Electrical Storage Systems Research Articles

Mathematical Model of a Local Grid with Small Modular Reactor NPPs

The technical and economic processes of the Local Grid, regional electricity system comprising small modular reactor nuclear power plants, renewable electricity generators, and electricity storage systems are investigated. Smart grid technologies are used in the management of such a system. In relation to the electricity system, the Local Grid acts as a consumer or producer of electricity depending on the price situation in the wholesale market and its own ability to balance the volume of electricity generation-consumption.
 The Local Grid market is considered to be perfect, otherwise the wholesale electricity market is characterized by imperfect competition. The mathematical model of the Local Grid is offered. The presented model adequately reproduces the characteristics of the interaction between the local market and the wholesale market. The mathematical model is generated in the form of the commitment problem for small modular reactors and electricity storage systems. The model reflects the technological limitations for the loading modes of small modular reactors and units of the energy storage system, which operate in the modes of direct and reverse energy conversion. In particular, the model reflects the shunting modes and start-shutdown modes of small modular reactors and charge-discharge modes of energy storage system units, which together determine flexibility of the operation modes for the entire power system. The commitment problem of small modular reactors of a nuclear power plant, units of the electricity storage system, and transmission lines connecting the Local Grid with the power system is a mixed integer programming problem with an objective function of minimized system costs.
 Cluster integer functions are used to reduce the dimensionality of the problems of mathematical modeling the loading modes of the Local Grid in the descriptions for the sets of the same type small modular reactors, as well as the same type energy storage units. The Local Grid model reproduces the modes of its disconnection from the system operator's network to increase nuclear safety in the event of a natural disaster or hostilities. The results of computational experiments on modeling the commitment modes of the local electrical grid are presented.
 The experiments used standard data on the volume of electricity consumption and its production from renewable energy sources. The results of the computational experiment confirm the adequacy of the suggested mathematical model for the Local Grid. The presented model is suitable for the use both independently – to analyze Local Grid functioning - and in combination with the models of electric power industry - to determine the impact of the Local Grids on the electricity system.
 The article is developed based on the results of the research carried out under target program “Support of State-Priority Research and Scientific and Technical (Experimental) Solutions of the Department of Physical and Technical Problems of Energy of the NAS of Ukraine for 2022 – 2023” with program expenditure classification code 6541230 (applied research).

A sustainable framework for long-term planning of the smart energy hub in the presence of renewable energy sources, energy storage systems and demand response program

Energy hub systems are known as the most important local energy systems and simultaneously meet the needs of their customers for different energies. Optimal design of energy hub systems has become a very important issue, as these systems have many customers. So, this paper presents a sustainable framework for the energy hub long-term planning in the presence of renewable energy sources (RESs). The hub is capable of supplying electrical, cooling and heating loads and is also equipped with three storage systems, electrical, thermal and cooling storage units. The uncertainties of different loads as well as photovoltaic (PV) panel output power are considered and the planning problem is dynamically modeled for a 15-year horizon. In addition, a Price-Based Demand Response (PBDR) program is included in the proposed model so that hub consumers can participate in it, leading to a modification of the demand curve and a reduction in operating cost. The planning and operation problem is modeled as a mixed-integer linear programming (MILP) problem and solved by the CPLEX solver in GAMS software. The effects of PBDR program, PV panels, uncertainties and energy storage systems on the sizing of equipment and operating costs have been studied in detail. The results show that the use of PBDR program reduces the installed capacity of the electrical storage system (EES) and thus leads to a reduction of about 5% of investment costs. In addition, the results show that the absence of PV panels in the model increases the operation costs by about 9%.

