Implementation Of Energy Storage System Research Articles

A review of the state of art and prospects in energy storage systems for energy harvesting applications

Due to the increasing trend in worldwide energy consumption, many new energy technology systems have emerged in the past decades. The implementation of energy storage system (ESS) technology in energy harvesting systems is significant to achieve flexibility and reliability in fulfilling the load demands. In this paper, several types of energy storage technologies available in the market are discussed to view their benefits and drawbacks. The main aim of this review is to provide a platform for readers especially those who seek to know more about ESS at a glance, to decide which ESS technology is best suited for any specific applications. This review would serve as a base for the initial state to make the right decision by referring to the criterias and characteristics of energy resources to get the optimal ESS technology. A comprehensive comparison among the various types of ESS technologies is outlined and elaborated to provide a better and clearer picture to the readers. Last but not least, the relevant recommendations and alternative choices for services related to the harvesting of solar PV energy are described too. It is hoped that the findings of this review article may be helpful to all readers interested in ESS technology.

Coordinated Control of the Onboard and Wayside Energy Storage System of an Urban Rail Train Based on Rule Mining

AbstractThere are three major challenges to the broad implementation of energy storage systems (ESSs) in urban rail transit: maximizing the absorption of regenerative braking power, enabling online global optimal control, and ensuring algorithm portability. To address these problems, a coordinated control framework between onboard and wayside ESSs is proposed in this study, and the related control strategy is obtained by transforming the global optimization problem into a combination of rule-based and local optimization problems. The design process of the strategy is divided into three parts: offline optimization, rule extraction, and local optimization. First, a genetic algorithm is used to optimize the charge/discharge threshold curves under typical operational conditions. Then, the rules of offline optimization results are obtained from an expert system, and the nonlinear rules are mined with local optimization methods. Finally, a coordinated strategy is presented based on the outcomes of the three parts. A power hardware-in-the-loop (PHIL) experimental platform based on RTLAB is built, and the above coordination strategy is verified based on data for the Beijing Metro Batong Line. The experimental results show that the strategy can effectively improve the energy-saving rate and reduce the regeneration failure rate substantially, with the effect being close to the offline global optimal solution. The algorithm proposed in this paper achieves near global optimal energy-saving optimization results with lower computational costs, and has strong portability, providing a good solution for the large-scale application of onboard and wayside energy storage coordination control.

Long-term energy transition planning: Integrating battery system degradation and replacement for sustainable power systems

The transition towards sustainable energy systems has gained significant importance globally due to high levels of environmental pollution caused by the use of fossil fuels. This study addresses a critical aspect of the global transition towards sustainable energy systems. We emphasize the impact of considering energy storage system degradation and replacement in long-term energy transition planning. The importance of this lies in mitigating the challenges posed by the intermittency and variability of renewable energy sources, such as wind and solar, without failing to consider the negative effect that excessive use of batteries as a storage energy system would have. We propose an optimization model that integrates power systems generation and transmission infrastructure with strategic energy storage system implementation to optimize their size, operation, and location for maximum efficiency and benefits. This paper offers a comprehensive approach to take into account the environmental effect of the depth of the discharge and replacement of battery systems over a long-term planning horizon considering hourly operation of representative time periods. The electricity system of Baja California, Mexico, a region heavily reliant on fossil fuels, is presented as a case study to show the applicability of the model. Results demonstrate that continuous replacement of dispatchable generators (natural gas power plants) for non-dispatchable generators (variable renewable power plants) may cause an unexpected increase of indirect greenhouse gas emissions from the continuous replacement of batteries when degradation is not considered. The results of the case study show an average emissions factor of 0.325 Ton CO2eq/MWh, approximately 24 % lower than government expectations, using the proposed MILP model.

