Parameters Of Energy Storage System Research Articles

Analysis of Impact of Control Strategies on Integrated Electric Propulsion System Performance During Icebreaking Process

Developing an efficient power system is an important way for icebreakers to respond to high maneuverability and strong fluctuation loads under icebreaking conditions. The performance of power systems under short-period, regularly fluctuating load-sea conditions has been intensively studied. However, the performance of the power system in the face of a long-period, stochastic multi-frequency fluctuation icebreaking process has not been fully explored, especially the parameter uncertainty and battery cycle life. In this study, an integrated electric propulsion system with an optimal control strategy is suggested for improving the power system’s dynamic performance and battery cycle life. First, an energy flow model with a diesel–electric unit as the main body and coupled energy storage system/hybrid energy storage system has been constructed. A comparative analysis of rule-based and optimization-based energy management strategies has been performed, and an optimized strategy with dynamic programming as global regulation at the upper level and model predictive control at the lower level is suggested to integrate the slow and fast dynamic powers and achieve adaptability to strong fluctuation loads. In this control strategy, the uncertainties of energy storage system/hybrid energy storage system parameters have been introduced to eliminate their impact on the system performance. Then, the icebreaking process with multi-frequency fluctuation has been simulated, and the hybrid energy storage system with battery and supercapacitor is recommended to reach multi-objective with the lowest power fluctuation of diesel–electric unit, highest efficiency, and the minimum battery degradation. Finally, the fuel oil consumption and emissions of the hybrid energy storage system have been discussed, and the optimized strategy can save fuel oil by up to 5.33% and reduce the CO2 emission by 22% during the icebreaking process, exhibiting great potential in the environmental friendliness and significant advantages in terms of low fuel oil consumption.

Tri-level expansion planning for transmission, energy storage, and renewable energy considering carbon emission limitation

In recent years, renewable energy (RE) has developed rapidly due to its environmentally friendly characteristics. However, RE has strong intermittency and volatility, and a high proportion of RE integration will have a huge impact on power systems. Moreover, some power systems also put forward requirements for RE utilization, which requires more flexible resources. Conventional units are limited in development under the carbon emission reduction policies. The energy storage system (ESS) can stabilize the volatility of RE power and alleviate transmission congestion. Therefore, to promote the energy transformation of power systems, it is necessary to jointly consider transmission network, ESS, and RE in power system planning. Considering that the planning decision-makers are different, this paper proposes a tri-level expansion planning model considering carbon emission limitation and RE development. In the upper-level (UL) problem, the transmission system operator constructs transmission lines and grid-side ESS to ensure load supply and carbon emission requirements. On the premise that the RE curtailment rate is within a certain range, the middle-level (ML) problem constructs RE units to maximize the RE installed capacity. Based on the construction results of the UL and ML problems, lower-level (LL) problems simulate economic dispatching from the perspective of the independent system operator. To solve the tri-level model, an equivalent bi-level model is transformed according to strong duality theory, and then the column and constraint generation (C&CG) algorithm is adopted to solve the bi-level problem. In case studies, the numerical results analyze the impacts of carbon emissions, RE curtailment rate, and ESS parameters on the planning results, which verifies the rationality of the approach proposed in this paper.

Optimal Sizing and Power System Control of Hybrid Solar PV-Biogas Generator with Energy Storage System Power Plant

In this paper, the electrical parameters of a hybrid power system made of hybrid renewable energy sources (HRES) generation are primarily discussed. The main components of HRES with energy storage (ES) systems are the resources coordinated with multiple photovoltaic (PV) cell units, a biogas generator, and multiple ES systems, including superconducting magnetic energy storage (SMES) and pumped hydro energy storage (PHES). The performance characteristics of the HRES are determined by the constant power generation from various sources, as well as the shifting load perturbations. Constant power generation from a variety of sources, as well as shifting load perturbations, dictate the HRES’s performance characteristics. As a result of the fluctuating load demand, there will be steady generation but also fluctuating frequency and power. A suitable control strategy is therefore needed to overcome the frequency and power deviations under the aforementioned load demand and generation conditions. An integration in the environment of fractional order (FO) calculus for proportion-al-integral-derivative (PID) controllers and fuzzy controllers, referred to as FO-Fuzzy-PID controllers, tuned with the opposition-based whale optimization algorithm (OWOA), and compared with QOHSA, TBLOA, and PSO has been proposed to control the frequency deviation and power deviations in each power generation unites. The results of the frequency deviation obtained by using FO-fuzzy-PID controllers with OWOA tuned are 1.05%, 2.01%, and 2.73% lower than when QOHSA, TBLOA, and PSO have been used to tune, respectively. Through this analysis, the algorithm’s efficiency is determined. Sensitivity studies are also carried out to demonstrate the robustness of the technique under consideration in relation to changes in the sizes of the HRES and ES system parameters.

