Research of active load regulation method for distribution network considering distributed photovoltaic and electric vehicles

Fang, Yaqi; Li, Rui; Wang, Linong; Song, Bin; Li, Enwen; Zhang, Qiushi

doi:10.1049/joe.2017.0768

Cited by 6 publications

(5 citation statements)

References 9 publications

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“…Limitation in the existing studies [3,7,9,14,26] EVs' charge/discharge rate threshold limits are not considered [13,34] EVs' battery SOC limit, that is, maximum and minimum, is missing [8,17] The SOC limit is considered, but the EV battery charge and discharge rate limits are not considered [10,11,13,16,25] Charging station aggregator not considered to coordinate a large fleet of EVs' energy [15,[26][27][28] EVs' battery capacity degradation-dependent variables are not considered [22,23] EVs' charging station power factor and the distribution network voltage limits are missing Abbreviations: EV, electric vehicle; SOC, state-of-charge. Finally, the PQ control strategy receives the control information from the EVCS aggregator control and available energy from EVCS.…”

Section: Referencesmentioning

confidence: 99%

“…An optimal active load control method of three‐phase unbalance in the distribution network is presented in Ref. [27]. An optimal dispatching strategy has been proposed to satisfy EVs' driving demand and maximise the aggregator's economic benefits when it participates in FR [28].…”

Section: Introductionmentioning

confidence: 99%

“…[13,34], and EVs battery capacity degradation not considered in Ref. [15,[26][27][28]. Furthermore, some works focus on the uncontrolled and uncoordinated EV charge/discharge rate characteristics, which affect EVs' battery life cycle due to overcharging, fully charge/discharge, and high charge/discharge rate.…”

Section: Introductionmentioning

confidence: 99%

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Coordinated control strategy for vehicle‐to‐grid support at distribution node

et al. 2022

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The increasing number of electric vehicles (EVs) creates voltage rise/drop problems when integrated into a distribution node (DN). This generally occurs when EVs inject energy to or draw energy from the DN in a stochastic manner. A vehicle-to-grid service for voltage support of DN through controlled and coordinated EV charging and discharging techniques to maintain the DN voltage within the threshold limits is proposed. In this context, a fuzzy logic control (FLC) is developed to generate reference power signal and the power flow direction based on DN voltage and electric vehicle charging station's (EVCS) available energy. Here, the EVCS is a place where the EVs are charged and/or participate for grid support. Then, an EVCS aggregator is implemented to coordinate the large fleet of EVs based on FLC output and EV's available energy. Furthermore, an EV's battery charge and discharge rate controller is developed to control the EV's energy based on EVCS aggregator output and charge/discharge rate threshold limits. Finally, an active and reactive power control methodology is implemented to maintain DN voltage profile within the threshold limits. Extensive simulations are conducted based on real data from a radial distribution system. The results show that the EVCS can successfully maintain the DN voltage within the threshold limit through the proposed control and coordination strategy.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Referencesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Coordinated control strategy for vehicle‐to‐grid support at distribution node

et al. 2022

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“…Almost all previous studies are based on centralized control and, therefore, they are generally complex and need local measurement and communication between a centralized master controller and the prosumers [22]. By contrast, in a distributed control scheme, control actions of each prosumer are decided based on local measurements [23][24][25]. Though, these studies do not deal with voltage imbalance, which is especially helpful for a more suitable practical implementation in existing networks.…”

Section: Prior Studies' Historical Context To the Researchmentioning

confidence: 99%

Photovoltaic Power Converter Management in Unbalanced Low Voltage Networks with Ancillary Services Support

et al. 2019

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The proliferation of residential photovoltaic (PV) prosumers leads to detrimental impacts on the low-voltage (LV) distribution network operation such as reverse power flow, voltage fluctuations and voltage imbalances. This is due to the fact that the strategies for the PV inverters are usually designed to obtain the maximum energy from the panels. The most recent approach to these issues involves new inverter-based solutions. This paper proposes a novel comprehensive control strategy for the power electronic converters associated with PV installations to improve the operational performance of a four-wire LV distribution network. The objectives are to try to balance the currents demanded by consumers and to compensate the reactive power demanded by them at the expense of the remaining converters’ capacity. The strategy is implemented in each consumer installation, constituting a decentralized or distributed control and allowing its practical implementation based on local measurements. The algorithms were tested, in a yearly simulation horizon, on a typical Portuguese LV network to verify the impact of the high integration of the renewable energy sources in the network and the effectiveness and applicability of the proposed approach.

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“…In Singh et al, the optimal charging and discharging schemes were presented to mitigate voltage imbalance and power loss. An active load control method in the distribution grid was presented by Fang et al to solve the problem of three‐phase imbalance caused by large‐scale photovoltaic generations and EV charging consumption. Shahnia et al designed a voltage imbalance sensitivity method based on EV charging/discharging in a residential low‐voltage distribution grid to predict voltage imbalance with the plug‐in EVs .…”

Section: Introductionmentioning

confidence: 99%

A Real‐Time Multilevel Energy Management Strategy for Electric Vehicle Charging in a Smart Electric Energy Distribution System

He³

et al. 2019

Energy Tech

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The randomness of electric vehicle (EV) charging has negative impacts on three‐phase imbalance and peak–valley difference in electric energy distribution systems. Traditional EV charging strategies have shortcomings: the performance of three‐phase imbalance mitigation may be limited if the grid‐connected EVs are extremely imbalanced on three phases; in addition, the comprehensive regulation of peak–valley difference and three‐phase imbalance is not developed, and the three‐phase imbalance of reactive power is ignored. Therefore, a real‐time multilevel energy management strategy (RMEMS) for EV charging is proposed. A tri‐level optimization model (TOM) is designed as the central system. In upper‐level optimization, the three‐phase selection (TPS) of EVs is optimized to balance active or reactive power consumption on three phases. Based on the results from upper‐level optimization, the charging active power is regulated in middle‐level optimization to reduce the peak–valley difference on each phase. In lower‐level optimization, the reactive power compensated by EV chargers is optimized based on the results from upper‐level and middle‐level optimization to balance the reactive power on three phases. Case studies show that the proposed RMEMS performs well for balancing active and reactive power consumption on three phases, and the peak–valley differences of active power consumption on each phase are all mitigated.

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Research of active load regulation method for distribution network considering distributed photovoltaic and electric vehicles

Cited by 6 publications

References 9 publications

Coordinated control strategy for vehicle‐to‐grid support at distribution node

Coordinated control strategy for vehicle‐to‐grid support at distribution node

Photovoltaic Power Converter Management in Unbalanced Low Voltage Networks with Ancillary Services Support

A Real‐Time Multilevel Energy Management Strategy for Electric Vehicle Charging in a Smart Electric Energy Distribution System

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