Smart energy systems for renewable energy communities: A comparative analysis of power-to-X strategies for improving energy self-consumption

Renewable energy communities (RECs) represent the new scheme for promoting the distributed renewable generation, which must be managed to maximise the local energy self-consumption. The aim of this paper is to assess and discuss strengths and weaknesses of small-scale sector coupling strategies in residential RECs by means of a comparative analysis of their applications. Different power-to-X strategies have been applied to twenty-seven REC configurations. The systems have been separately simulated by means of the EnergyPLAN software. Power-to-heat strategy turns out to be the most cost-effective solution to integrate the RES excess, however, its potential often is not enough to fully accommodate it. Power-to-vehicle has low infrastructure costs, but its limit depends on the electric vehicle penetration and citizens’ participation. Exploiting the electric vehicle batteries is always more cost-effective than installing stationary batteries. The competitiveness of power-to-power is extremely linked to the REC electrification level. Power-to-gas is promising in high-RES excess conditions, but rarely represents the best solution due to current high electrolyser costs. The implementation of energy storage systems is crucial for improving the local self-consumption and the cross-sector integration is a better solution in energy, economic and environmental terms than focusing only on the electricity sector.

Optimal sizing of renewable energy storage: A techno-economic analysis of hydrogen, battery and hybrid systems considering degradation and seasonal storage

Energy storage is essential to address the intermittent issues of renewable energy systems, thereby enhancing system stability and reliability. This paper presents the design and operation optimisation of hydrogen/battery/hybrid energy storage systems considering component degradation and energy cost volatility. The study examines a real-world case study, which is a grid-connected warehouse located in a tropical climate zone with a photovoltaic solar system. An accurate and robust Multi-Objective Modified Firefly Algorithm (MOMFA) is proposed for the optimal design and operation of the energy storage systems of the case study. To further demonstrate the robustness and versatility of the optimisation method, another synthetic case is tested for a location in a temperate climate zone that has a high seasonal mismatch. The modelling results show thatthe system in the tropical zone always provides a superior return when compared to a similar system in the temperate zone due to abundant solar resources.When comparing battery-only and hydrogen-only systems, battery systems perform better than hydrogen systems in many situations, with a higher self-sufficient ratio and net present value. However, if there is high seasonal variation and a high requirement for using renewable energy (the penetration of renewable energy is >80 %), using hydrogen for energy storage is more beneficial. Furthermore, the hybrid system (i.e., combining battery and hydrogen) outperforms battery-only and hydrogen-only systems. This is attributed to the complementary combination of hydrogen, which can be used as a long-term energy storage option, and battery, which is utilised as a short-term option. This study also shows that storing hydrogen in a long-term strategy can lower component degradation, enhance efficiency, and increase the total economic performance of hydrogen and hybrid storage systems. The developed optimisation method and findings of this study can support the implementation of energy storage systems for renewable energy.

Distributed Event-Triggered Optimal Control Method for Heterogeneous Energy Storage Systems in Smart Grid

Increasing implementation of energy storage systems (ESS) is an available way to mitigate the fluctuation of renewable energy sources (RES) in smart grid. This paper proposes distributed control strategies without/with event-triggered information delivery for a group of heterogeneous energy storage systems (HESS) with different parameters such that the power fluctuation of renewable generation and load variation can be smoothed, meanwhile ensuring power and energy sharing among various ESS. To mitigate the impacts of parameter differences in HESS, a weighted control matrix is designed, and the method of deriving optimal feedback control gain is designed with the help of Riccati control theory. Aiming at reducing communication burdens meanwhile guaranteeing system performance, an event-triggered information delivery strategy without Zeno behavior is introduced to the distributed control method. Convergence and stability of the proposed methods are verified by rigorous mathematical analysis. Simulation studies are conducted to verify the effectiveness of the proposed method. The results show that the proposed method can achieve the state of charge (SoC), the state of temperature (SoT) and the state of energy (SoE) balance of HESS, proportional power sharing and power tracking objectives, even if the states of HESS are interfered by random disturbances.