Investigating the influence of lithium-ion batteries degradation on the parameters of the electric power storage system

This article deals with the use of a battery-based energy storage system (ESS) to ensure the required power output of power plants (PP) based on renewable energy sources (RES) integrated into the electric power system (EPS). A model of a lithium-iron-phosphate battery-based ESS has been developed that takes into account the calendar and cyclic degradation of the batteries, and the limitations of the conversion subsystem. The nominal capacity and power of the ESS is proposed to be chosen based on two levels of tolerances: the preset range of RES-based power output and the relative period of deviation from the committed power. When choosing the ESS parameters, the features of its operation, as well as restrictions on the part of the EPS, were taken into account. The developed method was applied to the EPS model including solar power plants (SPP) and wind power plants (WPP). In the end of the article, the obtained results are analyzed and the effect of the ESS operation on its residual capacity and service life is shown.

Operating conditions of electric energy storage system in DC traction power supply for single-track sections of railways

Considered are the issues of using electric energy storage system in the traction power supply of direct current of a single-track section. An overview of the main directions of domestic and foreign research in the field of using these systems to increase the capacity and energy efficiency of power supply systems is given. Modeling the operation of energy storage system in traction power supply is based on the calculation of load graphs within the boundaries of inter-substation zones, formed depending on the conditions for the passage of trains and traction load on the railway section. The main provisions of the method for choosing locations and determining the parameters of energy storage system in traction power supply are considered. On the example of one of the inter-substation zones of the Sverdlovsk railway, the influence of the power of the active sectioning station on the increase in the minimum voltage level at the pantograph of the electric rolling stock is shown. The graphs of the degree of charge and the corresponding frequency distributions are given, which make it possible to evaluate the operating conditions of the electric energy storage system depending on the conditions for the formation of the traction load, as well as the graphs of the load of the electric energy storage system and the corresponding charging characteristics for the operating conditions at the sectioning post. On the example of the section under consideration, the dependence of the discharge depth of the electric energy storage system on the nominal energy intensity is shown. Based on the results of calculations, an evaluation was made of the options for passing train batches in the even and odd direction in comparison with the schedule of the performed train operation. The range of variation of the nominal values of power and energy intensity of the electric energy storage system is obtained. Comparison of the accumulation system parameters for single- and double-track sections of railways, including those with a predominance of passenger traffic, is carried out.

Robust Non-Fragile Fuzzy Control of Uncertain DC Microgrids Feeding Constant Power Loads

This paper investigates the problem of dynamic stabilization of dc microgrids (MGs) through a robust non-fragile fuzzy control synthesis of power buffer. The suggested robust fuzzy controller is designed to quickly stabilize the MGs by circulating the power between the dc link and an energy storage system (ESS). By employing the exponential stability analysis and Takagi–Sugeno fuzzy modeling, sufficient controller design conditions are derived in terms of linear matrix inequalities, which bring about a simple, systematic, and effective controller. The proposed approach is resilient against the uncertainties of the dc MG and ESS parameters. To show the merits of the proposed approach, it is applied to a dc MG that feeds one constant power load. It is shown that the proposed approach is more robust against system and controller uncertainties compared to the existing results. Finally, experimental results are then presented that show the transient performance improvement of the closed-loop system compared to the state-of-the-art methods.

Refined ramp event characterisation for wind power ramp control using energy storage system

With the advantages of fast response and bidirectional charge/discharge, an energy storage system (ESS) plays a promising role in wind power ramp control. In this study, an optimisation model based on refined ramp event characterisation is proposed to achieve continuous wind power ramp control using ESS. Firstly, four kinds of ramp scenarios are characterised considering both the wind power ramp event prediction and the charge/discharge state of ESS. State of charge of ESS is managed within its limits during ramp control, based on the classified ramp scenarios. Secondly, for the classified ramp scenarios, an active adjustment strategy is proposed to decide the expected charging/discharging energy of ESS according to the conditions of wind power and ESS. Thus, an appropriate energy storage reserve can be determined for anticipated ramp events. Refined ramp event characterisation is able to achieve better control performance with higher satisfaction of ramp requirement, less wind energy curtailment as well as promising adaptability to different ramp event predictions, wind conditions and changes of ESS parameters. The effectiveness of the proposed method is verified through case studies with real-world data from a 100 MW wind farm in China.