Robust optimal operation of energy hub incorporating integrated thermal and electrical demand response programs under various electric vehicle charging modes

Although the energy hub (EH) concept results in different benefits, the system uncertainties might affect the optimized decisions. Several studies have studied EH’s optimal operation, considering the system uncertainties. However, there is a research gap in proposing a novel EH’s robust optimal operation under various charging modes of electric vehicles (EVs), besides integrated electrical and thermal demand response programs (DRPs). The main purpose of this research is to fill such a knowledge gap. In this paper, the uncertainties of renewable energy distributed resources and electricity price have been concerned using the robust optimization method. The integrated charging load of EVs under coordinated and uncoordinated charging modes has been distinguished using the Monte Carlo simulation (MCS). Another contribution is to study different schemes of hybrid electrical, heat, and cooling energy storage systems in the introduced robust framework. Simulation results infer that a 15.87% decrement in EH’s operation cost is achievable by applying the integrated thermal and electrical DRPs, using the electric heat pump (EHP) and hybrid storage system consisting of the ice storage system. The comparative test results show that the advantages of integrated thermal and electricity DRPs and charging management of EVs are highlighted by using EHPs. The sensitivity analyses of the EH’s operation cost against the robustness efficiency parameters corresponding to the uncertainty level show that the advantages of the proposed method are highlighted while the EH’s uncertainties increase.

Hybrid Power Management Strategy with Fuel Cell, Battery, and Supercapacitor for Fuel Economy in Hybrid Electric Vehicle Application

The power management strategy (PMS) is intimately linked to the fuel economy in the hybrid electric vehicle (HEV). In this paper, a hybrid power management scheme is proposed; it consists of an adaptive neuro-fuzzy inference method (ANFIS) and the equivalent consumption minimization technique (ECMS). Artificial intelligence (AI) is a key development for managing power among various energy sources. The hybrid power supply is an eco-acceptable system that includes a proton exchange membrane fuel cell (PEMFC) as a primary source and a battery bank and ultracapacitor as electric storage systems. The Haar wavelet transform method is used to calculate the stress σ on each energy source. The proposed model is developed in MATLAB/Simulink software. The simulation results show that the proposed scheme meets the power demand of a typical driving cycle, i.e., Highway Fuel Economy Test Cycle (HWFET) and Worldwide Harmonized Light Vehicles Test Procedures (WLTP—Class 3), for testing the vehicle performance, and assessment has been carried out for various PMS based on the consumption of hydrogen, overall efficiency, state of charge of ultracapacitors and batteries, stress on hybrid sources and stability of the DC bus. By combining ANFIS and ECMS, the consumption of hydrogen is minimized by 8.7% compared to the proportional integral (PI), state machine control (SMC), frequency decoupling fuzzy logic control (FDFLC), equivalent consumption minimization strategy (ECMS) and external energy minimization strategy (EEMS).

An Energy-Based Assessment of Expected Benefits for V2H Charging Systems through a Dedicated Dynamic Simulation and Optimization Tool

Electricity from renewable energy sources represents the most promising way to decarbonize energy systems. A grid connection of car Electricity Storage Systems (ESSs) represents an opportunity to tackle issues regarding electricity production non-programmability, only if sufficiently smart bi-directional Vehicle to Grid technologies (V2G) are widely implemented. Fully Bi-directional grid capabilities are still poor and must be increased, both physically and in terms of management and billing possibilities (in the so-called smart-grid paradigm). However, some V2G technologies may be already implemented in smaller individual contexts: so-called Vehicle to Home, V2H technologies. Starting from these considerations, within the frame of an Italian publicly funded research project, the authors categorized and described many possible application contexts and developed an open-source dynamic simulation (fully available under request for the scientific community) to identify most promising conditions. To this aim, they also synthetized and tested an effective energy optimization algorithm which will soon be implemented on a prototypal wireless V2H device, built by ENEA in cooperation with Cassino University, in Italy. The performances of the system were assessed evaluating electricity auto-consumption and home auto-feeding ratios. Simulations show that very relevant performances can be obtained, up to the values 69% for electricity auto-consumption and 82% of home auto-feeding.

ქარის ენერგეტიკაში ელექტროენერგიის დამაგროვებლების გამოყენების ეფექტიანობის შეფასების ოპტიმალური ეკონომეტრიკული მოდელის შემუშავება და აპრობაცია საქართველოში

Based on the study of the world practice on methods for determining the efficiency of the introduction of electricity storage systems in electricity and a scientific approach to the problem, a complex econometric model for evaluating the efficiency of the use of electricity accumulators in wind energy has been developed. The possibility of generating electricity using the wind energy in Georgia has been assessed, the prospects for its introduction have been defined. The optimal econometric model for assessing the efficiency of the introduction of electricity collectors in wind farms is tested on the example of the wind power plant in Gori. Studies conducted at this power plant have established the high efficiency of the introduction of energy storage devices.

