Model Of Energy Storage System Research Articles

Impacts of magnetic field and hybrid nanoparticles in the heat transfer fluid on the thermal performance of phase change material installed energy storage system and predictive modeling with artificial neural networks

In this study, impacts of magnetic field and hybrid nanoparticle addition in the heat transfer fluid are numerically studied for a thermo-fluid system with embedded phase change material during charging mode of operation by using finite element method. The magnetic field is uniform in radial direction while different strengths are considered in various domains of the computational model. Parametric numerical investigation is performed for various values of Hartmann numbers (Ha1 and Ha2 between 0 and 40), solid nanoparticle volume fraction of hybrid particles (between 0 and 0.02) and porosity of the medium (between 0.40 and 0.60). It was observed that the charging time is reduced with the imposed magnetic field while fast phase transitions occur near the walls. Dynamic characteristic of liquid fraction curves are changed with the magnetic field effects, nanoparticle inclusion and porosity of the medium. A reduction up to 40% is achieved in the charging time when the magnetic field strength of the phase change material domain is increased to Ha=40. The improved thermal transport features with hybrid nanoparticle inclusion in the heat transfer fluid is obtained. As water and nanofluid at the highest solid volume fractions are compared, 18.5%, 17.8% and 15% of reduction in the charging time is attained when cases with various magnetic field strength combinations at (Ha1, Ha2)=(40,40), (0, 40) and (40,0) are considered. Finally, estimation of charging time for different magnetic field strengths of domains and solid volume fractions of the hybrid particles is performed by using the artificial neural network based modeling approach which delivers fast and accurate results.

Thermofluidic modeling and temperature monitoring of Li-ion battery energy storage system

The battery energy storage system (BESS) is widely used in the power grid and renewable energy generation. With respect to a lithium-ion battery module of a practical BESS with the air-cooling thermal management system, a thermofluidic model is developed to investigate its thermal behavior. The thermal model for a single battery is established and experimentally validated first, and then the thermofluidic model for this battery module is developed based on the single battery thermal model and validated by experimental data also. Simulations are performed considering the practical frequency regulation condition and some hypothetical situations with unexpectedly high heat generation rates. Thermal behaviors of the battery module under different conditions are carefully analyzed. Results show that the fans-on forced air convection cooling reduces the maximum temperature by 0.4 K and makes the maximum temperature appear in a different battery of the BESS module compared with the natural air convection cooling. Especially, the temperature monitoring strategy is studied. Due to technical and cost constraints, only a limited number of temperature monitoring points can be set and the temperature that can be monitored is the battery surface temperature or some connecting bars’ surface temperature. The rationality of the locations of different temperature monitoring points is analyzed. The obtained results clearly indicate that enough caution must be paid when setting the temperature monitoring points in practical BESSs. The bad temperature-monitoring strategy may largely underestimate the maximum temperature (by as much as 3 K under the normal frequency regulation condition, and probably much larger under harsh working conditions) in the BESS and fails at reflecting the thermal status of the BESS.

Operating and Investment Models for Energy Storage Systems

In the context of climate changes and the rapid growth of energy consumption, intermittent renewable energy sources (RES) are being predominantly installed in power systems. It has been largely elucidated that challenges that RES present to the system can be mitigated with energy storage systems (ESS). However, besides providing flexibility to intermittent RES, ESS have other sources of revenue, such as price arbitrage in the markets, balancing services, and reducing the cost of electricity procurement to end consumers. In order to operate the ESS in the most profitable way, it is often necessary to make optimal siting and sizing decisions, and to determine optimal ways for the ESS to participate in a variety of energy and ancillary service markets. As a result, many publications on ESS models with various goals and operating environments are available. This paper aims at presenting the results of these papers in a structured way. A standard ESS model is first outlined, and that is followed by a literature review on operational and investment ESS models at the transmission and distribution levels. Both the price taking and price making models are elaborated on and presented in detail. Based on the examined body of work, the paper is concluded with recommendations for future research paths in the analysis of ESS.

Convex Relaxation of Grid-Connected Energy Storage System Models With Complementarity Constraints in DC OPF

Including complementarity constraints in energy storage system (ESS) models in optimization problems ensure an optimal solution will not produce a physically unrealizable control strategy where there is simultaneous charging and discharging. However, the current approaches to impose complementarity constraints require the use of non-convex optimization methods. In this paper, we propose a convex relaxation for a common ESS model that has terms for both charging and discharging based on a penalty reformulation for use in a model predictive control (MPC) based optimal power flow (DC OPF) problem. In this approach, the complementarity constraints are omitted and a penalty term is added to the optimization objective function. For the DC OPF problem, we provide analysis for the conditions under which the convex relaxation of the complementarity constraint ensures that a solution with simultaneous ESS charging and discharging operation is suboptimal. Simulation results demonstrating ESS behavior with and without the penalty reformulation are provided for an MPC-based DC OPF problem on multiple IEEE test systems.

