A Grid-Connected Microgrid Model and Optimal Scheduling Strategy Based on Hybrid Energy Storage System and Demand-Side Response

Jing, Yaqian; Wang, Honglei; Hu, Yu-Jie; Li, Chengjiang

doi:10.3390/en15031060

Cited by 6 publications

(2 citation statements)

References 19 publications

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“…The difficulty of BESS sizing and estimating the costs of such networks is related to the stochastic nature of renewable energy generation and abrupt load fluctuations [16]. At the same time, not enough research has been devoted to the issue of developing a model for optimal BESS sizing that would take into account the rate of battery storage degradation [17]. In some cases, the battery lifetime may differ considerably from the manufacturer's stated lifetime due to different conditions of battery operation.…”

Section: Research Problem Statementmentioning

confidence: 99%

Review of Battery Energy Storage Systems Modeling in Microgrids with Renewables Considering Battery Degradation

et al. 2022

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The modeling of battery energy storage systems (BESS) remains poorly researched, especially in the case of taking into account the power loss due to degradation that occurs during operation in the power system with a large penetration of generation from renewables and stochastic load from electric vehicles (EV). Meanwhile, the lifetime varies considerably from the manufacturer’s claim due to different operating conditions, and also depends on the level of renewable energy sources (RES) penetration, cyclic operation, temperature, discharge/charge rate, and depth of discharge. Choosing a simplistic approach to the degradation model can lead to unreliable conclusions in choosing the best management strategy and significant investment and operating costs. Most existing BESS models in stationary applications either assume zero degradation costs for storage or simplify battery life to a linear function of depth of discharge (DOD), which can lead to additional error in estimating the cost of BESS degradation. The complexity of constructing a lifetime model of BESS is due to the presence of nonlinear degradation of BESS at the beginning and at the end of the lifetime, as well as the difficulty in obtaining a large amount of experimental data that are close to the real-world operating conditions for the construction of most models. This article analyzes the features of BESS that are specific to their operation in microgrids in terms of the influence of the main stress factors on the degree of BESS degradation. This study also provides a review of existing models for assessing battery degradation.

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Section: Research Problem Statementmentioning

confidence: 99%

Review of Battery Energy Storage Systems Modeling in Microgrids with Renewables Considering Battery Degradation

et al. 2022

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“…FIGURE 5General-topology diagram for (A) buck-boost converter-based charge controller. (B) Energy dispatch scheduling of grid-connected solar PV system with battery storage(Jing et al, 2022). (C) Ideal charging and discharging schedule for a hybrid PV-battery system(Kapoor and Sharma, 2020).…”

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Current and future prospective for battery controllers of solar PV integrated battery energy storage systems

Hasan

Altinoluk²

2023

Front. Energy Res.

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Solar photovoltaic (PV) microgrids have gained popularity in recent years as a way to improve the stability of intermittent renewable energy generation in systems, both off-grid and on-grid, and to meet the needs of emergency settings during natural catastrophes. Over the last several decades, researchers have been interested in improving the efficiency of photovoltaic (PV) systems. Solar-battery charge controllers based on various algorithms are continuously and intensively employed to improve energy transfer efficiency and reduce charging time. This paper presents state-of-the-art solar photovoltaic (PV) integrated battery energy storage systems (BESS). An overview of and motivations for PV-battery systems is initially introduced, followed by the survey methodology and its contributions. In addition, this study classifies residential solar PV systems and battery charge controllers with their corresponding references in the review structure, which also provides details on battery charger topologies. Subsequently, an analytical review of the PV-Battery charge controller and the failure probability of such systems is discussed to determine the system components that mostly fail and their importance in the system. Finally, recommendation amendments to the existing charge controller that potentially contribute to increasing the system efficiency, reducing the failure probabilities, and reducing the cost are presented as future design concepts for the entire system.

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Optimal operation and maintenance of energy storage systems in grid-connected microgrids by deep reinforcement learning

Pinciroli,

Baraldi,

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et al. 2023

Applied Energy

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A Grid-Connected Microgrid Model and Optimal Scheduling Strategy Based on Hybrid Energy Storage System and Demand-Side Response

Cited by 6 publications

References 19 publications

Review of Battery Energy Storage Systems Modeling in Microgrids with Renewables Considering Battery Degradation

Review of Battery Energy Storage Systems Modeling in Microgrids with Renewables Considering Battery Degradation

Current and future prospective for battery controllers of solar PV integrated battery energy storage systems

Optimal operation and maintenance of energy storage systems in grid-connected microgrids by deep reinforcement learning

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