grid using Grid to Vehicle and Vehicle to Grid operating modes. The controller provides good dynamic performance in terms of dc bus voltage stability, and the charging station design ensures minimal harmonic distortion of gridinjected current.

Development of an optimization model for the feasibility analysis of hydrogen application as energy storage system in microgrids

Hydrogen can be used as an Energy Storage System (ESS) in a microgrid allowing to store surplus generation of variable renewable sources for later use. Research in the area mainly refers to the sizing of the components, however few studies evaluate the optimal technology selection and operation of microgrids using hydrogen as ESS. In this work, a model to determines optimal selection and to dispatch of Distributed Energy Resources (DER) allowing to evaluate the viability of hydrogen application as ESS in a microgrid is developed. The model is implemented in GAMS, using mixed integer linear programming, and applied in a hypothetical microgrid using as input data load profiles and commercial data available in literature. The results indicate the economical and environmental benefits of DER adoption, but the currently high investment costs make it infeasible to adopt hydrogen into a microgrid. However, when considering environmental costs and market prospects, the adoption of this technology became a good alternative, improving the energy management and reducing the total annual cost of the microgrid by 14.1%.

Average Current Control with Internal Model Control and Real-time Frequency Decoupling for Hybrid Energy Storage Systems in Microgrids

Among hybrid energy storage systems (HESSs), battery-ultracapacitor systems in active topology use DC/DC power converters for their operations. HESSs are part of the solutions designed to improve the operation of power systems in different applications. In the residential microgrid applications, a multilevel control system is required to manage the available energy and interactions among the microgrid components. For this purpose, a rule-based power management system is designed, whose operation is validated in the simulation, and the performances of different controllers are compared to select the best strategy for the DC/DC converters. The average current control with internal model control and real-time frequency de-coupling is proposed as the most suitable controller according to the contemplated performance parameters, allowing voltage regulation values close to 1%. The results are validated using real-time hardware-in-the-loop (HIL). These systems can be easily adjusted for other applications such as electric vehicles.

Review on Ancillary Services and Optimal Sizing of Energy Storage System in Microgrid

Review on Ancillary Services and Optimal Sizing of Energy Storage System in Microgrid

Review on Recent Strategies for Integrating Energy Storage Systems in Microgrids

Energy security and the resilience of electricity networks have recently gained critical momentum as subjects of research. The challenges of meeting the increasing electrical energy demands and the decarbonisation efforts necessary to mitigate the effects of climate change have highlighted the importance of microgrids for the effective integration of renewable energy sources. Microgrids have been the focus of research for several years; however, there are still many unresolved challenges that need to be addressed. Energy storage systems are essential elements that provide reliability and stability in microgrids with high penetrations of renewable energy sources. This study provides a systematic review of the recent developments in the control and management of energy storage systems for microgrid applications. In the early sections, a summary of the microgrid topologies and architectures found in the recent literature is given. The main contributions and targeted applications by the energy storage systems in the microgrid applications is defined for each scenario. As various types of energy storage systems are currently being integrated for the reliable operation of the microgrids, the paper analyses the properties and limitations of the solutions proposed in the recent literature. The review that was carried out shows that a hybrid energy storage system performs better in terms of microgrid stability and reliability when compared to applications that use a simple battery energy storage system. Therefore, a case study for a DC microgrid with a hybrid energy storage system was modelled in MATLAB/Simulink. The presented results show the advantages of hybrid energy storage systems in DC microgrids.

Optimal Location and Sizing of Distributed Generators and Energy Storage Systems in Microgrids: A Review

This article reviews the main methodologies employed for the optimal location, sizing, and operation of Distributed Generators (DGs) and Energy Storage Systems (ESSs) in electrical networks. For such purpose, we first analyzed the devices that comprise a microgrid (MG) in an environment with Distributed Energy Resources (DERs) and their modes of operation. Following that, we examined the planning and operation of each DER considered in this study (DGs and ESSs). Finally, we addressed the joint integration of DGs and ESSs into MGs. From this literature review, we were able to identify both the objective functions and constraints that are most commonly used to formulate the problem of the optimal integration and operation of DGs and ESSs in MGs. Moreover, this review allowed us to identify the methodologies that have been employed for such integration, as well as the current needs in the field. With this information, the purpose is to develop new mathematical formulations and approaches for the optimal integration and operation of DERs into MGs that provide financial and operational benefits.