An Energy Storage Performance Improvement Model for Grid-Connected Wind-Solar Hybrid Energy Storage System.

This study introduces a supercapacitor hybrid energy storage system in a wind-solar hybrid power generation system, which can remarkably increase the energy storage capacity and output power of the system. In the specific solution, this study combines the distributed power generation system and the hybrid energy storage system, while using the static reactive power compensation system and the conductance-fuzzy dual-mode control method to increase output power in stages. At the same time, the optimal configuration model of the wind-solar hybrid power generation system is established using MATLAB/Simulink software. The output power of the microgrid to the wind-photovoltaic hybrid power generation system is calculated by simulation, and the optimization process of each component of the system is simulated. This study mainly uses the static reactive power compensation system and the conductance-fuzzy dual-mode control method to optimize the wind-solar hybrid power generation system. Using MATLAB software simulation verifies the feasibility and rationality of the optimal configuration of the system.

The Role of Mathematical Model of Energy Storage by Power Systems Computer Aided Design / Electromagnetic Transients including DC in Power Energy Security Control

In order to discuss the application of energy storage system in power energy control, in this study, the energy storage system in small wind power generation system is taken as the research object, and the converter mathematical model in the energy storage system is built. Meanwhile, in the control state of grid-connected operation, the energy storage system is analyzed and a Power Systems Computer Aided Design / Electromagnetic Transients including Direct Current (PSCAD/EMTDC) simulation model based on Power Quality (PQ) control and Space Vector Pulse Width Modulation (SVPWM) mode is built. And when Insulated Gate Bipolar Transistor (IGBT) fails on the upper bridge arm of A-phase Alternating Current (AC) converter in the energy storage system, the changes of AC voltage, AC current, active power, and reactive power in the system and simulated. The results show that the simulation model of energy storage system established by PSCAD/EMTDC is feasible under the PQ control of grid-connected operation. In addition, fault analysis shows that the current conduction of A phase is delayed in the negative half wave, and there is a positive Direct Current (DC) bias, but the distortion of current of B phase and C phase is not significant. And the active power and reactive power remain within the set reference range. Therefore, it is possible to determine the failure of the converter IGBT of the energy storage system by whether or not the three-phase current on the AC side of the energy storage system has a DC offset. This study aims to provide theoretical basis for the follow-up fault diagnosis and system protection of the energy storage system.

Research on Photovoltaic Energy Storage System and Supply-Side Power Dispatch Model in Paper Mill

With the increased awareness of environmental protection and the establishment of the spot market of electric power, renewable energy plays a more and more important role in energy structure adjustment. But the intermittence and instability of renewable energy often result in energy waste. Micro-grid energy storage can effectively improve the utilization rate, economy and reliability of renewable energy. To ensure the economical operation of the micro-grid system and improve the load curve, a two-stage optimal dispatch model was established based on non-dominated sorting genetic algorithm (NSGA-II) and deep Q-value reinforcement learning algorithm (DQN). In the first stage, to get the appropriate battery capacity, the minimum comprehensive operation cost and the minimum capacity fading of battery in the cycle life were selected as the optimization objectives. The optimal solution was calculated by using the improved non-dominated sorting genetic algorithm (NSGA-II). In the second stage, the DQN Algorithm was used to propose a scheduling strategy. Compared with the GA method, the DQN method was able to reduce the operating cost from 0.5829 % to 1.2294 %. The results showed that the method was feasible and effective.

Design and Simulation of an Energy Storage System with Batteries Lead Acid and Lithium-Ion for an Electric Vehicle: Battery vs. Conduction Cycle Efficiency Analysis

This work aimed to study and analyze the model of a conventional vehicle transformed into an electric vehicle self-sustaining, in this transformation process, the proposal was to simulate two proposals of energy storage system, being a bank with lead-acid batteries (Pb) and another bank with lithium-ion (Li-ion) batteries, considering three transmission options with different gear ratios. In this work, the MATLAB and ADVISOR software were used for modeling and simulation. Simulations were carried out using three driving cycles that represent the conditions of running in: a highway, a highway with an ascent of mountain and city, all conditions being based on routes in the Vale do Paraiba Paulista region. At the end of the proposed simulation models, a comparison was made between the proposed energy storage system models considering gear ratio and driving cycles based on electric vehicle model under development.

