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Abstract

The optimal energy management (OEM) in a stand-alone microgrid (SMG) is a challenging job because of uncertain and intermittent behavior of clean energy sources (CESs) such as a photovoltaic (PV), wind turbine (WT). This paper presents the effective role of battery energy storage (BES) in optimal scheduling of generation sources to fulfill the load demand in an SMG under the intermittency of theWT and PV power. The OEM is performed by minimizing the operational cost of the SMG for the chosen moderate weather profile using an artificial bee colony algorithm (ABC) in four different cases, i.e. without the BES and with the BES having a various level of initial capacity. The results show the efficient role of the BES in keeping the reliability of the SMG with the reduction in carbon-emissions and uncertainty of the CES power. Also, prove that the ABC provides better cost values compared to particle swarm optimization (PSO) and a genetic algorithm (GA). Further, the robustness of system reliability using the BES is tested for the mean data of the considered weather profile.

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Authors and Affiliations

Navin Kumar Paliwal
Asheesh Kumar Singh
Navneet Kumar Singh
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Abstract

This paper proposes an electromechanical transient method to build a battery energy storage system-based virtual synchronous generator model, suitable for a large-scale grid. This model consists of virtual synchronous generator control, system limitation and the model interface. The equations of a second-order synchronous machine, the characteristics of charging/discharging power, state of charge, operating efficiency, dead band and inverter limits are also considered. By equipping the energy storage converter into an approximate synchronous voltage source with an excitation system and speed regulation system, the necessary inertia and damping characteristics are provided for the renewable energy power system with low inertia and weak damping. Based on the node current injection method by the power system analysis software package (PSASP), the control model is built to study the influence of different energy storage systems. A study on the impact of renewable energy unit fluctuation on frequency and the active power of the IEEE 4-machine 2-area system is selected for simulation verification. Through reasonable control and flexible allocation of energy storage plants, a stable and friendly frequency environment can be created for power systems with high-penetration renewable energy.
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Authors and Affiliations

Juntao Cui
1
Zhao Li
2
ORCID: ORCID
Ping He
2
ORCID: ORCID
Zhijie Gong
2
Jie Dong
2
ORCID: ORCID

  1. Lanzhou Resources and Environment Voc-Tech University, China
  2. Zhengzhou University of Light Industry, China
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Abstract

In microgrid distribution generation (DG) sources are integrated parallelly for the economic and efficient operation of a power system. This integration of DG sources may cause many challenges in a microgrid. The islanding condition is termed a condition in which the DG sources in the microgrid continue to power the load even when the grid is cut off. This islanding situation must be identified as soon as possible to avoid the collapse of the microgrid. This work presents the hybrid islanding detection technique. This technique consists of both active and parametric estimation methods such as slip mode shift frequency (SMS) and exact signal parametric rotational invariance technique (ESPRIT), respectively. This technique will easily distinguish between islanding and non-islanding events even under very low power perturbations. The proposed method also has no power quality impact. The proposed method is tested with UL741 standard test conditions.
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Authors and Affiliations

S. Jayanthi
1
S. Arockia Edwin Xavier
2
ORCID: ORCID
P.S. Manoharan
2
ORCID: ORCID

  1. Sapthagiri College of Engineering, Periyanahali, Dharmapuri, India
  2. Thiagarajar College of Engineering, Madurai, India
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Abstract

The overall efficiency of battery energy storage systems (BESSs) strongly depends on the temperature uniformity of the batteries, usually disregarded in studies of the integrated performance of BESSs. This paper presents a new battery thermal management system (BTMS) using a personalized air supply instead of a central air supply. Thermal models are established to predict the thermal behavior of BESSs with 400 battery packs. Moreover, several optimizations comprising the effect of the position and number of air inlets, the number, and angle of the baffles on the air distribution in the ducts are proposed. The results show that the distributed air supply from the main air inlet makes the air velocity in the main air ducts more uniform. It is demonstrated that air deflection is the main source of airflow inhomogeneity at the air outlets. The airflow uniformity is better when the baffles are added at the entrance and the bottom of each riser duct than at other locations. The improved air supply scheme makes the nonuniformity coefficient of air velocity reduced from 1.358 to 0.257. The findings can guide the selection of a cooling form to enhance the safety of BESSs.
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Authors and Affiliations

Zhu Xinlong
1
Shi Hong
1
Xu Wenbing
1
Pan Jiashuang
1
Zhang Tong
2
Wang Yansong
2

  1. College of Energy & Power Engineering, Jiangsu University of Science and Technology, Mengxi, Jingkou, Zhenjiang 212003, China
  2. Key Laboratory of Aircraft environment control and life support, MIIT, Nanjing University of Aeronautics & Astronautics, Yudao Street, Nanjing 210016, China
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Abstract