Assessment of semi-organic electrolytes for redox flow battery: Life cycle assessment as a tool to steer industry toward green chemistry

The world is facing the crucial energy transition and it will require a rapid growth of renewable energy production. Given the intermittency of renewable energy sources, though, the ambitious decarbonization goals cannot be achieved without the implementation of energy storage systems. In this scenario, redox flow batteries (RFBs) stand as promising candidates, where vanadium RFBs have been established as the technological standard. Nevertheless, RFB systems based on metals pose environmental, socio-political and ethical problems; therefore, research is seeking new safer and more sustainable redox materials, shifting attention from metal-based to organic-based electrolytes. To our knowledge, up to now, a complete environmental assessment of an organic or semi-organic electrolyte RFB has not been carried out. In this study, an organic/halogen RFB, based on anthraquinone disulfonic acid (AQDS) and hydrobromic acid (HBr), is analyzed via Life Cycle Assessment (LCA). Influence of materials production on environmental performance of the energy storage system is evaluated via two synthesis scenarios. Organic/halogen battery is compared with an equivalent vanadium-based battery, taken as a standard reference for RFB technology. The analysis shows that the production of a semi-organic RFB may represent a valid environmental alternative to full vanadium RFB, as smaller effects in several impact categories (ReCiPe 2016) are determined. Nevertheless, LCA analysis showed that the results are strongly dependent on the synthetic route adopted to produce AQDS. As a result of such work a greener chemical pathway is open toward the benefits of switching from metal to organic RFBs.

Impacts of Solar Electricity Generation on the Thai Electricity Industry

This paper analyses the impacts of electricity generation from solar energy on the Thai electricity industry. In this paper, three scenarios (REF, Solar2015 and Solar2018) are developed to represent an increased levels of electricity produced from solar energy. A Low Emissions Analysis Platform (LEAP) model is employed, in this paper, to assess the impacts for the period 2019–2037. This paper assesses and analyses the scenario impacts in terms of diversification of electricity generation, fossil fuel requirement and emissions of CO2 and SO2. The analysis reveals that increased electricity generation from solar energy would help diversify energy supply for electricity generation, reduce fossil fuel imports, and therefore help improve energy security of the country. Furthermore, it would help mitigating CO2 and SO2 emissions – an issue of environmental significance. Despite several benefits, there are a number of emerging barriers for promoting electricity generation from solar energy in Thailand. These include the intermittency of solar energy, high-capital cost, unsupportable grid infrastructure and unfavourable regulatory framework. This paper, therefore, suggests that the implementation of energy storage system, provision of financial incentives to potential investors, improvement of grid flexibility and the revision of the regulations to support solar energy business could be effective strategies in order to address the barriers facing the Thai electricity industry.

Energy storage systems implementation and photovoltaic output prediction for cost minimization of a Microgrid

Energy storage system (ESS) has great importance in saving energy in new power systems. Optimum selection of these elements poses a new challenge to improve the energy management and prevent cost increases in the system. Also, renewable energy resources have been increasingly used in microgrids. The uncertainty and variation of renewable distributed generation (DG) affect the performance of power systems. In this paper, ESS implementations and photovoltaic (PV) power prediction are used to improve voltage/power profile of the system and reduce the total cost of the microgrid. The purpose of this paper is the optimal installation of ESSs in a microgrid to minimize the total cost where quantile nearest neighbour forecasting is utilized for PV output power prediction as an efficient approach. Gathering data of the last samples in time duration can be used for an effective prediction of PV output in this method, which can overcome PV uncertainty due to changes in solar irradiation and other parameters. Artificial neural networks combined with multi-layer perceptron and genetic algorithm are used for optimizing the size and location of ESSs in the system. Simulation results show that the proposed method improves the power profile as 14%, 21% and 28%, relatively to the scenarios of optimal ESS installation without PV prediction, using PV prediction but with no optimal ESS implementation and not using PV- no ESS implementation, respectively. Moreover, the accuracy of the proposed prediction method is more than the gradient-descent and RNN methods by about 12% and 5%, respectively, as shown in the simulation results. Also, the cost reduction of proposed method is enhanced as 24% and 31% relatively to the cases of optimal ESS installation without PV prediction and PV prediction without optimal ESS implementation, respectively.