REGIONALY IMPORTANT SINCRO.GRID SMART GRID PROJECT

Regional transmission and distribution challenges has evolved and changed a lot in recent years. Four contradictory influences increasingly affected the operations of Slovenian and Croatian electricity systems. Regional electricity systems experienced increasing support of RES integration to meet the EU targets, a lower electricity consumption due to the economic crisis, a growing lack of centralized electricity production for electric system support and the high interconnectivity between the neighboring control zones. TSOs and DSOs observed growing network overvoltage issues as well as a decrease in secondary reserve capacities. Such situation starts to impact national and regional renewable integration targets affecting the security of supply at European level. SINCRO.GRID joint investment project addressed the above-mentioned issues in a sustainable manner. Such cross-border systemic approach will bring synergetic benefits. It will enable an acceptable level of security of operation for at least the next ten years hosting levels of RES in line with the trends foreseen to reach the 2030 targets safely. The project is going to integrate new active elements in the transmission and distribution grids. It leans on the following main pillars: deployment of six compensation devices, deployment of advanced dynamic thermal rating (DTR) systems, deployment of electricity storage systems, integration of distributed renewable generation (DG) and deployment of a virtual cross-border control center (VCBCC). A key aspect of the SINCRO.GRID project lies in the synergy brought by the simultaneous innovative deployment of a portfolio of mature technology-based solutions bring high benefits and positive externalities for the region and European Union.

Unfolding the structural features of NASICON materials for sodium‐ion full cells

AbstractSodium‐ion batteries (SIBs) are potential candidates for the replacement of lithium‐ion batteries to meet the increasing demands of electrical storage systems due to the low cost and high abundance of sodium. Sodium superionic conductor (NASICON) structured materials have attracted enormous interest in recent years as electrode materials for safer and long‐term performance of SIBs for electric energy storage smart grids. These materials have a three‐dimensional robust framework, high redox potential, thermal stability, and a fast Na+‐ion diffusion mechanism. However, NASICON has low intrinsic electronic conductivity, which limits the electrochemical performance. This review describes the structural features of NASICONs to illustrate the ion storage mechanism and electrochemical performance of SIBs. Details of the NASICON crystal structure, the affiliated Na+‐ion diffusion mechanism, morphology, and electrochemical performance of these materials in sodium‐ion half‐cells as well as full cells are described. In addition to the application as electrode materials, the use of NASICONs as solid electrolytes is also elaborated in solid‐state SIBs. Based on these aspects, we have provided more perspectives in terms of the commercialization of SIBs and strategies to overcome the limitations of NASICONs. Hence, this review is expected to provide the researchers of energy storage with an in‐depth understanding of NASICON materials with the knowledge of structural features, which will provide a new avenue on the practicality of SIBs.

Using of heat thermal storage of PCM and solar energy for distributed clean building heating: A multi-level scale-up research

Solar energy coupled with electric heat storage is a promising energy saving technology for distributed building heating. Energy saving performance of this technology used in buildings has been widely investigated by prototype-scale experiments and numerical assessments. However, the commercial and economic feasibility of this technology during the operational phase of a real building have not been proven yet. This study conducted a comprehensive techno-economic analysis of the electric heat storage system coupled with solar energy installed in a three-story office building (2000 m2 heating area) in Tianjin, China. The electric heat storage system with the heat storage capacity of 1274.8 MJ was installed on the first floor of the building. The solar collector system with a total heat collection area of 160 m2 was installed on the roof of the building. Meanwhile, the long short-term memory was used to predict the heat gain of solar collector in order to adjust the quantity of storage heat of storage device. The results indicated that the prepared storage medium possessed an excellent thermal property with a total heat storage capacity of 448.8 kJ/kg within 50–150 °C. The average thermal efficiency of vacuum tube solar collector was 51.3%, its heat gain per square meter per day was 6.5 MJ. The use of the solar radiation prediction model stabilized thermal efficiency of heat storage reservoir at 95.8%. The specific operational cost of this system within an entire heating season was 15.6 renminbi (RMB)/m2/season. Distribute clean building heating (DCBH) system can save up to 61% of heating cost compared to the centralized heating. The results showed a great application potential of combination of electric heat storage and solar energy based on solar energy prediction for the heat dispatch of distributed building heating.