Spectrum-domain stability assessment and intrinsic oscillation for aggregated mobile energy storage in grid frequency regulation

This paper assesses the aggregation stability of mobile energy storage for the grid frequency regulation, which employs distributed electric-vehicle capacities. To reveal the aggregation dynamics, a multiple-aggregator model is established in the state space, which introduces aggregation factors coupled with the time for distributed vehicles. Interlinking the aggregated model of mobile energy storage system with the electrical grid model, an integration model is developed for the stability assessment. According to the transcendental model feature, an efficient stability region extraction method is then proposed to disclose the unstable risk, which consists of four sequential stages: quasi-polynomial formulation, Dixon-resultant based spectrum estimation, oscillation spectrum extraction, and stability map determination. In the first stage, Rekasius substitution is deployed converting the notoriously complicated model to a quasi-polynomial form. Since the real and imaginary parts of the quasi-polynomial have to vanish simultaneously, an elimination method called Dixon resultant is utilized, which constructs the necessary and sufficient assessment condition. After that, the discriminant is carried out to generate the imaginary spectra bound, which is scanned to finally determine the oscillation spectrum. It is revealed that the aggregation of mobile energy storage system might induce an oscillation spectrum due to asynchronous processes. Besides, the bound of the oscillation caused by the aggregation process is disclosed. Moreover, the established mapping relationship between the kernel curve and their offspring curves visualizes the complete stability map. The whole model and stability analysis are theoretically derived and verified through a typical grid frequency regulation system with mobile energy storage.

Reserve Model of Energy Storage in Day-Ahead Joint Energy and Reserve Markets: A Stochastic UC Solution

With many favorable advantages including fast response ability in particular, utility-level energy storage systems (ESS) are being integrated into energy and reserve markets to help mitigate uncertain renewable resources and fluctuant demands. This paper discusses a stochastic unit commitment (UC) model to explore capabilities of ESSs in providing valuable grid services by simultaneously joining energy and reserve markets. The proposed reserve model of ESSs presents the following features: (i) two constraints are proposed to formulate ESS's reserve provision ability in each hour via six operation modes, namely increasing/reducing the level of charge, switching to discharge, increasing/reducing the level of discharge, switching to charge; (ii) as an energy-limited asset, constraints on ESS's reserve deliverability across multiple hours is introduced to hold enough state of charge (SOC) headroom and floor room, guaranteeing that reserves cleared in individual hours are continuously deliverable over multiple successive hours without violating operation limits. Moreover, a scenario-based UC model, which addresses uncertainties of renewables and demands, is adopted to evaluate reserves provided by ESSs and generators. To effectively solve the stochastic UC problem, the progressive hedging algorithm with heuristic approaches is discussed. A 6-bus system and a modified IEEE 118-bus system are used to illustrate effectiveness of the proposed approaches.

Capacity Planning of Distributed Wind Power Based on a Variable-Structure Copula Involving Energy Storage Systems

Distributed wind power (DWP) needs to be consumed locally under a 110 kV network without reverse power flow in China. To maximize the use of DWP, this paper proposes a novel method for capacity planning of DWP with participation of the energy storage system (ESS) in multiple scenarios by means of a variable-structure copula and optimization theory. First, wind power and local load are predicted at the planning stage by an autoregressive moving average (ARMA) model, then, variable-structure copula models are established based on different time segment strategies to depict the correlation of DWP and load, and the joint typical scenarios of DWP and load are generated by clustering, and a capacity planning model of DWP is proposed considering investment and operation cost, and environmental benefit and line loss cost under typical scenario conditions. Moreover, a collaborative capacity planning model for DWP and ESS is prospectively proposed. Based on the modified IEEE-33 bus system, the results of the case study show that the DWP capacity result is more reasonable after considering the correlation of wind and load by using a variable-structure copula. With consideration of the collaborative planning of DWP and load, the consumption of DWP is further improved, the annual cost of the system is more economical, and the quality of voltage is effectively improved. The study results validate the proposed method and provide effective reference for the planning strategy of DWP.