Research on demand management of hybrid energy storage system in industrial park based on variational mode decomposition and Wigner–Ville distribution

In the industrial park microgrids, the curves of industrial load and photovoltaic output are unstable and unadjustable. The implementation of energy storage system (ESS) has proven successful in tackling these issues. Compared with the single-type battery energy storage (SBES), the hybrid energy storage system (HESS) is composed by energy-type energy storage and power-type energy storage, which can effectively improve the controllability and schedulability of renewable energy generation. The governments of most countries have implemented a two-part time-of-use tariff mechanism for industrial users. In this context, the paper proposes a solution for the reasonable low-cost configuration and operation of HESS in industrial parks. First of all, this paper creatively combines the Variational Mode Decomposition and Wigner–Ville Distribution (VMD-WVD) algorithm to break down the net load of the industrial park system, and installs the super-capacitors and lithium batteries to smooth the high frequency and low frequency components of the original net load. Secondly, this paper establishes a two-stage monthly and day-ahead optimization model, which is solved by the Chaos Particle Swarm Optimization (CPSO) algorithm. The monthly HESS capacity optimization configuration model is to minimize the total installation cost. And the day-ahead scheduling model maximizes the net income of life cycle, which further improves the user's peak-to-valley arbitrage. The results show that, compared with SBES, the installation of HESS can better achieve peak shaving and reduce grid connection fluctuations. Besides, the installation of HESS can greatly reduce the electricity cost and the basic electricity cost of industrial parks, so that it can save industrial users' production costs.

Optimization and Investment of Energy Storage System Implementation and Demand Response Pattern for Microgrid Cost Reduction with Approach of Bee Colony Algorithm

Optimization and Investment of Energy Storage System Implementation and Demand Response Pattern for Microgrid Cost Reduction with Approach of Bee Colony Algorithm

Fe-Cu Alloy-Based Flexible Electrodes from Ethaline Ionic Liquid

The effective implementation of energy storage systems within flexible structures has recently become of particular interest. Here, the fabrication of inexpensive flexible electrodes via a number of straightforward methods formed the motivation for this research. Thin film-based Fe-Cu alloys were cathodically electrodeposited on a graphite substrate. As ionic liquids consist purely of ions (not solvent), they have recently been used in some electrochemical applications. In this study, therefore, Fe-Cu alloy coatings were prepared from an ethaline ionic liquid containing iron and copper salts. The electrochemical behaviour of Fe-Cu alloy films was determined by scanning between − 1.0 V and − 0.3 V in 1 M KOH at various scan rates ranging from 5 mV s−1 to 200 mV s−1. These films were characterised in terms of their structural and morphological properties by means of Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and x-ray diffraction (XRD). Formation of iron and copper alloy was differentiated depending on applied potential. The supercapacitive ability of Fe-Cu-coated film observed in 1 M KOH electrolyte demonstrated a specific capacitance of 304 F g−1 at a scan rate of 5 mV s-1. The reaction between the alloy and the electrolyte was mainly controlled by a surface-controlled reaction. An asymmetric supercapacitor was constructed with an Fe-Cu-coated graphite negative electrode and a non-woven graphite positive electrode. Four asymmetric supercapacitors were connected in series and used to light up a blue light-emitting diode. This study shows that ethaline ionic liquid is a promising medium for the preparation of alloy-based electrodes in energy storage applications.

WITHDRAWN: Energy storage system solution – A cell balancing circuit

This research work assesses the cell balancing capacities of various commercial off-the shelf (COTS) super capacitor chargers to ultimately promote the design along with implementation of energy storage systems that are based on super-capacitors. Extensive simulations are executed with the manufacturer’s system and RC ladder circuit models. These work also observers the porous electrode structure and charges redistribution. It is also observed that the series resistance (ESR) equivalent supercapacitor may have quite significant effect on the variance of terminals voltage.