Research on Simulated Inertia Coordination Control Strategy of VSG Based on Energy Storage

With the development of new energy and micro grid, inverter plays an important role as the interface of distributed new energy to realize power conversion. However, the introduction of various power electronic components not only enhances the response speed and flexibility of the micro grid, but also greatly reduces the overall inertia of the system. VSG control technology is introduced in this paper. At the same time, through the in-depth analysis of energy storage system, the inertial parameters of energy storage system are deduced. The VSG control and the energy storage system inertial parameters are matched to increase the system inertia and damping. Aiming at the power response part of multi-machine system, the inertial parameters of multi-machine system are controlled uniformly, which makes the whole system achieve good power response and distribution. At last, a simulation model was set up by MATLAB for verification and analysis.

Prediction of Selected Parameters of Energy Storage System using Recurrent Neural Networks

This article presents a methodology of the prediction of chosen parameters of an energy storage system in subsequent recharging cycles. Because of a nonlinear description of process dynamics, a coupling of the terminal voltage and temperatures of a battery, the Recurrent Artificial Neural Network structure (R-ANN) is used. A training and testing data were gathered at the laboratory stand with the Valve-Regulated Lead-Acid Absorbent Glass Mat battery (VRLA AGM). As a result, we present an experimental evaluation of the proposed methodology.

A Heuristic Combinatorial Optimization Algorithm for Load-Leveling and Peak Demand Reduction using Energy Storage Systems

A method for applying combinatorial optimization algorithms to Energy Storage System (ESS) scheduling is presented in this paper. Scheduling is essential for the integration of ESS in electrical networks at grid level or at consumer level to achieve the objectives of integration such as constraint management or energy cost reduction and for efficient storage dispatch. It also shows that for a time-of-use (ToU) tariff scheme based on the shape of the demand profile with higher prices tied to peak periods, effective load-leveling, and peak demand reduction always leads to energy cost reduction. While other methods usually require more information such as generation cost curves or ToU tariffs to schedule ESS, the proposed method uses only demand profile information and ESS parameters to achieve load-leveling and peak demand reduction and also considers the entire optimization time horizon. This is done by combining heuristic bin packing and subset sum algorithms with specific modifications to the standard forms and through transformations. A case study is presented in which the algorithm is used to schedule household ESS with repurposed electric vehicle batteries and the results are compared to a demand response scheme on the same setup.

Optimal Energy Management and MPC Strategies for Electrified RTG Cranes with Energy Storage Systems

This article presents a study of optimal control strategies for an energy storage system connected to a network of electrified Rubber Tyre Gantry (RTG) cranes. The study aims to design optimal control strategies for the power flows associated with the energy storage device, considering the highly volatile nature of RTG crane demand and difficulties in prediction. Deterministic optimal energy management controller and a Model Predictive Controller (MPC) are proposed as potentially suitable approaches to minimise the electric energy costs associated with the real-time electricity price and maximise the peak demand reduction, under given energy storage system parameters and network specifications. A specific case study is presented in to test the proposed optimal strategies and compares them to a set-point controller. The proposed models used in the study are validated using data collected from an instrumented RTG crane at the Port of Felixstowe, UK and are compared to a standard set-point controller. The results of the proposed control strategies show a significant reduction in the potential electricity costs and peak power demand from the RTG cranes.

Energy storage system scheduling for peak demand reduction using evolutionary combinatorial optimisation

This paper is concerned with finding an optimal energy storage system (ESS) schedule for peak demand reduction and load-levelling given only the information certainly available to and controllable by the Distribution Network Operator (DNO) which are the substation demand profile information and the DNO-owned ESS parameters. Methods such as set-point control are usually suboptimal and can create new peaks. Other methods require more parameters and actions than the DNO can fully control to form the basis for optimisation and can be computationally complex. The method presented in this paper uses simple heuristics to find possible optimal operation points for the ESS and improves the solutions found using genetic algorithm optimisation. A case study is presented showing a UK distribution network with a peak capacity violation which is resolved using the method and the results are compared to a closed-loop set-point control method.

SOC Estimation of LiFePO4 Battery based on Improved Ah Integral Method

State of charge (SOC) is the most important status parameters of energy storage system, which is able to predict the available mileage of electric vehicle. In fact, the accuracy of SOC estimation plays a vital role in the usability and security of the battery. To fully consider the practical demands, a novel method to predict SOC of LiFePO4 battery is presented in this paper, which defines the correct coefficient separately under two working conditions of charging and discharging. Based on effective factors such as coulombic efficiency, charge and discharge current, and temperature, an Ah integral SOC estimation method with two kinds of efficiency correct coefficients is established by performing massive experimental study. Experiments prove that the estimated error of SOC is less than 5%. Compared with the original Ah method, the improved Ah method is more advantageous in the accuracy and reliability. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.3016