Electromobility in Australia: Tariff Design Structure and Consumer Preferences for Mobile Distributed Energy Storage

The adoption of electric vehicles (EVs) may contribute to decarbonisation of the transport sector and has the potential to offer value to consumers and electricity grid operators through its energy storage capabilities. While electricity tariffs can play an important role in consumer uptake of EVs, little is known about how EV charging tariff design affects EV users’ behaviour in participating in applications that can support the electricity grid, such as those applications classed under Vehicle-to-Everything (V2X). Examining the case of Australia, this study reviews the literature on electromobility with a focus on EV charging tariffs and its impact on consumer behaviour within the V2X context. The main findings drawn from up-to-date publications show that a well-designed EV tariff structure, available parking, and EV charging facilities can increase consumer participation in V2X. However, cooperation between EV users and grid operators is needed to establish a form of controlled charging agreement to harness the full potential of the EV electricity storage system for grid stability and battery support operations. To achieve this, the right tariff structure will have to be established to incentivise EV consumers to subscribe to V2X services. We also present recommendations for EV tariff design to support Australian consumer participation in V2G. Finally, we identify research gaps for further research.

Modelling of Battery Energy Storage System Providing FCR in Baltic Power System after Synchronization with the Continental Synchronous Area

This paper presents the case study of provisions of frequency containment reserve (FCR) with a battery electric storage system (BESS). The aim of the case study is the evaluation of the technical possibility to provide FCR in Latvian power systems after all Baltic power systems will synchronize with the Continental Europe Synchronous Area (CESA). To simulate the dynamics of BESS capacity and its state of charge (SOC), authors have developed an algorithm and mathematical model (it can be realized in different calculation programs). The case study calculations verified the model. The algorithm is conditionally divided into two parts—FCR provision and SOC recovery–which in turn is divided into three possible models of BESS state of charge recovery options: (1) overfulfillment—exceeding the specified FCR amount, (2) deadband utilization, and (3) BESS charging or discharging through scheduled transactions in intraday power market. The modelling was performed using historic frequency data of Latvian and French power systems. The case study of BESS with charging capacity of 12 MW and stored energy volume of 7 MWh for provision of determined FCR for Latvian power system was considered. The obtained results from the simulation were used in the separate model to evaluate economic feasibility of BESS for FCR.

Detecting Cyberattacks on Electrical Storage Systems through Neural Network Based Anomaly Detection Algorithm.

Distributed Energy Resources (DERs) are growing in importance Power Systems. Battery Electrical Storage Systems (BESS) represent fundamental tools in order to balance the unpredictable power production of some Renewable Energy Sources (RES). Nevertheless, BESS are usually remotely controlled by SCADA systems, so they are prone to cyberattacks. This paper analyzes the vulnerabilities of BESS and proposes an anomaly detection algorithm that, by observing the physical behavior of the system, aims to promptly detect dangerous working conditions by exploiting the capabilities of a particular neural network architecture called the autoencoder. The results show the performance of the proposed approach with respect to the traditional One Class Support Vector Machine algorithm.

Short-term resilience-oriented enhancement in smart multiple residential energy system using local electrical storage system, demand side management and mobile generators