Climate change is driving the transformation of energy systems from fossil to renewable energies. In industry, power supply systems and electro-mobility, the need for electrical energy storage is rising sharply. Lithium-based batteries are one of the most widely used technologies. Operating parameters must be determined to control the storage system within the approved operating limits. Operating outside the limits, i.e., exceeding or falling below the permitted cell voltage, can lead to faster aging or destruction of the cell. Accurate cell information is required for optimal and efficient system operation. The key is high-precision measurements, sufficiently accurate battery cell and system models, and efficient control algorithms. Increasing demands on the efficiency and dynamics of better systems require a high degree of accuracy in determining the state of health and state of charge (SOC). These scientific contributions to the above topics are divided into two parts. In the first part of the paper, a holistic overview of the main SOC assessment methods is given. Physical measurement methods, battery modeling, and the methodology of using the model as a digital twin of a battery are addressed and discussed. In addition, adaptive methods and artificial intelligence methods that are important for SOC calculation are presented. Part two of the paper presents examples of the application areas and discusses their accuracy.
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Authors and Affiliations

Marcel Hallmann
1
ORCID: ORCID
Christoph Wenge
2
ORCID: ORCID
Przemyslaw Komarnicki
1
ORCID: ORCID

  1. Magdeburg–Stendal University of Applied Sciences, Germany
  2. Fraunhofer IFF Magdeburg, Germany
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Abstract

The use of lithium-ion battery energy storage (BES) has grown rapidly during the past year for both mobile and stationary applications. For mobile applications, BES units are used in the range of 10–120 kWh. Power grid applications of BES are characterized by much higher capacities (range of MWh) and this area particularly has great potential regarding the expected energy system transition in the next years. The optimal operation of BES by an energy storage management system is usually predictive and based strongly on the knowledge about the state of charge (SOC) of the battery. The SOC depends on many factors (e.g. material, electrical and thermal state of the battery), so that an accurate assessment of the battery SOC is complex. The SOC intermediate prediction methods are based on the battery models. The modeling of BES is divided into three types: fundamental (based on material issues), electrical equivalent circuit (based on electrical modeling) and balancing (based on a reservoir model). Each of these models requires parameterization based on measurements of input/output parameters. These models are used for SOC modelbased calculation and in battery system simulation for optimal battery sizing and planning. Empirical SOC assessment methods currently remain the most popular because they allow practical application, but the accuracy of the assessment, which is the key factor for optimal operation, must also be strongly considered. This scientific contribution is divided into two papers. Paper part I will present a holistic overview of the main methods of SOC assessment. Physical measurement methods, battery modeling and the methodology of using the model as a digital twin of a battery are addressed and discussed. Furthermore, adaptive methods and methods of artificial intelligence, which are important for the SOC calculation, are presented. In paper part II, examples of the application areas are presented and their accuracy is discussed.
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Authors and Affiliations

Marcel Hallmann
1
ORCID: ORCID
Christoph Wenge
2
ORCID: ORCID
Przemyslaw Komarnicki
1
ORCID: ORCID
Stephan Balischewski
2
ORCID: ORCID

  1. Magdeburg-Stendal University of Applied Sciences, Germany
  2. Fraunhofer IFF Magdeburg, Germany
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Abstract

Nowadays, there is a need to increase the continuous usage of the power electronic converters like AC-DC, DC-DC, and DC-AC based on various applications like mobile charge controller and telecom base station. Also, for power stability control, these converters are utilized in the renewable energy system (RES). The output cannot be stable for a longer duration due to the inappropriate switching pulse and continued usage of the converter. For resolving the above issues, the soft-switching technique is implemented in the proposed system for controlling both converter and inverter for proper energy stabilization during the continuous operation of devices. The main objective of this work is to improve the solar power system using high voltage gain DC / DC converter. Similarly, an inverter delivers the continuous AC power to the grid system without any fluctuations. The revolutionary substantial transformative control (RSTC) technique has been employed to monitor and control the converters used in this system. The additional advantage of this system is battery-based energy management, which is only utilized under necessary conditions. During the initial stage, RSTC will track the solar power, and it compares with the reference voltage and produces the appropriate pulse to the converter switch. Based on the switching pulse, the full-bridge converter (FBC) will also enhance the DC voltage by providing the constant voltage for the grid-connected inverter system. Secondly, the proposed RSTC controller will be monitoring voltage amplitude and frequency of grid power system. If any variation appears due to source power fluctuation, the controller will recognize it and automatically vary the pulse width modulation (PWM) of an inverter and compensate the grid power. The design analysis and operating approaches of the proposed converter are verified by MATLAB / Simulink 2017b. The performance analysis has been done with various parameters like total harmonics distortion (THD), steady-state error and converter efficiency.
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Authors and Affiliations

S. Umamaheswari
1
R. Karthigaivel
1
G. Satheesh Kumar
2
N. Vengadachalam
3

  1. PSNA College of Engineering and Technology, Kothandaraman nagar, Dindigul – 624622 Tamil Nadu, India
  2. SSM Institute of Engineering and Technology, Dindigul-Palani Highway, Dindigul, Tamil Nadu - 624002 India
  3. Malla Reddy Engineering College for Women, Maisammaguda, Dhulapally, Secunderabad-500100 Telangana, India

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