Energy management strategy with two degrees of freedom for hybrid energy storage systems in islanded DC microgrids

Zhang, Yuhan; Du, Gonghuan; Lei, Yanxiong

doi:10.1049/iet-pel.2020.0404

Cited by 10 publications

(8 citation statements)

References 24 publications

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“…In addition, the sum of squares of the rank coefficients, ρ p , represents the statistical measure of how close the obtained fluctuations of C sp are to the regressionbased model employed in Pearson correlation coefficient (Equation [8]) 44 and is also known as the coefficient of determination. 45 A value close/equal to 1 indicates that the Pearson model captures all the variations of C sp .…”

Section: Sensitivity Analysis: Sim Scenariomentioning

confidence: 99%

“…This intricate balance is affected by the random yet inevitable fluctuations in the extrinsic and intrinsic parameters which eventually affects stability and durability of the EES systems. Previously, several control and energy management strategies have been developed for the battery-supercapacitor hybrid EES, 8 battery EES, 9 and supercapacitor-based auxiliary power systems. 10 All the aforementioned studies adopt a lumped model or a circuit model focused on developing the control and optimization strategies.…”

Section: Introductionmentioning

confidence: 99%

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Monte Carlo‐based sensitivity analysis of an electrochemical capacitor

et al. 2021

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The operation of electrochemical capacitors depends not only on extrinsic operating and design parameters, but also intrinsic physical, material, and electrochemical parameters. Fluctuations in these stochastic parameters can significantly influence the performance and may lead to quicker degradation of the electrochemical capacitors, thereby affecting their durability and reliability. Thus, it is important to quantify the sensitivities of these extrinsic and intrinsic parameters and correlate them with the performance, to delay the inevitable performance degradation. To achieve this, we perform Monte Carlo simulations (MCS) followed by sensitivity analysis under high and low charge/ discharge current (load) conditions. The MCS is statistically performed by varying all the stochastic parameters simultaneously. We then identify the critical parameters that affect the performance under different load conditions, which provides insights into optimal operation of electrochemical capacitors. The thickness of positive electrode and the radius of active material were identified as the most significant parameters under low and high load conditions, respectively. Furthermore, we derive reduced order surrogate models with at least 95% accuracy using supervised machine learning techniques to predict the performance without solving the full physics-based model.

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Section: Sensitivity Analysis: Sim Scenariomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Monte Carlo‐based sensitivity analysis of an electrochemical capacitor

et al. 2021

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“…However, balancing the PV's generated power and load is challenging due to the limitation on the availability of power and intermittency of generation. This challenge can be tackled by utilizing energy storage systems (ESSs) as well as implementing effective dynamic power and energy management systems [4,5]. Among many available ESS devices on the market, battery energy storages systems (e.g., lithium-ion or lead acid batteries) are one of the prevalent energy storages for various applications including residential buildings, renewable energy systems and microgrids.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, sudden changes in the input power of the HESS (e.g., a sudden load variation) may impose a considerable stress on the SC module that can immediately fully charge or discharge the SC. To avoid state of charge (SOC) violation of SC and increase the system efficiency adaptive filtering techniques can be applied [5, 23, 24]. In adaptive rule‐based filters, typically a rule‐based supervisory controller is utilized to relax or deactivate the filter if the SOC of SC violates a certain limit.…”

Section: Introductionmentioning

confidence: 99%

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A distributed rule‐based power management strategy in a photovoltaic/hybrid energy storage based on an active compensation filtering technique

Abadi

Bidram

2021

IET Renewable Power Gen

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This paper proposes a distributed rule-based power management strategy for dynamic power balancing and power smoothing in a photovoltaic (PV)/battery-supercapacitor hybrid energy storage system. The system contains a PV system, a battery-supercapacitor hybrid energy storage system (HESS), and a group of loads. Firstly, an active compensation technique is proposed which improves the efficiency of the power smoothing filter. Then, a distributed supervisory control technique is employed that prevents the BESS and SC from SOC violation while maintaining the balance between generation and load. To this end, the system components are divided into three different reactive agents including an HESS agent, a PV agent, and a load agent. These agents react to the system changes by switching their operational mode upon satisfying a predefined rule. To analyse the hybrid dynamical behaviour of the agents and design the supervisory controllers, the agents are modelled in hybrid automata frameworks. It is shown that the proposed distributed approach reduces the complexity of the supervisory control system and increases its scalability compared to its equivalent centralized method. Finally, the performance of the proposed approach is validated using a test system simulated in MATLAB/Simulink.

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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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Energy management strategy with two degrees of freedom for hybrid energy storage systems in islanded DC microgrids

Cited by 10 publications

References 24 publications

Monte Carlo‐based sensitivity analysis of an electrochemical capacitor

Monte Carlo‐based sensitivity analysis of an electrochemical capacitor

A distributed rule‐based power management strategy in a photovoltaic/hybrid energy storage based on an active compensation filtering technique

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

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