Optimal Configuration of Energy Storage Capacity on PV-Storage-Charging Integrated Charging Station

The rational allocation of a certain capacity of photovoltaic power generation and energy storage systems(ESS) with charging stations can not only promote the local consumption of renewable energy(RE) generation, but also participate in the energy market through new energy generation systems and ESS for arbitrage. In this paper, a system operation strategy is formulated for the optical storage and charging integrated charging station, and an ESS capacity allocation method is proposed that considers the peak and valley tariff mechanism. First, the system modeling of the photovoltaic storage and charging station is carried out, the topology structure is analyzed and the cost model of photovoltaic power generation and ESS and dispatching is established; second, the energy flow of the photovoltaic storage and charging station is analyzed and the system operation strategy is formulated; then, the optimal model of ESS capacity configuration is established with the goal of obtaining the maximum benefit from the photovoltaic storage and charging station under the peak and valley electricity price environment; finally, the optimal ESS capacity configuration of the photovoltaic storage and charging station is analyzed based on specific cases and the impact of the change of ESS price on the optimal capacity configuration is discussed.

Stochastic reserve scheduling of energy storage system in energy and reserve markets

Energy storage systems (ESSs) can be used to participate in both the energy and reserve markets to maximize their reserve benefits. In contrast to traditional thermal units, ESSs have three statuses: charging status, discharging status, and idling status. The energy-limited feature of ESSs makes it difficult to schedule the reserve in the joint energy and reserve markets. In this paper, a detailed energy and reserve model of ESSs is considered in the joint stochastic day-ahead unit commitment model. The main highlights of this paper are the reserve model of ESSs. Compared to existing studies, a proposed six-mode hourly power reserve model of ESSs can schedule more reserve amount to participate in the reserve market. The six reserve modes include more charging/discharging, less charging/discharging, and switch from another status to charging/discharging. Besides, multi-hour coupled reserve constraints are introduced to avoid ESSs failures to provide the reserves scheduled in the day-ahead market. Considering the uncertainty of demand and renewable generation, a scenario-based stochastic model is adopted to calculate both the energy and reserve costs of the whole system. Two different systems are used to discuss the benefits of the proposed reserve model and analysis on some crucial parameters.

Optimal Siting and Sizing of Battery Energy Storage System for Distribution Loss Reduction Based on Meta-heuristics

This paper presents an optimal sitting and sizing model of a lithium-ion battery energy storage system for distribution network employing for the scheduling plan. The main objective is to minimize the total power losses in the distribution network. To minimize the system, a newly developed version of cayote optimization algorithm has been introduced and validated based on different test functions and verified by some well-known meta-heuristics. The proposed algorithm is then applied to four different case studies in the presence of two photo voltaic (PVs) and without them. The optimization of the problems is applied based on two different trends including simultaneous and step-by-step optimization. Final results are compared with some meta-heuristics including cuckoo optimization algorithm, lion optimization algorithm, and cooperative random particle swarm optimization algorithm to show the algorithm higher efficiency. The results also showed that the presence of PVs reduces the total power losses and applying the simultaneous optimization gives higher efficiency with less total power losses.

Numerical simulation of underground seasonal cold energy storage for a 10 MW solar thermal power plant in north-western China using TRNSYS

This paper aims to explore an efficient, cost-effective, and water-saving seasonal cold energy storage technique based on borehole heat exchangers to cool the condenser water in a 10 MW solar thermal power plant. The proposed seasonal cooling mechanism is designed for the areas under typical weather conditions to utilize the low ambient temperature during the winter season and to store cold energy. The main objective of this paper is to utilize the storage unit in the peak summer months to cool the condenser water and to replace the dry cooling system. Using the simulation platform transient system simulation program (TRNSYS), the borehole thermal energy storage (BTES) system model has been developed and the dynamic capacity of the system in the charging and discharging mode of cold energy for one-year operation is studied. The typical meteorological year (TMY) data of Dunhuang, Gansu province, in north-western China, is utilized to determine the lowest ambient temperature and operation time of the system to store cold energy. The proposed seasonal cooling system is capable of enhancing the efficiency of a solar thermal power plant up to 1.54% and 2.74% in comparison with the water-cooled condenser system and air-cooled condenser system respectively. The techno-economic assessment of the proposed technique also supports its integration with the condenser unit in the solar thermal power plant. This technique has also a great potential to save the water in desert areas.