Battery Energy Storage System for Emergency Supply and Improved Reliability of Power Networks

This paper introduces the concept of a battery energy storage system as an emergency power supply for a separated power network, with the possibility of island operation for a power substation with one-side supply. This system, with an appropriately sized energy storage capacity, allows improvement in the continuity of the power supply and increases the reliability of the separated network at a specified time during the limitation of power transmission as a result of damage or disconnection of the main power line. This paper presents and describes a specific method of energy storage system dimensioning based on real measurement data. Based on the obtained parameters, an analysis of the reliability improvement of the considered network was performed. The implementation of the battery energy storage system will contribute to a more than 5-fold reduction in the occurrence of power outages in the time interval from 3 min to 1.5 h, which will clearly reduce the System Average Interruption Frequency Index and System Average Interruption Duration Index factors. In this paper, the network conditions for operational normality and failure are presented and the cost for implementation of an energy storage system (about EUR 1 million) is compared with the possible implementation of an additional power line (about EUR 5 million) to a specific power substation.

Grid-connected advanced energy storage scheme for frequency regulation

Secure and economic operation of the modern power system is facing major challenges these days. Grid-connected Energy Storage System (ESS) can provide various ancillary services to electrical networks for its smooth functioning and helps in the evolution of the smart grid. The main limitation of the wide implementation of ESS in the power system is the high cost, low life, low energy density, etc. However, improved battery technology is changing the scenario rapidly. Also, any mismatch in power demand and supply causes fluctuation in frequency. Therefore, this paper presents a way for reducing the frequency fluctuation using an Advanced Energy Storage System with utility inductors. To compensate for the mismatch of supply and demand, a new system is proposed so that the nominal frequency of the power system is maintained. Due to the very high penetration of energy systems, there is a need for frequency regulation, hence different control strategies are employed to overcome this problem. In case of extreme power supply, the ESS acts as a load and gets itself charged whereas during the power deficit the ESS supplies power to maintain balance in demand and supply, and hence it mitigates the frequency fluctuation. The simulation model contains an ESS connected to a grid with a varying commercial or residential load profile. Simulation results illustrate the effectiveness of grid-connected ESS in minimizing frequency variation.

Metal (boro-) hydrides for high energy density storage and relevant emerging technologies

The current energy transition imposes a rapid implementation of energy storage systems with high energy density and eminent regeneration and cycling efficiency. Metal hydrides are potential candidates for generalized energy storage, when coupled with fuel cell units and/or batteries. An overview of ongoing research is reported and discussed in this review work on the light of application as hydrogen and heat storage matrices, as well as thin films for hydrogen optical sensors. These include a selection of single-metal hydrides, Ti–V(Fe) based intermetallics, multi-principal element alloys (high-entropy alloys), and a series of novel synthetically accessible metal borohydrides. Metal hydride materials can be as well of important usefulness for MH-based electrodes with high capacity (e.g. MgH2 ~ 2000 mA h g−1) and solid-state electrolytes displaying high ionic conductivity suitable, respectively, for Li-ion and Li/Mg battery technologies. To boost further research and development directions some characterization techniques dedicated to the study of M-H interactions, their equilibrium reactions, and additional quantification of hydrogen concentration in thin film and bulk hydrides are briefly discussed.