Recently, many investigations have been studied on the effects of the uncommon extreme events like hurricanes in electrical distribution grids. These events leads to damage to distribution grid equipments, and they are cause widespread blackouts. This paper presents short-term resilience enhancement of the residential sections against hurricane at day-ahead. The lines outage in the electrical distribution grid is implemented as stochastic modeling by hurricane. The resilience enhancement is done in the multiple energy systems such as integrated gas, heat and electrical. The three-stage multi-objective functions optimization is proposed for resilience-oriented enhancement. The proposed strategy for resilience-oriented enhancement including installation of the mobile generators (MGs), implementation of the demand side management (DSM) strategy and local generation (LG) in each stage. In first stage optimization, minimizing the installation costs of the MGs is modeled subject to lines outage. The DSM strategy is modeled in second stage optimization as minimization of the electrical demand deviation than optimal demand level at day-ahead. Then, minimization of the 1) operation cost and 2) loss of power supply probability (LPSP) index are considered in third stage optimization. In addition to, installation of the MGs and DSM in first and second stages; LG by electrical storage systems (ESSs) in third stage optimization is taken into accounted. The effectiveness of the proposed strategies is confirmed on the IEEE 33-bus distribution grid as three case studies by numerical simulation. The obtained results for operation cost and LPSP index in first case are $1,098,833.4 and 0.11 kW, respectively. In second case, LPSP index is minimized by %52.2 than first case. Finally, operation cost and LPSP in third case and with participation of the ESS are reduced by %52.2 and %0.78 in comparison to second case, respectively.

Optimal operation of energy hubs including parking lots for hydrogen vehicles and responsive demands

Energy hubs (EHs) are units that enable the simultaneous supply of different types of energy demands by converting energy carriers, and using energy storage systems. Energy storage systems can significantly help maintain the balance between energy production and energy demand, while enabling the use of renewable energy resources, and improve the flexibility of energy hubs through the efficient management of energy supply. In this study, a stochastic model is designed for unit commitment (UC) in Energy hubs, which include hydrogen vehicle (HV) parking lot, electric heat pump (EHP), absorption chiller (AC), photovoltaic (PV) module, boiler, hydrogen electrolyzer (HE) and electric, thermal, cooling and hydrogen storage systems. Here, natural gas (NG) and electricity are the input of the EH and are used to supply electric, hydrogen, heat, cooling and NG demands. In this work, uncertainties of demands, the initial power of hydrogen vehicle tanks and PV power are modeled, and the impact of storage systems, parking lot and demand response on EH operation are also investigated. The proposed mixed integer linear programming (MILP) model is solved for unit commitment in EH using the CPLEX solver in the GAMS software. The results show that the EH operation cost is reduced by 27.58% in the presence of demand response, energy storage systems by 12.68%, and hydrogen vehicles by 2.9%. In addition, according to the results, it can be found that the cooling storage system by 6.19% has the significant impact on reducing EH operation costs compared to electrical, hydrogen and thermal storage systems, while electric demand response by 15.89% reduction in operation costs is more effective than others. Moreover, the impact of different contingencies on the EH operation is evaluated. The results indicate that the hydrogen demand is fully supplied despite the exit of the power grid. This is particularly due to the presence of hydrogen vehicles (HV tanks) in the model. Also, simulations show that the outage of the power grid leads to 1288.64 kW of energy not served.

Study on Collaborative Planning Method for the Electricity-gas Storage Regional Integrated Energy System

Abstract In order to fully play the role of electricity and gas storage in the regional integrated energy system, a common planning method for regional integrated storage of electricity and natural gas is proposed. On this basis, mathematical models of energy storage, gas storage, electricity grid, gas grid topology and p2g were created to minimize the costs of expanding energy storage. Finally, based on current project data in Zhejiang Province, the economic benefits of joint planning of the electricity and gas storage system are examined, and the results show that an electric gas storage system can reduce system pressure and optimize equipment selection.

Solid Gel Electrolytes with Highly Concentrated Liquid Electrolyte in Polymer Networks and Their Physical and Electrochemical Properties and Application to Sodium Secondary Batteries

Gel polymer electrolytes consisting of sulfolane (SL)-NaN(SO2CF3)2 liquid electrolyte and a polyether-based host polymer were prepared, and their physicochemical and electrochemical properties were investigated. The prepared gel electrolytes generally exhibited high thermal stability regardless of the NaN(SO2CF3)2 concentrations. The glass transition temperature decreased with the NaN(SO2CF3)2 concentration owing to the strong interaction between SL and Na+. The ionic conductivities of all gel polymer electrolytes were higher than 10−4 S cm−1 at 303.15 K as a result of the plasticizer effect of SL. Although a relatively large interfacial resistance of the electrolyte/Na metal electrode was observed owing to the high reactivity of the SL-NaN(SO2CF3)2 electrolyte, the fabricated [Na metal negative electrode∣gel polymer electrolyte∣sulfur-modified polyacrylonitrile positive electrode] cell, i.e., the Na-S battery, achieved reversible charge-discharge operation at 333 K and demonstrated its potential to serve as an electric power storage system capable of low-temperature operation.

