Coordinated optimisation of PEV charging with the support of reactive discharging and phase switching in unbalanced active distribution networks

Fu, Yang; Meng, Xiangbao; Su, Xiangjing; Jabalameli, Nasim; Dong, Zhaoyang

doi:10.1049/iet-gtd.2020.0117

Cited by 4 publications

(7 citation statements)

References 31 publications

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“…The optimisation process is carried out in a central controller at the head of the feeder in order to manage the PVs and EVs in a coordinated manner. In this sense, the optimisation problem is computed at each time t based on the (QP) model given by Equation (5).…”

Section: Optimisation Modelmentioning

confidence: 99%

“…However, similar to ref. [5], the optimality of the problem highly depends on the parametrisation of the meta-heuristic algorithm and the complexity of the non-linear terms of the model, which implies that each solution, in this case, in the Pareto front may not be the optimal global value of the problem. Kontis et al [9] presented a two-layer-based centralised approach to manage voltage regulation and voltage unbalances problems due to a high PV share in unbalanced low-voltage networks.…”

Section: Introductionmentioning

confidence: 99%

“…A smart charging strategy based on reactive power discharging and phase switching in unbalanced LV networks was proposed in ref. [5] to minimise the network losses and the charging cost of the users. The optimisation model was defined as a mixed‐integer non‐linear programming problem.…”

Section: Introductionmentioning

confidence: 99%

“…However, similar to ref. [5], the optimality of the problem highly depends on the parametrisation of the meta‐heuristic algorithm and the complexity of the non‐linear terms of the model, which implies that each solution, in this case, in the Pareto front may not be the optimal global value of the problem. Kontis et al.…”

Section: Introductionmentioning

confidence: 99%

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Optimal coordination of electric vehicle charging and photovoltaic power curtailment in unbalanced low voltage networks: An experimental case

Borray

Rauma

2022

IET Smart Grid

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This study introduces a quadratic programming-based optimisation method to coordinate electric vehicle (EV) charging and photovoltaic (PV) curtailment in unbalanced low voltage (LV) networks. The proposed model is defined as a convex model that guarantees the optimal global solution of the problem avoiding the complexity of non-linear models and surpassing the limitations of local solutions derived from meta-heuristics algorithms reported in the literature. The coordination is carried out through a centralised controller installed at the header of the LV feeder. The objective of the proposed strategy is to minimise the power curtailment of all PV systems and maximise the power delivered to all EVs by optimising at every time step a suitable setpoint for the PV units and the charging rate of each EV connected without surpassing network constraints. A new energy-boundary model is also proposed to meet the energy requirements of all EVs, which is based on a recurrent function that depends on the arrival-and-desired energy states of the vehicle to compute its charging trajectory optimally. The effectiveness of the proposed coordination strategy was successfully proven through three scenarios in a laboratory environment, making use of two commercial EVs and a PV inverter in a Power Hardware-in-the-Loop setup.

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Section: Optimisation Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal coordination of electric vehicle charging and photovoltaic power curtailment in unbalanced low voltage networks: An experimental case

Borray

Rauma

2022

IET Smart Grid

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“…By employing EVs, reactive power compensation based on V2G technology can not only reduce the investment cost of reactive power compensation devices, but also stabilize the bus voltage of the ADN [12]. Fu et al [13] propose a coordinated EV charging strategy in an unbalanced DN with the support of reactive discharging and phase switching. Saffari et al [14] propose an integrated framework for the coordinated optimization of the interdependent microgrid (MG) by considering the active-reactive power management of EVs.…”

Section: Introductionmentioning

confidence: 99%

Active and Reactive Power Collaborative Optimization for Active Distribution Networks Considering Bi-Directional V2G Behavior

Zhang

Yang

et al. 2021

Sustainability

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Due to their great potential for energy conservation and emission reduction, electric vehicles (EVs) have attracted the attention of governments around the world and become more popular. However, the high penetration rate of EVs has brought great challenges to the operation of the Active Distribution Network (ADN). On the other hand, EVs will be equipped with more intelligent chargers in the future, which supports the EVs’ high flexibility in both active and reactive power control. In this paper, a distributed optimization model of ADN is proposed by employing the collaborative active and reactive power control capability of EVs. Firstly, the preference of EV users is taken into account and the charging mode of EVs is divided into three categories: rated power charging, non-discharging, and flexible charging–discharging. Then, the reactive power compensation capacity of the plugged-in EV is deduced based on the circuit topology of the intelligent charger and the active–reactive power control model of the EV is established subsequently. Secondly, considering the operation constraints of ADN and the charging–discharging constraints of EVs over the operation planning horizon, the optimization objective of the model is proposed, which consists of two parts: “minimizing energy cost” and “improving voltage profile”. Finally, a distributed solution method is proposed based on the Alternating Direction Method of Multipliers (ADMM). The proposed model is implemented on a 33-bus ADN. The obtained results demonstrate that it is beneficial to achieve lower energy cost and increase the voltage profile of the ADN. In addition, the energy demand of EV batteries in their plugin intervals is met, and the demand preference of EV users is guaranteed.

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Multi-objective energy management strategy of unbalanced multi-microgrids considering technical and economic situations

Roustaee

Kazemi

2021

Sustainable Energy Technologies and Assessments

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Coordinated optimisation of PEV charging with the support of reactive discharging and phase switching in unbalanced active distribution networks

Cited by 4 publications

References 31 publications

Optimal coordination of electric vehicle charging and photovoltaic power curtailment in unbalanced low voltage networks: An experimental case

Optimal coordination of electric vehicle charging and photovoltaic power curtailment in unbalanced low voltage networks: An experimental case

Active and Reactive Power Collaborative Optimization for Active Distribution Networks Considering Bi-Directional V2G Behavior

Multi-objective energy management strategy of unbalanced multi-microgrids considering technical and economic situations

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