Implementation of energy storage systems in the Azores islands as a flexibility tool to increase renewable penetration

Implementation of energy storage systems in the Azores islands as a flexibility tool to increase renewable penetration

A Review on the Selected Applications of Battery-Supercapacitor Hybrid Energy Storage Systems for Microgrids

This paper presents a comprehensive categorical review of the recent advances and past research development of the hybrid storage paradigm over the last two decades. The main intent of the study is to provide an application-focused survey where every category and sub-category herein is thoroughly and independently investigated. Implementation of energy storage systems is one of the most interestingly effective options for further progression in the field of alternative energy technology. Apart from a meticulous garnering of the energy resources regulated by the energy storage, the main concern is to optimize the characteristic integrity of the storage devices to achieve a practically techno-economic size and operation. In this paper, hybrid energy storage consisting of batteries and supercapacitors is studied. The fact that the characteristic of batteries is mostly complementary to that of supercapacitors, hybridizing these storage systems enhances their scope of application in various fields. Therefore, the objective of this paper is to present an inclusive review of these applications. Specifically, the application domain includes: (1) regulation of renewable energy sources, (2) contributions to grid regulation (voltage and frequency compensation, contribution to power system inertia), (3) energy storage enhancements (life cycle improvement, and size reduction), (4) regenerative braking in electric vehicles, (5) improvement in wireless power transfer technology. Further, this review also descriptively highlights the control strategies implemented in these domains of applications. The application-oriented review explicates the principle advantages with the hybridization of battery and supercapacitor energy storage systems that can be used as an insight for further development in the field of energy storage technology and its applications.

Local Energy Storage and Stochastic Modeling for Ultrafast Charging Stations

Multi-stall fast charging stations are often thought to require megawatt-range grid connections. The power consumption profile of such stations results in high cost penalties due to monthly power peaks and expensive linkage fees. A local energy storage system (ESS) can be used to address peak power demands. However, no appropriate sizing method is available to match specific constraints, such as the contracted power available from the grid and the projected recharging demand. A stochastic distribution of charging events was used in this paper to model power demand profiles at the station, with a one minute resolution. Based on 100 simulated months, we propose an optimum number of charging points, and we developed an algorithm to return the required local ESS capacity as a function of the available grid connection. The role of ESSs in the range of 100 kWh to 1 MWh was studied for all stations with up to 2000 charging events per week. The relevance of ESS implementation was assessed along three parameters: the number of charging points, the available grid connection, and the ESS capacity. This work opens new possibilities for multi-stall charging station deployment in locations with limited access to the medium voltage grid, and provides sizing guidelines for effective ESSs implementation. In addition, it helps build business cases for charging station operators in regions with high demand charges.

Efficient Third-Party Abstraction of Lithium-Ion Batteries for Asset Modeling

As part of international strategies towards high penetration of renewable energy sources, the implementation of energy storage systems in power grids becomes increasingly necessary for short- and long-term energy deferral. Due to technical advantages in short-term and overall practical advantages, Lithium-Ion batteries are excellent storage mediums and already serve today widespread in a variety of applications both stationary and mobile. However, most storage systems are privately funded. To investors, battery storage is considered an asset with high capital expenditure and slow, only partially predictable return on investment. The value estimation of storage systems is intercepted by two major difficulties. The first issue is the inherent complexity of batteries regarding performance and aging, which requires in-depth knowledge for accurate statements. The second issue is the inability to determine the optimal operation strategy due to the sizable portfolio of potential applications, reaching from frequency response over arbitrage to peak-shaving, and the potential impact of each on the storage system. Investors are commonly provided with very few details on the battery itself and don’t always have the background knowledge necessary to accurately predict battery behavior and value generation in long term due to this complexity. This makes battery storage less tangible and less attractive than other assets. This presentation introduces a tool for potential customers of battery storage that can be applied to any market-available carbon-based Li-Ion battery technology. It aims to provide an approximation for the battery’s lifetime behavior based on a multi-physics model. Electrical, thermal and aging models are constructed from literature and scaled and enhanced through experimental data. The tool, which is developed in Python, takes as input the maximum amount of information available to customers in advance while making the minimum amount of assumptions about the storage system. The tool produces an approximation for the degradation of the storage system on an absolute and linear scale and can therefore be used inside optimization algorithms or as pre-processing tool. It is designed to be easily transferable and computationally efficient enough to allow for flexible parameter adjustment and multi-case comparison between storage providers and applications on any scale. Figure 1