Comparison of energy parameters of electric storage systems for DC and AC traction power supply systems

Introduction. The article discusses the energy parameters of electric power storage systems for DC and AC traction power supply systems. The purpose of the research is to evaluate the energy parameters of electric power storage systems located within the inter-substation zone boundaries of the AC traction power supply system at the 25 kV voltage.Materials and methods. The author used the methods of modeling, statistics and the experimental results processing. Moreover, the paper presented the parameter estimation of the energy accumulation system on the basis of the traction calculations for the AC rolling stock. In addition, the author made two variants of calculations — in the presence and the absence of the electric storage system. The researcher also made the simulation of the electric storage system for the voltage source connected to the sectioning post busbars.Results. Using the simulation modeling, the author presents active and reactive power graphs of the inter-substation zone boundaries in the active sectioning post operation conditions. Therefore, the article demonstrates the graph of the expected charge, the discharge depth calculations for the nominal energy capacity and the required charging features, which guarantee the charge restoration of the accumulation system to the initial level.Discussion and conclusion. The author offers the comparative assessment of the electric storage systems for the traction power supply with the DС voltage of 3 kV and the AC voltage of 25 kV. The research demonstrates the reducing potential of the nominal accumulation parameters.

A stochastic model for participation of virtual power plants in futures markets, pool markets and contracts with withdrawal penalty

Virtual power plants (VPPs) aggregate various distributed generation units and act as a single entity in electricity markets. The heterogenous generation units in VPPs increase their profit and flexibility in the markets. In this research, the objective is to develop a risk-averse two-stage stochastic model for participation of heat and power VPPs including combined heat and power unit, wind turbine, electric and thermal storage systems, adjustable and responsive demands in futures markets, pool markets and contracts with withdrawal penalty. The uncertainties of pool prices have been considered. The effect of different markets on VPP profit and risk has been investigated. The participation of VPPs in contracts with withdrawal penalty has been studied in details. The results show that the possibility of export through contracts with withdrawal penalty increases expected profit by 10.36%. Investigations on the effect of risk weight factor on VPP profit show that for risk weight factors below 5, the increase in risk weight factor increases conditional value-at-risk and decreases expected profit, while for risk weight factors above 5, the increase in risk weight factor does not tangibly change expected profit or conditional value-at-risk. The effect of perfect information on VPP profit has also been investigated which shows that the expected value of perfect information is as high as $301.31.

Keeping Electrical Railways Safe

Ensuring safety in rolling stock electrical storage and propulsion systems while maintaining the highest possible availability of equipment depends on identifying and dealing with faults at the earliest opportunity

Development and evaluation of an integrated operation strategy for a poly-generation system with electrical and thermal storage systems

In this study, a renewable energy-assisted poly-generation system with energy storage systems has been investigated with a newly developed integrated operation strategy (IOS). The IOS was designed to simultaneously decide the operation of the energy generation unit and energy conversion systems by considering the state of electrical and thermal storage systems. Subsequently, the developed strategy was applied to the poly-generation system for hospital building applications and it was compared with the system under typical operation strategies, including the minimum distance (MD) strategy and the following maximum electrical efficiency load (FML) strategy. A simulation model with validated and verified components was developed, and the performance of the system was evaluated in terms of multi-criteria (energy, environment, and economy). The results showed that poly-generation systems with the new operation strategy showed the best performance among those using the different strategies; 30.79% of primary energy saving ratio, 28.35% of carbon dioxide emission reduction ratio, and 36.86% of operating cost saving ratio with optimal operation variables, as compared to the conventional system. The results of the economic feasibility study indicated a payback period of 6.6 years for system under IOS, which was 1.4 and 3.9 years less compared to the payback period of the systems under MD and FML, respectively. The IOS flexibly controlled the electric cooling/heating ratio and prime mover operation to prevent energy storage systems from overcharging and over-discharging, which led to maximum utilization of the energy produced by the renewable energy system.