Collaborative optimization allocation of VDAPFs and SVGs for simultaneous mitigation of voltage harmonic and deviation in distribution networks

With the gradual development of bidirectional interacted future distribution network, it is necessary to enter distributed clean power sources with various characteristics, including wind turbine and solar panel. Traditional centralized control has difficulties to fulfill the demands of future distribution networks for safe, stable, and efficient operation. Aiming at the constrained power allocation problem widely studied in smart grid, with the cooperative control algorithm of continuous multi-agent system, this paper proposed a distributed optimization allocation strategy, which is free by the initial state. The proposed distributed algorithm implements parameterization by adding auxiliary variables. In the iterative process, the algorithm only needs to know the state of the distributed power supply of the neighbor, and finally solve the global optimal solution of the system. The simulations prove that the proposed scheme can effectively improve the economic dispatch performance. Furthermore, comparing to the existing algorithm, the proposed algorithm achieves faster optimal solution.

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

Sustainability ◽

10.3390/su13116489 ◽

2021 ◽

Vol 13 (11) ◽

pp. 6489

Author(s):

Gang Xu ◽

Bingxu Zhang ◽

Le Yang ◽

Yi Wang

Keyword(s):

Power Control ◽

Energy Cost ◽

Energy Demand ◽

Reactive Power ◽

Planning Horizon ◽

Distribution Networks ◽

Collaborative Optimization ◽

Voltage Profile ◽

Reactive Power Control ◽

Active And Reactive Power

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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