An adaptative control strategy for interfacing converter of hybrid microgrid based on improved virtual synchronous generator

Liang, Zhang; Wang, Xuesong; Zhang, Zhe; Cui, Ying; Lyu, Ling; Cai, Guowei

doi:10.1049/rpg2.12293

Cited by 50 publications

(20 citation statements)

References 20 publications

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“…At this time, the system angular frequency ω m and ω grid remain equal, and the system runs at a new equilibrium point. Table 1 summarizes the running status during this process [16,17].…”

Section: Principle Of Adaptive Virtual Inertia and Damping Coefficientmentioning

confidence: 99%

Power‐frequency oscillation suppression algorithm for AC microgrid with multiple virtual synchronous generators based on fuzzy inference system

Zhang

Zheng

Cai

et al. 2022

IET Renewable Power Gen

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In the microgrid, virtual synchronous generator technology can significantly enhance the anti‐interference characteristics of the system frequency and bus voltage, as well as solve the problems of insufficient damping and low inertia. However, the system frequency and active power oscillation caused by power fluctuations and grid faults threaten the stable operation of the grid seriously. Therefore, for an alternating current (AC) microgrid multi‐virtual synchronous generator (VSG) parallel system, an improved virtual synchronous generator control algorithm based on a fuzzy inference system is proposed, which adjusts the values of virtual inertia and damping coefficient dynamically through fuzzy logic rules to realize the coordinated control of the two. The enhanced VSG algorithm described in this research has a substantial influence on power‐frequency oscillation suppression, decreases active power and frequency overshoot, shortens the adjustment time, and improves system frequency stability active power, according to simulation and experimental findings.

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Section: Principle Of Adaptive Virtual Inertia and Damping Coefficientmentioning

confidence: 99%

Power‐frequency oscillation suppression algorithm for AC microgrid with multiple virtual synchronous generators based on fuzzy inference system

Zhang

Zheng

Cai

et al. 2022

IET Renewable Power Gen

Self Cite

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“…The authors in [66] conducted a study on reactive and active power flow regulation in islanded distributed microgrids. In [67,68], authors employed an optimum DR to Plugin Hybrid Electric Vehicles (PHEVs) aggregated at parking stations for contributing as ESSs and supplying in the power grid to obtain energy balancing equilibrium.…”

Section: Stochastic Techniquesmentioning

confidence: 99%

Optimal Demand-Side Management Using Flat Pricing Scheme in Smart Grid

Albogamy

Ashfaq

Hafeez³

et al. 2022

Processes

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This work proposes a framework to solve demand-side management (DSM) problem by systematically scheduling energy consumption using flat pricing scheme (FPS) in smart grid (SG). The framework includes microgrid with renewable energy sources (solar and wind), energy storage systems, electric vehicles (EVs), and building appliances like time flexible, power flexible, and base/critical appliances. For the proposed framework, we develop an ant colony optimization (ACO) algorithm, which efficiently schedules smart appliances, and EVs batteries charging/discharging with microgrid and without (W/O) microgrid under FPS to minimize energy cost, carbon emission, and peak to average ratio (PAR). An integrated technique of enhanced differential evolution (EDE) algorithm and artificial neural network (ANN) is devised to predict solar irradiance and wind speed for accurate microgrid energy estimation. To endorse the applicability of the proposed framework, simulations are conducted. Moreover, the proposed framework based on the ACO algorithm is compared to mixed-integer linear programming (MILP) and W/O scheduling energy management frameworks in terms of energy cost, carbon emission, and PAR. The developed ACO algorithm reduces energy cost, PAR, and carbon emission by 23.69%, 26.20%, and 15.35% in scenario I, and 25.09%, 31.45%, and 18.50% in scenario II, respectively, as compared to W/O scheduling case. The results affirm the applicability of the proposed framework in aspects of the desired objectives.

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“…where K is the portion of the power-electronic interface capacity, P i is the active load, and Q i is reactive at the Q-C buses [23][24][25][26][27][28][29][30][31][32][33][34][35][36].…”

Section: Proposed Algorithmmentioning

confidence: 99%

A New Approach for the Incorporation of the End-User’s Smart Power–Electronic Interface in Voltage Support Application

et al. 2022

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Technology advancement in power–electronic interfaces and their evolution open an opportunity to end-users to benefit from their newfound capability. For the end-users, power–electronic interfaces can act as Distributed Energy Resources (DERs) for reactive power injection and absorption. If these power–electronic interface capabilities can be properly integrated into traditional utility system operations, they can be used as beneficial tools for distribution management and voltage profile enhancement. Considering the present distribution system, it is not possible to communicate to all DERs. In this paper, we considered two proposed residential-control and droop-control methods. The multi-criteria decision-making technique (MCDM), along with fuzzy theory, was used to prioritize candidate buses for their participation in the Volt-VAR program. In this paper, the contribution of active DERs in reactive power compensation was evaluated.

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An adaptative control strategy for interfacing converter of hybrid microgrid based on improved virtual synchronous generator

Cited by 50 publications

References 20 publications

Power‐frequency oscillation suppression algorithm for AC microgrid with multiple virtual synchronous generators based on fuzzy inference system

Power‐frequency oscillation suppression algorithm for AC microgrid with multiple virtual synchronous generators based on fuzzy inference system

Optimal Demand-Side Management Using Flat Pricing Scheme in Smart Grid

A New Approach for the Incorporation of the End-User’s Smart Power–Electronic Interface in Voltage Support Application

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