Deterministic-based energy management of DC microgrids

Ghadimi, Noradin; Nojavan, Sayyad; Abedinia, Oveis; Dehkordi, Abbas Barzandeh

doi:10.1016/b978-0-12-817491-3.00002-7

Cited by 10 publications

(9 citation statements)

References 25 publications

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“…) where 𝐶 𝑏𝑢𝑠 is the DC bus capacitance, 𝐶 𝑆𝐶 the SC capacitance, 𝑣 𝑏𝑢𝑠 is the DC bus voltage, and 𝑣 𝑆𝐶 is the instantaneous voltage of the SC. Based on the proposed system configuration, the bus energy 𝐸 𝑏𝑢𝑠 can be expressed in function of the power-sharing through the DC bus as follows [26]: 𝐸 ̇𝑏𝑢𝑠 = 𝑃 𝑆𝐶𝑜 + 𝑃 𝐵𝑜 − 𝑃 𝑙𝑜𝑎𝑑 (12) where 𝑃 𝑆𝐶𝑜 and 𝑃 𝐵𝑜 are the transferred power from the SC and battery to the load, respectively, which can be calculated from Eqs. (13 and 14) as follows:…”

Section: B Flatness Control Based Hpsmentioning

confidence: 99%

“…Furthermore, the first input control represents the SC power reference which can be written from Eqs. (10)(11)(12)(13)(14)(15)(16)(17)(18)(19) as,…”

Section: Supercapacitor and Battery Control Loopmentioning

confidence: 99%

“…Therefore, this problem can be avoided using the SC, which supplies the required power to regulate the DC load voltage during transient operation or sudden load changes [8]. To improve their performance and increase the system efficiency, hybridizing these sources is considered to protect them from temperature shocks or a lack of state of charge (SOC) control of the battery [9][10][11][12]. Another advantage of using the SC is to alleviate the high-frequency system disturbances and fluctuation of current flowing in/out of the battery that affects the longevity of the battery.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Flatness Based Energy Management Strategy for Hybrid Supercapacitor/Lithium-ion Battery Power System

et al. 2022

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This article offers a flatness theory-based energy management strategy (FEMS) for a hybrid power system consisting of a supercapacitor (SC) and lithium-ion battery. The proposed FEMS intends to allocate the power reference for the DC/DC converters of both the battery and SC while attaining higher efficiency and stable DC bus voltage. First, the entire system model is analyzed theoretically under the differential flatness approach to reduce the model order as a flat system. Second, the proposed FEMS is validated under different load conditions using MATLAB/Simulink. Thus, this FEMS provides high-quality energy to the load and reduces the fluctuations in the bus voltage. Moreover, the performance of the FEMS is compared with the load following (LF) strategy. The obtained results show that the proposed FEMS meet the real load power under fast variations with good power quality compared to the classical LF strategy, where the maximum overshoot of the bus voltage is 5%.

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Section: B Flatness Control Based Hpsmentioning

confidence: 99%

“…Furthermore, the first input control represents the SC power reference which can be written from Eqs. (10)(11)(12)(13)(14)(15)(16)(17)(18)(19) as,…”

Section: Supercapacitor and Battery Control Loopmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Efficient Flatness Based Energy Management Strategy for Hybrid Supercapacitor/Lithium-ion Battery Power System

et al. 2022

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“…However, the short‐term fluctuations in the power systems cause stress in the storage devices, degrading their lifetime. Therefore, many solutions have been formulated by researchers to improve the efficiency of storage systems 28‐33 …”

Section: Introductionmentioning

confidence: 99%

Supply energy management methods for a direct current microgrid: A comprehensive review

Varshnry,

Lather,

Dahiya

2024

Energy Storage

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The revolution of microgrids (MGs) in the modern world has impacted the power systems to deal with the loads with optimal use of renewable energy resources (RERs). In the models consisting of energy management systems (EMS) and generation sources, there will be power fluctuations between the source and the load under certain conditions due to the unpredictable behavior of RERs. Therefore, a reliable scheme has to be implemented between the source and the load to ensure optimal performance of direct current (DC)‐MGs. This article has presented a review of the EMS models introduced by various researchers to enable optimal power supply and efficient operation of the DC‐MGs. A thorough illustration of the schemes adopted to provide efficient operations under grid‐connected and islanded mode of operations are provided. The effects and advantages of centralized and decentralized EMSs are discussed. The role of a battery energy storage system (BESS) in microgrid scheduling is presented and compared with a few other energy storage systems. The scheduling strategies implemented for optimal EMS using different algorithms and techniques are elaborated. In addition, the effects of battery degradation and the formulated solutions to improve the degraded models with improved battery life are also provided with cycle life and calendar life. Then, the lithium ion and lead acid BESS effect on microgrid EMS is presented. Finally, the energy management methods for DC‐MGs end with challenges, research gaps, and future direction.

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“…Demand response (DR) plays an important role in decreasing energy use at peak hours and can help increase efficiency and reliability in operation [2,[5][6][7]. DR is a program that encourages homeowners to decrease their energy consumption during periods of high-power demand.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Demand-Response-Based Intelligent Home Energy Management System with Binary Backtracking Search Algorithm

et al. 2020

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In many nations, limited power from providers and an increase in demand for electricity have created new opportunities that can be used by home energy management systems (HEMSs) systems to enforce proper use of energy. This paper presents a virtual intelligent home with demand response (DR) model home appliances that have an inverter air conditioner, water pump, washing machine, and inverter refrigerator. A binary backtracking search algorithm (BBSA) is proposed to introduce the optimal schedule controller. With the proposed BBSA schedule controller, the highest energy consumption during DR can be reduced by 33.84% during the weekends and by 30.4% daily during the weekdays. The results indicate the effectiveness of the proposed HEMS. Additionally, the model can control the appliances and maintain total residential energy consumption below the defined demand limit.

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Deterministic-based energy management of DC microgrids

Cited by 10 publications

References 25 publications

Efficient Flatness Based Energy Management Strategy for Hybrid Supercapacitor/Lithium-ion Battery Power System

Efficient Flatness Based Energy Management Strategy for Hybrid Supercapacitor/Lithium-ion Battery Power System

Supply energy management methods for a direct current microgrid: A comprehensive review

Optimization of Demand-Response-Based Intelligent Home Energy Management System with Binary Backtracking Search Algorithm

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