Optimal configuration of grid-side battery energy storage system under power marketization

From the view of power marketization, a bi-level optimal locating and sizing model for a grid-side battery energy storage system (BESS) with coordinated planning and operation is proposed in this paper. Taking the conventional unit side, wind farm side, BESS side, and grid side as independent stakeholder operators (ISOs), the benefits of BESS are divided into direct and indirect parts. The direct revenue for BESS is the arbitrage of the peak-valley electricity price and auxiliary service compensation. The indirect revenue refers to the benefits that BESS provides to other ISOs, including wind curtailed energy savings, a reduction in the operating cost of units, and a decrease in network loss. To maximize the comprehensive benefits of BESS, the outer layer is a multi-objective optimal model for BESS locating and sizing based on a cost-benefit analysis. The inner layer is an optimal scheduling model that coordinates wind power, units, and BESS. Thus, a multi-objective bi-level model for the optimal configuration of BESS is established. In addition, by considering the impact of a charge/discharge strategy on the life cycle of BESS, the interaction between BESS planning and operation is introduced into the model based on the equivalent life loss. The multi-objective particle swarm optimization (PSO) based on the information entropy method and the second-order cone relaxation method is employed to solve the optimal model. Results based on an improved IEEE 39-node system verify the feasibility and effectiveness of the proposed model.

Implementation of Transient Stability Model of Compressed Air Energy Storage Systems

This paper discusses the implementation of a transient stability model of Compressed Air Energy Storage (CAES) systems in a power system analysis package. A block-diagram based model of a two-machine CAES system is proposed, including specific controls for active power, reactive power, and State of Charge (SoC), which consider limits associated with the cavern pressure. As an application, the model is implemented in Powertech's TSAT software connected to the 9-bus WSCC benchmark power system, which is then used to study the impact of a CAES facility in the transient and frequency stability of the system. Several contingencies are simulated comparing the CAES performance to a gas turbine and a base-case without storage, demonstrating that the CAES system improves the system transient stability due to its charging stage, controls, and additional inertia. Finally, the CAES model is used to study the effects of cavern sizes in the frequency of the system. It is shown that CAES systems have certain special characteristics that make them attractive as a storage technology to provide stability and regulation services, besides their energy arbitrage capabilities.

Advanced Model of Hybrid Energy Storage System Integrating Lithium-Ion Battery and Supercapacitor for Electric Vehicle Applications

One of the main technological stumbling blocks in the field of environmentally friendly vehicles is related to the energy storage system. It is in this regard that car manufacturers are mobilizing to improve battery technologies and to accurately predict their behavior. The work proposed in this article deals with the advanced electrothermal modeling of a hybrid energy storage system integrating lithium-ion batteries and supercapacitors. The objective is to allow the aging aspects of the components of this system to be taken into account. The development of a model including the electrothermal behaviors makes it possible to evaluate the progressive degradation of the performance of the hybrid energy storage system. The characterization of both components constituting the hybrid system is carried out via a hybrid particle swarm-Nelder-Mead (PSO-NM) optimization algorithm using the experimental data of an urban electric vehicle. The obtained results show the good performance of the developed model and confirm the feasibility of our approach. The use of the PSO-NM optimization algorithm facilitated the identification of the parameters of the developed model with high efficiency, as the error observed is less than 3%. The advanced model associated with an adapted sizing method can be used in many cases to compare energy management strategies in electric vehicle applications.

Battery Energy Storage Systems in Microgrids: Modeling and Design Criteria

Off-grid power systems based on photovoltaic and battery energy storage systems are becoming a solution of great interest for rural electrification. The storage system is one of the most crucial components since inappropriate design can affect reliability and final costs. Therefore, it is necessary to adopt reliable models able to realistically reproduce the working condition of the application. In this paper, different models of lithium-ion battery are considered in the design process of a microgrid. Two modeling approaches (analytical and electrical) are developed based on experimental measurements. The derived models have been integrated in a methodology for the robust design of off-grid electric power systems which has been implemented in a MATLAB-based computational tool named Poli.NRG (POLItecnico di Milano—Network Robust desiGn). The procedure has been applied to a real-life case study to compare the different battery energy storage system models and to show how they impact on the microgrid design.

Properties Dynamic Simulation of the Flywheel Energy Storage System Model with Speed-Current Double Closed Loop

The random fluctuation of output power of modern distributed power generation system brings many hidden dangers to the safe operation of power grid, and the application of energy storage system is the most effective way to smooth the output power of distributed power generation. Based on the analysis of the structure and charge-discharge dynamic performance of the flywheel energy storage system, the permanent magnet brushless DC motor (PMBLDCM) is proposed as the flywheel motor, and the charging and discharging mathematical model of the flywheel energy storage system based on PMBLDCM is established. Using MATLAB/Simulink, the simulation model of flywheel energy storage system with speed-current double closed Loop is established. The simulation results show that the system can effectively control the flywheel energy storage system to achieve two-way energy conversion, and effectively stabilize power fluctuations.